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Gait analysis is one of the highly focused research areas inviting attention of academicians and practitioners. Being a prominent analytical tool to detect the abnormalities and onset of musculoskeletal disorders (MSDs), abundant literature is published in this area. Though a large number of gait analysis methods (GMSs) for motion analysis are available in the literature, very few studies are available to showcase the comparative analysis and applicability of various techniques. This study seeks to provide useful recapitulation of various gait measurement methods and interrogates the relative prevalence of various GMS based on the applications by various researchers. The paper summarizes the findings of a systematic review on gait measurement methods carried out using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. Fifty-three research papers published during 1998–2021 were included for critical review. The categories of gait measure ment systems were further compared based on certain criteria such as portability, cost, and accuracy, and ranked using analytic hierarchy process (AHP). The review helped to encapsulate various aspects of gait analysis, especially, the types of tasks, types of gait parameters (GPs), and the gait measurement systems adopted. The study provides suitable mappings between these factors and offers comparison between the gait measurement systems using a specially devised capability index. It further provides useful guidelines for selecting the gait systems based on the criteria. [ABSTRACT FROM AUTHOR]

This paper introduces a novel platform that integrates three preconditioning matrices based on conservative variables: the Turkel, Choi–Merkle and Onur matrices. The platform aims to compare these matrices in terms of accuracy and robustness by investigating their performance in solving three distinct and challenging high-gradient laminar flow problems: (i) Bi-Plane NACA0012 airfoil, (ii) lid-driven flow in a square cavity and (iii) flow in a planar T-junction. These problems serve as new and challenging test cases to accurately determine the abilities of the preconditioning matrices. The preconditioning matrices are applied to evaluate the numerical solutions, and their performance in complex flow fields is assessed in terms of accuracy and efficiency. By solving these flow problems, the effectiveness of the preconditioning matrices is thoroughly analyzed. By integrating these preconditioning matrices into a single platform, this paper significantly contributes to the field. The approach enables a direct and meaningful comparison of the performance of the Turkel, Choi–Merkle and Onur matrices in solving these new and challenging laminar flow problems. While all three matrices demonstrate comparable accuracy in predicting flow characteristics like pressure coefficients, Turkel's method shows superior convergence acceleration across the almost test cases due to alpha parameter and modifications of the momentum equations. In the external flow case, Turkel converges 22–53% faster than the other matrices by adjusting momentum terms with an alpha parameter. For the internal lid-driven cavity case, Turkel again accelerates convergence up to 38% over Choi–Merkle as Reynolds and Mach numbers increase. However, Onur's method stalls at high Reynolds/Mach numbers. At low values of Reynolds and Mach numbers, Onur reduces computational cost by 17%. Finally, for the T-junction case, Turkel and Choi–Merkle perform almost identically, decreasing CPU time by 55% vs Onur, which lacks convergence robustness. While the preconditioning matrices have similar accuracy, Turkel offers the best convergence improvement by accounting for momentum effects. Onur works well at low Reynolds/Mach numbers but shows limitations at higher values. The selection of the optimal preconditioning matrix should be based on whether momentum or viscosity dominates in the flow field, as well as the intensity of the viscosity gradient rate. [ABSTRACT FROM AUTHOR]

In this paper, we have established Cosine Trigonometric Operational Law (CTOL) and constructed Cosine Trigonometric Neutrosophic Weighted Averaging (CT-NWA) operator in the domain of generalized neutrosophic environment, which has been endorsed in a Multi-Criteria Group Decision Making (MCGDM) technique to select the best Anti-Pegasus software. In this study, the expertize recommendations and public opinion are well taken in context of debatable Pegasus issue in the Indian political, bureaucratic and democratic aspects. The problem has been addressed and resolved by using the integrated methodology of Analytical Network Process (ANP) and Evaluation based on Distance from Average Solution (EDAS) strategies. Here, we have optimized the weight factors and the gradation values of the decision makers as well as the sub-criteria of each criterion using Linear Programming (LP) model. Finally, we have performed the comparative analysis from various aspects to justify the reliability of our results. [ABSTRACT FROM AUTHOR]

Previous systematic literature reviews on pair programming (PP) lack in their coverage of industrial PP data as well as certain factors of PP such as infrastructure. Therefore, we conducted a systematic mapping study on empirical, industrial PP research. Based on 154 research papers, we built a new PP framework containing 18 factors. We analyzed the previous research on each factor through several research properties. The most thoroughly studied factors in industry are communication, knowledge of work, productivity and quality. Many other factors largely lack comparative data, let alone data from reliable data collection methods such as measurement. Based on these gaps in research further studies would be most valuable for development process, targets of PP, developers' characteristics, and feelings of work. We propose how they could be studied better. If the gaps had been commonly known, they could have been covered rather easily in the previous empirical studies. Our results help to focus further studies on the most relevant gaps in research and design them based on the previous studies. The results also help to identify the factors for which systematic reviews that synthesize the findings of the primary studies would already be feasible. [ABSTRACT FROM AUTHOR]

In the era of rapid growth of technologies, image matting plays a key role in image and video editing along with image composition. In many significant real-world applications such as film production, it has been widely used for visual effects, virtual zoom, image translation, image editing and video editing. With recent advancements in digital cameras, both professionals and consumers have become increasingly involved in matting techniques to facilitate image editing activities. Image matting plays an important role to estimate alpha matte in the unknown region to distinguish foreground from the background region of an image using an input image and the corresponding trimap of an image which represents a foreground and unknown region. Numerous image matting techniques have been proposed recently to extract high-quality matte from image and video sequences. This paper illustrates a systematic overview of the current image and video matting techniques mostly emphasis on the current and advanced algorithms proposed recently. In general, image matting techniques have been categorized according to their underlying approaches, namely, sampling-based, propagation-based, combination of sampling and propagation-based and deep learning-based algorithms. The traditional image matting algorithms depend primarily on color information to predict alpha matte such as sampling-based, propagation-based or combination of sampling and propagation-based algorithms. However, these techniques mostly use low-level features and suffer from high-level background which tends to produce unwanted artifacts when color is same or semi-transparent in the foreground object. Image matting techniques based on deep learning have recently introduced to address the shortcomings of traditional algorithms. Rather than simply depending on the color information, it uses deep learning mechanism to estimate the alpha matte using an input image and the trimap of an image. A comprehensive survey on recent image matting algorithms and in-depth comparative analysis of these algorithms has been thoroughly discussed in this paper. [ABSTRACT FROM AUTHOR]

This review reports the latest trends in the ceramic composite matrix used for the magnetoelectric (ME) effect. In the last few years, ME composite has become the center of attraction for use in various electrically and magnetically coupled devices. The growth and use of electronic components everywhere have propulsively accelerated the exploration of self-powered electronic and sensor network devices. ME is a feasible technique for addressing difficulties of traditional batteries such as short life span and frequent recharge difficulties. Self-charging multiferroic components have been found for the constant working of mobile electronics that use multiferroic composites in response to magnetoelectric energy transformation. Researchers have rigorously studied the rigid and flexible magnetoelectric composites for their suitability in applications. This paper gives a comparative study between rigid and flexible magnetoelectric composites based on their properties and provides knowledge about the materials for such types of composites. It reviews the latest polymer-based ME materials as well as the related fabrication and polarization methods. The review finally encapsulates the applications in biomedicine, ranging from mechanical energy harvesters to sensors and actuators. [ABSTRACT FROM AUTHOR]

The idea of causality has lasted for over thousands of years. Unlike the idea of statistical correlation and regression, performing causal modeling and prediction is an even more challenging job. Under the intervention framework of causality, causal modeling is gaining popularity given the advances of big data and computational ability in recent years. In different scientific research areas, there exist three powerful causal modeling methodologies, namely, the potential outcomes method in statistics, the instrumental variables method in economics and Judea Pearl's causal diagram method (do-calculus) in computer science and artificial intelligence. In this paper, by linear causal modeling assumption, we prove that the above three causal methodologies are equivalent. That is, given a causal problem, all of the three modeling methods will generate the same causal relationship conclusion, despite that they own different causal inference processes. During the past one-and-half years, the global economy suffers severe impacts from the COVID-19 pandemic. To fight the deadly pandemic, various social distancing measures and actions, taken by the countries, are effective in curbing the impact of the pandemic over the population. However, such social distancing policy has an adverse effect over the global economy growth; if more stringent measures were taken, then there would be suffering in the forms of much slower economic growth and higher unemployment. In this paper, we study the causal relationships between social distancing, fatality rate and economy growth. This work provides a useful tool for the governments to keep balance between controlling the pandemic and maintaining economic growth. [ABSTRACT FROM AUTHOR]

Context: Model comparison plays a central role in many software engineering activities. However, a comprehensive understanding about the state-of-the-art is still required. Goal: This paper aims at classifying and performing a thematic analysis of the current literature. Method: For this, we have followed well-established empirical guidelines to define and perform a systematic mapping study. Results: Some studies (14 out of 40) provide generic model comparison techniques, rather than specific ones for UML diagrams. Conclusion: Fine-grained techniques are still required to support ever-present and complex model comparison tasks during the evolution of design models. [ABSTRACT FROM AUTHOR]

This paper presents the structure and operational principles of high-frequency electronically controllable sinusoidal oscillators employing current-feedback operational amplifiers (CFOAs) with externally accessible compensation node z as active components. The resonant circuits in the oscillators are connected to the terminal z , and for them in the selective network varactor diodes or varicaps as the variable capacitances are utilized, which are controlled by external DC voltage. Based on an analysis of the proposed circuit configurations, analytical expressions for the characteristic equation in a steady-state mode of operation and formulas for the basic electrical parameters have been obtained. In order to verify the functionality of the proposed electronic circuits and the effectiveness of the derived analytical expressions, an experimental and simulation study of sample electronic circuits with commercially available integrated circuit CFOAs AD844 in the frequency range up to about 10 MHz is performed. The obtained results for the studied electronic circuits confirm the theoretical studies and hypotheses, and the comparative analysis shows that the maximum value for the relative error does not exceed 10%, which is acceptable considering the tolerances of the technological parameters of the used passive and active elements. [ABSTRACT FROM AUTHOR]

In this paper, the reliability of a cable-stayed bridge with a span of 640m is investigated and compared in three different scenarios. While both the first and second scenarios assumed a fixed end for the bridge supports used, they differed in terms of material and geometric behavior. Finally, the third scenario differed from the second by incorporating a soil–pile–structure interaction (SPSI) to account for the flexibility of the underlying support. This study accounts for uncertainties in the structure, pile, and soil parameters. The Latin hypercube sampling (LHS) method and dynamic time history analysis were used to estimate the structural responses. Artificial earthquake records at four different risk levels are used for the dynamic time history analysis. Using the machine learning method, several additional results were generated and used in the seismic reliability evaluation. In the case where the SPSI was a simulation, the reliability analysis showed a higher probability of cable failure than other criteria. The element of the tower in the fixed support case also has a high probability of failure. The results of the reliability analysis of the nonlinear models showed a higher probability of failure for a cable-stayed bridge on flexible support than on fixed support. [ABSTRACT FROM AUTHOR]

With the exponential increase of data on the web, the manual acquisition of ontology has become a time-consuming and tedious task. Thus, switching to ontology learning enables the ontologies' acquisition automation. In this paper, we deal with the phase of concepts' extraction. Our motivation is to capitalise on the confirmed advantages of deep learning (DL) models and word embedding techniques to automatically extract relevant concepts from large amounts of textual data. A four phases approach is proposed where different models and techniques are applied and a comparative study is achieved: the preprocessing phase, the classification phase, based on DL models, the terms filtering phase, where we experimented and compared three methods to extract the relevant terms, and the semantic enrichment phase experimenting and comparing word embedding techniques to semantically enrich the discovered concepts. The approach is implemented and evaluated on different medical datasets. The obtained results proved the suitability of the experimented models and techniques for the concepts' extraction. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the dynamic relationship between economic growth and CO2 emissions for a set of 98 countries over the lengthy period from 1951 to 2014. We describe the topology and hierarchy of countries and introduce a different concept of economic performance based on the idea of dynamic regimes. These regimes are defined by the average levels of per-capita CO2 emissions and the growth rates of per-capita GDP. By presenting a nonparametric clustering technique, the paper identifies two main groups. One cluster can be identified as the group of developed countries, which presents a homogeneous structure and tends toward more similar dynamics over time. The other cluster, associated with developing countries, is homogeneous but the dynamics of the countries do not show convergence. The study also finds some, though little, mobility between the groups. [ABSTRACT FROM AUTHOR]

Nowadays, a variety of Big Data architectures are emerging to organize the Big Data life cycle. While some of these architectures are proposed for general usage, many of them are proposed in a specific application domain such as smart cities, transportation, healthcare, and agriculture. There is, however, a lack of understanding of how and why Big Data architectures vary in different domains and how the Big Data architecture strategy in one domain may possibly advance other domains. Therefore, this paper surveys and compares the Big Data architectures in different application domains. It also chooses a representative architecture of each researched application domain to indicate which Big Data architecture from a given domain the researchers and practitioners may possibly start from. Next, a pairwise cross-domain comparison among the Big Data architectures is presented to outline the similarities and differences between the domain-specific architectures. Finally, the paper provides a set of practical guidelines for Big Data researchers and practitioners to build and improve Big Data architectures based on the knowledge gathered in this study. [ABSTRACT FROM AUTHOR]

In the design of high performance complex arithmetic logic circuits, ground bounce noise, leakage current and leakage power are important and challenging issues in nanometer down scaling. In this paper, the low power and reduced ground bounce noise using 10 transistor full adder has been proposed. Full adder is the most important basic building of digital circuits employing arithmetic operation. Adder circuit is widely used in many digital circuits not only for arithmetic operation but also for address generation in processors and microcontrollers. It is therefore necessary to make these systems more efficient so that they consume less power. Here, we use stacking power gating technique to evaluate leakage current, power and ground bounce noise. This paper describes reduction of leakage power and ground bounce noise from the 10 T full adder circuits to make it more reliable to be used to have low power and stable and errorless output. All the simulation in this paper has been carried out using cadence virtuoso at 45 nm technology at various voltages and various temperatures. By using this technique the leakage current reduction can be improved by 80% and leakage power to 70% as compared to conventional 10 T full adder. Ground bounce noise cam be reduced to 60% as compared to the base full adder. [ABSTRACT FROM AUTHOR]

The scope of this paper is to make the best use of cellular automaton. It is important that they can simulate not just a discrete model but also used to solve practical problems. To stimulate the research in this field, we define Fuzzy Graph Cellular Automaton (FGCA) and classify the fuzzy rule matrix according to the rules of the cellular automaton. We also provide the details of the generations of FGCA. To cover the defined concept, the parking recommendations have been figured out to show the effective performance of the research. In this proposed model, the fuzzy neighbourhood function represents the possible cell to which the vehicle can moved so that an efficient parking management can be maintained. By using fuzzy graph cellular automaton in parking recommendations, the results are more accurate than the other models. A comparative analysis is also done. In parking recommendations, the possibility of the available parking space can be predicted appropriately using the defined concepts. The results are simulated with C + + coding in MATlab. [ABSTRACT FROM AUTHOR]

In this paper for the first time, we have studied various structures of nanosheet field-effect transistors (NSFET) and the effect of various devices and process parameters such as nanosheet width, length, interspacing, S/D doping, channel doping, random dopant fluctuations studied on these device structures. Comparative analysis has been done between JL-NSFET, GS-JL-NSFET, JL-SiGeNSFET and JL-GS-SiGeNSFET in terms of analog parameters. Nanosheet-based FETs are likely to be the successor of FinFET beyond the 5-nm node. NSFETs have better control over gate, variable sheet width and more current per device footprint which gives them the advantage of circuit design versatility. NSFET offers better gate control, better current and switching per device footprint. NSFETs are preferred over NWFETs due to better electrostatics, greater channel widths, decreased SCEs and increased device reliability. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of lattice-matched II–VI ZnS-ZnMgS stack as the gate insulator on the propagation delay of a 4-state quantum spatial wavefunction-switched (SWS)-CMOS-based inverters and SRAMs. The novelty is the smaller density of interface states which reduces the fluctuations in the various threshold voltages of the SWS-FETs and logic and memory devices using them. Two SWS-CMOS-based inverter models using SiO2 and lattice-matched II–VI ZnS-ZnMgS stack as the gate insulator, are presented. Cadence simulations are used for comparing the single stage propagation delay of each inverter and their four-state logic transitions. [ABSTRACT FROM AUTHOR]

This paper analyzes the necessary and sufficient conditions for successful innovation in design and engineering companies (DECs) of the aerospace industry in Mexico. It is argued that successful innovation activity is a condition for achieving a high-performance level (HPL) among DECs. Seven innovation capabilities are analyzed to determine whether an HPL exists. Based on the dynamic capabilities approach, this research suggests that learning capability (LRC), research and development capability (RDC), creative capability (CRC), collaborative innovation capability (CIC), knowledge sharing capability (KSC), and exploitation capability (EXTC) are necessary conditions to achieve an HPL in DECs of the aerospace industry in Mexico. The fuzzy-set qualitative comparative analysis (fsQCA) methods are applied in this research to get insight into the configuration complexity that determines configurational causal relationships between HPL and innovation capabilities among firms of this industry in Mexico. [ABSTRACT FROM AUTHOR]

In this paper, thermoelastic dissipation or thermoelastic damping (TED) in micro/nanorings with rectangular cross-section is examined by accounting for small-scale effect on both structural and thermal areas. The modified couple stress theory (MCST) and nonlocal dual-phase-lag (NDPL) heat conduction model are exploited for incorporating size effect within constitutive relations and heat conduction equation. By employing simple harmonic form for asymmetric vibrations of the miniaturized ring and solving the heat conduction equation, for one-dimensional (1D) and two-dimensional (2D) cases of heat transfer, the solution of temperature distribution in the ring is extracted in the form of infinite series. By employing the definition of TED on the basis of entropy generation approach, an analytical relation in the series form containing structural and thermal scale parameters is established to estimate TED value. To appraise the precision and validity of the developed solution, a comparison study is performed by utilizing the outcomes of researches published in the literature. An exhaustive parametric study is then conducted to ascertain the role of structural and thermal scale parameters in the magnitude of TED. The influence of some key parameters such as vibration mode, geometrical properties, directions of heat conduction (1D and 2D model) and material on TED is also addressed. [ABSTRACT FROM AUTHOR]

The challenge of assessing semantic similarity between pieces of text through computers has attracted considerable attention from industry and academia. New advances in neural computation have developed very sophisticated concepts, establishing a new state of the art in this respect. In this paper, we go one step further by proposing new techniques built on the existing methods. To do so, we bring to the table the stacking concept that has given such good results and propose a new architecture for ensemble learning based on genetic programming. As there are several possible variants, we compare them all and try to establish which one is the most appropriate to achieve successful results in this context. Analysis of the experiments indicates that Cartesian Genetic Programming seems to give better average results. [ABSTRACT FROM AUTHOR]

Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), to rank some of the user preferred alternatives. The system considers the choice of the user and the quality of the alternatives to rank them. User preferences on the criteria are taken as inputs in the form of best–worst comparison vectors to measure the choice of the user. These values are applied to calculate the numeric weights of each of the criteria. These weights reflect the preference of the user. A dataset of secondary schools in Bangladesh has been compiled and used for automatic quantitative pairwise comparison on the alternatives to calculate the score of each alternative in every criterion, which reflects its quality in that criterion. These scores are calculated using AHP. The weights of the criteria as well as the scores of these alternatives in those criteria are then used to calculate the final score of the alternatives and to rank them accordingly. An extensive experimental analysis and comparative study is reported at the end of this paper. [ABSTRACT FROM AUTHOR]

This paper describes a study on bi-level multi-objective transportation problem in fuzzy environment. To alleviate a difficulty of transporting goods within nodes for long distances, we venture to formulate a transportation problem using bi-level criteria. Again, in this paper, we incorporate the real-life uncertain situation in bi-level transportation system through fuzziness. It produces a new class of transportation problem, namely fuzzy bi-level multi-objective transportation problem (FBMOTP). We solve FBMOTP with and without priority of the 1st level of transportation problem (TP) using the Vogal Approximation Method (VAM) which are called respectively Approach 1 and Approach 2. A special emphasis of this paper is to introduce a new approach namely Approach 3 for solving the FBMOTP in addition to the considered two approaches. In this regard, we incorporate an algorithm for Approach 3 to find compromise solution of the FBMOTP using VAM. Thereafter, the proposed algorithm is illustrated to show the usefulness by taking a numerical example. A comparative analysis with the existing studies is provided to understand the effectiveness of the proposed methodology. At last, conclusions are described with the lines of future study of the paper. [ABSTRACT FROM AUTHOR]

In this research, a comparative study of four Quantum Machine Learning (QML) models was conducted for fraud detection in finance. We proved that the Quantum Support Vector Classifier model achieved the highest performance, with F1 scores of 0. 9 8 for fraud and nonfraud classes. Other models like the Variational Quantum Classifier (VQC), Estimator Quantum Neural Network (QNN), and Sampler QNN demonstrate promising results, propelling the potential of QML classification for financial applications. While they exhibit certain limitations, the insights attained pave the way for future enhancements and optimization strategies. However, challenges exist, including the need for more efficient quantum algorithms and larger and more complex datasets. This paper provides solutions to overcome current limitations and contributes new insights to the field of QML in fraud detection, with important implications for its future development. [ABSTRACT FROM AUTHOR]

This paper develops a Fuzzy Adaptive Backstepping Control (FABC) and a Fuzzy Adaptive Backstepping Sliding Mode Control (FABSMC) for Single-Input Single-Output (SISO) nonlinear-systems with unmeasured states. The proposed adaptive schemes are fully compared. Thus, the Fuzzy Type-2 (FT2) concept and the High-Order Integral-Chain Differentiator (HOICD) are used as two universal approximators. Indeed, the first one is employed to approximate the nonlinear system model's and the second one to estimate the unknown states. Special attention is paid for the used approximators robustness under unmodeled dynamics, parameter variations and process noise. It should be noted that the asymptotic stability of both the fuzzy adaptive controls and the observer convergence for each scheme have been proved. In addition, the employed schemes have been simulated on a two-tank coupled nonlinear system. Thus, from simulation results, we can prove that the proposed methods guarantee that all signals for closed loop systems are both regular and bounded. Specifically, it can be shown that the performances of the proposed Fuzzy Interval Type-2 (FIT2) schemes are significantly improved compared with Fuzzy Type-1 (FT1) schemes in presence of external disturbances. [ABSTRACT FROM AUTHOR]

The two-degree-of-freedom (2-DOF) aerial manipulator is composed of a quadrotor aircraft and a 2-DOF manipulator, which significantly expands the scope of grabbing and transporting objects. After the manipulator is installed on the quadrotor, the manipulator and the load will cause serious interference to the quadrotor, resulting in difficulty of system control and even instability. This paper presents a mathematical model of the angular velocity system of the 2-DOF aerial manipulator. The model considers the influence of the manipulator and the load on the quadrotor. Based on this model, the nonlinear dynamics of the angular velocity system of the 2-DOF aerial manipulator are analyzed by solving the equilibrium points, calculating the Lyapunov exponents, analyzing the dynamic bifurcation diagram, and drawing the dynamic region distribution map. It is found that angular velocity can produce the dynamic behaviors of sink, period-doubling, and chaos under certain circumstances. By analyzing the nonlinear dynamic behaviors of the angular velocity system under different manipulator postures, different manipulator configurations, different load masses, and different load resistances, the stability of the angular velocity system is analyzed to guide the use of the aerial manipulator more safely and efficiently. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the discrete-time fractional systems from the following aspects. First, the discrete-time fractional unified system in Caputo sense is established with the help of Euler's discretization method. Furthermore, the dynamic behaviors of the discrete-time fractional Lü system (DFLS) which is deemed as a representative for unified system are observed. Then, the correlation dimension ( D 2 ) and Kaplan–Yorke dimension ( D K Y ) of the DFLS are evaluated by the aid of Grassberger–Procaccia algorithm and the Lyapunov exponent spectrum, respectively. Finally, the intrinsic connections between D 2 and D K Y are analyzed by the statistical modeling idea when the DFLS is in chaotic vibrations. The main results show that D 2 shares a positive correlation with D K Y for the chaotic DFLS, while the differences between D 2 and D K Y are not only related to the ratio of the largest and smallest Lyapunov exponents, but also closely tied up with the fractional order v itself. [ABSTRACT FROM AUTHOR]

In this paper, we performed a comparative study of the different data replication strategies such as Adaptive Data Replication Strategy (ADRS), Dynamic Cost Aware Re-Replication and Rebalancing Strategy (DCR2S) and Efficient Placement Algorithm (EPA) in the cloud environment. The implementation of these three techniques is done in JAVA and the performance analysis is conducted to study the performance of those replication techniques by various parameters. The parameters used for the performance analysis of these three techniques are Load Variance, Response Time, Probability of File Availability, System Byte Effective Rate (SBER), Latency, and Fault Ratio. From the analysis, it is evaluated that by varying the number of file replicas, it shows deviations in the outcomes of these parameters. The comparative results were also analyzed. [ABSTRACT FROM AUTHOR]

This paper adds to the growing remanufacturing literature by investigating a collaborative model in which the manufacturer serves as the remanufacturer's distributor while selling its own product. The paper extends the collaborative model that we have studied previously by characterizing it as a channel power structure under which the manufacturer plays the leader role in the collaboration. Furthermore, the paper compares this collaborative model with a competitive model in which the manufacturer competes with the remanufacturer in the market on pricing, sales volume and profit and finds that even if the manufacturer chooses to collaborate with the remanufacturer, it does not give up its market position; the manufacturer keeps the price of its product unchanged as the remanufactured product becomes increasingly acceptable to the consumer, and its product's sales volume remains unchanged in both models. Finally, this paper observes that the collaborative model benefits the manufacturer more than the competitive model, whereas the competitive model benefits the remanufacturer more than the collaborative model. Obviously, if collaboration benefits both of the manufacturer and remanufacturer, they will choose to collaborate, and the manufacturer will transfer part of its profit to the remanufacturer, but if competition brings them more profit, they will choose to compete in the market, and the remanufacturer will transfer part of its profit to the manufacturer. [ABSTRACT FROM AUTHOR]

The forced responses of bladed disks are highly sensitive to inevitable random mistuning. Considerable computational efforts are required for the sampling process to assess the statistical vibration properties of mistuned bladed disks. Therefore, efficient surrogate models are preferred to accelerate the process for probabilistic analysis. In this paper, four surrogate models are utilized to construct the relation between random mistuning and forced response amplitudes, which are polynomial chaos expansion (PCE), response surface method (RSM), artificial neural networks (ANN) and Kriging interpolation, respectively. A bladed disk with 2-degrees-of-freedom (2-DOF) each sector is used to validate the effectiveness of the surrogate models. The effects of number of training samples on the surrogate model accuracy are discussed. The responses results of one blade (single output) and maximum response of all blades (multi-output) indicate that PCE and Kriging interpolation could yield accurate and stable predictions of the statistical characteristics of the forced responses. PCE is recommended for the mistuned response predictions due to its accuracy and efficiency. [ABSTRACT FROM AUTHOR]

This paper aims to measure the operating efficiency of 22 Chinese domestic and foreign-funded life insurance companies from 2013 to 2017 and outline the path to achieve high-quality development. The DEA-Malmquist was used to evaluate the total factor productivity on the sample of 22 Chinese domestic and foreign-funded life insurance companies. A fuzzy set qualitative comparative analysis (fsQCA) was also used to analyze the configuration of determinants affecting technical efficiency. The results show that the overall operating efficiency of life insurance companies in China is relatively satisfying. The changes in total factor productivity are mainly caused by changes in technical efficiency and changes in efficiency. However, changes in scale efficiency have little effect on Chinese domestic and foreign-funded life insurance companies. There is a significant difference in the operating efficiency between Chinese domestic and foreign-funded life insurance companies. In contrast, the operating efficiency is slightly higher than that of foreign-funded life insurance companies, which is mainly reflected in the difference in pure technical efficiency. The realization path of a life insurance company's operating efficiency is primarily composed of high employee education and low overclosing ratio, high employee education and low reinsurance ratio, and all-factor positive investment. The weak employee quality and excessive overclosing are the main reasons for the low operating efficiency of some enterprises. This paper systematically analyzes the impact of the organization's internal structure on the operating efficiency of life insurance companies. Finally, based on the configuration perspective, we explain the internal logic and path of achieving better operating efficiency. In the end, we also provide decision-making references for further improving the efficient operation of life insurance companies in China. [ABSTRACT FROM AUTHOR]

ABC analysis is a commonly used inventory classification technique which consists in splitting a large number of inventory items into three categories, A, B and C: category A consists in the most important items, category B consists in the moderately important items and category C consists in the least important ones. Through this classification, inventory items are managed in an efficient way. In this paper, we argue the benefits of cross-fertilization of both Artificial Intelligence (AI) and MultiCriteria Decision Making (MCDM) techniques to carry out the ABC classification of inventory items. For this purpose, we develop some new hybrid inventory classification models based on metaheuristics (AI techniques) to generate the criteria weights and on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method (MCDM technique) to compute the overall weighted score of each item on which the ABC classification is performed. To evaluate the effectiveness of the proposed classification models with respect to some classification models from the literature, a comparative study — based on a service-cost analysis and three real datasets — is conducted. The computational analysis demonstrates that our proposed hybrid models are competitive and produce satisfactory results. The results have also shown, that our proposed models outperform some existing models from the literature. [ABSTRACT FROM AUTHOR]

A recent paper by Gunn-Allison-Abbott (GAA) [L. J. Gunn et al., Scientific Reports 4 (2014) 6461] argued that the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange system could experience a severe information leak. Here we refute their results and demonstrate that GAA's arguments ensue from a serious design flaw in their system. Specifically, an attenuator broke the single Kirchhoff-loop into two coupled loops, which is an incorrect operation since the single loop is essential for the security in the KLJN system, and hence GAA's asserted information leak is trivial. Another consequence is that a fully defended KLJN system would not be able to function due to its built-in current-comparison defense against active (invasive) attacks. In this paper we crack GAA's scheme via an elementary current-comparison attack which yields negligible error probability for Eve even without averaging over the correlation time of the noise. [ABSTRACT FROM AUTHOR]

Data security, privacy and authenticity are crucial in wireless data transmission. Low power consumption is the main requirement for any chip design targeting the Internet of Things (IoT) applications. In this research paper, a comparative study of eight authenticated encryption and decryption algorithms, selected from the "Competition for Authenticated Encryption: Security, Applicability and Robustness" (CAESAR), namely, ACORN, ASCON, CLOC, JOLTIK, MORUS, PRIMATEs, SCREAM and SILC, is presented. The FPGA and ASIC implementations of these eight algorithms are synthesized, placed and routed. Power, area, latency and throughput are measured for all algorithms. All results are analyzed to determine the most suitable algorithm for IoT applications. These results show that ACORN algorithm exhibits the lowest power consumption of the eight studied at the expense of lower throughput and higher latency. MORUS algorithm gives the highest throughput among the eight selected algorithms at the expense of large area utilization. [ABSTRACT FROM AUTHOR]

In this paper, three genomic materials -- DNA sequences, protein sequences, and regions (domains) are used to compare methods of virus classification. Virus classes (categories) are divided by various taxonomic level of virus into three datasets for 6 order, 42 family, and 33 genera. To increase the robustness and comparability of experimental results of virus classifi-cation, the classes are selected that contain at least 10 instances, and meanwhile each instance contains at least one region name. Experimental results show that the approach using region names achieved the best accuracies -- reaching 99.9%, 97.3%, and 99.0% for 6 orders, 42 families, and 33 genera, respectively. This paper not only involves exhaustive experiments that compare virus classifications using different genomic materials, but also proposes a novel ap-proach to biological classification based on molecular biology instead of traditional morphology. [ABSTRACT FROM AUTHOR]

This paper elucidates a comparative analysis of hysteresis current control space vector modulation (HCC-SVM) and 3-dimensional space vector modulation (3D-SVM) for control of 3-level neutral point clamped (NPC) inverter. The NPC inverter topology is much suitable for single input applications and medium and high power applications. The detailed comparative analysis of total harmonic distortion (THD) for both modulation control strategies is analyzed. Among various modulation strategies, these two control strategies increased more attention due to the improved output compared to the other conventional methods. The simulation and hardware results are evident that 3D-SVM is the most efficient controller for capacitor balancing, common mode voltage minimization, THD minimization and attain low voltage stress across switch, but in terms of system design and complexity in switching time calculation is simple in the HCC-SVM method. The simulation and hardware results are verified using simulink and FPGA processor, respectively. [ABSTRACT FROM AUTHOR]

The present paper proposes a new investigation area in automata theory - jumping finite automata. These automata work like classical finite automata except that they read input words discontinuously - that is, after reading a symbol, they can jump over some symbols within the words and continue their computation from there. The paper establishes several results concerning jumping finite automata in terms of commonly investigated areas of automata theory, such as decidability and closure properties. Most importantly, it achieves several results that demonstrate differences between jumping finite automata and classical finite automata. In its conclusion, the paper formulates several open problems and suggests future investigation areas. [ABSTRACT FROM AUTHOR]

This paper provides a comparative survey of natural language understanding (NLU) methodologies used for processing multiple documents. The scope of these methodologies is to generate a text output with reduced information redundancy and increased information coverage. The purpose of this paper is to inform the reader what methodologies exist and their features, capabilities and maturities based on evaluation criteria selected by users and developers. Tables of comparison, at the end of this survey, provide a quick glance of these technical attributes and maturity indicators abstracted from available information in the publications. [ABSTRACT FROM AUTHOR]

One can either use machine learning techniques or lexicons to undertake sentiment analysis. Machine learning techniques include text classification algorithms like SVM, naive Bayes, decision tree or logistic regression, whereas lexicon-based sentiment analysis uses either general or domain-based lexicons. In this paper, we investigate the effectiveness of domain lexicons vis-à-vis general lexicon, wherein we have performed aspect-level sentiment analysis on data from three different domains, viz. car, guitar and book. While it is intuitive that domain lexicons will always perform better than general lexicons, the actual performance however may depend on the richness of the concerned domain lexicon as well as the text analysed. We used the general lexicon SentiWordNet and the corresponding domain lexicons in the aforesaid domains to compare their relative performances. The results indicate that domain lexicon used along with general lexicon performs better as compared to general lexicon or domain lexicon, when used alone. They also suggest that the performance of domain lexicons depends on the text content; and also on whether the language involves technical or non-technical words in the concerned domain. This paper makes a case for development of domain lexicons across various domains for improved performance, while gathering that they might not always perform better. It further highlights that the importance of general lexicons cannot be underestimated — the best results for aspect-level sentiment analysis are obtained, as per this paper, when both the domain and general lexicons are used side by side. [ABSTRACT FROM AUTHOR]

Text is a typical example of unstructured and heterogeneous data in which massive useful knowledge is embedded. Sentiment analysis is used to analyze and predict sentiment polarities of the text. This paper provides a survey and gives comparative analyses of the latest articles and techniques pertaining to lexicon-based, traditional machine learning-based, deep learning-based, and hybrid sentiment analysis approaches. These approaches have their own superiority and get the state-of-the-art results on diverse sentiment analysis tasks. Besides, a brief sentiment analysis example in the tourism domain is displayed, illustrating the entire process of sentiment analysis. Furthermore, we create a large table to compare the pros and cons of different types of approaches, and discuss some insights with respect to research trends. In addition, a lot of important sentiment analysis datasets are summarized in this survey. [ABSTRACT FROM AUTHOR]

This paper presents the exploratory study conducted with the goal of developing an understanding of the current state of information representation and knowledge organisation in cultural heritage collections in Arabian Gulf countries and perspectives for future developments. This comparative case study focused on three institutions (an archive, an academic library, and a museum), including early adopters and leaders in digital archiving in the region. The mixed-methods research combined semi-structured interviews with in-depth comparative content analysis of metadata records that represent items in institutions' collections. Despite the limitations of the small-sample analysis, this exploratory case study makes a substantial contribution to research and practice. It is the first study to evaluate information representation and knowledge organisation practices in cultural heritage collections of Arabian Gulf countries. This study also can inform planning and implementation of the large-scale study of the state and perspectives of information representation and knowledge organisation across digital and physical collections of libraries, museums, and archives in the region. Suggestions for future research are included. Practical implications of the study include empirical support for the need for metadata training, developing and documenting metadata creation guidelines and crosswalks, collection and use of feedback from users and knowledge management professionals to improve information representation and knowledge organisation. Results also provide insights into interoperability potential of metadata for future regional, national and international aggregations of cultural heritage digital collections across the Arabian Gulf region. [ABSTRACT FROM AUTHOR]

The study and analysis of repairable systems is an important topic in reliability. Analytical techniques become very complicated and unrealistic especially for modern complex systems. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. The purpose of this paper is to develop a novel Markov system dynamics (MSD) simulation framework for the reliability modeling and analysis of a repairable system. This paper proposes a hybrid approach called as MSD approach which combines the Markov approach with system dynamics simulation approach for reliability modeling. This approach will have the advantages of both Markov as well as system dynamics methodologies. The proposed framework is illustrated for a repairable two component system. The results of the simulation obtained in this work when compared with that obtained by traditional Markov analysis clearly validate that this novel MSD approach is an alternative approach for reliability modeling and analysis. [ABSTRACT FROM AUTHOR]

In this paper, the Homotopy perturbation transform method and New Iterative transform method are implemented to evaluate the time-fractional Cauchy reaction–diffusion equation's solution. In this method, Elzaki transform is combined with the Homotopy perturbation method and New Iteration method. Four problems are investigated to show, demonstrate and validate the efficacy of the current technique. The analytical results achieved by the current technique indicate that the approach is easy to implement and accurate. These solutions reveal that the suggested method is very useful and straightforward to perform the problems of engineering sciences. [ABSTRACT FROM AUTHOR]

Regularization strategies have attracted attention in the structural damage detection (SDD) field. However, there is lack of studies on regularization strategies for damage patterns in the existing methods. This paper proposes regularization strategies for contiguous and noncontiguous damages of structures and performs comparative studies. The objective functions are first defined to consider effects of strategies on SDD by adding distinct norm penalties, and then are solved by the particle swarm optimization (PSO). Three numerical simulation models are employed to assess the applicability of three strategies. The results show that the l 2 norm regularization is suitable for detecting multiple damages, the l 1 norm regularization performs well in contiguous damages, and the sparsest solutions can be obtained by the l 1 / 2 norm regularization. [ABSTRACT FROM AUTHOR]

The Biswapped-Torus is a recently reported optoelectronic node-symmetrical member of Biswapped-framework family. In this paper,optimized parallel approach is presented for prefix sum computation on N × N Biswapped-Torus. The proposed parallel algorithm demands total 7 N + 6 electronic and three optical moves on odd network size or 7 N electronic and three optical moves on even network size. The algorithmic performance of the suggested parallel algorithm is also compared with the performances of recently reported optimal prefix sum algorithms on N × N Biswapped-Mesh and d h -dimensional Biswapped Hyper Hexa-cell. Based on the comparative analysis, Biswapped-Torus claims to map prefix sum faster that require fewer communication moves compared to the Grid-based traditional architecture of biswapped family named Biswapped-Mesh. Moreover, the former also has architectural benefit of node-symmetry that leads to advantages such as easy embedding, mapping and designing of routing algorithms. Compared to symmetrical counter-part of biswapped family named Biswapped-Hyper Hexa-Cell, Biswapped-Torus is cost-efficient, but requires comparatively more communication moves for mapping prefix sum. [ABSTRACT FROM AUTHOR]

In recent years, everyone has his/her own handheld digital devices such as PDAs and camera phones which are used to capture any documents, for example, posters, magazine and books. This is the simplest way to disseminating and collecting information. Unfortunately, the snapshot of this document in an uncontrolled environment has been suffering from different perspectives and geometric distortions, especially when a picture is taken from rolled document, page of thick book, multi-folded documents and crumpled pages. In such cases, the most common distortion appeared is warping text lines. In this paper, we present a survey and a comparative study of document image dewarping techniques which aim to solve the curled lines and geometric distortion problems. We introduce a new classification of the available dewarping document image techniques and investigate their available datasets. Finally, we present the evaluation metric to test these techniques. [ABSTRACT FROM AUTHOR]

In 2003, a digitally controlled oscillator (DCO) for cellular mobile phones was first proposed and demonstrated, and after that DCOs are widely used along with the rapid development of wireless communications. DCOs based on LC structure gain an advantage over ring oscillators in phase noise and thereby become research hotspot during the last decade. This paper presents a review of inductance capacitance (LC)-DCOs classified by circuit topologies and performance. For each DCO structure, the principle exposition and performance analysis are given in detail. Moreover, a comparison among all kinds of DCOs mentioned in this paper is presented in tabular form. Finally, we discuss the obstacle to the development of DCOs and the possible tendency for future work in summary. [ABSTRACT FROM AUTHOR]

Hazard and operability (HAZOP) analysis technique is used to identify and analyze hazards and operational concerns of a system. It provides a structured framework that can be used to perform a step-by-step safety analysis of a system. This paper details how to apply this method to safety-related scientific software. In this paper, we have developed (1) a nomenclature that singles out 30 primary concepts (2) a canonic set of abstractions of software programming constructs as a function of the primary concepts; (3) a process of translation from an existing design representation to the target design representation in the form of finite state machines; (4) HAZOP templates for each canonical form; and (5) an input variable prioritization method. We also developed a computational tool that can be used to perform HAZOP analysis of scientific software. Its results are compared with those obtained during manual HAZOP analysis by calculating the value of Shannon entropy, correctness, and the time required to perform each analysis. Overall, this method helps identify useful information about the impact of variables in the code that can then be utilized to develop robust code for making safety-critical decisions. [ABSTRACT FROM AUTHOR]

Patients with insomnia frequently use acupuncture as an alternative treatment to pharmacotherapy globally. The aim of this paper is to assess the effect of acupuncture on insomnia. Seven medical databases, including MEDLINE, EMBASE, CENTRAL, CNKI, RISS, NDSL, and OASIS, were used to identify studies published through July 09, 2020. Twenty-four randomized controlled trials (RCTs) were included in this qualitative review comparing acupuncture to either pharmacotherapy or sham-acupuncture therapy. Methodological quality was assessed, using the Cochrane risk of bias (ROB). In the subsequent quantitative meta-analysis of studies comparing acupuncture versus pharmacotherapy, fifteen RCTs demonstrated that acupuncture had a significant effect on patients with insomnia as assessed by the Pittsburgh sleep quality index (PSQI) (RR: –0.74; 95% CI: –1.07 to –0.40; P ¡0.0001; I 2 = 89%; n = 1475). A subgroup analysis showed that there was no significant effect after weeks 1 and 2, but six studies found that acupuncture had a significant effect insomnia at week 3 (RR: –0.97; 95% CI: –1.65 to –0.28; P = 0.006; I 2 = 91%; n = 463) and nine studies demonstrated a significant effect at week 4 (RR: –0.70; 95% CI: –1.15 to –0.25; P = 0.002; I 2 = 85%; n = 594). These results suggest that insomnia patients may experience significant improvement in symptoms after more than three weeks of acupuncture treatment compared to pharmacological treatments. [ABSTRACT FROM AUTHOR]

Sorting is a technique which is used to arrange the data in specific order. A sorting technique is applied to rearrange the elements in numerical order as ascending order or descending order or for words in alphabetical order. In this paper, we propose an efficient sorting algorithm known as Enhanced Bidirectional Insertion Sorting algorithm which is developed from insertion sort concept. A comparative analysis is done for the proposed Enhanced Bidirectional Insertion Sort algorithm with the selection sort and insertion sort algorithms. When compared to insertion sort algorithm the proposed algorithm outperforms with less number of comparisons in worst case and average case computing time. The proposed algorithm works efficiently for duplicated elements which is the advanced improvement and the results are proved. [ABSTRACT FROM AUTHOR]

Reconstructing causal networks from observed time series is a common problem in diverse science and engineering fields, and the challenge can increase with network size. Unfortunately, systematic comparisons of causal inference techniques have tended to concentrate on small motifs rather than graphs which it would be natural to label as complex networks. In this paper, six widely used methods of causal network reconstruction are systematically benchmarked and contrasted using neuronal models coupled on networks of varied size. Our purpose is concisely to review and explain the basic problems of causality detection using time series, and to compare the performance of varied and practical methods under the extremely relevant, but relatively neglected, conditions of highly nonlinear dynamical systems coupled via networks of many nodes. We find that convergent cross mapping consistently provides the highest precision, but transfer entropy can be preferable when high recall is important. The advantages of convergent cross mapping and transfer entropy over other methods can increase with network size. [ABSTRACT FROM AUTHOR]