Unified Performance Research Articles

An efficient storage and service method for multi-source merging meteorological big data in cloud environment

With the development of the meteorological IoT (Internet of Things) and meteorological sensing network, the collected multi-source meteorological data have the characteristics of large amount of information, multidimensional and high accuracy. Cloud computing technology has been applied to the storage and service of meteorological big data. Although the constant evolution of big data storage technology is improving the storage and access of meteorological data, storage and service efficiency is still far from meeting multi-source big data requirements. Traditional methods have been used for the storage and service of meteorological data, and a number of problems still persist, such as a lack of unified storage structure, poor scalability, and poor service performance. In this study, an efficient storage and service method for multidimensional meteorological data is designed based on NoSQL big data storage technology and the multidimensional characteristics of meteorological data. In the process of data storage, multidimensional block compression technology and data structures are applied to store and transmit meteorological data. In service, heterogeneous NoSQL common components are designed to improve the heterogeneity of the NoSQL database. The results show that the proposed method has good storage transmission efficiency and versatility, and can effectively improve the efficiency of meteorological data storage and service in meteorological applications.

Performance evaluation of Unified Memory with prefetching and oversubscription for selected parallel CUDA applications on NVIDIA Pascal and Volta GPUs

The paper presents assessment of Unified Memory performance with data prefetching and memory oversubscription. Several versions of code are used with: standard memory management, standard Unified Memory and optimized Unified Memory with programmer-assisted data prefetching. Evaluation of execution times is provided for four applications: Sobel and image rotation filters, stream image processing and computational fluid dynamic simulation, performed on Pascal and Volta architecture GPUs—NVIDIA GTX 1080 and NVIDIA V100 cards. Furthermore, we evaluate the possibility of allocating more memory than available on GPUs and assess performance of codes using the three aforementioned implementations, including memory oversubscription available in CUDA. Results serve as recommendations and hints for other similar codes regarding expected performance on modern and already widely available GPUs.

Reconciling modern machine-learning practice and the classical bias-variance trade-off.

Breakthroughs in machine learning are rapidly changing science and society, yet our fundamental understanding of this technology has lagged far behind. Indeed, one of the central tenets of the field, the bias-variance trade-off, appears to be at odds with the observed behavior of methods used in modern machine-learning practice. The bias-variance trade-off implies that a model should balance underfitting and overfitting: Rich enough to express underlying structure in data and simple enough to avoid fitting spurious patterns. However, in modern practice, very rich models such as neural networks are trained to exactly fit (i.e., interpolate) the data. Classically, such models would be considered overfitted, and yet they often obtain high accuracy on test data. This apparent contradiction has raised questions about the mathematical foundations of machine learning and their relevance to practitioners. In this paper, we reconcile the classical understanding and the modern practice within a unified performance curve. This "double-descent" curve subsumes the textbook U-shaped bias-variance trade-off curve by showing how increasing model capacity beyond the point of interpolation results in improved performance. We provide evidence for the existence and ubiquity of double descent for a wide spectrum of models and datasets, and we posit a mechanism for its emergence. This connection between the performance and the structure of machine-learning models delineates the limits of classical analyses and has implications for both the theory and the practice of machine learning.

On the performance of wireless powered communication networks over generalized [formula omitted] fading channels

The wireless powered communication network (WPCN) is considered as a promising network paradigm to overcome the energy scarcity problem suffered by the wireless devices. In this paper, we investigate the performance of wireless powered communication network in a point-to-point scenario which consists of one hybrid access point (HAP), and an energy harvesting enabled user equipment (UE) operating over generalized κ−μ fading channels. For the considered system, we derive a new form of mathematical expressions through Meijer’s G function and then employed it to evaluate the system performance such as outage probability, ergodic capacity, achievable throughput and average bit error rate. Unlike previous studies, we carry out an unified performance analysis of the system over the different fading environment. Furthermore, an optimal time duration between energy harvesting and the information transfer has been studied under two different transmission scenarios to achieve the maximum throughput. Numerical results are provided to show the impact of energy harvesting time and the fading parameters κ and μ on the system performance. The accuracy of the derived theoretical results are validated through Monte−Carlo simulation results.

Research on target management of 21 medical institutions in Anhui province

Objective To understand the status quo of the target management assessment of medical institutions in Anhui province, and provide a basis for further improving the performance appraisal mechanism and strategy of medical institutions. Methods In June 2017, 21 medical institutions in Anhui province conducted a questionnaire survey on the setup and implementation of target management indicators. Results Among the 21 medical institutions, there were 2, 16 and 3 hospitals in the first, second and third grades respectively.The average number of available beds was 681.35, and the average time for conducting target assessment was 4.42 years.The coverage rates of the clinical departments, medical technology departments, efficiency and efficiency, scientific research teaching, and department management of 21 medical institutions were 80%(316/397), 84%(52/63), 71%(120/168), 38%(48/126) and 60%(61/102)respectively.There were significant differences in coverage rates between clinical departments, medical technology departments, efficiency and efficiency, and research and teaching in different levels of medical institutions(P<0.05). Judging from the effectiveness of the current target assessment, it was considered that 64%(37/78)of the overall assessment results of the departments were in line with expectations, and the ratio of target management to hospital development management, department quality management, and functional department execution was 75%(42/64). Conclusions The status quo of performance assessment of medical institutions in Anhui province is running well, but the target management indicators and models of different medical institutions are different.It is necessary for the health administrators to establish a unified, authoritative and standard target performance assessment system. Key words: Hospitals; Target management; Performance assessment; Questionnaires

Toward a Unified Performance Metric for Benchmarking Steganography Systems

Recent advances in network speeds for exchanging multimedia data over insecure networks has resulted in an increased interest in steganography techniques. These techniques are usually evaluated based on their performance in three attributes; namely, capacity, imperceptibility, and robustness. Each of these attributes has its own measurement metric. Hence, comparing two different steganography schemes based on these individual metric tools becomes inconsistent. In this paper, a novel measurement metric tool is introduced for benchmarking steganography schemes. This new tool, named the “Combined Capacity-Quality-Robustness Effectiveness” (CCQRE) metric, combines the three opposing attributes of a steganography system into one conglomerate performance measure. Comparative results demonstrate the effectiveness of the proposed CCQRE metric for benchmarking various steganography schemes based on the researcher’s interest in capacity, imperceptibility, or robustness.

Integrated and concurrent detailed design of a mechatronic quadrotor system using a fuzzy-based particle swarm optimization

Mechatronics design is complex by nature as it involves a large number of couplings and interdependencies between subsystems and components alongside a variety of sometimes contradicting objectives and design constraints. Mechatronics design activity requires cross-disciplinary and multi-objective thinking. In this paper, a fuzzy-based approach for the modeling of a unified performance evaluation index in the detailed design phase is presented. This index acts as a multidisciplinary objective function aggregating all the design criteria and requirements from various disciplines and subsystems while taking into account the interactions and correlations among the objectives. Then this function is optimized using a particle swarm optimization algorithm alongside all the constraints facing each subsystem. As an application, the mechatronics design of a vision-guided quadrotor unmanned aerial vehicle is carried out to demonstrate the effectiveness of the proposed method. Thus, a thorough modeling of system dynamics, structure, aerodynamics, flight control and visual servoing system is carried out to provide the designer with all necessary design variables and requirements. The final results and related computer simulations show the effectiveness of the proposed method in finding solutions for an optimal mechatronic design.

The 80-year history of the professional associations of nutritionists in Brazil: A historical-documentary analysis

ABSTRACT Objective To carry out a mapping of the historical trajectory of the professional associations of nutritionists (scientific associations, councils and professional labor unions) in Brazil. Methods The study consists of a historical-documentary analysis. To obtain the data, information and documents, the websites of the Federal Council of Nutritionists; Brazilian Association of Food and Nutrition; National Federation of Nutritionists and Nutritionists’ Unions were browsed. A systematic bibliographic survey was carried out in the databases of the Scientific Electronic Library Online and National Library of Medicine to retrieve scientific articles about the associations of nutritionists in Brazil over the 80 years of their history, focusing on the last ten years. Results The historical analysis indicates that, over the course of eighty years, there has been strengthening of professional associations of nutritionists and achievements concerning training regulation, professional practice, fields of work and working conditions. The labor reform act of 2017 reduces the rights related to working conditions, creating setbacks in the achievements of nutritionists. Conclusion The professional associations of nutritionists have played an important role in the process of professionalization and legitimacy of training and performance of the profession in the country. There are indications of the unified performance of professional associations, but it is still incipient and scarce. Nowadays, unified, transparent and committed action of these professional associations is imperative for the professionalization and improvements of the working conditions of Brazilian nutritionists.

Unified performance of free space optical link over exponentiated Weibull turbulence channel

This study investigates the unified performance of a free space optical link with a finite-sized receiver over an exponentiated Weibull distributed atmospheric turbulence in the presence of a misalignment error (ME). The unification is done for two detection techniques namely heterodyne and intensity modulation/direct detection. First, the unified expressions for probability density function, cumulative distribution function, moment generating function, and moments of instantaneously received signal-to-noise ratios (SNRs) at the receiver, have been derived. By utilising the derived statistics, the unified novel expressions for outage probability, average error probability (AEP), and ergodic capacity are obtained. Furthermore, the AEP performance is examined at a high SNR in order to obtain the diversity order and coding gain, analytically. The derived results clearly demonstrate the impact of severe atmospheric conditions, ME, aperture size, and type of detection scheme on the system performance. The derived analytical results are verified through simulations.

ED performance over [formula omitted]/IG and [formula omitted]/IG generalized fading channels with diversity reception and cooperative sensing: A unified approach

This study investigates the unified performance analysis of an energy detector (ED) over α-η-μ/IG and α-κ-μ/IG generalized fading channels. The probability density functions (PDF) of the received signal-to-noise ratio (SNR) for the composite fading channels are derived using Gauss-Laguerre method. Novel analytical expressions for the average probability of detection (PD) for a single user and cooperative spectrum sensing (SS) are derived. The effects of diversity and noise uncertainty on the average PD are also presented. Rapidly convergent infinite series representations for the average PD are derived in terms of the upper bound of the truncation error. These expressions are used to analyze the behavior of ED-based SS over moderate, severe and extreme fading conditions, and to investigate the use of cooperation and diversity as a means of mitigating the fading effects. The accuracy of the derived expressions is validated through comparison of results obtained by Monte-Carlo simulations.

STEPS OF VERIFICATION AND VALIDATION ROUTE AIMED AT OBTAINING THE SOC MODEL ABLE TO PERFORM TARGET TASKS AND ALGORITHMS WITH SPECIFIED CHARACTERISTICS

In order to ensure the convergence of SoC design based on its performance on real applications the entire route of SoC development starting with the architectural design to the qualification tests for topological netlist should be focused on the early localization of performance issues and the confirmation of consumer characteristics of SoC before its tapeout. The article describes some of the details of of SoC verification flow, based on the convergence of performance requirements. Also the results of the work of tools used in research of SoC and its components at various abstraction levels are presented. Verification flow is based on the usage of templated test environments and unified performance analysis tools. Method of description of input stimuluses based on graphs is proposed. This method allows recovering the scenarios which discovered errors and simulateing of real traffic. Steps of system verification and validation route, oriented to the SoC model capable to perform targeted objectives and algorithms with preset characteristics are proposed. An example of a system verified by principle of performance metrics control is given.

A unified performance analysis of energy detector over [formula omitted]/lognormal and [formula omitted]/lognormal composite fading channels with diversity and cooperative spectrum sensing

In this paper, our objective is to formulate a generalized composite distribution which includes both α-η-μ and the α-κ-μ distributions for modelling small scale fading while shadowing effect is captured by the lognormal distribution. An approximate closed-form of generalized/lognormal (GL) distribution is derived using Gauss-Hermite (GH) integration. Subsequently, the distribution is utilized to formulate analytical expressions for the average probability of energy detection (PD) as well as average area under the receiver operating characteristic curve (AUC) with and without maximal ratio combining (MRC) diversity reception technique. The proposed solutions are expressed in terms of single and bivariate Fox’s H functions, which are currently being used in open literature. Further, the derived average PD is utilized for analysing the performance of energy detector (ED) over square-law selection (SLS) and square-law combining (SLC) diversity schemes. Optimization of detection threshold and number of cooperative sensing nodes to minimize the total error rate has been discussed for CSS network with erroneous feedback channels. Finally, the simplified closed-form asymptotic expressions of the average PD and AUC are also derived. The analytical expressions are validated by comparing them with the exact numerical results and Monte Carlo simulation.

Unified performance measures in network localization

With the evolving Internet of Things, location-based services have recently become very popular. For modern wireless sensor networks (WSNs), ubiquitous positioning is elementary. Hence, the demand of everlasting and low-cost sensor nodes is rapidly increasing. In terms of energy-efficiency, received signal strength (RSS)-based direction finding is a prospective approach providing location information in low-power sensor networks. Unfortunately, RSS-based direction finding is, as radio-based localization is in general, prone to multipath propagation of the wireless channel. Therefore, the impact of multipath fading as well as all other error source have to be modeled correctly and have to be considered in the design of a locating WSN.In this paper, we derive the classical Cramér-Rao Lower Bound (CRLB) for RSS-based direction-of-arrival (DOA). The drawbacks of the classical CRLB and its influence on the optimal network topology are discussed. The CRLB indicates that the minimum variance unbiased estimator (MVUE) does not exist for the problem of RSS-based DOA due to the nature of its measurement function. Hence, beyond the CRLB, we derive performance metrics for the maximum likelihood estimator (MLE) and compare position estimation errors for the MVUE and the MLE for different network topologies. Since both approaches, the CRLB and the maximum likelihood (ML) limits, are not capable of handling ambiguities, we introduce another measure for the variance of a measurement and its corresponding position estimate based on information theory. This way, the amount of information for a set of RSS measurements can be quantified exactly, even in the case of ambiguous probability densities. Thus, the proposed technique gives a holistic view on the information obtained from sensor measurements which can be utilized for network topology optimization.

Different stakeholders’ opinions toward the sustainability of common textile wastewater treatment technologies in Turkey: A Case study Istanbul province

This study aims to investigate the differences in stakeholders opinions about the sustainability of the common wastewater treatment technologies for textile mills in Turkey, through a ranking hierarchy that provides a unified performance evaluation scheme in economic, technical, environmental and social dimensions. To achieve this goal, a Multi-Attribute-Decision-Making (MADM) method has been developed using the analytical hierarchy process approach (AHP). Sustainability performance scores and their importance weights were collected from three carefully selected stakeholders. The discrepancies in their perceptions of the sustainability paradigm were evaluated. The results are interpreted with sustainability criteria and their relevant indicators provided a detailed view about their opinion, and awareness to address the characteristics and limitations of different types of wastewater treatment technologies. In the case of our study, the findings show that chemical treatment related technologies demonstrated lowest sustainable alternatives in the case of textile industry. On the other hand, membrane biological reactor (MBR), rotating biological contactor (RBC), and sequencing batch reactor (SBR) were competitive technologies in terms of the sustainability criteria.

A unified performance analysis of decode‐and‐forward dual‐hop relaying‐based wireless energy harvesting with space modulation

AbstractSpace modulation techniques (SMTs) are a group of multiple‐input–multiple‐output wireless systems in which the spatial indexes of transmit antennas are utilized to convey additional information bits. The SMTs promise significant enhancements in terms of spectral and energy efficiencies and attract significant research interest in literature. Several SMTs have been proposed including spatial modulation (SM) and quadrature SM. In this study, the performance of dual‐hop decode‐and‐forward relaying SM and quadrature SM in the presence of wireless power transfer is analyzed and thoroughly discussed. Specifically, we derive exact closed‐form expressions for the pairwise error probability (PEP). In addition, we derive simple and accurate asymptotic expressions for the PEP at high signal‐to‐noise ratio, which provides insight into the influence of different system parameters. The obtained PEP expressions are then employed to evaluate the overall average bit error rate (BER). It is worth highlighting that the derived expressions are unified in the sense that they are valid for the aforementioned SMTs and for two well‐known practical energy harvesting protocols, namely, power‐splitting receiver and time‐switching receiver. In addition, we derive a unified closed‐form expressions for the outage probability and achievable throughput at the destination node. The impact of diverse system parameters, such as the power‐splitting factor, the energy‐harvesting time factor, and the distance between the source and the relay nodes, on the overall system performance is studied. The accuracy of the analytical derivations is validated through Monte Carlo simulations results.

Cooperative spectrum sensing over generalized fading channels based on energy detection

This paper analyzes the unified performance of energy detection (ED) of spectrum sensing (SS) over generalized fading channels in cognitive radios (CRs). The detective performance of SS will be obviously affected by fading channels among communication nodes, and ED has the advantages of fast implementation, no requirement of priori received information and low complexity, so it is meaningful to investigate ED over various fading channels. The probability density function (p.d.f.) of α-κ-μ distribution is derived to evaluate energy efficiency for sensing systems. The detection probability with Marcum-Q function has been derived and the close-form expressions with moment generating function (MGF) method are deduced to achieve SS. Furthermore, exact closed-form analytic expressions for average area under the receiver operating characteristics curve (AUC) also have been deduced to analyze the performance characteristics of ED over α-κ-μ fading channels. Besides, cooperative spectrum sensing (CSS) with diversity reception has been applied to improve the detection accuracy and mitigate the shadowed fading features with OR-rule. At last, the results show that the detection capacity of ED will be evidently affected by α-κ-μ fading channels, but appropriate channel parameters can improve sensing performance. In addition, the established ED-fading pattern is approved by simulations, and it can significantly enhance the detection performance of proposed algorithms.

Unified Performance Analysis of Transmit Antenna Selection With OSTBC and Imperfect CSI Over Nakagami- m Fading Channels

A unified error analysis of multi-antenna systems with orthogonal space-time block coding (OSTBC) using transmit antenna selection (TAS) over Nakagami- $m$ channels in the presence of feedback delay and channel estimation error is presented, where the number of transmit antennas is arbitrarily selected. For imperfect channel state information (CSI), the Nakagami- $m$ channel is modeled as the sum of Nakagami- $\hat{m}$ channel and independent Gaussian channel error. By this model, accurate and closed-form approximate bit error rate (BER) expressions of TAS-OSTBC for M-ary quadrature amplitude modulation and M-ary phase-shift keying are derived by using the moment generating function of received SNR. With the approximate BER formula, the number of antennas to be selected for transmission can be adapted by minimizing the BER of the system with imperfect CSI. The diversity and coding gains of TAS-OSTBC with $K$ receive antennas and $M$ antennas selected from $N$ transmit antennas for transmission are analyzed at high SNR. For noninteger $mK$ , the upper and lower bounds of the diversity gain for different CSI and estimation error scenarios are derived. But for integer $mK$ , the results indicate that the upper and lower bounds are equal achieving the full diversity order of $mKN$ for perfect CSI, zero diversity order and partial diversity order of $mMK$ for estimation error variance being fixed and being a decreasing function of average SNR, respectively. The coding gain is affected by $M$ , $N$ , $K$ , Nakagami parameter $m$ , code rate, modulation, and channel correlation coefficients. Simulation results verify the validity of the theoretical analysis and effectiveness of the adaptive antenna selection scheme.

Exponential stabilization for fuzzy sampled-data system based on a unified framework and its application

This article deals with the exponential stabilization problems of Takagi–Sugeno (T–S) fuzzy system under aperiodic sampling. The objective is to solve the H∞, L2−L∞, passive and dissipative stability and stabilization problems based on a unified performance index-extended dissipativity. Some new stability conditions consisting of both exponential stability and extended dissipativity criterion are first established. A sampling period dependent Lyapunov–Krasovskii function together with a novel efficient integral inequality, which has the advantage of reducing conservativeness, is adopted. On the basis of the stability conditions, a sampled-data controller that can not only exponentially stabilize the system but also guarantee the prescribed extended-dissipativity performance is then designed. Moreover, an exponential decay rate can be set in advance to achieve better system performance. Finally, a quarter-vehicle active suspension system with considering payload uncertainties and aperiodic sampling is provided for evaluating the validity and superiority of the extended dissipative control approach proposed in this article.

Do United States manufacturing companies benefit from climate change mitigation technologies?

Climate change mitigation technologies play a critical role in controlling greenhouse gas emissions. How the technologies affect firm performance is a research issue of great importance to firm managers and policymakers. Using a dataset on major United States manufacturing firms, this study identifies five types of climate change mitigation technologies: eco-efficiency, low-carbon energy, green design, pollution control, and management system. This paper develops measures to capture the firms' unified (operational and environmental) performance using data envelopment analysis, and examines the effects of different climate change mitigation technologies on the unified performance. The research finds that the adoption of low-carbon energy technology positively and significantly affects the unified performance, whereas the adoption of pollution control technology has a significantly negative effect. Moreover, increasing the share of investment in low-carbon energy out of total technology investment can positively and significantly affect the unified performance, and the share of pollution control has a negative and significant effect. The other technologies do not display significant impacts on unified performance. The results underscore that firms should take into consideration the differential effects of the climate change mitigation technologies when making investment decisions to cope with climate change. The reasons behind the findings and implications for management practices are discussed.

Characteristics of Long-run Return and Risk: A Unified Performance Metric

It is well documented in the literature that long-run asset prices do not follow a random walk, thus their returns are not independent and identically distributed (i.i.d.) over time. But how can this notion—long-run returns and volatilities being horizon dependent—be incorporated into formal pricing models? In this paper, we develop a unified risk-adjusted return metric that is applicable to both private assets and public securities. Since such metric is based on a pair of empirically determined return and risk characteristic lines that depict the horizon impact on return and volatility, our performance metric is rooted in empirical evidence rather than assumptions. The results suggest that long-run asset performance cannot be adequately measured by single-period return and volatility. Rather, prudent long-run investment decisions must include careful consideration of the anticipated holding period and a proper understanding of the long-run return and risk characteristics.