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Structured light systems (SLSs) are commonly used for precision dimensional measurements. These are active systems in that the projected structured light pattern is used to establish correspondence between the projector and the camera(s) to provide more accurate 3D reconstruction as opposed to passive camera-based systems that rely on the user or features in images to identify corresponding points between the cameras. Errors in the calibration of the model parameters of an SLS can lead to systematic errors in dimensional measurements. In this paper, we explore the topic of performance testing of an SLS, specifically, the sensitivity of the length tests described in the VDI/VDE 2634-2 guideline and the ISO 10360-13 standard to the model parameters (such as intrinsic parameters of the camera and the projector, and camera-projector geometry parameters) of an SLS. The results are based on a hybrid approach of simulations performed using data obtained experimentally from an SLS mounted on a Cartesian coordinate measuring machine (CMM) which is used primarily to position the target at different points within the measurement volume. The results show that the length tests described in the ISO 10360-13 standard provide better sensitivity to the model parameters than the VDI/VDE 2634-2 guideline. However, even the ISO 10360-13 length tests do not detect all parameters with high sensitivity. A model-based approach in identifying length tests (i.e., the position and orientation of reference lengths) such as described in this paper provides better sensitivity to model parameters and therefore is more likely to detect systematic errors in SLSs. • Built a structured light system on a CMM and determined the length errors between points in a rectangular grid. • Assessed the sensitivity of lines defined in the VDI/VDE 2634-2 and ISO 10360-13 documents to systematic errors in SLSs. • Identified position/orientation of lines in the measurement volume that provides maximum sensitivity to systematic errors. • Demonstrated the superiority of our sensitivity analysis-based approach in detecting SLS systematic errors. [ABSTRACT FROM AUTHOR]

Quantification is a fundamental aspect of performance of an analytical system. Paper-based analytical device (PAD) as an on-site detection platform has drawn wide attention mainly due to its portability and cost effectiveness. In this work, a portable and low-cost PAD for online preconcentration and sensitive determination of fluorescent whitening agent (FWA) was demonstrated, which was consisted of ultra violet light-emitting diode (UV LED), macro-focusing lens, smartphone and miniaturized DC voltage source. Taking a widely used FWA component VBL as the analyte, the performance of the PAD enhanced with electrokinetic stacking (ES) and fluorescence imaging detection was systematically investigated. With ES, the sensitivity of the PAD system was 160-fold enhanced, and a limit of detection (LOD) of 0.06 μg mL −1 was achieved. The dynamic range was 0.1–10.0 μg mL −1 (linear in 0.1–0.7 μg mL −1 , R 2 = 0.99). With manual operation, the relative standard deviation (RSD) of intra-day and inter-day were all below 15%. Eventually, VBL from different napkin samples and toilet paper was determined with average recovery rates in the range of 90%–95% (RSD = 8.0%–12.0%). This work shows that with ES, the sensitivity of PAD can be greatly improved, and a LOD close to a desktop fluorescent spectrophotometer can be achieved as demonstrated by the detection of FWA component. [ABSTRACT FROM AUTHOR]

This study evaluates the effect of presentation media (PC tablet versus pencil and paper) on the performance, level of visual fatigue, and subjective preference of those taking visuospatial tests. Fifty university students participated and performed three visuospatial short-term memory tests and three visuospatial ability tests by using both types of display media. The display medium substantially affected all of the measured variables ( p < 0.01). On average, the paper–pencil test scores of the visuospatial short-term memory tests were about 10% higher and the answer time was about 20% shorter than those of the PC tablet tests. The average paper–pencil test score of the visuospatial ability tests was about 35% higher than the average test score of the PC tablet test. The visuospatial performance was substantially decreased under the PC tablet condition compared with that under the pencil–paper condition. In addition, visual fatigue was greater when participants used the PC tablet than when they used a pencil and paper. [ABSTRACT FROM AUTHOR]

Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for deep neural networks to learn new tasks from just a few labeled samples without forgetting the previously learned ones. This setup can easily leads to catastrophic forgetting and overfitting problems, severely affecting model performance. Studying FSCIL helps overcome deep learning model limitations on data volume and acquisition time, while improving practicality and adaptability of machine learning models. This paper provides a comprehensive survey on FSCIL. Unlike previous surveys, we aim to synthesize few-shot learning and incremental learning, focusing on introducing FSCIL from two perspectives, while reviewing over 30 theoretical research studies and more than 20 applied research studies. From the theoretical perspective, we provide a novel categorization approach that divides the field into five subcategories, including traditional machine learning methods, meta learning-based methods, feature and feature space-based methods, replay-based methods, and dynamic network structure-based methods. We also evaluate the performance of recent theoretical research on benchmark datasets of FSCIL. From the application perspective, FSCIL has achieved impressive achievements in various fields of computer vision such as image classification, object detection, and image segmentation, as well as in natural language processing and graph. We summarize the important applications. Finally, we point out potential future research directions, including applications, problem setups, and theory development. Overall, this paper offers a comprehensive analysis of the latest advances in FSCIL from a methodological, performance, and application perspective. • In-depth survey on FSCIL methods, applications, performance. • Categorizing FSCIL into five subcategories for clear analysis. • Evaluating FSCIL research on benchmarks for strengths, weaknesses. • FSCIL applications in computer vision, NLP, and graph. [ABSTRACT FROM AUTHOR]

Our study addresses the following research questions: Are there differences between handwriting movements on paper and on a tablet computer? Can experienced writers, such as most adults, adapt their graphomotor execution during writing to a rather unfamiliar surface for instance a tablet computer? We examined the handwriting performance of adults in three tasks with different complexity: (a) graphomotor abilities, (b) visuomotor abilities and (c) handwriting. Each participant performed each task twice, once on paper and once on a tablet computer with a pen. We tested 25 participants by measuring their writing duration, in air time, number of pen lifts, writing velocity and number of inversions in velocity. The data were analyzed using linear mixed-effects modeling with repeated measures. Our results reveal differences between writing on paper and on a tablet computer which were partly task-dependent. Our findings also show that participants were able to adapt their graphomotor execution to the smoother surface of the tablet computer during the tasks. [ABSTRACT FROM AUTHOR]

The antioxidant capacity of two active papers (based on solid and emulsion paraffin) with cinnamon essential oil was studied. Mushroom samples were introduced in macroperforated PET trays covered with the active papers, and weight loss and browning monitored for 9 days. The antioxidant capacity of the different papers was evaluated based on scavenging 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and tyrosinase inhibition kinetics, and the release of aromatic volatile oils was determined by HSPME–GC–MS. Differences in performance were observed: the active papers were more efficient at avoiding weight loss and mushroom browning when compared to the non-active paraffin-based papers. The efficiency increased when the bottom and walls of the trays were covered rather than the bottom alone. Better results were observed when cinnamon was incorporated as emulsion paraffin instead of a solid. [ABSTRACT FROM AUTHOR]

Examining gains in undergraduate writing abilities, Haswell (2000) applied a multi-dimension construct of writing to impromptu writing exams composed at the first- and third years. This project replicates Haswell's original study to impromptu writing exams composed at the same points, and extends that methodology to course papers written for common undergraduate curricular contexts—first-year composition, general education requirements, and advanced undergraduate writing in the disciplines requirements—to consider the use of such assessment scores as plausible and appropriate evidence for outcomes assessment purposes within a validational framework (articulated by Kane, 2006, 2013). This study considers the feasibility of reporting such localized assessment information as an alternative to represent progress for undergraduate writing ability, and reports preliminary evidence suggesting positive effects of distributed writing requirements across undergraduate curriculums on student writing performance. [ABSTRACT FROM AUTHOR]

• Polymer desiccant wheel with high water uptake and low regeneration temperature is studied. • Polymer's adsorption capacity of 1.15 g kg−1 at 90 %RH is five times that of silica gel. • Polymer's desorption rate coefficient is 1.32–1.64 times that of silica gel at 40–70 °C heat sources. • The maximum ∆ Y and DCOP of the polymer desiccant wheel are 4.0 g kg−1 and 0.66, respectively. • Polymer desiccant wheel offers a promising measure for ultra-low dew point humidity control. Desiccant wheels have been widely used in humidity control, particularly under conditions with ultra-low dew point temperatures. However, traditional desiccants such as silica gel and zeolites are subject to relatively low adsorption capacity and high regeneration temperature. To address these challenges, a type of polymer material with high water uptake and low regeneration temperature is investigated in this paper. Firstly, the adsorption/desorption capacity of this polymer is thoroughly tested. Results reveal that its remarkable equilibrium adsorption capacity and desorption rate coefficients k LDF,de are 350% and 32–64% higher than that of silica gel, respectively. Moreover, its required regeneration temperature is just about 40–70 °C. The performance of the desiccant wheel using this polymer is simulated by a model validated by experiments tests. Parameter analysis demonstrates that the desiccant wheel is suitable for cool and humid conditions, reaching the maximum moisture removal (∆ Y) and dehumidification coefficient of performance (DCOP) of 4.0 g kg−1 and 0.66, respectively. Furthermore, the corresponding relationship between other parameters and the optimal rotation speed is discussed in detail. The ω opt is around 18 rph, enabling the attainment of the highest ∆ Y. Finally, the performance comparison with a traditional silica gel desiccant wheel is carried out. The results indicate that the polymer one performs 17–53.9% higher in terms of both ∆ Y and DCOP than the silica gel counterpart. And the most significant improvement is observed in low relative humidity conditions (45%RH), where ∆ Y and DCOP are 1.25–1.53 times that of the silica gel's, highlighting the advantageous utilization of the polymer material. [ABSTRACT FROM AUTHOR]

In this paper, an experimental study of a magnetic refrigerator was carried out to identify static and dynamic models, which can be used for proposing and tuning control strategies. For the experimental evaluation, a 40 liter thermally insulated compartment was coupled to a magnetic refrigeration system equipped with an active magnetic regenerator. The influence of fluid flow rate, blow fraction, and magnetic cycle frequency on the temperature behavior inside the refrigerated compartment and on the power consumption of the system was evaluated. The results of the characterizations show that it is possible to reach equivalent cabinet temperatures by changing the flow rate of the thermal fluid or the cycle frequency. However, the former has a greater influence on the temperature of the cabinet, and the latter has a greater impact on the energy consumption and is associated with slower transients. Additionally, the temperature of the cabinet at steady state showed a parabolic behavior with respect to the fluid flow rate, demonstrating that there is an optimal flow rate for a given operating condition. • A magnetic refrigerator is experimentally evaluated at different operating conditions. • A thermally insulated compartment and real heat exchangers are employed. • Control-oriented dynamic and static models based on experimental data are provided. • Fluid flow rate, blow fraction, and magnetic cycle frequency are manipulated. • Temperature of the cabinet and energy consumption are measured. [ABSTRACT FROM AUTHOR]

In addition to the BeiDou regional navigation satellite system (BDS-2) backward compatible B1I and B3I signals, the BeiDou global navigation satellite system (BDS-3) also broadcast the B1C and B2a signals for compatibility with other Global Navigation Satellite System (GNSS), and providing satellite-based augmentation service for the International Civil Aviation Organization. Considering that the majority of the existing researches on the BDS-3 precise orbit determination (POD) and precise point positioning (PPP) are based on the B1I/B3I signals, the special attention that systematically comparing the data quality, POD accuracy and PPP performance through B1I/B3I and B1C/B2a signals is aroused in this paper. Signal characteristics of different receivers and antennas for the aforesaid four various signals were analyzed in terms of the carrier-to-noise density ratio (C/N0), pseudorange multipath and observation noise. The B1C signal exhibits the minimum C/N0 values, and the B3I and B2a signals have the smaller pseudorange multipath errors. The smallest pseudorange noise can be observed form the B2a signal, while the root mean squares (RMSs) for carrier phase noise show tiny differences among the four signals. The BDS-3 POD results indicate that the orbit overlapping arc error in three-dimensional (3D) direction is 0.069 and 0.076 m for the B1C/B2a and B1I/B3I, and the standard deviation of the satellite laser ranging validation is 0.041 m for both the two schemes. The clock offset products were evaluated with respect to the precise clock products from Deutsches GeoForschungsZentrum (GFZ), and the standard deviations (STDs) are 0.166 and 0.176 ns for the B1C/B2a and B1I/B3I. Finally, there is no apparent difference in the RMSs for B1C/B2a and B1I/B3I static PPP, while the convergence time that shortened by 31.4 % can be achieved for B1C/B2a. For kinematic PPP, the 3D RMS is 0.043 m and the convergence time is 31.1 min for the B1C/B2a, which is reduced by 14.0 % and 35.2 %, respectively, compared to B1I/B3I. [ABSTRACT FROM AUTHOR]

Highlights: [•] Investigates benchmarked performance of global and emerging knowledge cities. [•] Introduces a knowledge-based urban development performance assessment model. [•] Applies the assessment model into an international comparative study. [•] Reveals insights on scrutinizing the development perspectives of knowledge cities. [ABSTRACT FROM AUTHOR]

• A phase duration calculation method is proposed based on multi-phase identification. • The components' fuzzy state probability vectors are acquired using the evidential reasoning rule. • A performance evaluation model of cyclic phased-mission systems is constructed by multi-valued decision diagrams. • A phase duration adjustment method based on the evaluation results is proposed. • The proposed method is verified by a performance evaluation case study on satellite turntable system. Phased-mission systems (PMS) often perform different missions that have multiple consecutive, non-overlapping phases. Many recent studies have focused on the reliability analysis for PMS. However, not much attention has been paid to the PMS performance evaluation and the phase cycle characteristic of PMS. In this paper, a performance evaluation method of non-repairable cyclic phased-mission systems (CPMS) is proposed. Considering the uncertainty caused by the change of phase duration and component performance degradation, the average duration of each phase and the fuzzy state probability vector of each component are obtained by the evidential reasoning rule (ER rule). Then, the multi-valued decision diagrams (MDD) manipulation rules suitable for cyclic phase conditions are proposed, and the component state composition path generation method based on cycle-end component states is developed. On the above basis, MDD models for CPMS (CPMS-MDD) in different states are established, and the system performance is evaluated by the continuous time Markov chains (CTMC). A phase duration adjustment strategy is further proposed based on the evaluation results. The effectiveness and correctness of the proposed method are verified by case studies on performance evaluation of satellite turntable system. Comparative study shows the concise and efficient of the proposed method. [ABSTRACT FROM AUTHOR]

At crime scenes, fingerprints are often found on paper. The visualization of invisible fingerprints, so-called latent fingerprints (LFPs), is critical in forensic investigation. Laser-induced fluorescence technology for fingerprint detection has the advantages of sensibility, high-resolution, non-destructiveness and non-contact. In this paper, the characteristics of commonly used paper and the interaction between ultraviolet light and porous paper are briefly analyzed firstly. Next the fingerprint detection device is introduced. Then the output energy of the laser is optimized and a series of experiments are carried out. Local gray value stretching and power enhancement algorithms are used to process the fingerprint fluorescence data, and the high contrast fingerprint images are obtained. The experimental results show that the fingerprint substance and paper are degraded in different degrees under the excitation of ultraviolet light, and the second or third detection can improve the signal-to-noise ratio of detection. By the method of this paper, clear fingerprint images can be obtained quickly, and more than 10 secondary fingerprint structures can be extracted from these fingerprint images, which provides quantitative evidences for criminal investigation. • No sample paper pre-treatment required, and it is non-destructiveness and non-contact. • It can quickly detect the fingerprint on large-scale paper. • It can realize sensitive and high resolution detection. • It can get high signal-to-noise ratio of fingerprint detection on paper. • It can obtain secondary fingerprint structures. [ABSTRACT FROM AUTHOR]

This paper examines the use of high-powered performance-based incentives for civil servants, focusing on drug-related cases registered by the Russian police. Using an event study approach and bunching analysis, I show that the incentives arising from the performance evaluation system of police officers can significantly influence their behavior. Specifically, I find evidence suggesting that this impact can result in the manipulation of drug quantities seized by the police, moving offenders from below to above the punishment threshold. Further negative consequences of the strong performance-based incentives are inequality in the enforcement of law, prolonged sentences, and increased probability of pretrial detention. Thus, I determine that police officers are more likely to manipulate the drug quantities seized from men. I also find that the manipulation increases the probability of pretrial detention by 9% and adds one more year of incarceration, which is a 67% increase on the average sentence length without manipulation. [ABSTRACT FROM AUTHOR]

This paper discusses the design procedure and first results of a large-scale magnetic air-conditioning system prototype demonstrated in a relevant environment compatible with the Technology Readiness Level (TRL) 6. The prototype, which contains all components of a functional cooling system, was experimentally evaluated in an especially developed calibrated calorimeter designed according to international technical standards for testing split-type air-conditioning units. The proposed experimental analysis is one of the first to quantify the impact of external losses associated with the heat exchangers on the cooling system performance. For outdoor and indoor temperatures fixed at 35 and 27 °C, respectively, the coefficient of performance disregarding thermal, flow and mechanical losses beyond the limits of the active magnetic regenerator was 5.72, corresponding to a second-law efficiency of 20.7%. When these losses and other essential operating variables, such as the heat exchanger fan power and the valve power consumption, are included, one-order-of-magnitude reductions are observed in the performance parameters, indicating that they should not be neglected in realistic assessments of not-in-kind cooling technologies. • Design and evaluation of a TRL-6 magnetic air-conditioning prototype is presented. • Tests conducted in a calibrated calorimeter for split-type air-conditioning units. • Impact of heat exchanger losses on the performance parameters is quantified. • The AMR coefficient of performance and second-law efficiency are 5.72 and 20.7%. • Internal and external losses are highly detrimental to the system performance. [ABSTRACT FROM AUTHOR]

A fuel cell is a power generation device that directly converts chemical energy into electrical energy through chemical reactions; fuel cells are widely used in aerospace, electric vehicle, and small-scale stationary engine applications. The complex phenomena including mass/heat transfer, electrochemical reactions, and ion/electron conduction, can significantly affect the energy efficiency and durability of fuel cells, but are difficult to determine completely. Machine learning (ML) performs well in solving complex problems in engineering applications and scientific research. In this paper, a systematic review is conducted to explore ML methods, including traditional ML and deep learning (DL) methods, applied to fuel cells for performance evaluation (material selection, chemical reaction modeling, and polarization curves), durability prediction (state of health, fault diagnostics, and remaining useful life), and application monitoring. Then comparisons of traditional ML and DL methods are discussed, while the similarities and differences between ML and integrated physics simulations are also concluded. Eventually, the scope of ML methods applied to fuel cells is presented, and outlooks of future researches on ML applications in fuel cells are identified. • A systematical review is conducted to study on tradition ML and DL methods applied to fuel cells. • Applications of ML in performance evaluation, durability prediction and application monitoring of fuel cells are analyzed. • The comparisons of tradition ML and DL methods are investigated. • Similarities and differences between ML and that integrated physics simulation are discussed. • Scope of ML methods applied to fuel cells for local and global problems is presented. [ABSTRACT FROM AUTHOR]

Network-on-Chip (NoC) is the state of the art on-chip interconnection network for packet based communication. NoCs can offer low packet latency, high bandwidth, high throughput with minimum area, better energy efficiency and fault tolerance. Routers are the basic building blocks of the NoCs. In this paper, we present the design of a Congestion Aware Router for NoC which is then implemented using Vivado HLS. The router is then used to develop a scalable NoC based on mesh topology. Using the NoC as a test bed we carry out simulations and estimate performance metrics like latency, waiting time and total packets handled for various configurations of NoC. Provisions to alter parameters like buffer depth, packet size, packet injection interval and traffic are also added. Further, we propose a simple mechanism for detecting congestion at the router. The congestion metric is then used to adapt the XY dimension order routing into a Congestion Aware minimal adaptive X/Y routing strategy with very low hardware overhead. The proposed routing method is compared against conventional XY DOR, GCA routing and RCS based routing algorithms for different parameter variations. The results show that the proposed routing method can reduce packet latency for different traffic patterns at medium packet injection rates. • A Vivado HLS implementation of NoC Simulator. • Performance metrics like latency, waiting time and total packets are estimated. • Effect of traffic pattern, size of the mesh and packet size is carried out. • Proposed routing algorithm has been compared with GCA and RCS algorithms. • HLS NoC simulator results are compared against state-of-the-art Booksim simulator. [ABSTRACT FROM AUTHOR]

In this paper, we explore the sensitivity of the length tests described in the VDI/VDE 2634-1 guideline to systematic errors in a passive stereo vision system. The results reported here are based on a stereo vision system set up on the table of a Cartesian coordinate measuring machine (CMM) and simulations that match the experimental conditions. The stereo vision system is calibrated using a checkerboard pattern resulting in estimates for 26 camera model parameters. Errors in these model parameters cause errors in the triangulated 3D points, thus resulting in length errors evaluated from those points. In the first part of this study, we consider a grid of points in the measurement volume of the stereo vision system and simulate the effect of induced systematic errors in each model parameter to determine the resulting error in the length for all lines (i.e., between all pairs of points) in that grid. We identify the lines that provide the maximum error in the length for each model parameter. Thus, we identify a collection of lines, which we refer to as model-based lines, that provide maximum sensitivity to the model parameters. Also, through simulations, we assess whether the lines defined in the VDI/VDE guideline are sufficient to detect the systematic errors in the stereo vision system. In the second part of this study, we evaluate the performance of the stereo vision system, i.e. , assess the effect of errors in the model parameters, by using the CMM as the reference. For this purpose, the CMM is commanded to move to the set of points in the rectangular grid previously considered in the simulations with the stereo vision system tracking a small checkerboard target installed on the ram of the CMM. We compare the VDI/VDE and model-based lines in terms of the experimentally obtained length errors. The studies show that selection of lines based on the model (determined through simulations and verified experimentally) is advantageous because of the superior ability in detecting systematic errors in stereo vision systems. • Assessed the sensitivity of lines defined in the VDI/VDE 2634-1 guideline to systematic errors in passive stereo-vision systems. • Identified the position and orientation of lines in measurement volume that provides maximum sensitivity to systematic errors. • Built a stereo-vision system on a CMM and experimentally determined the length errors between any pair of points in a rectangular grid. • Compared the length errors for the VDI/VDE 2634-1 lines against the length error we identified through simulation. • Demonstrated that the lines based on the model is advantageous because of the superior ability in detecting systematic errors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proposed a low-carbon fuel ship power system configuration approach. • Ship demands from the perspective of water area, routes and ship types. • Constructing green low-carbon fuel ship power system from five dimensions. • Demand-configuration-integration-evaluation form a selection framework. The current global consensus to reduce greenhouse gas emissions has placed the maritime industry under increasing pressure to achieve carbon reduction and decarbonization. Low-carbon and zero-carbon power stand out as crucial means for ships to effectively cut emissions. However, implementing such power for ships is immensely intricate due to constraints like water conditions, routes, vessel types, demand, alternative fuels, and carbon reduction policies. Addressing these challenges, this paper establishes a high-level framework for low-carbon power systems in ships. Firstly, it focuses on low-carbon fuels like liquefied natural gas (LNG), liquefied petroleum gas (LPG), methanol, and biofuels, analyzing and summarizing the demands for low-carbon power in ships. Secondly, it offers a comprehensive overview of the configuration elements of low-carbon ship power systems across five dimensions: fuel, power module, propulsion method, aftertreatment module, and propulsion module. Based on this analysis, the paper proposes a configuration approach termed "demand-configuration-integration-evaluation" and presents six typical configurations for low-carbon ship power systems. Lastly, the paper outlines steps for evaluating low-carbon power systems. This framework and methodology cater to various water conditions (inland/offshore/offshore) and are adaptable to different vessel types (container ships, bulk carriers, cruise ships, and offshore engineering vessels). This systematic study offers crucial insights and references for ship designers and owners in the selection and design of new low-carbon power ships. [ABSTRACT FROM AUTHOR]

• Investigation of a solar energy storage system under low-grade solar energy. • Dynamic heat storage and release processes under multiple parameters. • Matched collecting areas for different grades of meteorological conditions. • Performance optimization process of the solar thermal energy storage system. Designed and operational parameters matter greatly in how successful an energy storage system performs. However, a current challenge in matching suitable these parameters lies in the poor understanding of such systems' performance under dynamic weather conditions. In this paper, we investigated a phase change material (PCM) storage unit that is particularly aimed for poor-solar areas, and connected the unit to a flat plate solar collector to establish a complete solar thermal energy storage system (STESS). To optimize the system performance, different grades of solar radiation and outdoor ambient temperatures are introduced, and the effects of heat transfer fluid (HTF) flow rates and solar collecting areas are investigated numerically through multiple performance evaluation parameters. The results indicate that the solar collecting area has a significant effect on the performance of the STESS compared to that of the water flow rate. And different collecting areas of 1 m2, 1.5 m2, and 3 m2 with an optimal water flow rate of 0.06 m3/h are matched to different average daily solar radiation of 203.4 W/m2, 155.2 W/m2, 92.7 W/m2, respectively. Further for the heat release process, different heat release efficiencies from 88.32 % to 97.12 % with different energy consumption of the fan from 0.003 kWh to 0.063 kWh are obtained when the air flow rate is increased from 30 m3/h to 90 m3/h. One of the air flow rates of 60 m3/h is superior for the STESS considering higher heat release efficiency and lower energy consumption of the fan. The findings of this paper will contribute to optimizing the performance of a STESS in practical applications. [ABSTRACT FROM AUTHOR]

[Display omitted] • An optimized and efficient PV panel modeling is introduced in this paper. • A realistic analysis of five PV configurations is done using temperature prediction. • The analysis is based on the output power, fill factor and mismatch loss. • The parallel configurations are more efficient than the serial configurations. In this paper, a temperature prediction-based approach for realistic performance analysis of the solar photovoltaic system has been investigated. Dissimilar to general methods, the change in module temperature, due to changing solar irradiance, has been considered for realistic and accurate performance evaluation results under mismatch conditions. The module temperature is predicted by a linear equation representing the effects of ambient temperature, wind speed, and irradiance. An optimized technique has been implemented for photovoltaic panel modeling. It provides an accurate estimation of the series and shunt resistances of the photovoltaic panel. The proposed modeling method provides an accuracy of less than 0.02% at the maximum power point. The temperature prediction-based approach has been applied to a solar photovoltaic system of 16 panels, modeled using the proposed technique. Further, five photovoltaic configurations were investigated: Series, Series-Parallel, Honey-Comb, Bridge-Linked, and Total-Cross-Tied. The performance evaluation of each configuration is based on the generated maximum power, fill factor, and mismatch loss. Under mismatch conditions, the Total-Cross-Tied configuration shows a good immunity against mismatch by minimizing losses in all the considered mismatch patterns. The proposed approach provides more accurate results than the available ones because it considers the temperature effect (due to variation in ambient temperature, solar radiation, and wind speed), accounting for up to 12% reduction in output power of photovoltaic modules. [ABSTRACT FROM AUTHOR]

BeiDou Global Navigation Satellite System (BDS-3) not only performs the normal positioning, navigation and timing (PNT) functions, but also provides featured services, which are divided into geostationary orbit (GEO) and medium earth orbit (MEO) satellite-based featured services in this paper. The former refers to regional services consisting of the regional short message communication service (RSMCS), the radio determination satellite service (RDSS), the BDS satellite-based augmented service (BDSBAS) and the satellite-based precise point positioning service via B2b signal (B2b-PPP). The latter refers to global services consisting of the global short message communication service (GSMCS) and the MEO satellite-based search and rescue (MEOSAR) service. The focus of this paper is to describe these featured services and evaluate their performances. The results show that the inter-satellite link (ISL) contributes a lot to the accuracy improvement of orbit determination and time synchronization for the whole constellation. Compared with some other final products, the root mean squares (RMS) of the BDS-3 precise orbits and broadcast clock are 25.1 cm and 2.01 ns, respectively. The positioning accuracy of single frequency is better than 6 m, and that of the generalized RDSS is usually better than 12 m. For featured services, the success rates of RSMCS and GSMCS are better than 99.9% and 95.6%, respectively; the positioning accuracies of single and dual frequency BDSBAS are better than 3 and 2 m, respectively; the positioning accuracy of B2b-PPP is better than 0.6 m, and the convergence time is usually smaller than 30 min; the single station test shows that the success rate of MEOSAR is better than 99%. Due to the ISL realization in the BDS-3 constellation, the performance and capacities of the global featured services are improved significantly. [ABSTRACT FROM AUTHOR]

• Investigated the performance evaluation of a containerized parcel network (CPN). • Studied how container utilisation, sortation and cost changes affect the performance. • Modeled a realistic network using information/data from a postal service provider. • Method: leveraged a combination of mixed-integer programming and machine learning. • Obtained strategic insights offering realistic benchmarks for future investigations. This paper investigates different factors that affect the performance of containerised transportation in parcel delivery networks. Motivated by challenges confronted by a postal delivery company in Australia, we study how container utilisation rate, sortation decisions, and changes in cost parameters can affect the overall performance of a parcel delivery network. Leveraging a combination of mixed-integer programming and machine learning, we model a realistic parcel delivery network and evaluate its performance using data from a major postal service provider. The insights obtained from our analysis offer valuable guidance to parcel delivery companies, empowering them to make informed parcel sortation and containerisation decisions. [ABSTRACT FROM AUTHOR]

Robot comprehensive performance optimization is a high dimensional non-convex problem, which is of great significance in the practice of robotic intelligent manufacturing. Existing methods still face many challenges in performance evaluation, local optima, and planning efficiency. In this paper, a novel method based on accelerated gradient descent and directed-mutagenesis genetic algorithm (AGD-DGA) is proposed for efficient robotic motion planning and comprehensive performance optimization. Firstly, the time, energy consumption, and impact (T-E-I) are taken as the optimization objectives. In particular, the power loss sub-model is constructed, which is rarely considered in the previous research on motion optimization, and it is combined with the driving power sub-model to improve the evaluation accuracy. Next, a novel directed-mutagenesis genetic algorithm (DGA) is proposed to address the local optima problem. Compared with existing methods based on random sampling, the DGA further improves the success rate and efficiency by updating the probability model based on the adaptive Gaussian process. Moreover, a hierarchical weight updating mechanism is established to overcome the impact of additional performance indicators on the success rate of collision-free path planning. To improve planning efficiency, an incremental optimization mechanism and an adaptive fine-tuning strategy for population size are proposed to reduce unnecessary sampling, evaluation, and sorting. The simulation and experimental results in different scenarios demonstrate that the proposed AGD-DGA achieves better results than most of the mainstream algorithms in terms of optimization efficiency, success rate, and motion performance. In addition, it is also verified that the modified energy consumption model can achieve an average evaluation accuracy of more than 90% while maintaining the calculation efficiency. [ABSTRACT FROM AUTHOR]

• A morphing nose cone that can achieve length and bending angle adjustments is introduced into an underwater glider. • The optimal configurations of morphing nose cone are determined by multi-objective optimization and surrogate models. • A novel design scheme for the driving mechanism of the morphing nose cone and its principle prototype. • The morphing nose cone effectively balances the glider energy utilization rate, static stability, and voyage velocity. As an autonomous underwater vehicle with low energy consumption, underwater glider has been widely applied to long-term ocean exploration missions. To better deal with complex working environments and various mission requirements, morphing underwater gliders are receiving increasing attention. This paper attempts to introduce the morphing nose cone that can achieve length and bending angle adjustments into the glider to improve its comprehensive performance. The performance indicators of the glider include energy utilization rate, static stability, and voyage velocity. Based on dynamic analysis and CFD simulation, performance evaluation models of a glider are established, and the effect of morphing nose cone configurations on the glider's hydrodynamic characteristics is discussed. Then, mathematical optimization models for morphing parameters of the nose cone are established, and they are solved by a multi-objective optimization algorithm and surrogate model technology. Especially, the diving and ascending motion processes of the glider are separately considered in the above optimization. Finally, the multi-objective optimization results are used for guiding the driving mechanism design of the morphing nose cone, and the principle prototype of a novel design scheme is manufactured to verify the feasibility. The research methods and results will provide new development direction for the morphing underwater glider technology. [ABSTRACT FROM AUTHOR]

It is analyzed that the important part of the fingerprint image is concentrated in one part of the image, and the gray image is the part with useful information in the whole image. Therefore, this paper combines a new fingerprint image encryption algorithm proposed by combining two new one-dimensional chaotic systems, nonlinear functions, and rules with a dynamic "X" model. We propose two new one-dimensional chaotic systems, one is Sin-Cos chaotic system (SCCS) and the other is Cos-Cos chaotic system (CCCS). Firstly, the fingerprint image is binarized and the contour is extracted to get the area of the fingerprint in the image. Then, for the fingerprint area, a round of encryption is carried out by using nonlinear rules and 24 rules of the dynamic X model. Then the whole image is separated into several parts according to the fingerprint position, read into a sequence at one time, and the whole fingerprint image is scrambled and diffused synchronously by using nonlinear rules and functions. The entropy, NPCR, and UACI of the algorithm are very close to the ideal value, and the performance in time efficiency is passable. The algorithm is extremely secure in a large number of test performance analysis results. [ABSTRACT FROM AUTHOR]

Thermodynamic systems play an inestimable role in engineering applications. With the rising demands for information and automation in operation and maintenance in thermodynamic systems, the essential technologies of operation management have been quickly advancing in recent years. It is challenging to direct engineers to choose a focused strategy to accomplish effective matching between the rich monitoring information, experiential knowledge, and practical applications given the variety of thermodynamic technologies now available and suggested for distinct functional requirements. The limited adaptability of field applications is further hampered by the low compatibility between the current technologies and engineering backgrounds. The detailed technical advancements and drawbacks of managing thermodynamic systems using dynamic modeling, performance simulation, system control, fault detection, and isolation were summarized in this paper. There is a thorough comparison and analysis of the traits and adaptability of various technologies, a thorough discussion of the technical shortcomings impeding engineering applications, and some fresh suggestions for future advancement. These studies primarily focus on the use of advanced dynamic modeling techniques, effective performance simulation approaches, precise operating control schemes, and sophisticated defect detection algorithms to increase the reliability, automation, and informationalization of engineering decision-making. It supports the information development of knowledge-intensive thermodynamic systems toward human–computer intelligent interaction by providing scientific basis, improvement direction, and unique additions to contemporary research for engineers and researchers. Additionally, it offers certain focused strategies for effectively resolving technical issues. [ABSTRACT FROM AUTHOR]

A new high accuracy position measurement system has been developed. It measures the position of a 0.1 mm diameter copper-beryllium wire that informs alignment of energy beams in advanced particle accelerators. This new measurement system employs air pads to provide precision and friction free rotation of a sensor. To enable the measuring system to be positioned over the wire, a slot is required in the measuring device rotor. To optimise the design of this measuring system it was necessary to understand the performance of the air pads as they pass over the gaps (slots) in the rotor. This paper describes modelling and experiments that were performed to gain understanding of air pad performance when encountering such a surface gap. Particularly, an analytical model of the variation of load of a 20 mm × 40 mm porous air pad during the passing of a 1.5 mm wide slotted surface. Subsequent experimentation revealed that the general behaviour of the load variation had been captured effectively. The results of this analysis reveal that air pads of this size can reliably pass above an opening of this size with about 14% reduction in force. The results and the methodology presented in this paper can be used as an effective basis for future designs and studies. • Model predicting load variation, for designs of air bearings with open shafts. • Measurements of 20 × 40 mm air pads load variation when sliding over a hole. • Confirmation that the air pads can slide without friction over a hole. [ABSTRACT FROM AUTHOR]

• Ensuring the resilience of transport infrastructure assets is a challenge for governments. • A resilient performance measurement framework (PMF) is useful to future-proof transport assets. • A new PMF enabling governments to future-proof their assets against climate change is proposed. • The implications of the PMF for policy development are identified. Having efficient and effective transport infrastructure (e.g. bridges, roads, railways, airways and tunnels) in place is essential for supporting the economic and social well-being of an economy. External disturbances that emerge as a result of climate change, for example, are impacting its performance. Delivering, managing and maintaining transport assets that are resilient and adaptive to changing environmental conditions have become a priority for many governments worldwide. Central to ensuring that transport infrastructure functions at their optimum and is resilient to external changes is performance measurement, as it enables those processes that need to be modified and improved for enhancing the asset's adaptability throughout their lifecycle to be identified. Despite the importance of performance measurement in ensuring the resilience of transport infrastructure, it has received limited attention by governments in their policy making. Therefore, this paper provides a review of the extant literature and proposes a life-cycle resilient performance measurement framework (PMF) within transport context. The developed PMF is robust in comprehensively capturing the underlying perspectives that are significant for: (1) understanding the current state of the resilient level of transport assets; and (2) enabling a higher ability of the assets to adapt to environment-related changes in the future. The implications of the proposed framework for transport policy development are also discussed in this paper. [ABSTRACT FROM AUTHOR]

• Quantitative benchmark of classifiers in business process predictive monitoring. • Considers 20 classifiers from 5 families, with different sampling and validation. • Tested on real world data sets. • Credal tree emerges as most likely superior performer. Predictive analytics is an essential capability in business process management to forecast future status and performance of business processes. In this paper, we focus on one particular predictive monitoring task that is solved using classification techniques, i.e. predicting the next event in a case. Several different classifiers have been recently employed in the literature in this task. However, a quantitative benchmark of different classifiers is currently lacking. In this paper, we build such a benchmark by taking into account 20 classifiers from five families, i.e. trees, Bayesian, rule-based, neural and meta classifiers. We employ six real-world process event logs and consider two different sampling approaches, i.e. case and event-based sampling, and three different validation methods in order to acquire a comprehensive evaluation about the classifiers' performance. According to our benchmark, the classifier most likely to be the overall superior performer is the credal decision tree (C-DT), followed by the other top-4 performers, i.e. random forest, decision tree, dagging ensemble, and nested dichotomies ensemble. We also provide a qualitative discussion of how features of an event log can affect the choice of best classifier. [ABSTRACT FROM AUTHOR]

This paper summarises the scientific evaluation of the performance of a novel modelling tool, the Accident Damage Assessment Module (ADAM), developed by the Joint Research Centre (JRC) of the European Commission (EC) to assess the consequences of an industrial accident resulting from an unintended release of a dangerous substance. The ADAM tool is specifically intended to assist Competent Authorities in the European Union (EU) and European Economic Area (EEA), and their supporting research institutions, responsible for the implementation of the Seveso Directive in their countries, as well as governmental and research organisations of EU Accession and Candidate Countries, and European Neighbourhood Policy countries involved in chemical accident prevention and preparedness. In particular, the tool provides decision-making support to various functions associated with industrial risk management, enforcement and oversight, including risk analysis, land-use and emergency planning, inspection and monitoring, and the preparation and review of safety reports. Consequence assessment models are characterised by high level of complexity and of uncertainty. It is therefore of paramount importance to assess their limits. The scientific evaluation was conducted across the entire consequence assessment cycle, including the source terms and the physical effects calculations associated with the concentration toxics after airborne dispersion, the thermal radiation of chemical fires, and the explosion of vapour flammable clouds. The evaluation described in this paper was conducted on a series of relevant scenarios, by benchmarking the outcome of ADAM with the results obtained by similar software tools and with the experimental data obtained on a series of reference field campaigns, as taken from the literature. [ABSTRACT FROM AUTHOR]

• The work presented is in line with the new circular economy concepts for enabling steel-concrete composite structures to deconstruct. • The paper addresses for the first time the behaviour of demountable shear connectors at elevated temperature conducted at the University of Manchester over a period of over 2 years' time. • The results are important for both the standard committees and modelling practitioners, especially for providing the results of advanced testing programmes. This paper presents the results of an experimental programme to investigate the performance of a new composite shear connector that can be used to build deconstructable composite floors. A total of 21 push-out tests were conducted to quantify the effects of different design parameters, including different nominal temperature levels (20 °C , 100 °C , 300 °C , 450 °C , 600 °C), with the steel decking perpendicular and parallel to the steel section, two different embedded shear stud lengths and two different grades of concrete (C40/50 and C20/25). The tests were mainly carried out under steady-state condition where the specimen temperatures were increased to the desired target and the load was then applied until failure of the specimen. A few transient tests were also carried out, in which a load equal to the load carrying capacity of the steady-state test at 600 °C was applied, followed by increasing the specimen temperature until failure. Three modes were observed: (i) concrete crushing with stud fracture, (ii) stud fracture and (iii) concrete pull-out. Concrete pull-out occurred only on one specimen with concrete grade C20/25. It is found that the main failure mode at elevated temperatures not exceeding 400 °C was initiated by concrete crushing, concomitantly producing ductile stud damages. At elevated temperatures above 400 °C, the failure mode changed to shear stud fracture. The Eurocode 4 calculation equations were shown to produce shear connector resistances to be in reasonable agreement with the steady state results for the higher-grade concrete, even though the previous equations were developed for welded shear studs. The transient state tests failed at lower temperatures than the target temperature of 600 °C, indicating it may not be safe to use steady state tests for evaluation of shear connector resistance at high temperatures. [ABSTRACT FROM AUTHOR]

• LNG vaporizer uses the multi-stream type with cold energy recovery. • Cryogenic liquid self-evaporating gas serves as the medium for heat exchange. • Three multi-stream heat exchangers integrate into a heat exchange network. • Multi-objective algorithm based thermal-hydraulic model evaluates performance. • The feasibility of this design verifies by liquid nitrogen gasification experiment. Vaporizers are the key heat transfer device in the regasification process of liquefied natural gas (LNG), especially for the conventional onshore LNG receiving stations. This paper has proposed a novel intermediate fluid vaporizer by employing multi-stream plate-fin heat exchanger (MPFHE-IFV). Compared to traditional shell-and-tube IFVs, it can not only achieve a higher heat transfer efficiency with more compact structure using MPFHE but also realize the recovery and reuse of LNG cold energy with intermediate fluid. In this ingenious design, the self-evaporating gas of cryogenic liquid is adopted as the intermediate medium of IFV so that the equipment freezing can be effectively avoided under large flow conditions. A thermal-hydraulic design model has been established for MPFHE-IFV to determine the detailed structural dimensions as well as the heat transfer performance, and a corresponding multi-objective optimization algorithm has been adopted to obtain the minimum equipment volume, the optimal channel arrangement and fin structure, the maximum cold energy recovery efficiency and the optimal number of internal cycles. Meanwhile, the transmission process of the cryogenic exergy in MPFHE-IFV has been revealed according to the analysis of the system temperature-entropy diagram. Finally, two experimental cases based on the liquid nitrogen regasification process are conducted to evaluate the practical performance of the novel MPFHE-IFVs using the design and optimization method proposed in this paper. The results indicate that this new type of IFV can reach the highest cold energy recovery efficiency up to 95% within the 8% error range when the heat transfer capacity is 11.5 kW and the heat medium flow rate is near 330 L/h. [ABSTRACT FROM AUTHOR]

The exploitation of renewable energy sources and the use of primary energy saving techniques have been recognized as key solutions to face climate changes. The consequent energy policies are pushing the transition from a centralized power generation system to a distributed polygeneration system able to meet simultaneous heating, cooling and electricity demand. However, small scale polygeneration plants do not ensure any primary energy and cost saving without a proper sizing and operation of the plant. Furthermore, a flexible configuration of the waste heat recovery system (WHRS) adopted for polygeneration purposes can be equally important. Therefore, starting from the experimental data concerning a 15 kW micro-CHP plant previously designed and prototyped, the paper addresses the performance assessment of a CHCP plant configuration based on the same basic engine-electric generator system through the 1D thermo-fluid dynamic characterization of an alternative double water circuit WHRS. This configuration, delivering thermal power at different temperature level, could be useful to meet thermal and cooling demand from different user or when seasonal energy demand occurs. This paper also provides an effective approach for the design of WHRS which are capable to ensure a reasonable matching between the temperature level required by the user and that provided by the plant. In this way, being the energy saving dependent on the thermal power recovered and actually exploited, and so on the temperature level which characterizes the user's heat demand, primary energy savings are more easily achievable even when small scale polygeneration applications are considered. Results shows the possibility of supplying an absorption chiller and obtaining a coolling capacity of about 10.5 kW from the resulting CHCP plant configuration. [ABSTRACT FROM AUTHOR]

• High levels of automation have brought new challenges to risk management. • Traditional methods are not adequate to monitor the performance of today's modern system • System engineering perspective can give a new direction in this perspective. • However, application of this perspective requires further analysis. The paper presents a method for the development of safety indicators for a process industry application based on a system engineering perspective. Traditional approaches use probabilistic risk assessment or linear accident models which assume that accidents are linear chains of events and do not consider complex systemic factors and interactions. After BP's Texas City refinery incident, the investigation committee reported that BP had a false sense of safety performance due to providing more focus on managing personal safety rather than process safety. System engineering concepts may help the process industry to operate their activities without any severe accidents by establishing a better safety management system. This paper adopts the STAMP (System-Theoretic Accident Model and Processes) accident causation model to identify system specific indicators and also describes the proposed method with the help of a simple process industry application which is an LNG ship to ship transfer process. It compares the developed method with other methods for practical case applications. The first step of the present method is to establish the safety control structure, then safety performance indicators are identified. Further work is necessary to investigate to what degree these STAMP based indicators are complementary to indicators developed by other methods. [ABSTRACT FROM AUTHOR]

In this paper, the performance space measurement of regional innovation system was studied based on neuropsychology. Firstly, the neuropsychology and neural evolution theory were elaborated. Secondly, the genetic algorithm was used to design a regional enterprise performance space measurement model, and this was obtained by connecting the ERP production module and RBF neural network order forecast module. Finally, the algorithm and model constructed in this paper were used to predict the performance of regional foreign trade innovation system. Then, it is concluded that the model constructed in this paper includes the network with the lowest network structure complexity, the smallest training error and the least test error. Therefore, based on this premise, a good neural network that meets the actual needs of users can be obtained, which indicates that the improved method based on evolutionary neural network is effective to measure the performance of regional innovation system. [ABSTRACT FROM AUTHOR]

Elastomer seal assemblies are critical components for maintaining well integrity. Evidence suggests that failure of seal can lead to health, safety, and environmental consequences such as blowouts and oil spill. Regulators and the industry have acknowledged the need for improving design and qualification of elastomer seals, particularly for high pressure and high temperature applications. This paper provides a comprehensive review of literature, research studies, and industry standards relevant to elastomer seal assemblies used in the oil and gas wells. The paper aims to investigate failure modes and various parameters influencing the performance of seal assemblies. The ultimate objective of the review is to discuss gaps in industry standards and propose major areas of research for improving seal reliability. The industry standards primarily focus on material testing and lack sufficient guidance on equipment level design of elastomer seals. Seal qualification processes are not customized according to design, scale, and function of seal assembly. Research efforts need to be extended beyond material testing to design aspects of seal equipment such as energization method, design of housing and supporting components, functional failures, etc. There is also an imperative need for reliable techniques to extrapolate lab-scale results to field-scale applications spanning years of service. • Identification and review of material and functional failure modes. • Extensive review and gap analysis of industry standards. • Performance evaluation of seal assembly and influencing parameters. • Review of relevant experimental, modelling, and theoretical studies. • Specific research gaps for future studies. [ABSTRACT FROM AUTHOR]

Ultra-high Performance Concrete (UHPC) is an attractive choice for connecting Precast Concrete Shear Walls (PCSWs), because of its high bond strength with rebars allowing for reduced lapped rebar lengths and precision requirements. This paper proposes a new type of PCSW that uses UHPC connections only at the boundary elements, significantly streamlining the installation process of wall panels and improving construction efficiency. To evaluate its seismic behavior, a total of five walls comprising three PCSWs and two Cast-In-Place (CIP) walls were tested by cyclic loadings under both low and high axial loads. Similar failure modes characterized by bending-shear damage were captured in all five specimens. The proposed precast walls display 7.8%–8.1% greater bearing ability and 41.8% higher ductility in comparison to CIP counterparts. These precast walls also demonstrated superior energy dissipation ability, particularly under high axial loads. Following NEHRP, it was validated that the proposed precast walls using UHPC connections at boundary elements could be used in regions with high seismic activity. Moreover, the finite element (FE) models were developed, yielding simulated results that aligned reasonably with the experimental findings, and the parametric predictions were performed to further broaden the scope of experimental works. • A new type of PCSW using UHPC connections at boundary elements only is proposed. • Full-scale cyclic loading tests are performed under both low and high axial loads. • Seismic behavior is evaluated based on acceptance criteria for shear wall systems. • FE analysis is presented to simulate the structural behavior of test specimens. [ABSTRACT FROM AUTHOR]

• An experimental dataset of flow boiling heat transfer in mini channels with pin fins was built. • A transfer learning framework was proposed to predict the heat transfer coefficient. • The effects of different factors on heat transfer coefficient prediction accuracy was identified. Flow boiling in mini channels with micro pin fins is a promising heat sink technique to achieve high-efficient aircraft thermal management. The accurate prediction of its heat transfer coefficient is critical for the practical design of two-phase heat exchanger based on mini channels with micro pin fins. Previous investigation shows that heat transfer coefficient prediction accuracy of the machine learning method is generally better than that of conventional empirical correlations. However, the machine learning method cannot guarantee its prediction accuracy among different data domains. To extend the application region of the conventional machine learning method, a transfer learning framework was proposed in present study. First of all, an experimental system was built to acquire test data from different sample domains (i.e., the diamond pin fins with different geometries). Then a conventional machine learning model was developed based on the deep learning method. Furthermore, the developed deep learning model was adjusted with transfer learning process, and the performance of these two kinds of models (i.e., conventional machine learning model and transfer learning model) was comprehensively evaluated. Results showed that the conventional machine learning model had a good prediction accuracy with an overall deviation of 4.11 % but was only confined in the same data domain as training data. Differently, the transfer learning model with 70 % data set from the new domain can achieve appropriate prediction in the new domains with deviation of 4.28 %. The results of this paper demonstrated that the conventional machine learning model can extend into different domains with reasonable prediction accuracy through transfer learning frameworks. It will benefit the practical design of high-efficiency heat exchangers for aircraft thermal management. [ABSTRACT FROM AUTHOR]

This paper represents a single component multi-rate Real-Time Hybrid Simulation (mrRTHS) strategy for structural assessment of a cantilever Glass Fiber Reinforced Polymer (GFRP) beam loaded at the tip by a sinusoidal point load. This emulated structure is implemented as a simplified wind turbine blade in terms of geometry, scale and load – here with special attention paid to the root and max-chord section. Thus, the experimental substructure comprises the clamped end of the GFRP beam while the free end makes up the numerical substructure. The partitioning between the numerical and experimental substructure – referred to here as the shared boundary – includes a discrete point with 3 degrees-of-freedom (dof). The numerical substructure generates a displacement signal through a Taylor basis with a coarse time step to optimize computational resources. Using the previous displacement data points, a finer control signal is generated to ensure accurate actuator control in the transfer system. A DIC and inertia compensator is implemented to account for the compliance and dynamics imposed by the load train in the transfer system. The structural response is investigated by mrRTHS for an execution frequency in the range: 0.074 Hz – 2.96 Hz for the sinusoidal point load. The system performance is evaluated against an experimental test setup of the emulated structure – referred to here as the experimental reference. With a root-mean-square (RMS) error in the order of 8–20% between the mrRTHS and reference, the system proved successful in terms of stability and overall correlation at the shared boundary, which is considered an important milestone towards single component mrRTHS on a structure like e.g. a wind turbine blade, aircraft wing or similar cantilever-shaped large load carrying structure. • Demonstration of a single component hybrid simulation strategy capable of handling a complex partitioning. • mrRTHS strategy enables accurate actuator control by operating the numerical substructure at two different rates. • Successful single component multi-rate real-time hybrid simulation demonstrated on a cantilever beam loaded at the tip. [ABSTRACT FROM AUTHOR]

Fiber-reinforced eco-efficient concrete (FREC), as a new composite material with super high mechanical properties, has been widely used in the engineering construction. This paper reports a series of mechanical tests, covering the uniaxial compression test (UCT), Brazilian splitting test (BST), axial compression test (ACT), and four-point bending test (FBT), aimed at delving into the mechanical attributes and failure behavior of FREC incorporating steel fibers (SF) or carbon fibers (CF), with a range of dosage: 0.0 %–3.5 % straight steel fibers (SSF), 0.0 %–3.5 % hooked steel fibers (HSF), and 0.0 %–0.5 % CF. The key findings unveil the superiority of SF over carbon CF in enhancing concrete strength and elastic modulus. With the increment of fiber dosage, the mechanical parameters of FREC follow two distinct trends: one is a continuous increase; the other is an initial increment succeeded by a decrement. During the failure process, non-fiber-reinforced concrete (NFRC) and carbon fiber-reinforced eco-efficient concrete (CFREC) experience complete separation upon failure, while steel fiber-reinforced eco-efficient concrete (SFREC) exhibits delayed fracture expansion, marked by a conspicuous "fracturing but continuous" phenomenon. Furthermore, SF induces an alteration in the fracture patterns of concrete, transitioning from tensile failure to shear failure or tensile-shear failure. This study also focuses on a performance optimization and evaluation model, assessing the impact of SF and CF on a spectrum of mechanical parameters, such as strength, ductility, toughness, and cracking-resistance of FREC. Results underscore the efficacy of 3.5 % SSF in enhancing four key indicators: strength, deformability, toughness, and cracking resistance, while 3.5 % HSF improves ductility and cracking-resistance, and 0.5 % CF enhances ductility. These findings offer vital theoretical support for the deployment of FREC in anti-slide pile structures for rocky landslide scenarios, bearing substantial engineering implications. • Conduct UCT, BST, ACT and FBT to investigate the mechanical characteristics and failure behaviour of FREC with steel/carbon fibers. • Establish a comprehensive performance evaluation model of FREC using strength, deformability, ductility, toughness, and cracking-resistance indicator. • Propose optimization recommendations for the application of FREC in resistant structures of rocky slopes. [ABSTRACT FROM AUTHOR]

• As one of the key components in the high temperature PbLi experimental platform, the recuperator acts as waste heat recovery and saving electricity power. • The improved JF factor is proposed as the evaluation criteria, namely JF/D , which can determine the optimal design of recuperator that has better comprehensive performance. • The thermal hydraulic and thermal-mechanic analyses are performed to verify that it can satisfy with the multiple requirements, i.e. outlet temperature under different operating conditions, flow distribution as well as structural strength. As a candidate blanket for China Fusion Engineering and Test Reactor (CFETR), the supercritical carbon dioxide (sCO 2) cOoled Lithium-Lead (COOL) blanket is under development. To solve the key scientific issue, i.e. MagnetoHydroDynamics (MHD) effect, the high temperature PbLi experimental platform is planned for construction at the Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP). As one of the key components in this platform, the recuperator acts as waste heat recovery and saving electricity power. In this paper, two types of recuperator are designed and analyzed, including the double-tube and hairpin. Firstly, the theoretical and empirical models are used to obtain different designs by changing the structure dimensions and arrangement, then the non-dimensional evaluation criteria is improved and adopted to determine the optimal design that has better comprehensive performance, i.e. higher heat transfer capacity, lower flow resistance to reduce pressure drop and smaller consume volume of liquid metal to increase economy. Finally, the thermal-hydraulic and thermal-mechanical analyses based on the optimal design of the 3D model are further carried out, which obtains the fields of temperature, pressure, velocity as well as stress, and the results can satisfy with the multiple requirements, i.e. outlet temperature under different operating conditions, flow distribution as well as structural strength. The design methodology and analysis results will provide useful technical and data support for the following engineering design and construction of the PbLi experimental platform. [ABSTRACT FROM AUTHOR]

As photovoltaic plants (PV) age, the need for efficient monitoring of operations & maintenance (O&M) increases, helping to understand the situation of the plant, identify problems and propose solutions for future strategies. In this context, the objective of this paper is to propose a set of key performance indicators (KPIs), responsable to evaluate O&M performance in PV power plants, considering their importance and complexity mensuration levels. After refining and validating a set of KPIs using Delphi method with industry specialists, the KPIs are classified by energy performance assessment and O&M services assessment. Subsequently, the levels of importance and complexity of measurement are evaluated with stepwise weight assessment ratio analysis (SWARA) method. Finally, after obtaining this information, an importance-complexity matrix is developed, thus contemplating the proposed set of KPIs. This study presents a comprehensive set of 25 KPIs capable of quantitatively measuring the O&M performance of a PV plant. The results show that the KPIs, Performance Ratio and Spare Parts Availability are the most important in this evaluation, and KPI Contractual Availability presents greater complexity in measuring its parameters. Based on the importance-complexity matrix, it is possible to verify that the KPI, Schedule Compliance stands out compared to the others, presenting a high level of importance and a low level of complexity in its measurement. The information resulting from this study seeks to help PV plant managers to select the appropriate KPIs to measure the status of the O&M management of the PV plant. • Identification of 25 KPIs through SLR and Delphi Method. • Evaluation of importance and complexity levels of measurement with SWARA method. • Prioritization of KPIs in the importance-complexity matrix. • Performance Rate and Spare Parts Availability are the most important KPIs. • Contractual Availability KPI presents greater complexity in measuring its parameters. [ABSTRACT FROM AUTHOR]

Providing aeration is the primary purpose of a flotation machine. Novel flotation machines have directly driven significant developments in the aeration system. This paper provides a comprehensive review of the developments and evolution of bubble generation methods used in the flotation field. The gas-in-liquid dispersion mechanisms were extracted and linked to different aerator designs. The aeration methods used in flotation were classified into six major groups and further broken down into twenty sub-types. The gas dispersion characteristics and the practical engineering features of the aerators were then critically analyzed. Based on these, an evaluation scheme for aerator performance was proposed. It was suggested that three factors – technical capability, the reliability of operation, and economic viability – made up a successful aerator. When evaluating all various aerator types discussed in the current work, it was found that it was difficult for current techniques to achieve all three goals, which suggested the future direction for developing new aerators. The results benchmark an aerator operation in a flotation machine, and the resulting reflection of the current state of bubble generation systems spurs opportunities for the development of the next generation of aerators and flotation machines. The knowledge can be translatable to other areas of application of any three-phase system. • Aerators were classified into 6 groups and further broken down into 20 sub-types. • A novel perspective of preferred bubble size in flotation systems is given. • A database of bubble size and gas rate of various aerators is established. • The practical engineering features of various aerators were compared. • An evaluation scheme for aerator performance was proposed. [ABSTRACT FROM AUTHOR]

• An intelligent fire emergency response analysis model incorporating HTCPN is proposed. • A SHAP sensitivity analysis is conducted to identify the relevant importance of key factors. • Busy rate of place and the utilization rate of transition are used to identify the key influence parts. • Uncertainties underlying complex coordination among various departments are considered. • The proposed model can significantly improve the efficiency of emergency response processes. This paper proposes an intelligent fire emergency rescue analysis model in which the Hierarchical Timed Colored Petri nets (HTCPN) are incorporated to realize process control and coordination. Two indicators of places and transitions are employed to identify the key parts of HTCPN. A diagnostic analysis of group allocation is developed to determine the most appropriate way to deploy firefighters. A sensitivity analysis based on SHapley Additive exPlanations (SHAP) is conducted to identify the relevant importance of key factors on the performance of emergency. The proposed approach is applied at a Wuhan metro station. Results indicate that: (1) The firefighting and rescue part is of uppermost priority for emergency rescue time controlling; (2) Among all 19 influential factors, six key factors are tested as exerting more significant impacts on the performance of emergency; (3) The proposed model could significantly improve the efficiency of the emergency response, reducing the overall response time by 14.3%. The novelty of this research lies in the developed digital emergency rescue model, which is capable of taking uncertainties underlying complex coordination among various departments into account. The model has the potential to provide basic technology to support decision-making and help develop a human-centered emergency rescue system. [ABSTRACT FROM AUTHOR]

Information fusion systems are widely applied in many fields. However, how to quantitatively evaluate the performance of information fusion systems is still an open issue. To pioneeringly address the issue, in this paper, a performance evaluation model of information fusion systems based on Deng entropy is proposed. The proposed model quantitatively indicates the ability of evidential data fusion algorithms, including Dempster's combination rule, average combination method, Murphy's combination method, Yager's combination rule, and Dubois's combination rule, to eliminate uncertainty during the fusion process. Deng entropy serves as an indicator to characterize the uncertainty before and after fusion. We define the fusion efficiency parameter η , to numerically evaluate the performance of information fusion systems. Conflict among evidences can also be manifested in the efficiency parameter η. Several examples are presented to illustrate properties of the model. Finally, two real applications in classification are given to verify the practicability of this model. [ABSTRACT FROM AUTHOR]

From the early developments of machines for reasoning and decision making in higher-level information fusion, there was a need for a systematic and reliable evaluation of their performance. Performance evaluation is important for comparison and assessment of alternative solutions to real-world problems. In this paper we focus on one aspect of performance assessment for reasoning under uncertainty: the accuracy of the resulting belief (prediction or estimate). We propose a framework for assessment based on the assumption that the system under investigation is uncertain only due to stochastic variability (randomness), which is partially known. In this context we formulate a distance measure between the "ground truth" and the output of an automated system for reasoning in the framework of one of the non-additive uncertainty formalisms (such as imprecise probability theory, belief function theory or possibility theory). The proposed assessment framework is demonstrated with a simple numerical example. • A framework for quantitative evaluation and comparison of machine reasoning systems. • Assumption 1: the underlying phenomenon is uncertain purely due to stochastic variability. • Assumption 2: probabilistic models available for reasoning are only partially known. • A demonstration using a simple numerical example for evaluation of prediction accuracy. [ABSTRACT FROM AUTHOR]

Abstract City managers need indicators for target setting, performance assessment, monitoring, management and decision-making purposes. The choice of the most suitable indicator framework is crucial, but difficult, as it requires expert knowledge. To help cities in their choice, this paper compares seven recently published indicator standards for Smart sustainable cities. A taxonomy was developed to evaluate each of their 413 indicators against five conceptual urban focuses (types of urban sustainability and smartness), ten sectoral application domains (energy, transport, ICT, economy, etc.) and five indicator types (input, process, output, outcome, impact). The results clearly discriminate between indicator standards suited for evaluating the implementation of predominantly smart city approaches versus standards more focused on sustainability assessment. A further distinction is possible in standards almost fully oriented towards impacts reached, and standards that allow for progress evaluation according to steps in the implementation process. Some standards provide a narrow focus on output indicators evaluating the progress in implementing smart urban ICT solutions (e.g. number of smart meters installed). Cities are encouraged to complement such evaluations with impact indicators that demonstrate the effects of those solutions. This paper provides guidance for city managers and policy makers to select the indicators and standard that best correspond to their assessment need and goals, and align with their stage in Smart sustainable city implementation. Graphical abstract Unlabelled Image Highlights • 7 city indicator standards (413 indicators) analyzed and compared • Clear differences in focus on sustainability or smartness and the role of ICT • Some standards focus on short-term evaluation of efficiency in smart city deployment. • Others allow evaluation of progress in steps, and achieved (sustainability) impacts. • Guidance for choice of an indicator standard that best suits your goal and need [ABSTRACT FROM AUTHOR]

Highlights • A new ground water source heat pump with a pre-conditioner (GWHP-FAP) is proposed. • The ground water (GW) is used twice in the GWHP-FAP system. • GW is used firstly to cool fresh air and secondly to remove the condensation heat. • GWHP-FAP can maximally use the low-grade energy stored in the GW. • The energy saving performance of the GWHP-FAP is proven to be excellent. Abstract From the perspective of cascade utilization of low-grade energy stored in the ground water, a new type of ground water-source heat pump (GWHP) system with a fresh air pre-conditioner using the ground water (abbreviated to GWHP-FAP) is proposed in this paper. For the GWHP-FAP, the ground water will be firstly used to cool/heat the fresh air in a pre-conditioner, and then enters the condenser/evaporator of heat pump (HP) unit for the secondary utilization. Thus the low-grade energy stored in the ground water is maximally used, and the energy consumption of the whole HP system and buildings is reduced. The working principle and the air treatment schemes of the GWHP-FAP are described in detail in this paper. To evaluate the performance of the GWHP-FAP, an office building is taken as an example to apply the system, and six typical cities distributed in three different climatic areas in China, i.e., Beijing, Zhengzhou, Wuhan, Chengdu, Changde, Guangzhou, are selected to preliminarily discuss the applicability. The results show that the energy saving performance of the GWHP-FAP is very good. The GWHP-FAP compared with the conventional GWHP, its seasonal energy saving rates are respectively 39.2%, 34.2%, 30.1%, 36.7%, 28.4% and 16.6% for the six typical cities during the cooling mode. [ABSTRACT FROM AUTHOR]

Abstract Although researchers recognize the synergy between lean and green manufacturing, the concepts around this topic remain unstructured. When it comes to performance assessment, the elements that allow evaluating the integrated performance of lean and green are still unknown, since each separate system (lean and green) has a specific logic to assess performance. Thus, this paper systematizes the available knowledge about the relationship between lean and green to identify how these practices relate to performance criteria and how they could be integrated into a unique assessment system. To achieve this goal, we applied a systematic review aiming to extract the main contributions and gaps from the lean and green literature. The systematic literature review was conducted in two stages: selection and analysis of the studies. After selecting a set of 65 articles, the paper provides an overview of the literature trends regarding journals addressed, most cited papers, applied methods, and current research streams. Then, through a content analysis of the articles, the paper identifies the performance criteria and practices of lean and green and their relationships. Based on the main findings, we proposed a conceptual framework that helps in understanding the concepts and relationships involved in the lean and green performance assessment system. From the literature review and inspired in the framework, we suggested some possible research questions for further investigation. [ABSTRACT FROM AUTHOR]