Miracle-dz/UniFAR-FTUs huggingface dataset:
Studies on the Genus Trachys Fabricius from China (2)–Descriptions of Six New Species (Coleoptera: Buprestidae: Agrilinae: Tracheini)

Abstract This paper is the second in a series on the genus Trachys Fabricius from China. Six new species are described and illustrated from China: Trachys lingdongshanensis Peng, new species; Trachys albopilosus Peng, new species; Trachys latipennis Peng, new species; Trachys aureolus Peng, new species; Trachys quadripennis Peng, new species; and Trachys scapulis Peng, new species.
Ontology for Relating Risk and Vulnerability to Cost Overrun in International Projects

Risk management is about identifying risks, assessing their impacts, and developing mitigation strategies to ensure project success. The difference between the expected and actual project outcomes is usually attributed to risk events and how they are managed throughout the project. Although there are several reference frameworks that explain how risks can be managed in construction projects, a major bottleneck is the lack of a common vocabulary for risk-related concepts. Poor definition of risk and patterns of risk propagation in a project decrease the reliability of risk models that are constructed to simulate project outcomes under different risk occurrence scenarios. This study aims to extend previous studies in risk management by presenting an ontology for relating risk-related concepts to cost overrun. The major idea is that cost overrun depends on causal relations between various risk sources (namely, risk paths) and sources of vulnerability that interfere with these paths. Ontology is used to develop a database system that represents risk event histories of international construction projects and to construct a model for estimation of cost overrun. It will form the basis of a multiagent system that can be used to simulate the negotiation process among project participants about sharing of costs considering the risk allocation clauses in the contract, sources of vulnerability, and causal relations between risk events and their impacts. The ontology is constructed by interaction with Turkish contractors working in international markets and extensive literature review on risk-related concepts. The validation test results provide evidence that the ontology is fairly effective to help Turkish contractors to assess cost overrun by considering sources of vulnerability and risk in international construction projects.
Attribution Model of Travel Intention to Internet Celebrity Spots: A Systematic Exploration Based on Psychological Perspective

Previous studies have shown that the empathy process is the main driving factor that triggers tourists’ intention to visit Internet celebrity spots. However, the academic community has not yet formed a unified understanding of the concrete mechanism. Based on this, this study combines the connotations of meme theory and empathy theory and applies Structural Equation Modeling (SEM) to empirically analyze 340 valid samples of Internet celebrity spots visitors to explore the influence mechanism of attributional factors on travel intention. The result shows that mechanism of travel intention can be presented as a psychological model in which travel attribution of tourists to visit Internet celebrity spots is the independent variable, the travel intention is the dependent variable, and the empathy process is the intermediary variable. The influence intensity of internal attribution on affective empathy is higher than that of external attribution, while the influence intensity of external attribution on cognitive empathy has a comparative advantage, and there is a significant difference between them. Empathy process has a significant mediating effect on the relationship between travel attribution and travel intention of tourists to visit Internet celebrity spots, and the mediating effect of affective empathy is significantly greater than that of cognitive empathy. Overall, this study reveals the segmentation elements with strong explanatory power in the behavior of “internet celebrity spots punch in,” examines the practical effect of empathy process in the behavioral intention of traveling, and provides a theoretical reference for the transformation and upgrading of tourist destinations and marketing planning of online communication in the future.
Cultural Variations in Evaluation of Creative Work: A Comparison of Russian and Emirati Samples

The study investigates how cultural variations influence evaluation of creative work. Russian and Emirati undergraduate college students were asked to judge alien creature drawings produced by their country mates in previous studies’ structured imagination test. We found cultural differences in creativity judgment. Emirati participants’ judgments were significantly lower than Russian participants’ judgments. We also found that Russians judged their compatriots significantly higher than the Emirati judged their compatriots. Russians also judged foreigners significantly lower than the Emirati judged foreigners. These findings were speculatively placed in the context of the cultural differences in the implicit theory of creativity.
Interrupting the Weaponization of Trauma-Informed Practice: “… Who Were You Really Doing the ‘Saving’ for?”

Abstract We analyze tweets authored by educators during the COVID-19 pandemic, which Ibram Kendi has called a viral and a racial pandemic, and illustrate how Whiteness feeds the blaming of children and communities of color for trauma. We evaluate tweets that (1) misused trauma-informed teaching practice in ways characterized by White saviorism; (2) pushed back on these distortions by identifying and interrupting; and (3) proposed systemically trauma-informed teaching practice (SysTIP). We demonstrate the use of a set of tools for educators looking to identify and interrupt the weaponization of trauma-informed practice.
Effects of anchor pads in micro-scale BGA

Micro-scale BGA has attracted more and more interest due to their high performance/area ratio. This technology is essential for the next generation of portable devices, such as cellular phones, wireless terminals, palm computers, global position systems, and other hand-held devices. With the decrease of solder ball sizes, however, the reliability problem becomes the major concern for this kind of packages. Also with the decrease of solder volume, the function of self-alignment of solder is reduced in solder reflow process. One solution to these problems is introducing an anchor pad at each corner of packages, which is used only for mechanical connection. In this study, 3-D finite element models are used to access the effects of anchor pads to solder joint reliability of micro-scale BGA. Three configurations are considered here: normal 144 I/O BGA, 144 I/O BGA with anchor pads, and 144 I/O BGA without anchor pads. Two creep models are considered for solder joint modeling. It was found that the maximum creep strain in critical solder joints is greatly reduced after introducing anchor pads at the corner. Therefore, it is a good option to introduce the anchor pads to improve the reliability of solder joints in micro-scale BGA.
A Performance Assessment of the US Baldrige Quality Award Winners

Since 1987, 17 businesses have won the US Baldrige Quality Award, established to promote awareness of quality management among US businesses. Assesses the financial and competitive performances of these 17 companies. Previous research with respect to the quality‐performance relationship has shown a positive relationship between quality improvement and financial or market share performance. Finds that while substantial improvements in operations performance characteristics among Baldrige Award winners have coincided with the implementation of quality improvement programmes, these improvements have not always resulted in financial success. Firms should therefore view quality improvement programmes as a method for building a strong competitive foundation, not as a panacea guaranteed to result in economic health.
Recycling Wasted Energy for Mobile Charging

The rapid popularization of wireless power transfer (WPT) technology promotes the wide adoption of wireless rechargeable sensor networks (WRSNs). Traditional methods only focus on how to optimize network performance, and most of them overlook the energy waste issue induced by WPT. In this paper, we explore the potentials of recycling wasted energy when using WPT by means of freeloading. Specifically, with a slight modification on hardware, we expand the functionality of the mobile chargers (MCs), enabling them to harvest and recycle the WPT-induced wasted energy in the air to serve more sensors, which promotes energy efficiency. We model the problem, termed MEFree, as maximizing network energy efficiency by utilizing a limited number of freeloading MCs and scheduling their freeloading behaviors. Through jointly scheduling freeloading and charging tasks, the proposed scheme is able to solve the problem with a (1 − 1/e)/2 approximation ratio with a slightly relaxed budget. Extensive simulations are conducted and corresponding numerical results show that our proposed scheme significantly improves network energy efficiency by at least 18.8% and outperforms baseline algorithms by 19.1% on average in various aspects. Our test-bed experiments further demonstrate the practicability of our scheme in actual scenes.
Wideband monopulse sonar performance: cylindrical target simulation using an acoustic scattering center model

A time-domain simulation that lends itself to the study of complex ocean environments, including complex seafloor shapes and suspended objects, has been developed. This simulation is used to study the response of a monopulse sonar to the presence of rigid cylinders near the seafloor. An acoustic-scattering-center model is developed to represent the cylinders, and several examples are presented and discussed. >
Disturbance observer based control system design for inertially stabilized platform

Inertially stabilized platform (ISP) is indispensable for various imaging systems to segregate the base angular movement and achieve high LOS (Line-Of-Sight) stability. The disturbance rejection ratio and command following performance are of primary concern in designing ISP control systems. In this paper, the redundant gimbals ISP system is considered and it is shown to experience complex disturbance and parameter variation during operation. To meet advanced LOS stabilization requirement, a disturbance observer based (DOB) dual-loop controller design for ISP is proposed of which the DOB is the internal-loop. Using a nominal plant model and a low-pass filter, the disturbance signal is estimated and used as a cancellation input added to the current command of torque motor. If the DOB works well, the disturbance torque and mismatch between nominal plant and actual plant will be compensated and the internal-loop will behave as nominal model parameters. On the other hand, the external-loop will be designed for nominal model parameters to meet stabilization requirements. This paper will mainly focus on the DOB design method. Since the low-pass filter of DOB determines the sensitivity and complementary sensitivity function as will be shown in this paper, designing the filter is the most important consideration. In this paper, an optimal low-pass filter design method is proposed. The method is intuitive, simple to implement and allows on-line tuning. Simulation results show the performance enhancement of our control structure in the presence of disturbance and measurement noise.
New integrated model to estimate the manufacturing cost and production system performance at the conceptual design stage of helicopter blade assembly

This paper describes a new integrated model development to estimate the manufacturing cost and production system performance at the conceptual design stage. A fully automated conceptual framework for design for manufacturing (DFM) has been developed. An integrated product process design concept using activity based costing is applied in this paper. The new integrated model consists of four sub-modules: the geometric parameters generation module, processing time estimation module, activity based costing (ABC) module and production system performance module. All of the input-output data flows of developed modules are fully integrated for automated manufacturing cost analysis and production system performance. A developed integrated model is very useful for designers or integrated product development team to make a decision for evaluating the design alternatives and trade-offs between design and manufacturing phases at the conceptual design stage. A case study for a composite helicopter rotor blade is included.
Multi-species Seagrass Detection Using Semi-supervised Learning

This paper introduces a semi-supervised two-stage framework that leverages a large collection of unlabelled seagrass data with the guidance of a small amount of labelled seagrass data. First, a state-of-the-art Convolutional Neural Network (CNN) named EfficientNet is trained on a small number of labelled seagrass image patches. Next, the trained classifier generates pseudo labels for the unlabelled seagrass image patches. Finally, this classifier is retrained on the combination of labelled and pseudo labelled seagrass image patches. This approach achieves 98.0% multi-species detection accuracy on a newly developed seagrass dataset. Our approach on the publicly available ‘DeepSeagrass’ dataset achieves an overall accuracy of 91.3% and 93.0%, which outperforms the state-of-the-art multi-species seagrass detection accuracy of 88.2% and 92.4% for four and five classes, respectively.
ISRaft Consensus Algorithm for Autonomous Units

Consensus protocols are a key feature in decentral-ized systems where multiple unreliable nodes operate, e.g., in Blockchain technologies with many worldwide applications such as supply chain management, cryptocurrencies and information sharing. ISRaft is a consensus protocol built upon Raft, a previously developed protocol that is used for replicated state machines when a group of nodes is required to achieve a consensus related to the state of the machine. This paper therefore proposes an alternative version of the ISRaft consensus protocol to allow communication among nodes in a secured fashion while maintaining the security features of the original ISRaft algorithm even in the presence of adversarial nodes. The proposed model utilizes a trust parameter to enforce cooperation, i.e., a trust value is assigned to each node to prevent malicious activities over time. This is a practical solution for autonomous units with resource-constrained devices where a regular encrypted communication method can negatively affect the system performance.
Application of UAV-based PIV to Rivers

Flow data are key information for effective river management. In recent years, the UAV (Unmanned Aerial Vehicle) technology has been experiencing rapid development and has exhibited unique advantages in the field of ground surveying and mapping. A recent advancement in river flow measurement involves the use of UAV as an aerial platform for acquiring water surface flow velocity distributions through Large Scale Particle Image Velocimetry (LSPIV). In this paper, a uniform rotation platform has been first developed to mimic water motion and used to study the influences of time interval and UAV drift on the measurement. The results show that it is crucial to choose the appropriate time interval of the image pairs so as to reduce the calculation errors of cross correlation between PIV interrogation windows. In addition, it has been found crucial to carry out image rectification to eliminate the influence of UAV drift before cross-correlation calculation. The SURF (Speeded-Up Robust Features) method has been used for image rectification and has been illustrated to be an effective and practical method in the real-world survey of the water surface flow field on Qinhuai River, Nanjing, China and River Cam in the UK.
Parameter calibration of VIC model based on intelligent algorithm

The parameters of the hydrological model are important parts of the model, and parameter calibration plays a key role in the output of the model. To analyze the influence of different calibration methods on the simulation results of the VIC hydrological model, the parameter calibration methods are coupled with the VIC model combining the characteristics of the Qinhuai River Basin. Three automatic optimization methods, including the genetic algorithm, simulated annealing algorithm and SCE-UA(shuffle complex evolution algorithm) algorithm, are used to automatically calibrate the 6 parameters of the VIC model. Three evaluation methods of the Nash efficiency coefficient (NSE), mean square error (MSE) and percentage deviation (PBIAS) are used to optimize the parameters. The model’s simulated runoff results are compared and analyzed. The results show that the SCE-UA algorithm with the Nash efficiency coefficient as the objective function can make the VIC model parameter calibration achieve ideal results. Different objective functions have different effects on the peak runoff during the model simulation verification period. By optimizing the parameters with the Nash efficiency coefficient and mean square error as objective functions, the simulated peak runoff is more similar to the measured data. The results can provide a reference for other models parameters automatic calibration, and are of great practical significance for rapid emergency response of hydrological simulation and forecasting.
Sliding Mode Control in Power Converters and Drives: A Review

Sliding mode control (SMC) has been studied since the 1950s and widely used in practical applications due to its insensitivity to matched disturbances. The aim of this paper is to present a review of SMC describing the key developments and examining the new trends and challenges for its application to power electronic systems. The fundamental theory of SMC is briefly reviewed and the key technical problems associated with the implementation of SMC to power converters and drives, such chattering phenomenon and variable switching frequency, are discussed and analyzed. The recent developments in SMC systems, future challenges and perspectives of SMC for power converters are discussed.
Poster: Enabling Fast Forwarding in Hybrid Software-Defined Networks

Emerging Software-Defined Networking (SDN) technique brings new opportunities to improve network performance. Some SDN-enabled programmable switches are deployed in legacy networks, and thus legacy and programmable switches could coexist, generating hybrid SDNs. In this paper, we study the node upgrade for layer-2 hybrid SDN and propose Shortcutter to accelerate the transmission. Preliminary results show that the proposed Shortcutter can reduce the forwarding path’s length 7% on average, compared with baseline solutions.
Nondestructive inspection technology for plant steel structures using magneto-optical images using deep generative models

Measures against deterioration of infrastructures that were built during the high economic growth period are facing significant challenges with regard to the maintenance of infrastructures in Japan. The development of optimal nondestructive sensing and imaging technology according to the material and structure of buildings is underway to contribute to efficient and reliable maintenance of infrastructures. However, owing to the large number of materials and structures used for buildings, as well as the types of defects to be targeted, many basic studies are yet to reach the stage of practical use. In this study, we developed a magneto-optical (MO) sensor in order to visualize a “crack” in the plant steel structure and automatically detected the defects in the plant steel structure by performing deep learning on the MO image obtained. As a pretreatment for detecting anomalies in defects using the AI, we focused on the nondestructive inspection using MO imaging and performed an unprecedented image filter processing. As a result, automatically evaluation the several types of MO images using AI, the accuracy of defection identification was improved.
Emergy-based environmental accounting and analysis of the floodplain of the Lower Yellow River

The floodplain ecosystem has attracted much attention because of its great benefits in river water and sediment transportion, water environment and ecology protection, regional economic development. Different from the existing research, an emergy-based environmental accounting and analysis for the floodplain of the Lower Yellow River has been presented in this paper. The types and characteristics of the floodplain ecosystem services have been clarified. The process of emergy input-output in the floodplain of the Lower Yellow River has been analyzed. According to them, the value of ecosystem services in the floodplain of the Lower Yellow River in 2015 has been accounted. Then, based on Emergy evaluation indices, the potential sustainability has been valued. Analytical results show that, the total emergy inflow for the floodplain ecosystem of the Lower Yellow River in 2015 is 1.15E+22sej, and the total emergy outflow is 6.32E+21sej. In emergy inflow, the feedback emergy ratio is 48.77%, and the renewable emergy ratio is 25.14%. The emergy density of the ecosystem is 4.16E+12sej/m2, yet emergy per capital is 7.95E+15sej/capita, which are very low compared to the whole Yellow River Basin. The emergy yield ratio is 1.12, the emergy investment ratio is 0.92, which are also less than that of the Yellow River Basin. It implies that the development level of the Floodplain of the Lower Yellow River is very low and mainly depends on natural resources. The emergy self-support ratio of the ecosystem is 0.51, the environment load ratio is 2.98 and the emergy sustainable indice is 0.38. It indicates that the development potential is very large.
ADOR: A New Medical Dataset for Sentiment-based IR

Sentiment analysis has received attention in retrieval applications. Combining opinions such as user feelings with semantics would enhance the performance of these applications, especially when the level of urgency is essential, e.g., medical domain. However, no widely medical benchmark is known for evaluating sentiment-aware IR. In this paper, we create a dataset based on Amazon reviews for medical products and make it publicly available. To assess the compatibility of the benchmark with opinions and concepts we propose a sentiment-aware extension of TF.IDF and apply it to the dataset. This model is derived from linear combinations of sentiment-based TF.IDF score with term-based and conceptual TF.IDF scores. The benchmark could help healthcare organizations to effectively detect, rank and filter the most urgent notifications based on patient’s health status
Towards a characterization to aid in ontology reuse

Developing ontologies is not a trivial task. Reusing existing ontologies can be helpful in this matter. However, with the high number of ontologies available on the web, selecting the ontology that best fits the needs of the ontology engineer is still a complex task. Knowing the characteristics of the candidate ontologies can help the ontology engineer better decide which one to reuse. In this sense, this paper gives the first step toward an ontology characterization to aid reuse. We propose a set of properties that can be easily accessed and interpreted by the ontology engineer to make a decision about which ontology to reuse. We exemplify the use of the proposed characterization to select ontology patterns by using the GoopHub tool.