Miracle-dz/UniFAR-FTUs huggingface dataset:
Quasi-static modeling of a novel growing soft-continuum robot

Soft-continuum robots attract researchers owing to their advantages over rigid-bodied robots such as adaptation of the flexible structure to tortuous environments, and compliant contact mechanics. The need for new modeling methods to attain precise control for such systems has emerged from the recent rapid progress in soft robotics. This article presents a quasi-static model for a growing soft-continuum robot that is propelled via thin-walled inflated tubes, and steered by the difference between tube lengths. Therefore, the robot shaft is modeled as a series of inflated beams under deformation. A quasi-static model coupled with a kinematic model is developed to accurately position the end effector while accounting for the inflated beam stiffness and end-effector loads. The proposed model calculates control parameters, namely tube lengths and tendon tensions required to maintain the end effector at a certain position. Tip deflection due to end-effector loading is calculated and kinematic model inputs are updated to correct positioning error caused by shaft deformation. The model is simulated for the soft-continuum robot moving on a path to show the change in model parameters for various end-effector positions. Results demonstrate the significance of including pressurized tube stiffness in the model for growing robots of similar type. Second, the need for tendons in addition to pneumatic actuation is emphasized for accurate positioning of the end effector under loading. The proposed model offers a potential method for simulation and control of similar growing soft-continuum robots presented in the literature.
Research of elevator real time monitoring method based on spark

With the development of economy, elevator has become one of the essential means of transportation in people’s life. However, due to the complexity of the elevator internal system, the sensors collect a large number of elevator operation data so that the reliability and real-time of data processing is very important for the safety monitoring of elevator operation. To solve this problem, this paper proposes an elevator real-time monitoring method based on spark. By using the stream data processing method provided in spark streaming, a large number of real-time data are divided into time windows, the data is divided into small batches of data below the second level and submitted to spark engine for analysis and processing, which greatly improves the speed and throughput of data processing.
Improved EMD-Based Complex Prediction Model for Wind Power Forecasting

As a response to rapidly increasing penetration of wind power generation in modern electric power grids, accurate prediction models are crucial to deal with the associated uncertainties. Due to the highly volatile and chaotic nature of wind power, employing complex intelligent prediction tools is necessary. Accordingly, this article proposes a novel improved version of empirical mode decomposition (IEMD) to decompose wind measurements. The decomposed signal is provided as input to a hybrid forecasting model built on a bagging neural network (BaNN) combined with K-means clustering. Moreover, a new intelligent optimization method named ChB-SSO is applied to automatically tune the BaNN parameters. The performance of the proposed forecasting framework is tested using different seasonal subsets of real-world wind farm case studies (Alberta and Sotavento) through a comprehensive comparative analysis against other well-known prediction strategies. Furthermore, to analyze the effectiveness of the proposed framework, different forecast horizons have been considered in different test cases. Several error assessment criteria were used and the obtained results demonstrate the superiority of the proposed method for wind forecasting compared to other methods for all test cases.
Seismoelectric and electroseismic responses to a point source in a marine stratified model

We investigate the seismoelectric/electroseismic wavefields excited by a point source in an air/seawater/three‐layered porous medium configuration containing a hydrocarbon layer. The results show that if an explosive source for excitation is used, receivers at seafloor can record the coseismic electromagnetic fields accompanying the P, S, fluid acoustic waves and the interface responses converted from the acoustic waves at seafloor interface and from the seismic waves at the interfaces beneath the seafloor. Employing a vertical electric dipole source shows that, with the exception of the interface responses converted from electromagnetic waves at seafloor, the interface responses converted from transmitted electromagnetic waves at the interfaces beneath the seafloor can also be identified. Given that the strength of the explosive source is within excitation capability of industry air guns, the generated interface responses from the hydrocarbon layer can be detected by current electromagnetic sensors considering the low ambient noise at the seafloor. Our results demonstrate the feasibility of the seismoelectric method applied to marine hydrocarbon exploration. Electroseismic modelling results suggest that it is not practical to employ this method to prospect marine hydrocarbon layer due to the weak interface response signal, unless a much larger current is injected into seafloor.
Data-Driven ILC for Trajectory Tracking in Nonlinear Dynamic Systems

The aim of this work is to propose a data-driven ILC algorithm that features fast convergence for nonlinear dynamic systems. This idea utilizes adaptive filtering that implicitly identifies the time-varying system inverse along the trajectory being tracked. By feeding the error signal through the copied inverse filter, it results in a rapidly convergent inversion-based ILC. This approach is compared to a nonlinear extension of the data-driven ILC that uses system adjoint as the learning filter. The developed algorithm is validated through simulation on a fully actuated 2 DOF Furuta pendulum.
Quantifying intrafraction organ motion and its impact on prostate and lung radiotherapy

It is well known, that intrafractional tumor motion can be remarkable in prostate and lung radiotherapy, but the clinical impact on single patients and patient populations is still under investigation. In this work, real-time motion data of implanted transponders gathered with an electromagnetic tumor tracking system during two clinical trials performed at dkfz was used for evaluations concerning this matter. For both tumor entities the occurring motion was characterized and quantified, first. Based on this data, investigations for prostate radiotherapy deal with implications of this motion on the size of safety margins and the experimental and computational quantification of dosimetric consequences for individual patients. In this first clinical trial on electromagnetic tumor tracking in lung, analyses focused on the quantification of inter- and intrafractional variations of the transponder geometry due to breathing motion and tumor shrinkage. Additionally, the correlation between internal measured lung tumor motion and external chest motion was assessed. According to our results, we conclude that real-time monitoring of the internal motion is necessary for both tumor entities to enable motion management reducing dosimetric consequences, in particular if a hypofractionated radiotherapy is applied. For lung patients it is additionally required to perform a regular control of internal tumor and transponder geometry through patient imaging.
Analysis of e-readiness on fish disease diagnosis applications and e-commerce applications to improve the competitiveness of the aquaculture sector in Indonesia

As a maritime country, Indonesia's fisheries and marine sector is the focus of the government to be developed. This sector has enormous potential. This can be seen from the GDP growth in the fisheries sector which is always above the national GDP and agriculture sector GDP, with a growth value of 6.79% until the third quarter of 2017. Ironically, this has no direct impact on the welfare of fishermen in Indonesia. Fish farmers and fishermen still face various obstacles in running their businesses. Based on the level of production, aquaculture has a very high production level, reaching more than 70% of the total national fisheries production. In order to improve the competitiveness of aquaculture products, optimal utilization of digital technology is needed from upstream to downstream. When fish farmers are able to guarantee that their products are of good quality free from disease pathogens and free antibiotics, this will be a good added value for farmers. Moreover, when they have the ability to reach market access through e-commerce applications, the welfare of fish farmers can become a reality. Although the existence of Information and Communication Technology (ICT) is known to be able to encourage the strategic role and competitiveness of businesses, its utilization among small businesses, especially fish farmers, is still relatively low. So this study aims to (1) Measure the readiness of fish farmers using upstream and downstream digital applications by measuring e-readiness index; (2) Analyzing the behavior of fish farmers on the acceptance and use of technology, and their impact on increasing the scale of business; and (3) Formulating an effective strategy for fish farmers based on mapping the existing conditions. As an initial portrait, the research was carried out in the West Java region. The analytical tool used in this study is descriptive analysis, Cluster analysis K-means, Structural Equation Modeling (SEM) and Analytical Hierarchy Process (AHP). The research hypothesis in general is that farmers who have a high level of e-readiness index category will be better at utilizing and using related digital applications. So in the end the optimal use of digital applications can increase business scale and competitiveness in the market. Keywords— technology acceptance model, aquaculture, e-readiness, fish disease diagnosis, internet marketing
Building Virtual Communities for Health Promotion Emerging Best Practices through an Analysis of the International Health Challenge & Related Literature in Second Life

Contemporary Multi-User Virtual Environments (MUVEs) allow health educators, researchers, and practitioners (ERPs) to engage students, participants, and patients through innovative and uniquely rewarding methods. The technology’s value lies in its access to non-traditional participant pools, novel forms of social interaction, and cost-effective improvements to existing methods. These benefits are built on key Web 2.0 principles, namely social networking, community synthesis, and collaborative content generation. In light of ongoing dynamic development of virtual platforms, advancements in networking and immersion technology, and sustained consumer interest, the appeal of these environments will likely increase. Linden Lab’s Second Life (SL), a widely recognized and heavily populated MUVE, illustrates the technology’s broad spectrum of possibilities through the documented efforts of early adopters involved in health promotion, research, and therapy. However, ERPs must be mindful of the medium’s complexities, technological and social parameters, and weaknesses before considering development within virtual worlds (in-world). As these environments operate independently of the real world in some aspects, knowledge of gathering and creating relevant in-world and real-world resources, attracting and retaining project interest, and addressing common obstacles is essential. Through an analysis of DOI: 10.4018/978-1-61520-777-0.ch020
Secure Energy-Efficient Resource Allocation Algorithm of Massive MIMO System with SWIPT

In this paper, we consider the resource allocation problem to maximize the minimum (max–min) user’s secure energy efficiency (SEE) in downlink massive multiple-input multiple-output (MIMO) systems with simultaneous wireless information and power transfer (SWIPT). First, transmission power and power splitting ratio are designed to achieve the max–min user’s SEE subject to harvested energy threshold, the constraints of transmission power, and power splitting ratio. Secondly, the optimization problem is non-convex and very difficult to tackle. In order to solve the optimization problem, we converted to a series of parameter optimization subproblems by fractional programming. Then, we employ the first-order Taylor expansion and successive convex approximation (SCA) method to solve parameter optimization problems. Next, a secure energy-efficient resource allocation (SERA) algorithm with the bisection method is proposed to find the max–min SEE of the system. Finally, simulation results show the effectiveness and superiority of the SERA algorithm.
Magnitude effects in lending and borrowing: empirical evidence from a P2P platform

ABSTRACT For varying borrowing and lending amounts, the corresponding subjective discount rates will also vary. A situation where high amounts correspond to lower discount rates is called a conventional magnitude effect, while the opposite is called a reverse magnitude effect. We present an overview of the theoretical arguments for both kinds of magnitude effects. Against this background, we then offer the first comprehensive empirical analysis of this issue based on real-life transaction data. To do so, we rely on more than 9,000 credit applications from the formerly largest German peer-to-peer (P2P) lending platform, Smava, between February 2007 and April 2013. We confirm that there is a conventional magnitude effect for lending money to others but a reverse magnitude effect for borrowing decisions. We suggest, as an explanation for our findings, the prevalence of cost-based determinants of magnitude effects in this special setting.
Traceable Dynamic Public Auditing with Identity Privacy Preserving for Cloud Storage

In cloud computing era, an increasing number of resource-constrained users outsource their data to cloud servers. Due to the untrustworthiness of cloud servers, it is important to ensure the integrity of outsourced data. However, most of existing solutions still have challenging issues needing to be addressed, such as the identity privacy protection of users, the traceability of users, the supporting of dynamic user operations, and the publicity of auditing. In order to tackle these issues simultaneously, in this paper, we propose a traceable dynamic public auditing scheme with identity privacy preserving for cloud storage. In the proposed scheme, a single user, including a group manager, is unable to know the signer's identity. Furthermore, our scheme realizes traceability based on a secret sharing mechanism and supports dynamic user operations. Based on the security and efficiency analysis, it is shown that our scheme is secure and efficient.
When N1=|N2|: A potential new class of model highly viscoelastic micellar fluids based on functionalised-Dipeptide solutions

Low molecular weight gels (LMWG) are used in a wide range of applications, including optoelectronics, directing cell growth and controlled drug release. Here, we investigate the rheological properties of a LMWG based on a functionalised-dipeptide (“2NapFF”) [1] which appears to behave as a surfactant at high pH in the “precursor” phase (i.e. prior to a gelation phase caused by a pH or temperature change). This new hydrogel exhibits very “stringy” behaviour and has been shown to have extremely high relaxation times using capillary breakup extensional rheometry (CaBER) [1]. Believing that it should be possible to vary the micellar aggregates formed from this gelator, and hence the rheology, by varying simple parameters such as the nature of the counterion we prepared solutions of 2NapFF at a pH of 11 using one of a number of hydroxide salts (LiOH, NaOH, KOH, RbOH, CsOH or tetrabutylammonium hydroxide (TBAOH)) to deprotonate the terminal carboxylic acid (all at a fixed concentration of 10mg/mL). We then characterised the rheology of the resulting solutions in small amplitude oscillatory shear, steady shear and extension (CaBER). Using a cone-and-plate geometry and a dedicated protocol [2] we are able to measure the first normal-stress difference N1 and using a parallel-plate geometry to measure (N1-N2). In so doing, we find for these systems that they are highly elastic (e.g. for shear rates greater than 10s N1>10 where  is the shear stress) and also, in contrast to polymeric solutions and all other reported wormlike micelles in the literature, we find that N2 is very large and equal in magnitude to N1 (i.e. N1=-N2). Given this highly elastic and unique behaviour, we propose that these solutions have the potential to be used as a new class of model highly viscoelastic fluids.
The Uses of Ludobiography: Life Writing and Game Studies

INTRODUCTION Videogames and auto/biography are not obvious bedfellows. While the idea that gamers should ‘get a life’ is not so prevalent as it once was, many would still argue that playing videogames is not really living or, at least, not the kind of living you would choose to include in an auto/biography, a genre that has tended to dwell on ‘the meaning of public achievement’ rather than the attainment of Steam Achievements (Smith and Watson 2001, 2). One might equally object that, as a form still widely understood as a vehicle for considered retrospective narratives in which authors account for past actions and assess their significance, auto/biography is fundamentally incompatible with gaming; after all, gaming culture is centred on media that address players on a subperceptual, pre-personal level, resisting ‘meaning’ (Kirkpatrick 2011, 95). It is also markedly future-oriented (Atkins 2007), perpetually anticipating the next level, the next upgrade, the next generation. The notion of interactive autobiography, meanwhile, poses its own problems. How can a game be a faithful retelling of a life story if players can alter the sequence of events? And how can it be a worthwhile game if they can’t?
Nudging construction workers towards better sun-safety behaviour: summary of the evidence for practitioners

Abstract Excessive exposure to solar ultra-violet (UV) radiation can cause skin cancer, but inadequate exposure to sunlight limits the production of vitamin D. We report a text messaging and supportive smartphone app intervention to reduce UV exposure in the summer and promote vitamin D intake in winter. Results suggest that many workers had insufficient circulating vitamin D in winter, but for the intervention group vitamin D levels increased significantly compared to the control group. In summer, workers were exposed to relatively high UV levels, which were sufficient to importantly increase their risk skin cancer. The sun-safe intervention failed to reduce exposure to solar UV, which we attribute to an entrenched belief that a suntan is desirable. We argue that a more prescriptive risk-based approach is needed to reduce the risk of skin cancer among outdoor construction workers. Graphical Abstract
A Novel Approach to Detect the Acute Lymphoblastic Leukemia Based on the Color Orthonormal Basis Entropy (COBE) and the Distribution of the Pixel Intensity (DoPI)

: One of the most dangerous cancer is acute leukemia lymphoblastic (ALL). This type of leukemia has been attacking the most of children. This research aims to detect the ALL diseases through the principal features of the object. Furthermore, this paper contributes by providing a new approach to detect the ALL disease based on the Color Orthonormal Basis Entropy (COBE) and the Distribution of the Pixel Intensity (DoPI). There are some novelties in this research. Firstly, we combined three channels features to characterize an object for increasing the performance accuracy. Secondly, we have developed a model to improve the image through a contrast enhancement filter, the noises from the image can be recognized and removed automatically, and better image result has been delivered through enhancement of the green channel selection. In this research, we proposed a novel approach to detect the ALL based on the COBE and the DoPI. This new approach is divided into four main stages, i.e., image enhancement, segmentation, feature extraction, and performance measurements. Firstly, an image was enhanced through a channel separation, enhancement of the green channel, and fusion of the green channel enhancement with the original channel, i.e., the red and blue channels. An image enhancement process is conducted by a gamma correction of the contrast stretching. The hue channel is an output of the first stage. Secondly, the Otsu algorithm was employed to obtain the best threshold. Thirdly, the COBE and the DoPI were included to discover the main features. Lastly, the Manhattan method was employed to measure performance. In this research, the second Acute Lymphoblastic Leukemia-Image Database (The 2nd ALL-IDB, usually it is called as ALL-IDB2). It is carried out to evaluate the proposed approach. The results show this proposed method has produced high accuracy at 91.67% and small standard deviation at 0.022.
Analog Optical Spatial Differentiators Based on Dielectric Metasurfaces

Analog spatial differentiator is an important optical computational device that can be potentially used in the field of high‐speed edge detection and optical image processing. In the current stage, a general method is still required to robustly design compact devices for various spectrum or complex situation. In this work, a dielectric metasurface method is proposed and experimentally demonstrated to build optical spatial differentiators. This is physically realized by a high‐quality magnetic resonance mode that is hybridized with the classic bounded surface wave via grating coupling. Experimentally, a well‐defined first‐order differentiation effect is observed at oblique light incidence. The application potential of this device is evaluated by inputting various figures. It is shown that it can perform an optical processor to trace the profiles of the figure content with a resolution better than 30.8 µm. This work may pave a robust way to build ultracompact optical computation devices for real‐time image processors, which can be freely extended to various frequencies.
Transversely Slotted SIW Leaky-Wave Antenna Featuring Rapid Beam-Scanning for Millimeter-Wave Applications

Loading effects of radiating discontinuities have been explored to increase the phase constant’ frequency sensitivity of leaky-wave antennas (LWAs), based on which a quasi-uniform transversely slotted substrate integrated waveguide LWA featuring rapid beam-scanning and its hexagonal array have been proposed and investigated for millimeter-wave applications. The design concept is simply based on the use of a short period of unit cells and a long transverse slot with a sharp inductive reactance, and it has been theoretically elaborated and effectively validated by both full-wave and circuit-based simulations. A taper design with −25 dB Taylor amplitude distribution is implemented for the proposed LWA to have a low sidelobe radiation. For practical system applications, a hexagonal array consisting of six proposed LWAs is developed to provide an omnidirectional coverage in the azimuth plane while remaining the rapid frequency-driven beam-scanning in the elevation plane. Both the measured and simulated results are in an acceptable agreement with respect to the LWA block and the associated hexagonal array in terms of circuit and radiation performances. The proposed antenna will be a good candidate to be applied for prospective millimeter-wave systems such as autonomous driving and flying.