Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Bat Algorithm Optimization Strategy for Observation Matrix

Bat algorithm, as an optimization strategy of the observation matrix, has been widely used. Observation matrix has a direct impact on the reconstructed signal accuracy as a projection transformation matrix, and it has been widely used in various algorithms. However, for the traditional experimental process, randomly generated observation matrices often result in a larger reconstruction error and unstable reconstruction results. Therefore, it is a challenge to retain more feature information of the original signal and reduce reconstruction error. To obtain a more accurate reconstruction signal and less memory space, it is important to select an effective compression and reconstruction strategy. To solve this problem, an adaptive bat algorithm is proposed to optimize the observation matrix in this paper. For the adaptive bat algorithm, we design a dynamic adjustment strategy of the optimal radius to improve its global convergence ability. The results of our simulation experiments verify that, compared with other algorithms, it can effectively reduce the reconstruction error and has stronger robustness.
Dreidimensionale Uptake- und Volumenanalyse von onkologischen PET-Studien: Voxel-basiertes Bildverarbeitungstool am Beispiel von NSCLC

Der standardisierte Aufnahmewert (SUV) der 18FDG-PET ist ein wichtiger Parameter fur Dignitatseinschatzung, Therapie-Monitoring, Prognoseabschatzung und Verlaufskontrolle. Zur Bestimmung ist eine Abgrenzung des VOI (volume of interest) gegen die Umgebung erforderlich. Ziel: Entwicklung eines Verfahrens zur automatisierten Bildsegmentierung sowie Uptake- und Volumenquantifizierung von Herden mit gesteigertem Nuklid-Uptake. Patienten, Methoden: Ein Region-growing-basierter Algorithmus wurde entwickelt, der folgende Arbeitsschritte durchlauft: 1. Vorgabe eines Startpunktes innerhalb der Lasion durch den Benutzer, 2. automatische Bestimmung des maximalen Uptake der Lasion, 3. Errechnen eines Schwellenwertes als prozentualer Anteil des Maximum, 4. Schwellenwert-basierte automatische dreidimensionale Bildsegmentierung, 5. Quantifizierung des segmentierten Volumens. Das Verfahren wurde unter CAPP (Clinical Applications Programming Package, CTI) entwickelt und in die Siemens/ECAT-7.2-Software implementiert. Die Validierung erfolgte an einem Jaszczak-Phantom (unterschiedlich grose Hohlkugeleinsatze bei verschiedenen Kontrastverhaltnissen) sowie durch den Vergleich der PET-Volumina mit computertomografisch bestimmten Tumorvolumina von speziell selektierten Patienten mit NSCLC. Ergebnisse: Die Phantomstudien zeigten einen mittleren Fehler von 3,5% fur eine Volumenquantifizierung mit einem Schwellwert von 41% bei Phantomvolumina >5 ml und einem Kontrastverhaltnis ³5 : 1. Der Vergleich mit CT-Volumina ergab fur homogen nuklidbelegte Tumorherde mit nur geringer Aktivitatsaufnahme in der Umgebung eine gute Korrelation der Ergebnisse beider Verfahren (r = 0,98). Die Aktivitatskonzentration wird um durchschnittlich –41% unterschatzt, bei Verwendung eines empirischen Schwellwertes von 50% reduziert sich die Unterschatzung auf –34%. Schlussfolgerungen: Der Algorithmus ist im klinischen Alltag einfach und routinemasig anwendbar. Er ermoglicht die automatische, benutzerunabhangige und bei Vorgabe gleicher Ausgangsbedingungen reproduzierbare Segmentierung und Quantifizierung von Lasionen mit erhohtem Uptake. Das Verfahren wurde an Daten von NSCLC-Patienten validiert und sollte grundsatzlich auch fur andere Tumorarten einsetzbar sein.
An evaluation of minimum flexural reinforcement in concrete girders with an emphasis on post-tensioned segmental members

Providing the minimum flexural reinforcement requirements for concrete girders specifies that additional reserve capacity is provided over the flexural cracking limit state. This ensures that collapse will not occur upon flexural cracking. The AASHTO LRFD Bridge Design Specifications (2017) for the minimum flexural reinforcement requirement are experimentally based on research from 1962 and did not include segmental girders, which were not prevalent at the time. Furthermore, there has not been research regarding the minimum flexural reinforcement for segmental girders. There is also research suggesting that scale effects have an influence that was not captured in previous experimental programs. This thesis is completed to evaluate the minimum flexural reinforcement in concrete girders as part of the National Cooperative Highway Research Program (NCHRP) 12-94 project. The details of the construction of the reinforced concrete and pretensioned girders are presented. Experimental results and commentary of the testing on two reinforced concrete and three pretensioned girders have been documented. Further study was completed with the design and analytical study of segmental girders on important parameters used in deriving the minimum flexural reinforcement requirements regarding the AASHTO LRFD Bridge Specifications (2017). The overstrength moment ratio required through the AASHTO LRFD Bridge Specifications (2017) has been clarified, which allows for an adequacy evaluation for minimally reinforced girders. Through the experiments, it is shown that the full-scale girders perform adequately, despite having the minimum or less than minimum flexural reinforcement. There is also further evidence provided for a decreasing modulus of rupture value for an increasing beam depth. The bond condition of the reinforcement is shown to be a
The influence of boot longitudinal flexural stiffness on external mechanical work and running economy during skate roller-skiing: A case study

This case study examines the impact of boot longitudinal flexural stiffness on the total external mechanical work of a skier’s centre of mass per distance travelled in the forward direction ( W ¯ EX (J/m)) and on running economy during skate roller-skiing under submaximal steady-state conditions. Moreover, it analyses time derivatives of total W EX , of W EX performed by the roller-skis and poles, respectively, and of the directly useful mechanical work (the sum of the work to overcome centre of mass’ gravity and rolling resistance) within a typical roller-skiing cycle. Multiple roller-skiing trials (G3 technique) were performed by one subject on an inclined treadmill with boots of soft, intermediate, and stiff flexural stiffness. The orientation and magnitude of the roller-ski and pole ground reaction forces, body kinematics, VO2, and lactic acid concentration were monitored. The stiff boots had 13.4% (p < 0.01) lower W ¯ EX compared to the intermediate boots, and 20.7% (p < 0.001) lower W ¯ EX compared to the soft boots. Regarding running economy, the soft boots had 2.2% (p < 0.05) higher VO2 compared to the intermediate boots, but the same VO2 compared to the stiff boots. In conclusion, the soft boots had significantly higher W ¯ EX and running economy, while stiff boots had significantly lower W ¯ EX and intermediate boots significantly lower running economy. Moreover, W ¯ EX appears to be a better indicator of the boot flexural stiffness impact on energy efficiency than running economy.
Small-Beads Transmission and Its Application to Robot Joints

Small-beads are everywhere in our daily life. A collection of small-beads can behave macroscopically like liquid and flow. This paper presents a power transmission method referred to as “small-beads transmission” that can transmit power in all directions and convert linear motion into rotational motion and vice versa. The force transmission ratio is dependent on the resistance coefficient that is proposed to reflect the friction of small-beads and the dynamic responses of the internal particle force chains to external forces. Experiments on the resistance coefficient in pipes are conducted. The experimental results show that the proposed transmission method has great capability to provide isolation from external vibration and shock. Based on the experimental results, a small-beads transmission joint is designed and applied to robot legs to achieve human gait-like movement. This concept is also applicable to designing robotic joints and limbs, or orthoses and exoskeleton devices. The configuration of small-beads transmission is similar to that of the conventional hydraulic or pneumatic transmission in cylinder–piston system. However, the proposed method does not necessitate the use of tight sealing as that needed by hydraulic and pneumatic transmission, it is much easier to fabricate and also fit for hazardous environments.
Nonlinear Model Predictive Control for Mobile Robot Using Varying-Parameter Convergent Differential Neural Network

The mobile robot kinematic model is a nonlinear affine system, which is constrained by velocity and acceleration limits. Therefore, the traditional control methods may not solve the tracking problem because of the physical constraint. In this paper, we present the nonlinear model predictive control (NMPC) algorithm to track the desired trajectory based on neural-dynamic optimization. In the proposed algorithm, the NMPC scheme utilizes a new neural network named the varying-parameter convergent differential neural network (VPCDNN) which is a Hopfifield-neural network structure with respect to the differential equation theory to solve the quadratic programming (QP) problem. The new network structure converges to the global optimal solution and it is more efficient than traditional numerical methods. In the simulation, we verify that the proposed method is able to successfully track reference trajectories with a two-wheel mobile robot. The experimental validation has been conducted in simulation and the results show that the proposed method is able to precisely track the trajectory maintaining a high robustness based on the VPCDNN solver.
Prediction Method for Overconsolidation Ratio of Marine SoftSoil Based on the Piezocone Penetration Tests

Because of the strong structural and sensitive behavior, the properties of marine soft soil change greatly when subjected to external disturbances, which leads to great difficulty in reflecting its real mechanical properties in the laboratory soil tests. The piezocone penetration test (CPTU) is one of the main technologies for in situ testing of geotechnical engineering. CPTU has the advantages of being fast and convenient, no sampling, low disturbance to soil, large amount of data, and reliable testing. The determination of the overconsolidation ratio (OCR) based on the CPTU results can solve the problems of soil disturbance and stress release, which occur during the consolidation test in the laboratory. However, there are still some problems such as lack of strict theoretical analysis of penetration mechanism and incomplete interpretation theory of in situ test parameters of CPTU. In this paper, the CPTU cone head is assumed to be hemispherical considering the penetration mechanism of CPTU. Moreover, the compaction modes of the CPTU probe penetrating into soil are adopted as spherical and cylindrical cavity expansion modes, respectively. The ultimate expansion pressures of the probe penetrating into soil under the spherical and cylindrical cavity expansion modes are first obtained by virtue of the theory of cavity expansion. Then, two prediction methods for OCR considering the roughness and penetration rate of the cone are proposed by combining the ultimate expansion pressures of the probe penetrating the approximate closed solution of cavity expansion in the modified Cambridge model, which is suitable for predicting the OCR of marine soft clay. Finally, to verify the reliability of the two proposed prediction methods, comparisons with the in situ CPTU tests of marine soft clay in two coastal areas and two existing prediction methods are made. The comparison results show that predictions of OCR of marine soft clay in this paper are close to Wayne’s method and more accurate than Chanmee’s method since the factors such as cone roughness and penetration rate are considered in the new proposed prediction methods. In order to improve the applicability in different cases of the OCR predictions, the average values of the two proposed methods are recommended as the reference value for the OCR of marine soft soil.
An Overview and Comprehensive Comparative Evaluation of Current-Fed-Isolated-Bidirectional DC/DC Converter

Renewable energy generations have been attracting sustained attentions in academic and industry. Current-fed-isolated-bidirectional dc/dc converters (CF-IBDCs) are widely adopted in low-voltage high-current applications such as solar photovoltaic fuel cell with energy storage. This paper gives an overview and a comprehensive comparative evaluation of CF-IBDCs. The active clamped, dual half-bridge, L-L type dual active bridge, resonant-type, naturally clamped, and other type topologies of CF-IBDCs are investigated, analyzed, and compared regarding their circuit topological structures, operation characteristics, modulation methods, and soft-switching technologies. In addition, component cost models and loss models of converters are deduced and presented. On this basis, quantitative and comprehensive performance comparison of seven typical CF-IBDC topologies selected from each type is conducted in terms of costs, losses, weight, volume, and power density for the given system specifications and design constraints. Finally, the application range of different CF-IBDCs and future trend are presented to encourage further development.
The clustering methods in graph models of social networks

Analysis of social networks based on graph models allows determining the associated subgroups and visualizing the results. The basic methods of research communities in graph models of social networks are clustering methods: Modularity, Centrality, Hierarchical, Spectral, K-means, PAM (Partitioning Around Medoids). In the methods of searching for communities, the results essentially depend on the chosen metric the measure of similarity of the participants. As a measure of similarity, we proposed to choose an averaged centrality, which takes into account a number of properties for participants. The new method for clustering graph models based on averaging of centrality is represented. As an example, clustering of a subgroup of a social network consisting of hundreds of participants is performed. The results of clustering for the proposed method are compared with the main methods. The similarities of the distinguished subgroups are verified by means of the cosine and correlation coefficients of vertex similarity, the Jaccard and Dice similarity coefficients. We proposed a new metric the average coefficient based on the coefficients of vertex similarity. A comparative analysis of clustering results showed that the proposed method for clustering graph models has an accuracy in determining clusters that is comparable with methods Spectral, Hierarchical, K-Means, and surpasses the accuracy of methods PAM, Centrality, Modularity 1008 T. V. Zudilova and S. E. Ivanov
Anonymization of Sensitive Quasi-Identifiers for l-Diversity and t-Closeness

A number of studies on privacy-preserving data mining have been proposed. Most of them assume that they can separate quasi-identifiers (QIDs) from sensitive attributes. For instance, they assume that address, job, and age are QIDs but are not sensitive attributes and that a disease name is a sensitive attribute but is not a QID. However, all of these attributes can have features that are both sensitive attributes and QIDs in practice. In this paper, we refer to these attributes as sensitive QIDs and we propose novel privacy models, namely, (l1, …, lq)-diversity and (t1, …, tq)-closeness, and a method that can treat sensitive QIDs. Our method is composed of two algorithms: An anonymization algorithm and a reconstruction algorithm. The anonymization algorithm, which is conducted by data holders, is simple but effective, whereas the reconstruction algorithm, which is conducted by data analyzers, can be conducted according to each data analyzer's objective. Our proposed method was experimentally evaluated using real data sets.
Mining Weakly Labeled Web Facial Images for Search-Based Face Annotation

: This paper investigates a framework of the search-based totally face annotation by mining weakly labeled facial images that are freely available on the world wide web. the one difficult trouble for the search-based face annotation scheme is how to efficiently perform annotation by means of exploiting the list of most comparable facial images and their weak labels which might be regularly noisy and incomplete. Tackleof this trouble, we recommend an powerful unsupervised label refinement method for refining the labels of web facial images the use of machine learning strategies. We formulate the learning trouble as convex optimization and develop powerful optimization algorithms to remedy the huge-scale learning task efficiently. further speed up the proposed scheme, we additionally recommend a clustering-primarily based approximation algorithm which can enhance the scalability extensively. We have got carried out an intensive set of empirical researches on a huge-scale web facial image test bed, in which encouraging outcomes showed that the proposed ULRalgorithms can considerably enhance the overall performance of the promising SBFA scheme.
Inkjet-based deposition of polymer thin films enabled by a lubrication model incorporating nano-scale parasitics

Thin film lubrication theory has been widely used to model multi-scale fluid phenomena. Variations of the same have also found application in fluid-based manufacturing process steps for micro- and nano-scale devices over large areas where a natural disparity in length scales exists. Here, a novel inkjet material deposition approach has been enabled by an enhanced thin film lubrication theory that accounts for nano-scale substrate parasitics. This approach includes fluid interactions with a thin flexible superstrate towards a new process called Jet and Coat of Thin-films (JCT). Numerical solutions of the model have been verified, and also validated against controlled experiments of polymer film deposition with good agreement. Understanding gleaned from the experimentally validated model has then been used to facilitate JCT process synthesis resulting in substantial reduction in the influence of parasitics and a concomitant improvement in the film thickness uniformity. Polymer films ranging from 20 to 500 nm mean thickness have been demonstrated with standard deviation of less than 2% of the mean film thickness. The JCT process offers advantages over spin coating which is not compatible with roll-to-roll processing and large area processing for displays. It also improves over techniques such as knife edge coating, slot die coating, as they are limited in the range of thicknesses of films that can be deposited without compromising uniformity.Thin film lubrication theory has been widely used to model multi-scale fluid phenomena. Variations of the same have also found application in fluid-based manufacturing process steps for micro- and nano-scale devices over large areas where a natural disparity in length scales exists. Here, a novel inkjet material deposition approach has been enabled by an enhanced thin film lubrication theory that accounts for nano-scale substrate parasitics. This approach includes fluid interactions with a thin flexible superstrate towards a new process called Jet and Coat of Thin-films (JCT). Numerical solutions of the model have been verified, and also validated against controlled experiments of polymer film deposition with good agreement. Understanding gleaned from the experimentally validated model has then been used to facilitate JCT process synthesis resulting in substantial reduction in the influence of parasitics and a concomitant improvement in the film thickness uniformity. Polymer films ranging from 20 to 500 n.
Governing environmental change in international river basins: the role of river basin organizations

Environmental change such as variability in water availability, extreme events like floods and droughts, or water pollution pose a serious challenge to the effective management of internationally shared water resources. River basin organizations (RBOs) play an important role in addressing such challenges, developing responses and building resilience. The purpose of this paper is to investigate the ability of RBOs to respond to changes by identifying institutional mechanisms and management practices that have been established by the respective institutions to react to transformations in the basins’ environment. Drawing on the literature of neo-institutionalism and hydropolitics, an analytical framework is developed that includes the following potential determinants for adaptive capacity: membership structure, functional scope, decision-making mechanisms, data and information sharing, dispute-resolution mechanisms, finances and donor support. Subsequently, the framework is applied to two case studies, the Okavango and the Mekong Basin. It is found that the inclusion of adaptation mechanisms contributes to ensuring river basins’ resilience to environmental change while the lack of RBO-internal adaptation mechanisms can hamper resilience and threaten sustainable development. Among these, the membership structure, functional scope as well as data and information-sharing mechanisms are particularly important for building the basis for long-term resilience to change.
A Knowledge Development Perspective on Literature Reviews: Validation of a new Typology in the IS Field

Literature reviews (LRs) play an important role in the development of domain knowledge in all fields. Yet, we observe a lack of insights into the activities with which LRs actually develop knowledge. To address this important gap, we (1) derive knowledge building activities from the extant literature on LRs, (2) suggest a knowledge-based typology of LRs that complements existing typologies, and (3) apply the suggested typology in an empirical study that explores how LRs with different goals and methodologies have contributed to knowledge development. The analysis of 240 LRs published in 40 renowned IS journals between 2000 and 2014 allows us to draw a detailed picture of knowledge development achieved by one of the most important genres in the IS field. An overarching contribution of our work is to unify extant conceptualizations of LRs by clarifying and illustrating how LRs apply different methodologies in a range of knowledge building activities to achieve their goals with respect to theory.
Performance Evaluation of Recycled Asphalt Pavement Materials and Cold Recycling Mixtures Designed with Vibratory Compaction Method

In this paper, the basic composition and performance evaluation of the recycled asphalt pavement (RAP) materials were firstly analyzed, and two methods were proposed to evaluate strength characteristics of RAP materials, including a triaxial method for the residual strength and the mortar cementing method for the strength of RAP lump. Then, the cold recycling technology was applied on RAP materials with emulsified asphalt by using vibratory compaction and heavy-duty compaction methods (Proctor compaction method), and the results showed that the maximum dry density obtained by heavy-duty compaction was closer to the actual situation. Finally, the effects of wetting water, emulsified asphalt dosage and curing conditions on the performance of the specimens were investigated. It was found that when the emulsified asphalt was mixed uniformly, whether or not to add the wetting water have almost no effect on the strength of the molded specimens. When the matrix asphalt content of the emulsified asphalt was 30%~60%, the water could be directly added to the cold recycling mixture. The intensity of accelerated curing for two days at 40 °C was approximately equal to that of natural curing for three days, while that of accelerated curing for three days at 40 °C was approximately equal to that of natural curing for seven days, which provided a basis for the short-term laboratory test.