Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Batteryless UAVs by Mimicking Bird Flight

We demonstrate the first flight of battery-free, energy harvesting, and small-sized Unmanned Aerial Vehicle (UAV). UAVs' flight times are severely constrained due to being forced to navigate the tradeoff between battery energy storage and weight. Even for UAVs that recharge their batteries mid-flight, eventually, the batteries must be replaced. We explore a new paradigm of UAVs that can survive entirely off energy harvested from the sun. These UAVs store energy momentarily in small super-capacitors before using that energy to create lift. By removing the requirement for battery recharging and replacement, these UAVs can provide extended flight times and open up new applications. Unfortunately, the design space for these UAVs is complex and interdependent. Materials, wing structure, UAV type, motor and harvester efficiency, environmental effects, and many other things significantly affect the aircraft's performance. We engage in a principled design space exploration of various UAV designs to reach battery-free mechanical flight. We explore and test multiple prototypes before landing on an ornithopter-like UAV with a solar rack on top and a single BLDC motor. We then perform the first flight of a battery-free ornithopter. This is the first work to explore zero maintenance long-term flight for small craft and could enable numerous new applications that require large-scale, sustained aircraft flight, such as wildfire monitoring, smart agriculture, and urban air quality assessment.
Skeleton-based Generative Adversarial Networks for Font Shape Style Transfer: Learning text style from some characters and transferring the style to any unseen characters

This paper presents a new font shape style transfer technique that employs a generative adversarial network (GAN) and skeleton-based input feature maps to modify a target text to match a target font shape while retaining the original text content. Our GAN model is modified from a Shape-Matching GAN which utilizes a StyleNet generator and a PatchGAN discriminator. Rather than using a base-font character images as input to the generator like other existing font transfer models, we utilize the proposed skeleton-based features as input. The experimental results show that our model can produce the unseen characters in the desired font style better than an existing method.
Self-adaptive Methods with Flexible Detection Criteria of the Battery Cell Dent Defect

For the battery cell production lines using automatic defect detection equipment, it becomes necessary to control the fluctuation of the yield rate of the production line, and adapt to the difference among the cell replacements and the incoming material processes of each batch. So the defect detection algorithm needs to adjust the detection criteria according to the target preferential rate range, which is a new challenge for artificial intelligent manufacturing in the battery industry. Taking the dent defect on the side of the battery cell as an example, based on both the traditional algorithm and the deep learning algorithm, two kinds of self-adaptive adjustment method of the defect detection criteria are proposed. The traditional algorithm employs the linear interpolation method to classify good and bad products based on depth and area information, and calculates the optimal critical values of depth and area that meet the target yield rate. The deep learning algorithm combines the convolutional neural network and the support vector machine classifiers, with the histogram of oriented gradient feature as the classifier input, so as to classify different degrees of defective products. The test results show that the detection criteria can be adjusted flexibly and automatically for the side dent defects, which could realize the self-adaption of algorithm to the target yield rate, save the manual operation time, and improve the production efficiency.
An Infrared Dim-small Target Detection Method Based on Improved YOLOv7

Efficient detection of dim-small targets with high accuracy is a difficult task in the field of infrared target tracking since the tiny size of small infrared targets significantly reduces the accuracy of conventional models. To address this issue, this paper improves YOLOv7 so that it can be applied to the detection of infrared dim-small targets. Initially, an enhanced MPConv-based pooling structure is proposed, which reduces the high false detection rate caused by white point noise. Then, a CBAM attention module is added to the backbone structure, which employs both spatial and channel attention to preserve more of the original characteristics of infrared faint targets. Finally, the EIOU loss is utilized in the Head module to increase the speed of model convergence. Experiments reveal that the improved algorithm achieves a model mAP of 70.8% on the dim-small target dataset, which represents a 3.4% improvement over YOLOv7 and outperforms other conventional algorithms.
Personalizing Time Loss Aversion to Reduce Social Media Use

This study examines the effectiveness of a novel personalization approach for persuasive and behavior change systems: time loss aversion. Focusing on time instead of money, it influences behavior. Two interventions were developed and tested to reduce daily social media use and boost non-digital activities. Participants received information about their average daily social media use in terms of a week, month, and year, with one intervention offering substitute activities. Among 231 participants, both interventions successfully reduced intentions for future social media use, revealing generational effects, with Gen Zs using social media more than Millennials. These results have practical implications for personalizing interventions that reduce excessive digital engagement.
Flexcomm Simulator: Exploring Energy Flexibility in Software Defined Networks with ns-3

The digitalization of energy generation and distribution systems opens new opportunities for devising network operation and traffic engineering strategies capable of adapting to the energy availability and sources. Despite the potential, developing and testing new approaches are challenging in production environments. Furthermore, no simulators support such integration between the communication infrastructure and the power grid. Thus, this paper introduces Flexcomm Simulator, a tool based on ns-3 that supports developing and assessing multiple strategies toward green networking and communications driven by real-time information from the power grid (i.e., Energy Flexibility). The proof-of-concept results demonstrate this contribution’s potential by implementing an energy-aware routing algorithm that adapts to real-world Energy Flexibility data in a Metropolitan Area Network (MAN). Also, it showcases the simulator’s capacity to deal with large-scale simulations through MPI-based distributed environments.
Pre-Training Across Different Cities for Next POI Recommendation

The Point-of-Interest (POI) transition behaviors could hold absolute sparsity and relative sparsity very differently for different cities. Hence, it is intuitive to transfer knowledge across cities to alleviate those data sparsity and imbalance problems for next POI recommendation. Recently, pre-training over a large-scale dataset has achieved great success in many relevant fields, like computer vision and natural language processing. By devising various self-supervised objectives, pre-training models can produce more robust representations for downstream tasks. However, it is not trivial to directly adopt such existing pre-training techniques for next POI recommendation, due to the lacking of common semantic objects (users or items) across different cities. Thus in this paper, we tackle such a new research problem of pre-training across different cities for next POI recommendation. Specifically, to overcome the key challenge that different cities do not share any common object, we propose a novel pre-training model named CATUS, by transferring the category-level universal transition knowledge over different cities. Firstly, we build two self-supervised objectives in CATUS: next category prediction and next POI prediction, to obtain the universal transition-knowledge across different cities and POIs. Then, we design a category-transition oriented sampler on the data level and an implicit and explicit transfer strategy on the encoder level to enhance this transfer process. At the fine-tuning stage, we propose a distance oriented sampler to better align the POI representations into the local context of each city. Extensive experiments on two large datasets consisting of four cities demonstrate the superiority of our proposed CATUS over the state-of-the-art alternatives. The code and datasets are available at https://github.com/NLPWM-WHU/CATUS.
Some Hybrid Soft Sets and Their Application in Decision Making

In this chapter the notions of two hybrid soft sets, namely fuzzy parameterized soft sets and vague soft sets has been discussed and some operations on them are defined. Some properties of these two hybrid soft sets under these operations are also studied. Application of fuzzy parameterized soft sets and vague soft sets in decision making has also been shown. Then the notion of similarity measure between two hybrid soft sets has been introduced and their basic properties are studied. Applications of these similarity measures in various problems like medical diagnosis and decision making have been shown. The idea of entropy of a fuzzy parameterized soft set has been introduced.
Aerodynamic and acoustic analysis of an extruded airfoil with a trailing edge device using Detached Eddy Simulation with a Discontinuous Galerkin method

In this paper the Discontinuous Galerkin (DG) method is applied for the simulation of an airfoil with a small trailing edge device (TED). The method discretizes the Reynoldsaveraged Navier-Stokes (RANS) equations including the Spalart-Allmaras turbulence equation, which can be extended easily to a Detached Eddy Simulation (DES) model. As the DG method is a high-order method, the turbulent length scale is adapted with the polynomial degree of the basis function to take the cell interior into account. This adaptation is validated on two examples, a backward facing step and a circular cylinder. The acoustic evaluation of the TED case is carried out in a post-processing step with a Ffowcs WilliamsHawkings (FW-H) method. A comparison to wind tunnel tests and a standard finite volume (FV) method for both the aerodynamic results and the acoustic results is presented.
Symplectic invariants and moduli spaces of integrable systems

Author(s): Palmer, Joseph | Advisor(s): Pelayo, Alvaro | Abstract: In this dissertation I prove a number of results about the symplectic geometry of finite dimensional integrable Hamiltonian systems, especially those of semitoric type. Integrable systems are, roughly, dynamical systems with the maximal amount of conserved quantities. Though the study of integrable systems goes back hundreds of years, the earliest general result in this field is the action-angle theorem of Arnold in 1963, which was later extended to a global version by Duistermaat. The results of Atiyah, Guillemin-Sternberg, and Delzant in the 1980s classified toric integrable systems, which are those produced by effective Hamiltonian torus actions. Recently, Pelayo-Vu Ngoc classified semitoric integrable systems, which generalize toric systems in dimension four, in terms of five symplectic invariants. Using this classification, I construct a metric on the space of semitoric integrable systems. To study continuous paths in this space produced via symplectic semitoric blowups, I introduce an algebraic technique to study such systems by lifting matrix equations from the special linear group SL(2,Z) to its preimage in the universal cover of SL(2,R). With this method I determine the connected components of the space of semitoric integrable systems. Motivated by this algebraic technique, I introduce the notion of a semitoric helix; the natural combinatorial invariant of semitoric systems. By applying a refined version of the algebraic method to semitoric helixes I classify all possible minimal semitoric integrable systems, which are those that do not admit a symplectic semitoric blowdown. I also produce invariants of integrable systems designed to respect the natural symmetries of such systems, especially toric and semitoric ones. For any Lie group G, I construct a G-equivariant analogue of the Ekeland-Hofer symplectic capacities. I give examples when the capacity is an invariant of integrable systems, and I study the continuity of these capacities using the metric I defined on semitoric systems. Finally, as a first step towards constructing a meaningful metric on general integrable systems, I provide a framework to study convergence properties of families of maps between manifolds which have distinct domains by defining a metric on such a collection.
A New Model for Time-Varying Graphs

We propose a new model for finite discrete time-varying graphs (TVGs), suitable for the representation of dynamic networks, for instance. The model we propose is based on the concept that in this class of TVGs there is typically a finite number of nodes and also a finite number of time instants. In this context, roughly speaking, an edge is able to connect any pair of nodes in any pair of time instants. This leads to the conception that in this environment an edge should be represented by an ordered quadruple of the form $(u, t_p, v, t_q)$, where $u$ and $v$ are nodes and $t_p$ and $t_q$ are time instants. Building upon this concept, we propose a new model that defines a TVG as an object $G_d = (V, E, T, \Phi)$, where $V$ is the set of nodes, $T$ is the set of time instants on which the TVG is defined, $E \subseteq V \times T \times V \times T$ is the set of edges in the TVG and $\Phi$ is a function that assigns a weight to each edge. In this on-going work, we show how key concepts such as degrees, journeys, distance, connectivity, are handled in this environment and also study the data structures used for the representation of dynamic networks built following our model. Moreover, we proof that when the TVG nodes can be considered as independent entities in each time instant, the analyzed TVG is isomorphic to a directed static graph. The basic idea behind the proof is hinted by the fact that if the nodes are elements of $V \times T$, an edge in the TVG could be seen as a pair $((u,t_p), (v,t_q))$, which in this case would represent a directed edge from node $(u, t_p)$ to node $(v,t_q)$, reducing the TVG to a simple directed graph. This is an important theoretical result because this allows the application of known results from the theory of directed graphs in the context of dynamic networks, either in a straightforward way when the nodes can be treated as independent in each time instant, or as a means for adapting known results to the more general TVG environment. In order to ascertain the generality of our proposed model, we show it can be used to represent several previous cases of dynamic networks found in the recent literature, which in general are unable to represent each other.
Online information on chronic pain in 3 countries: an assessment of readability, credibility, and accuracy

Supplemental Digital Content is Available in the Text. The quality of online information on chronic pain based on readability, credibility, and accuracy is disappointing and should be improved internationally to facilitate better chronic pain (self-) management. Abstract Objectives: To assess the readability, credibility, and accuracy of online information on chronic pain in Australia, Mexico, and Nepal. Methods: We assessed Google-based websites and government health websites about chronic pain for readability (using the Flesch Kincaid Readability Ease tool), credibility (using the Journal of American Medical Association [JAMA] benchmark criteria and Health on the Net Code [HONcode]), and accuracy (using 3 core concepts of pain science education: (1) pain does not mean my body is damaged; (2) thoughts, emotions, and experiences affect pain; and (3) I can retrain my overactive pain system). Results: We assessed 71 Google-based websites and 15 government websites. There were no significant between-country differences in chronic pain information retrieved through Google for readability, credibility, or accuracy. Based on readability scores, the websites were “fairly difficult to read,” suitable for ages 15 to 17 years or grades 10 to 12 years. For credibility, less than 30% of all websites met the full JAMA criteria, and more than 60% were not HONcode certified. For accuracy, all 3 core concepts were present in less than 30% of websites. Moreover, we found that the Australian government websites have low readability but are credible, and the majority provided all 3 core concepts in pain science education. A single Mexican government website had low readability without any core concepts but was credible. Conclusion: The readability, credibility, and accuracy of online information on chronic pain should be improved internationally to support facilitating better management of chronic pain.
Perbandingan Pre-Processing Opini Netizen Terhadap RUU PKS Menggunakan Algoritma Naive Bayes Classifier

Abstrak Proses pengesahan RUU-PKS menjadi topik pembicaraan dikalangan masyarakat khususnya sosial media, banyaknya opini yang disampaikan menyulitkan Netizen atau pengguna sosial media untuk membedakan opini negatif, positif ataupun netral. Dengan analisis sentimen opini acak tersebut dapat digabungkan dan diolah menjadi data sehingga menghasilkan sebuah informasi yang lebih jelas, pada proses sentimen analisis terdapat tahapan pre-processing. Untuk melakukan proses klasifikasi atau analisis data digunakan teknik machine learning bernama Naive Bayes sebuah metode yang dibuat untuk mengklasifikasikan data berbentuk text yang mampu dimanfaatkan dalam memprediksi suatu nilai dari sekumpulan data, namun penggunaan opini terhadap isu sebagai data penelitian menghasilkan jumlah data yang tidak seimbang atau imbalance sehingga diperlukan perhitungan akurasi dengan menggunakan metode confusion marix untuk meringkas kinerja klasifikasi yang memiliki data imbalance. Penelitian ini memiliki tujuan untuk mengetahui berapa nilai f1-score dari pre-processing opini Netizen terhadap RUUPKS dengan menggunakan algoritma Naive Bayes Classifier, Mengetahui apakah tahapan preprocessing memiliki efektivitas dalam melakukan analisis sentimen pada opini Netizen terhadap RUU-PKS, Mengetahui berapa hasil perbandingan opini Netizen terhadap RUU-PKS dengan menggunakan kumpulan data cuitan pada media sosial Twitter serta mengetahui bagaimana hasil dari keseluruhan opini Netizen terhadap RUU-PKS pada sosial media Twitter. Penelitian ini menghasilkan empat kondisi pre-processing dengan 2.021 data opini dari Twitter mendapatkan nilai f1-score tertinggi pada kondisi preprocessing C yang tidak melakukan tahapan stopword namun melakukan tahapan normalisasi sebesar 72%.
An Improved Method of Iris Location

How to find the true iris position in an iris image is a key problem to be solved in iris recognition. An improved method of iris location is presented based on the previous two-step iris location combining coarse location with fine location and the improvement focuses on coarse location. The principle of the improved coarse location approach is as followings: Firstly, the grey scale difference curve for each row can be gotten after several rows are chosen which aren't adjacent each other; And then some boundary iris or pupil points are found according to the value of the cumulative sum of several adjacent points on the grey scale difference curve; At last, the iris or pupil boundary is fitted from the boundary points. Experiments show the improved method is faster and more robust.
Influence of bridge structure manipulation on the electrochemical performance of π-conjugated molecule-bridged silicon quantum dot nanocomposite anode materials for lithium-ion batteries

To assess the influence of bridge structure manipulation on the electrochemical performance of π-conjugated molecule-bridged silicon quantum dot (Si QD) nanocomposite (SQNC) anode materials, we prepared two types of SQNCs by Sonogashira cross-coupling and hydrosilylation reactions; one is SQNC-VPEPV, wherein the Si QDs are covalently bonded by vinylene (V)–phenylene (P)–ethynylene (E)–phenylene–vinylene, and the other is SQNC-VPV. By comparing the electrochemical performances of the SQNCs, including that of the previously reported SQNC-VPEPEPV, we found that the SQNC with the highest specific capacity varied depending on the applied current density; SQNC-VPEPV (1420 mA h g−1) > SQNC-VPV (779 mA h g−1) > SQNC-VPEPEPV(465 mA h g−1) at 800 mA g−1, and SQNC-VPV (529 mA h g−1) > SQNC-VPEPEPV (53 mA h g−1) > SQNC-VPEPV (7 mA h g−1) at 2000 mA g−1. To understand this result, we performed EIS and GITT measurements of the SQNCs. In the course of investigating the lithium-ion diffusion coefficient, charge/discharge kinetics, and electrochemical performance of the SQNC anode materials, we found that electronic conductivity is a key parameter for determining the electrochemical performance of the SQNC. Two probable causes for the unique behavior of the electrochemical performances of the SQNCs are anticipated: (i) the SQNC with predominant electronic conductivity is varied depending on the current density applied during the cell operation, and (ii) the degree of surface oxidation of the Si QDs in the SQNCs varies depending on the structures of the surface organic molecules of the Si QDs and the bridging molecules of the SQNCs. Therefore, differences in the amount of oxides (SiO2)/suboxides (SiOx) on the surface of Si QDs lead to significant differences in conductivity and electrochemical performance between the SQNCs.
Prevalence and Risk Factors of Trichomonas vaginalis Infection among Female Students of Prince Abubakar Audu University, Nigeria

Objective: This study aimed to determine the prevalence rate and associated risk factors of Trichomonas vaginalis infection among undergraduate female students at Prince Abubakar Audu University, Anyigba, Kogi State, Nigeria. Methods: This cross-sectional and institutional-based study involved female students who consented to screening. A total of four hundred (400) high vaginal swab samples were randomly collected from consenting female students and analyzed by wet mount preparation. Demographic and clinical information about the participants was obtained using prepared questionnaires. Results: It was observed that the overall prevalence of T. vaginalis infection among the 400 female participants was 170 (42.5%). The age ranges 14–18 and 24-28 had the highest prevalence of 50%, while the age range 19–23 had the least prevalence of 41.2%. The Ebira tribe had the highest prevalence of 60%, while the lowest prevalence was 0.0% among Hausa and others. Islam had the highest prevalence of 66.7%, while Christianity had the lowest prevalence of 40.5%. Students at the 100 level had the highest prevalence of 50%, and those at the 200 level had the least prevalence of 38.5%. There was no significant association between T. vaginalis infection and predisposing factors such as douching, sanitation, and sexual habits. However, the study did find that females who did not use sanitary pads were at a significantly higher risk of infection, while females who did not douche their vagina with antiseptic or deodorant products had a slightly higher risk of infection. Conclusion: It is clear from the results of the present study that Prince Abubakar Audu University's undergraduate female students are at a high prevalence of 42.5% for Trichomonas vaginalis infection. The study offers crucial information about the incidence of T. vaginalis infection and the risk factors connected to it among female participants in the study area. The high prevalence of infection highlights the need for increased awareness and education about the infection and its prevention in the study area.