Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Reconfigurable Full-Metal Cavity-Backed Slot Antennas Using Movable Metal Posts

Novel design concept of reconfigurable full-metal cavity-backed slot antennas (CBSAs) using movable metal posts is proposed in this article. It is found that the cavity mode with purely directional electric field is only affected by the metal post to be placed in parallel to its electric field. Thus, two orthogonal cavity modes TE101 and TE011 can be perturbed by two respective metal posts so as to independently tune the resonant frequencies of these two modes. Electromagnetic energy of the cavity modes can be radiated out through the slots on the top wall of the cavity. In this context, reconfigurable slot antennas with different functionalities, such as single-band, dual-band, dual-mode wideband, the tunable frequency with constant bandwidth, and tunable bandwidth with constant frequency, are thus constituted to demonstrate its attractive design feasibility. The frequency-reconfigurable cavity-back slot antenna with movable metal posts is proposed for the first time. The utilization of the metal posts allows us to achieve a continuous frequency tuning property, while the full-metal structure of the proposed antenna holds a high power-handling capacity and a high radiation efficiency. In final, a prototype of the dual-mode wideband slot antenna is designed, fabricated, and tested to reveal its total efficiency higher than 88% and stable radiation pattern over the tuning band. Good agreement between the measured and the simulated results well validates the presented design concept.
A Low-Cost Portable Smart Card Based Attendance System

Managing attendance may be a vital record-keeping activity in any institution. There are different methods of maintaining the attendance from manual system where attendance is marked in sheets to automated attendance on the likes of biometrics. The combination of frequency Identification (RFID) with fingerprint biometric technology was to enhance the safety level and integrity of the records. The designed system not only makes the system design simpler but also enhances the productivity of the institution both in terms of man power and time. The system doesn’t only simplify the method of taking attendance but reduces error and allows for faster verification of student attendance, all with minimal human interaction. This technique will help the authorities manage the attendance system in a more organized, efficient and time saving manner. The planning of the system is straightforward and portable making it an honest candidate for commercial and academic purpose. A GUI based version and app-based version has been designed to make the system both PC and mobile friendly. The system is built with various levels of access permissions and security. The system was tested for a small group of 100 students and was found to provide accurate marking of attendance for all users.
One-step synthesis of ultrathin nanobelts-assembled urchin-like anatase TiO2 nanostructures for highly efficient photocatalysis

Nanostructured TiO2 materials with a controlled morphology and structure have drawn considerable attention to both fundamental research and practical applications owing to their unique characteristics. Herein, a novel, facile, and one-step hydrothermal approach was developed to synthesize urchin-like anatase TiO2 hierarchical nanostructures assembled from ultrathin nanobelts using urea as the morphology-directing agent. The effects of the urea concentration in the preparation process were discussed intensively. Photocatalytic experiments showed that the urchin-like anatase TiO2 nanostructures possessed a much higher degradation rate of methyl orange and phenol than the most successful commercial semiconductor photocatalyst P25. The reasons for the highly efficient photocatalytic activity was ascribed to the high specific surface area (171 m2 g−1) and ultrathin 1D nanobelts of anatase TiO2 self-assembled into the urchin-like hollow spheres. The urchin-like anatase TiO2 nanostructures as photocatalysts have potential applications in environmental and energy fields for photocatalytic degradation, hydrogen production, Li-ion batteries, and dye-sensitized solar cells. In addition, new hydrothermal method can be developed for synthesis of other hierarchical nanostructures.
INLINE THERMAL AND XENON FEEDBACK ITERATIONS IN MONTE CARLO REACTOR CALCULATIONS

In this work, we describe a method for converging nonlinear feedback during the convergence of the neutron fission source in a Monte Carlo reactor simulation. This approach involves updating feedback physics during discard batches in the Monte Carlo simulation rather than fully (or partially) converging the neutronics prior to the nonlinear update. This approach is demonstrated for a single PWR pin with thermal feedback and with both thermal and xenon feedback. Converging these feedbacks inline with the fission source is shown to have the benefit of reducing numerical instability by effectively underrelaxing the tallied quantities in the Monte Carlo simulation and improving computational performance by converging feedback within (or near to) the number of discard batches required to converge the fission source even without any feedback.
Concentration‐Specific Constitutive Modeling of Gelatin Based on Artificial Neural Networks

Gelatin phantoms are frequently used in the development of surgical devices and medical imaging techniques. They exhibit mechanical properties similar to soft biological tissues [1] but can be handled at a much lower cost. Moreover, they enable a better reproducibility of experiments. Accurate constitutive models for gelatin are therefore of great interest for biomedical engineering. In particular it is important to capture the dependence of mechanical properties of gelatin on its concentration. Herein we propose a simple machine learning approach to this end. It uses artificial neural networks (ANN) for learning from indentation data the relation between the concentration of ballistic gelatin and the resulting mechanical properties.
A spectroscopic study of the low redshift dwarf galaxy SDSS J134326.99+431118.7 to calculate star formation rate

We present a spectroscopic study of an interacting emission-line dwarf galaxy SDSS J134326.99+431118.7. We analyzed eight-strong emission lines of wavelength in a range of 3902. 1Å to 6619. 1Å. Among them, the strongest emission line is OIII, with an intensity of 1043.6 x 10-17 erg/s/cm2/Å. These characteristic lines show a perfect Gaussian fit with a coefficient of regression greater than 98%, where the derived full width half maximum (FWHM) is less than 3.8 Å. The line ratio between Ha and Hb, (Ha/ Hb), is 2.73. This suggests that the galaxy is a starburst galaxy. Star Formation Rate (SFR) of the galaxy derived from Ha emission line flux is 0.019 and emission line metallicity derived from flux ratio between NII and Ha is 7.85 dex. These morphological and physical properties of SDSSJ134326.99+431118.7 are very similar to those of a typical Blue Compact Dwarf (BCD) galaxy. We conclude that we have presented another evidence of forming a BCD-type galaxy through a merger. BIBECHANA 18 (2021) 100-107
Understand and Search for New Aromatic Hydrocarbon Superconductors

Haiqing Lin∗,a Zhongbing Huang,a,b Guohua Zhongc and Xunwang Yand aBeijing Computational Science Research Center Beijing 100084, China bFaculty of Physics and Electronic Technology, Hubei University Wuhan 430062, China cCenter for Photovoltaics and Solar Energy, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences and The Chinese University of Hong Kong Shenzhen, 518055, China cSchool of physics and electrical engineering, Anyang Normal University Henan 455000, China E-mail: haiqing0@csrc.ac. cn, huangzb@hubu.edu. cn, gh.zhong@siat.ac. cn, xwyan@csrc.ac. cn
Implementation of the coupled two‐mode phase field crystal model with Cahn–Hilliard for phase‐separation in battery electrode particles

In this article, we present the behavior of two‐mode phase field crystal (2MPFC) method under a concentration dependent deformation. A mixed finite element formulation is proposed for the 2MPFC method that solves a 10th‐order parabolic equation. Lithium concentration diffusion in the electrode particle is captured by the Cahn–Hilliard (CH) equation and the host electrode material, LixMn2O4 (LMO), which has a face‐centered cubic (fcc) lattice structure, is modeled using 2MPFC. The coupling between 2MPFC and CH models brings about the concentration dependent deformation in the polycrystalline LMO electrode particle. The atomistic dynamics is assumed to operate on a faster time‐scale compared to the diffusion of lithium, thereby both the 2MPFC and CH models evolve on two different time‐scales. The coupled 2MPFC–CH system models the diffusion induced grain boundary migration in LMO capturing the charging and discharging state of the battery.
Epistemic Injustice and Indigenous Women: Toward Centering Indigeneity in Social Work

Using the theoretical framework of epistemic injustice articulated by philosopher Miranda Fricker as an analytic tool, we analyze recent victories of Indigenous feminist activism in gathering the stories of Indigenous women, challenging dominant meta-narratives and rewriting the herstory of Canada. We use the epistemic concept of the hermeneutic gap to consider the implications of this resistance in conjunction with the increased visibility of the intersectional positionality of Indigenous women. To illustrate our analysis, we focus on two case studies. Firstly, an individual perspective through the life journey of a feminist Anishinaabe Activist, Bridgett Perrier. Secondly, we conduct a systemic analysis of the recent Report on the National Inquiry into the Missing and Murdered Indigenous Women and Girls (MMIWG). We close with a discussion on how critical it is for social workers—especially non-Indigenous social workers—to relearn and document the meaning of the MMIWG issues. This includes recognizing Indigenous resistance, activism, and the newly formulated hermeneutic understandings that are emerging. Then, the final task is to apply these concepts to their practice and heed the calls to action which the report calls for.
A PROTOCOL STUDY FOR THE INVESTIGATION OF CHEMICALLY-ASSISTED PERFORMANCE ENHANCEMENT IN FOUR DOMAINS

Chemically-assisted performance enhancement (CAPE), which involves the use of substances in order to prevent illness or improve performance and appearance, is a recent trend of our society. CAPE has been extensively investigated in competitive sports, however, there is only limited evidence with respect to other life domains such as work and study. The objective of the present paper is to describe the protocol of a study that will address the above-mentioned gaps in the literature. The study involves a longitudinal evaluation of predictive factors derived from the Theory of Triadic Influence and Goal Systems Theory. The study aims to: a) propose a sound and comprehensive theoretical model that will include the commonalities of the manifestation of CAPE behaviours across different settings and b) highlight the conceptual differences that are necessary to be taken into account for tailor-made intervention in these settings. The study is expected to assist in the development of a comprehensive understanding of performance enhancement behaviours across different life domains. The longitudinal design of the study and the breadth of the measured variables are considered as an asset that will contribute to understanding commonalities and conceptual differences in performance enhancement behaviours across different life domains and provide the evidence base for tailor-made intervention in these domains.
Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning

Visual odometry (VO) refers to incremental estimation of the motion state of an agent (e.g., vehicle and robot) by using image information, and is a key component of modern localization and navigation systems. Addressing the monocular VO problem, this paper presents a novel end-to-end network for estimation of camera ego-motion. The network learns the latent subspace of optical flow (OF) and models sequential dynamics so that the motion estimation is constrained by the relations between sequential images. We compute the OF field of consecutive images and extract the latent OF representation in a self-encoding manner. A Recurrent Neural Network is then followed to examine the OF changes, i.e., to conduct sequential learning. The extracted sequential OF subspace is used to compute the regression of the 6-dimensional pose vector. We derive three models with different network structures and different training schemes: LS-CNN-VO, LS-AE-VO, and LS-RCNN-VO. Particularly, we separately train the encoder in an unsupervised manner. By this means, we avoid non-convergence during the training of the whole network and allow more generalized and effective feature representation. Substantial experiments have been conducted on KITTI and Malaga datasets, and the results demonstrate that our LS-RCNN-VO outperforms the existing learning-based VO approaches.
KF-Swoosh: An Efficient Spark-Based Entity Resolution Algorithm for BigData

Entity matching (EM), which is, the task of identifying records that refer to the same entity, is a critical task when constructing data warehouses. This task is often very expensive at the running time because data must be compared in pairs. This problem becomes more important when dealing with large-scale data. We propose a new parallel algorithm that divides the data using K-Medoid algorithm implemented with Spark framework. The computational experiments are done and show that we can improve the solution of a set of instances in a reduced execution time.
Caractérisation du pouvoir incrustant d'une eau et évaluation de l'efficacité d'un traitement antitartre chimique au moyen d'une sonde thermique

La precipitation forcee du carbonate de calcium peut etre provoquee par le chauffage d'une surface metallique dans des conditions controlees. On mesure ensuite l'impedance electrochimique en fonction du temps de chauffage ce qui permet d'evaluer la vitesse de depot et de caracteriser sa compacite et sa texture par la valeur de la resistance haute frequence. La methode demontre l'efficacite d'un inhibiteur d'entartrage, l'acide aminotris(methylenephosphonique) (ATMP).
The Effect of Clustering Classification and Pre-processing of Text on Improving the Accuracy of Hadith

Clustering is widely used in the context of the text, especially in classification. On the other hand, text pre-processing has a major impact on improving accuracy. This study aims to study of effect text pre-processing on improving the accuracy of hadith text, and building a model to classify the hadith categories into Saying, Doing, Reporting, and Describing, according to what was attributed to the Prophet Muhammad (PBUH), using learning algorithms. Also, this study is concerned with studying the impact on improving the accuracy of classification on text on different classifications of Hadith according to the text of Hadith and four categories of accuracy. Two Way Cluster Analysis was used to classify Hadiths according to the tags present in each Hadith. Results showed that the number of tags could be used to distinguish different classes of Hadith especially the Da'if and Maudu as the classification results showed distinct groups of both types while classification showed low accuracy or capability of the separation between Sahih and Hasan Hadiths. Also, the experimental results showed that the best classifier had given high accuracy was SGD Classifier; it achieved higher accuracy followed by Logistic Regression, and finally, Bernoulli NB.
Adaptation of the Chabot Emotional Differentiation Scale: Turkish version validity and reliability study

BACKGROUND The aim of the study was to adapt the Chabot Emotional Differentiation Scale (CED) for use in Turkey and to contribute to the Turkish literature by conducting a validity and reliability study on the scale. PARTICIPANTS AND PROCEDURE The study sample consisted of 369 volunteers between 18 and 52 years of age: 279 females (75.6%) and 90 males (24.4%), selected by the convenience sampling method. The construct validity of the scale was first tested with exploratory factor analysis and subsequently with confirmatory factor analysis. The Depression Anxiety and Stress Scale (DASS-42) and the Differentiation of Self Inventory-Short Form (DSI-SF) were used to test the convergent validity of the scale. The reliability of the scale was calculated by internal consistency and test-retest methods. RESULTS Exploratory and confirmatory factor analysis revealed that the scale has a single factor structure. In the Turkish version of the scale, the 14th item was removed from the scale due to its low factor loading. The Cronbach’s α internal consistency coefficient of the scale was found to be . 86 while the test-retest reliability coefficient was calculated as . 76. CONCLUSIONS The analysis indicates that the Turkish version of the Chabot Emotional Differentiation Scale constitutes a reliable and valid measurement tool for use with a sample in Turkey.
Recognition of Contact Event Based on MFCC of Force Signals

組立ての自動化はロボット工学の中でも古くから研究されて きたテーマであり,かつ今日においても学界・産業界双方で重 要な課題として議論されている. すでに多くの組立て工程が実 用レベルで自動化されているが,作業が高次になるに従って教 示のコストが膨大になるのが課題である. 接触を伴う作業のた め,接触モデルの非線形性と複雑さによってプログラミングに よる教示が困難なケースがしばしば生じる. プログラミングコ ストを削減するために人の作業データを用いて教示する模倣学 習 [1] [2]が研究されている. 模倣学習の問題は動作検出,動作認識,動作生成に分類でき る [3]. 最も広く研究されているのは動作そのものを模倣する動 作生成技術である [4] [5]. 高次の動作を自律的に生成するため には複雑な動作を簡易な動作の組み合わせとして構造化し,解 析する必要がある [6]. そのためにタスクの分節化を論じた研究 も活発に進められており [7],動作認識はその基盤となる技術で ある. サブタスクの成否を判定することができればより確実に 複合的なタスクを遂行できるようになることから,成否判定に 動作認識を利用することも想定される [8]. 動作認識は位置情報に基づくものが多く,主に画像や内界セ ンサが利用される. 動作の内容は接触状態に強く依存すること から,上記のセンサ類に基づいて接触状態を検知し,動作認識 する研究もなされている [9]. しかし,特に精密組み立てのよう に対象物どうしの接触を伴い,かつ位置のクリアランスが小さ
Wide hybridization for fruit crop improvement: A review

Wild plant species related to crop plants form an important source of useful traits for fruit quality improvement and biotic and abiotic stress tolerance. Wide hybridization involving crop wild relatives and related taxa has gained momentum in the recent fruit crop improvement programs. It breaks the species barrier for gene transfer and makes it possible to transfer the genome of one species to another, which results in changes in genotypes and phenotypes of the progenies. The incompatibilities or barriers in wide hybridization occur as prezygotic and postzygotic barriers. Techniques of chromosome doubling, bridging species, protoplast fusion and embryo rescue are highly beneficial in recovering fertile progenies by overcoming various barriers in wide crossings. The present article reviews the techniques involved in distant crossing and their applications in fruit crop improvement.
Importance of the Innovative Business Models for the Future Success of the Company

During the last decade, the market environment for the businesses has been influenced by digital developments and as a result, the focus on business model innovations has rapidly grown. Businesses started moving away from the classic method of creating competitive advantage like a new product development. Thus, this influenced business activities as well as companies’ business models into innovations of new products and services, a new ways of company relationships with customers and employees. Customers started expecting to receive services at a level comparable to digital solutions. Simultaneously, it put pressure on organizations to reflect on their current strategy and discover new business opportunities at the early stages. Digitalization is a one of the significant reasons for innovation on the business model of companies. Currently, business model as a tool is becoming a very popular topic due to its benefits received by companies and this topic studied by various researchers. This paper is based on theoretical perspective and the study was done by analysing previous researches, articles and papers in the present context. The study emphasizes that business model innovation can be a basis of sustainable competition for companies and innovators may increase their returns 4 times than product and service developers.
A Simulation Model for Macro- and Micro-Fusion Algorithms in the CPU Core

The article discusses the features of modern processor’s microarchitecture, the method of instruction’s and micro-operation’s accelerated execution. The research focuses on the organization of the decoding stage in the CPU core pipeline and Macro- and Micro-fusion algorithms. The Macro- and Micro-fusion mechanisms are defined. A computer simulator has been developed to explore these mechanisms. The developed software has a user-friendly interface, is easy to use, and combines training and research options. The computer simulator demonstrates the sequence of mechanism’ s implementation; the resulting macro-or microoperations set after Macro- and Micro-fusion, and also reflects each algorithm features for different processor’s families. The software allows you to use either a pre-prepared file with Assembler (x86) code fragments as source data, or enter/change the source code fragments at your request. The main combinations of machine instructions that can be fused into a single macro-operation are considered, as well as instructions that can be decoded into fused micro-operations. The simulator can be useful both for in Computer Science & Engineering students, especially for on-line education and for researchers and General-purpose CPU cores developers.
Mid-Day Meal Analytics Using Machine Learning

The concept is to prevent the wastage of food from the mid-day meal scheme and to identify the fraudulence that is being happened in the mid-day meal scheme. In this process, QR-code reader is used to the number of students is enroll their count for food within some pre-determined time through their ID card. A touch screen display is placed at the food issuing place which shows the menu for a particular day. Food can be monitored through a Web camera and it also placed at the food issuing place take snapshot of every individual student which provides the count of students reported with the required students count the amount of food needs to be prepared for that day is known. This snapshot photo is compared with the photo taken by the Web camera at the place where the food is prepared. The Raspberry-pi is to process the machine learning concept to identify the meal. To develop the mobile application to send the notification to a higher authority when fraudulence action is detected via camera.
Hibiscus sabdariffa L. leaf extract mediated green synthesis of silver nanoparticles and its use in catalytic reduction of 4-nitrophenol

ABSTRACT In the present study, the authors explored the green synthesis of silver nanoparticles (AgNP) using Hibiscus sabdariffa, L. leaf extract as reducing agent and nanoparticles stabilizer. The silver nanoparticles were formed at room temperature in a short period of time using the leaf extracts of H. sabdariffa and silver nitrate at room temperature. The resulting nanoparticles were characterized by UV-visible spectroscopy, transmission electron microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. UV-visible spectroscopy shows characteristic surface plasmon resonance band of spherical silver nanoparticles. The synthesized AgNPs were effective in catalyzing the reduction of 4-nitrophenol.