Miracle-dz/UniFAR-FTUs huggingface dataset:
Data pair selection for accurate classification based on information-theoretic metric learning

Data classification is one of the main technique in data analysis which has become more and more important in various fields of business. Automatic classification is the problem that classification category label is learned from training data. One of the effective approaches for automatic classification is the k-nearest neighbour (kNN) method based on distances between data pairs, combining with the well-known distance metric learning. In this study, we focus on information-theoretic metric learning (ITML) method. In ITML, the optimisation problem is formulated as learning metric matrix so that the distance between each pair of data belonging to the same class becomes smaller than a constant, while the distance between each pair of data belonging to different classes becomes larger than the other constant. In this study, we propose an improved procedure by choosing the data-pairs which affect clarifying the boundaries effectively. We verify the effectiveness of our proposed method by conducting the simulation experiment with benchmark dataset.
Additive Manufacturing of an Extended-Release Tablet of Tacrolimus

An extended-release tablet of tacrolimus as once-daily dosing was fabricated using 3D printing technology. It was developed by combining two 3D-printing methods in parallel. Indeed, an optimized mixture of PVA, sorbitol, and magnesium stearate as a shell compartment was printed through a hot-melt extrusion (HME) nozzle while an HPMC gel mixture of the drug in the core compartment was printed by a pressure-assisted micro-syringe (PAM). A 3D-printed tablet with an infill of 90% was selected as an optimized formula upon the desired dissolution profile, releasing 86% of the drug at 12 h, similar to the commercial one. The weight variation, friability, hardness, assay, and content uniformity determination met USP requirements. A microbial evaluation showed that the 3D-printed tablet does not support microbial growth. SEM analysis showed smooth surfaces with multiple deposited layers. No peak interference appeared based on FTIR analysis. No decomposition of the polymer and drug was observed in the printing temperature, and no change in tacrolimus crystallinity was detected based on TGA and DSC analyses, respectively. The novel, sTable 3D-printed tablet, fabricated using controllable additive manufacturing, can quickly provide tailored dosing with specific kinetic release for personalized medicine at the point-of-care.
Deep Tensor Attention Prior Network for Hyperspectral Image Denoising

Hyperspectral imaging techniques can generate continuous narrowband images with a high spectral resolution. However, owing to environmental disturbances, atmospheric effects, and hardware limitations of hyperspectral imaging sensors, captured hyperspectral images (HSIs) often contain complex noises that significantly degrades their quality and limits their utility. In this article, we design a deep tensor attention module based on a canonical-polyadic (CP) decomposition of a feature tensor, referred to as a deep CP attention module (DCPAM), which can disentangle spatial and channel information and further enhance the topological structure of features. It has been shown that the DCPAM is effective and relatively simple to integrate into some well-known network architectures. And taking the network with the DCPAM as a deep prior, we propose a deep tensor attention prior network (DTAPNet) for HSI denoising tasks. Extensive experiments on simulated and real HSIs demonstrate that our proposed DTAPNet outperforms existing state-of-the-art HSI denoising models.
Normal Forms and Equivalence of K-periodically Routed Graphs

We introduce K-periodically Routed Graphs, which are extensions of Marked Graphs with routing nodes, governed by ultimately periodic binary sequences. We study data relations and dependencies, as well as equational transformations of the network topology. We show the existence of expanded normal forms. We prove that some transformations preserve external flow equivalence. Issues arising from internal flow interleavings and permutations are also tackled.
Topology‐based distributed optimization for multi‐UAV cooperative wildfire monitoring

Cooperative small‐sized unmanned aerial vehicles (UAVs) can contribute to wildfire monitoring missions. By distributing UAVs into groups to cover different segments of the fire‐front contour, the mission efficiency can be improved. In this paper, according to the requirements of a wildfire mission, we formulate the multi‐UAV cooperation problem in a distributed network. A consensus‐based method is proposed to allow the group‐level cooperation among UAVs. The optimal UAV cooperation strategy is obtained through mathematical analysis. The effectiveness of the methodology is verified in an independent fire simulation environment.
External Structural Congenital Anomalies Diagnosed at Birth in Tamale Teaching Hospital

Background: In the year 2013, about 276,000 of the 2.71 million neonatal deaths were directly attributable to congenital anomalies of which an estimated 95%, occurred in low and middle-income countries.Materials and method: This study was part of surveillance on external structural congenital anomalies conducted in the Tamale teaching hospital from 1st January 2011 to 31st December 2015. Aggregate data on maternal characteristics and outcome of deliverywere collected from the records in the antenatal clinics, labour and delivery room, and midwifery monthly returns.Results: A total of 35,383 live births were recorded in the study. Overall, 161 external congenital anomalies were recorded over the period. The overall incidence of external congenital anomalies over the five-year period was 455 per 100,000 live births. The gastrointestinal (GIT) system accounted for (77) 47.8%, Central nervous system (65) 40.4%, Major musculoskeletal (9) 5.6%, Genitourinary system about (2) 1.2%, Multisystemic and syndromes accounted for (8) 5.0% of all external structural congenital anomalies. The incidence of specific congenital anomalies found during the study period were as follows; Spina bifida 104.6 per 100,000 live births, Exomphalus/omphalocele 84.8 per 100,000 live births and Anencephaly 5.7 per 100,000 live births. The incidenceof Oro-facial cleft, Hydrocephalus and Imperforate anus were 73.5, 48.0 and 39.6 per 100,000 live births respectively.Conclusion: External structural congenital anomalies rate in the northern sector of Ghana is unacceptably high. Trend analysis has demonstrated the steady decline in neural tube defects.
AN EMPIRICAL STUDY ON ACADEMIC SUSTAINABILITY OF MOBILE LEARNING AT UNIVERSITY LEVEL

This study proposes an investigation model for merging Technology Acceptance Model (TAM) for mobile learning utilization in the field of academic sustainability. Mobile education is not fully employ in the universities of Pakistan, so that is the reason why students/teacher Attitude Towards Technology (ATT) and learning teaching through empirical knowledge is at very low level in universities. The grounds of present study were to investigate state of contemporary adaptation of models in M- learning. This work supported the sustainability of portable learning through m-learning by mastery the elements that affect intention of users to use mobile education prior to apply it to make certain continuity or success. The key goal was to facilitate universities a comprehend sight of those elements that can affect the degree to which learners or students adopt any new technology. Resulted outcomes of present study can help academics along with managers to fully acknowledge the way mobile educating system utilization can affect learners’ educational sustainability as well as academic performance. To achieve these results, an enlarge Technology Acceptance Model (TAM) was evolved, which bring out literature relevant to Mobile learning use in Pakistan universities. Furthermore there was no such research in this perspective in Pakistan which has integrated three models as TAM (Technology Acceptance Model), BIM (Behavior Intention Model), and TTF (Task Technology Fit Model) for acceptance of Mobile learning. The aim of present work was to couple essential features of TAM and constructivism with academic sustainability
Quality of Soybean Seeds after Microwave Drying

The use of electromagnetic energy for drying seeds has been shown to be a promising alternative. However, studies show that the technique still lacks careful evaluation due to the sensitivity of soybean seeds to damage caused using microwaves. Studies have shown that the use of microwaves during drying can be safe in seeds of soybeans, corn, and beans, among others. These studies recognize that drying using microwaves has a great potential for savings in the drying process, as it considerably reduces the drying time. This work aimed to evaluate the immediate damage caused in soybean seeds subjected to drying at temperatures of 40, 50, and 60 °C, with power of 0, 0.5, and 1 W/g at a frequency of 2.45 GHz. The results of the vigor and germination tests showed that the action of microwaves on seeds was not only safe and more efficient but also brought about increases in seed germination and vigor. However, the process must be judicious and obey precise indices of power and temperature to not cause damage to the seeds.
ASSOCIATIONS BETWEEN SMALL-SCALE STRUCTURE IN LOCAL GALACTIC NEUTRAL HYDROGEN AND IN THE COSMIC MICROWAVE BACKGROUND OBSERVED BY PLANCK

High-resolution galactic neutral hydrogen (HI) data obtained with the Green Bank Telescope (GBT) over 56 square degrees of sky around l = 132°, b = 25° are compared with small-scale structure in the Cosmic Microwave Background observed by PLANCK, specifically at 143 and 857 GHz, as well as with 100 μm observations from the IRIS survey. The analysis uses data in 13 2° × 2° sub-areas found in the IRSA database at IPAC. The results confirm what has been reported previously; nearby galactic HI features and high-frequency continuum sources believed to be cosmological are in fact clearly associated. While several attempts strongly suggest that the associations are statistically significant, the key to understanding the phenomenon lies in the fact that in any given area HI is associated with cirrus dust at certain HI velocities and with 143 GHz features at different velocities. At the same time, for the 13 sub-areas studied, there is very little overlap between the dust and 143 GHz features. The data do not imply that the HI itself gives rise to the high-frequency continuum emission. Rather, they appear to indicate undiagnosed brightness enhancements indirectly associated with the HI. If low density interstellar electrons concentrated into clumps, or observed in directions where their integrated line-of-sight column densities are greater than the background in a manner similar to the phenomena that give rise to structure in diffuse HI structure, they will profoundly affect attempts to create a foreground electron mask used for processing PLANCK as well as WMAP data.
Android Based Educational Mobile Robot Design and Pilot Evaluations

Educational robotics is a powerful tool for STEM and STEAM education. However, in practice, while trying to introduce educational robotics into a well-established educational process, a number of significant problems might arise. These include a high cost of an equipment and a lack of necessary competencies in the field of educational robotics among teachers. In this paper, we describe a concept of an inexpensive mobile robot equipped with a mobile device running Android operating system. We present sample projects that demonstrate how to extend capabilities of the educational mobile robot through the use of the mobile device. The proposed approach was preliminary evaluated in “Educational robotics” Bachelor level course and “Introduction to robotics” Master level course at Kazan Federal University.
Design of dual band and wideband circularly polarised slot antenna for wireless applications

ABSTRACT In this paper, two circularly polarised (CP) antennas are proposed. One is dual band CP (DBCP) while the other is wideband CP (WBCP). Both the slot antennas are coplanar waveguide-fed corner truncated structure with an L-shaped radiating patch. The CP bandwidth is significantly improved by connecting one end of the L-shaped patch to the ground plane which also resulted in miniaturisation of the antenna with a size of 48 × 43 mm. DBCP is generated by adding an extra rectangular stub to the ground plane while WBCP by cutting two additional slots in the ground plane. The dual band antenna has a measured impedance bandwidths (S11 < −10 dB) of 34% (2.2–3.1 GHz) and 42% (4.6–7.1 GHz) while the corresponding 3 dB axial ratio bandwidths (ARBWs) are 34% (2.2–3.1 GHz) and 28.6% (4.8–6.4 GHz). The measured impedance bandwidth and ARBW of the wideband antenna are 102% (2.2–6.8 GHz) and 93% (2.3–6.3 GHz), respectively.
Characterising Angular Accelerometers using a Two-Axis Motion Simulator

Fault-Tolerant Flight Control (FTFC) systems reconfigure aircraft flight control laws to help restore a controlled flight and preserve acceptable performance under systemfaults. A typical approach to achieve fault tolerance is using inertial sensor measurementswhich can provide robustness to abrupt changes in the aircraft dynamics. This method does not rely on an accurate and full aerodynamic model, but only requires an estimate of the control effectiveness and an additional reconfiguration mechanism to the control laws such as switching, model following, matching, and adaptive compensation. With the inertial sensor being at the very heart of the control laws, to have proven and well-understood sensors is essential to increase the operational performance of a post-failure aircraft. Recent developments lead to FTFC systems that require angular acceleration feedback, which with the current conventional Inertial Measurement Unit (IMU) is obtained by taking the first derivative of the angular rates measured by gyroscopes. Because differentiation commonly intensifies noise and incurs a delay, a direct measurement of angular acceleration is anticipated to enhance the quality of the feedback signal. However, angular accelerometers are currently not part of the commercial aircraft system, which prompts the need to understand their characteristics. This thesis aims to investigate how an angular accelerometer can be evaluated and calibrated in a systematic fashion.
Efficient 2nd order full band digital IIR integrator design using Cuckoo search algorithm

An optimization approach to design an efficient 2nd order infinite impulse response (IIR) digital integrator (DI) is proposed using Cuckoo search algorithm (CSA). The unique feature of the proposed approach has been the formulation of the condition for obtaining ideal DC frequency response which has been attained by forcing the sum of the z-term coefficients in the denominator equal to zero during optimization. Optimization of the 2nd order DI was performed for minimum integral of absolute error (IAE) between magnitude frequency responses of ideal and the optimized designs. The performance index such as IAE in full Nyquist band of the proposed design is compared with the several other recently reported 2nd, 3rd and 4th order DIs designed using various other optimization techniques. The comparative analysis by using frequency response and Absolute magnitude error (AME) clearly indicates the superiority of CSA based design.
Development and test of a broadband absolute frequency reference with sub-MHz precision based on a GHz mode locked laser source

Space lidar instruments for missions like AEOLUS or MERLIN require advanced high-power laser systems with according technical and financial effort. In order to increase the impact of such missions, it is advantageous to expand the versatility of their instruments. In the case of trace gas sensing, the ability to detect multiple trace gas species with the same instrument greatly enhances their value. Multi-species trace gas differential absorption lidar (DIAL) systems require absolute frequency referencing across large spectral bandwidths. While absorption cell based references need individual lasers at online and offline wavelengths for each species, a broadband mode locked laser – offering a frequency comb – can provide the required frequency accuracy over the complete spectral range of the lidar instrument. In the frame of the LEMON project, we developed a combined design for an absolute frequency reference based on a wavemeter for coarse frequency determination (<500 MHz accuracy) and a broadband mode locked laser for precise frequency detection by means of heterodyne beat generation. It features a large spacing of 1 GHz and is optimized for spectroscopic lidar applications covering the spectral range from 980 nm to 1100 nm and 1500 nm to 2300 nm. The achieved accuracy of <100 kHz of the optical frequency, satisfies the requirements needed to atmospheric gas analysis from space. The broadband approach offers a cost-effective solution to address multiple gas species simultaneously. The system can also be adapted to different spectral ranges of interest for gas spectroscopy and other applications. Additional presentation content can be accessed on the supplemental content page.
Développement de méthodes d'estimation modale de signaux multidimensionnels. Application à la spectroscopie RMN multidimensionnelle

La these porte sur le developpement d'algorithmes d'estimation rapides pour l'analyse modale de signaux multidimensionnels (R-D) presentant des problemes de resolution et de complexite numerique. Un signal multidimensionnel de dimension R est la superposition de produits de R sinusoides. L'application visee est la spectroscopie RMN. Dans un premier temps, apres un etat de l'art des methodes d'estimation dites " algebriques ", nous proposons une methode parametrique basee sur les tenseurs. Celle-ci utilise le treillis multidimensionnel du tenseur du signal R-D et exploite la structure des vecteurs propres du sous-espace signal obtenus en utilisant la decomposition en valeurs singulieres d'ordre superieur. Contrairement a la plupart des approches tensorielles, la methode proposee permet d'eviter la phase d'appariement des coordonnees des modes dans chacune des dimensions ou d'une diagonalisation conjointe. Dans un deuxieme temps, le probleme d'estimation modale multidimensionnelle est presente comme un probleme d'approximation parcimonieuse dans lequel le dictionnaire est obtenu par la discretisation de fonctions exponentielles complexes. Afin d'atteindre une bonne resolution spectrale, il est necessaire de choisir une grille tres fine, ce qui conduit a la manipulation d'un dictionnaire de grande taille avec tous les problemes calculatoires sous-jacents. Nous proposons alors une methode originale qui consiste a combiner une approximation parcimonieuse et une approche multigrille sur plusieurs niveaux de resolution. L'approche est validee au travers de plusieurs exemples 1-D et 2-D. En outre, une etude sur l'influence du choix du dictionnaire initial sur la convergence est egalement menee. Les methodes developpees sont ensuite appliquees a l'estimation des parametres de signaux de spectroscopie RMN 1-D et 2-D. Afin de reduire le cout de calcul dans le cas de signaux bidimensionnels de grande taille, nous proposons egalement une approche exploitant la notion de parcimonie simultanee, pour estimer les coordonnees des modes sur chacune des dimensions. La procedure consiste a effectuer deux approximations parcimonieuses 1-D suivies d'une phase de reformation des paires de modes 2-D.
Weapons of mass instruction

When comedians and musicians are asked what the hardest part of their job is, "life on the road" is a common answer. Yet their touring life comprises only a single daily performance, given to civilized adults who have voluntarily paid to attend. The lecturer for the annual Institute of Physics schools tour, on the other hand, must perform twice daily to 14–16 year olds who come along because their teachers tell them to. You will be heartened to learn that, in contrast to the aforementioned mollycoddled prima donnas, I enjoyed every minute of it.
Centre Based Chromosomal Representation in Genetic Algorithms for Class Division of New Students

This paper is presented to explain application of Genetic Algorithms in class division of new students. It is very essential, since good educational service for a large number of students needs grouping of them into several classes in which each class consist of similar students. There is no clustering method can handle it due to the capacity of each class. The supervised clustering method can only cluster students where number of class is predefined, but it cannot handle the capacity of class. The proposed approaches are Genetic Algorithms which succeeded in solving difficult optimization problems. Since clustering method can be solved by minimizing the distance between each object in the cluster with the corresponding cluster centre, we proposed Genetic Algorithms with cluster centre based chromosomal representation in two different approaches: student based cluster centre and coordinate based cluster centre. We developed each approach as software and evaluated them with random data. The result showed that the class generated by the proposed approach consists of more similar students than the class produced by traditional sorting method. Beside it, the result also showed that the second proposed approach provided no advantage over the first one.
Forecast Content and Content Horizons for Some Important Macroeconomic Time Series

The pattern of decay of forecast content (or skill) with increasing horizon is well known for many types of meteorological forecasts; by contrast, little generally accepted information about these patterns or content horizons is available for economic variables. In this paper we estimate content horizons for a variety of macroeconomic quantities; more generally, we characterize the pattern of decay of forecast content as we project farther into the future. We find a wide variety of results for the different macroeconomic quantities, with models for some quantities providing useful content several years into the future, for other quantities providing negligible content beyond one or two months or quarters.
Robust Classification Model with Multimodal Learning for Home Service Robots

We propose an auxiliary data stream structure as a robust classification model. The model treats one modal as the main input and the other modals as supports. The model chooses how much of the sub-modal is used for classification. We experimented with two and three modal inputs. Moreover, we added pseudo-shadows to the visual information for the experiment with three modal inputs. In all experiments, our proposed model improves the accuracy and robustness to environmental disturbances by using multiple modals.