Miracle-dz/UniFAR-FTUs huggingface dataset:
Reflect-Express-Transform: Investigating Speech-Based Iterative Digital Design for Young Designers

We investigate speech-based input as a means to enable reflective thinking for younger individuals (middle - and high-school students) during design iterations. Verbalization offers a unique way to externalize ideas in early design and could therefore lead to new pathways for exploration and iteration, especially for K-12 students who possess the creative potential but are not technically trained in the design process. Interactive design systems, however, by-and-large utilize sketching, multi-touch, and gestural inputs. As a result, (1) there is little know-how regarding how to operationalize verbal inputs as a meaningful way to facilitate idea exploration and (2) there is little fundamental understanding of the underlying cognitive mechanisms for iteration through verbal communication. We take the initial steps towards these gaps by first designing and implementing the ShapOrator interface that takes verbal descriptions of geometric parameters (shape, size, instances) in a semi-natural language form and determines the appropriate transformations to a given design artifact modeled as a shape assembly. Using ShapOrator as our experimental setup we conducted an in-depth observational study on 10 middle - and high-school students tasked with designing spaceships. Our study revealed that participants were able to create a variety of designs while associating functional and topical contexts to their spaceships throughout the design iteration process.
La medición de la eficiencia energética y su contribución en la mitigación de las emisiones de CO2 para 26 países de América Latina y el Caribe

A partir de la aplicacion de modelos de frontera estocastica, se obtuvo la estimacion de la demanda de energia final, asi como la eficiencia para los paises de la muestra (de America Latina y el Caribe), entre 1970 y 2010. Se construyo un ranking por paises de la eficiencia energetica y se contrasto con el patron que se obtiene cuando es utilizada la intensidad energetica como aproximacion de la eficiencia. Se evidencio que no siempre la intensidad energetica ofrece un resultado confiable para evaluar la eficiencia del uso final de la energia. Se estimo la demanda ideal de energia y el volumen de emisiones de CO2 correspondientes y se determino finalmente el potencial de ahorro de energia y de mitigacion de emisiones resultante del mejoramiento de la eficiencia energetica para cada pais, informacion que puede resultar un referente importante en la determinacion de metas voluntarias de mitigacion.
Theory of associative memory in randomly connected Boolean neural networks

The Aleksander model of neural networks replaces the connection weights of conventional models by logic devices (or Boolean functions). Learning is achieved by adjusting the Boolean functions stepwise via a 'training-with-noise' algorithm. The authors present a theory of the statistical dynamical properties of the randomly connected model and demonstrate that, in the limit of large but dilute connectivity c of the nodes, the storage capacity for associative memory is of the order (2/c2)2c, which corresponds, roughly speaking, to an average of one nearest-neighbouring pattern stored at site distances 2 on each node. Two parameters are introduced into the learning algorithm: qr and qc being respectively the probabilities to register a correct bit and erase an incorrect one. The effects of varying qr, qc and the training noise level on the storage capacity (after very long training) are discussed. In the limit of low training noise level, the training algorithm is equivalent to the so-called 'proximity rules'. Study of its retrieval properties shows that the model can be described as 'short ranged', whereas the Hopfield model is 'long ranged'. The advantages and disadvantages of introducing the intermediate u state into the system are also discussed.
The Prevention, Diagnosis, and Treatment of Rapid Oral Health Deterioration (ROHD) among Older Adults

The world’s population is aging. Older adults are at risk for multiple chronic medical problems as they age. The management of these diseases requires these people to take a variety of medications, which may have undesired side effects. These medical issues can impact oral healthcare and result in a precipitous decline in oral health. A standardized teaching model has been developed to help novice dental practitioners learn how to access and treat oral health problems in older adults. This model is called rapid oral health deterioration (ROHD) risk assessment. The model has four steps for assessment and four categories of risk. This paper describes the components of the ROHD risk assessment, and how it can be used to prevent, diagnose and treat ROHD among older adults.
Fault diagnosis of rolling bearing based on wavelet transform and envelope spectrum correlation

Monitoring of incipient faults is vital for the safe and reliable operation of rolling element bearings. In this paper, the combination of discrete wavelet transform and envelope analysis is proposed to extract the characteristic spectrum of rolling bearing vibration data. Then spectrum cross-correlation coefficient is applied to identify different operating conditions of rolling bearings. The proposed method is applied to fault diagnosis of rolling bearings with several different faults. The results show that the proposed method has high classification accuracy, and performs better than alternative approaches based on conventional characteristic defect frequency extraction.
Maximizing Heterogeneous Server Utilization with Limited Availability Times for Divisible Loads Scheduling on Networked Systems

Most of the available divisible-load scheduling models assume that all servers in networked systems are idle before workloads arrive and that they can remain available online during workload computation. In fact, this assumption is not always valid. Different servers on networked systems may have heterogenous available times. If we ignore the availability constraints when dividing and distributing workloads among servers, some servers may not be able to start processing their assigned load fractions or deliver them on time. In view of this, we propose a new multi-installment scheduling model based on server availability time constraints. To solve this problem, we design an efficient heuristic algorithm consisting of a repair strategy and a local search strategy, by which an optimal load partitioning scheme is derived. The repair strategy guarantees time constraints, while the local search strategy achieves optimality. We evaluate the performance via rigorous simulation experiments and our results show that the proposed algorithm is suitable for solving large-scale scheduling problems employing heterogeneous servers with arbitrary available times. The proposed algorithm is shown to be superior to the existing algorithm in terms of achieving a shorter makespan of workloads.
Kinematics and internal dynamics of planetary nebulae in the small Magellanic Cloud

Kinematical and dynamical data for 44 SMC planetary nebulae (PNs) are presented at a velocity resolution of 12 km/s.The PNs form an unstructured spheroidal population apparently associated with the Bar with centroid at alpha 00 h 49 m 39 s, delta -73 deg 30 min (1950) and with a mean radial velocity of -17 km/s.Their velocity dispersion implies a mass of 900 million solar masses within a radius of 3 kpc of the centroid.These PNs, which form a population of age greater than about 100 million years, appear to be loosely associated with the lower velocity component of the H I, suggesting that the high-velocity H I component is dynamically young.A remarkably good correlation between the expansion velocity and the excitation class is found, which may show that the mass of the white dwarf central star is the major variable influencing the expansion velocity of PNs. 39 references.
Wireless Power Transfer in Electric Vehicles: A Review on Compensation Topologies, Coil Structures, and Safety Aspects

The scarce availability of non-renewable sources and the staggering amount of pollution have inevitably provoked many countries to opt for renewable sources. Thence, invariably, more renewable energy-based applications are hoarded by market stakeholders. Compared to all spheres of renewable energy applications, a considerable part of the energy is pulled into transportation. Wireless power transfer techniques play a significant role in charging infrastructure, considering the current development and advancement in the automotive industry. It will promise to overcome the widely known drawbacks of wired charging in electric vehicles. The effectiveness of wireless charging depends on coil design, compensation techniques, and the airgap between the coils. However, coil misalignment, improper compensation topologies, and magnetic materials reduce the efficacy. We can improve efficacy by overcoming the problems mentioned above and optimizing charging distance, time, and battery size. This paper comprehensively discussed the various electric vehicle charging technologies in conjunction with common charging standards, a list of factors affecting the charging environment, and the significance of misalignment problems. Furthermore, this review paper has explored the suitable coil design structure and different compensation techniques for an efficient wireless charging network.
Testing the Resilience of MEC-Based IoT Applications Against Resource Exhaustion Attacks

Multi-access Edge Computing (MEC) is an emerging computing model that provides the necessary on-demand resources and services to the edge of the network, ensuring powerful computing, storage capacity, mobility, location, and context awareness support to emerging Internet of Things (IoT) applications. Nonetheless, its complex hierarchical model introduces new architectural interdependencies, which can influence the resilience of IoT applications against cyber attacks. Although application resilience has been investigated in the context of cloud computing, existing studies are not directly applicable to such an extended edge-cloud paradigm. The use of different enabling technologies at the edge of the network, such as various wireless access technologies and virtualization, implies several threats and challenges that make the analysis and deployment of resilience mechanisms a technically challenging problem. In this article, we first present an overview of the threat model, describing the threats for the different layers of this paradigm. We then study the impact of resource-exhausting attacks – a particularly relevant class for this paradigm - on three different IoT applications exploiting the services offered by the MEC-based architecture. We adopt a testing-based methodology conceived to characterize the resilience of such applications under attack. A set of most important resilience-related indicators are also identified. The characterization's results are useful to support the analyst in planning proper protection means at individual architectural layers.
Accuracy assessment of RTK/PPK UAV-photogrammetry projects using differential corrections from multiple GNSS fixed base stations

Abstract Unmanned aerial vehicles (UAVs) equipped with global navigation satellite system-real-time kinematic (GNSS RTK) receivers allow direct georeferencing of the photogrammetric project without using ground control points (GCPs). However, it is necessary to establish the correct methodologies to reduce the errors inherent in these systems, i.e. to reduce the systematic error of the elevation data. For this purpose, multiple GNSS fixed base stations have been used simultaneously. The results showed how the fact of using different bases and averaging their corrections allows to obtain results that improve the altimetric accuracy without the need to use GCPs or oblique photographs. For flight altitudes of 50 m, improvements in altimetric accuracy of 14% were obtained, while for flight altitudes of 70 and 90 m, the improvements in altimetric accuracy reached 35%. Regarding planimetric accuracy, no significant improvements have been found. However, the total errors are similar to those obtained with various combinations of GCPs and closed to the ground sampling distance (GSD) of the photogrammetric project.
Image Tracking Analysis And Simulation

The problem considered herein is that of tracking a well-resolved object with an active direct detection sensor system. The sensed object image is corrupted by additive as well as multiplicative (speckle) noise. A steady-state object tracking filter based on a discounted weighted least-squares procedure is derived in closed-form, along with its error covariance properties. The filter, which is of a polynomial-in-time type, estimates the position, velocity, and acceleration of an object moving in space, based on noisy measurements of position offset in the focal plane array. The position offset measurements are obtained using the Fitts correlation algorithm. The error covariance matrix of the Fitts algorithm is derived in closed-form for both additive and multiplicative noise. The discounted weighted least-squares filter has the advantage of requiring only a single parameter, the discount factor, as opposed to three parameters in the conventional a-0-y filter. Most importantly, the discount factor guarantees a certain degree of stability in the filter. Simulation results are given for the case of a computer-generated speckled image. Tracking performance results are presented for the discounted weighted least-squares filter, the a-0-y filter, and the recursive Kalman filter, using the Fitts correlation algorithm for generating position offset measurements in all cases.
Crystal truncation rod X‐ray scattering: exact dynamical calculation

A new method is presented for a calculation of the reciprocal-space distribution of X-ray diffracted intensity along a crystal truncation rod. In contrast to usual kinematical or dynamical approaches, the method is correct both in the reciprocal-lattice points and between them. In the method, the crystal is divided into a sequence of very thin slabs parallel to the surface; in contrast to the well known Darwin dynamical theory, the electron density in the slabs is constant along the surface normal. The diffracted intensity is calculated by a matrix formalism based on the Fresnel reflection and transmission coefficients. The method is applicable for any polarization of the primary beam and also in a non-coplanar scattering geometry.
FL-Lightgbm prediction method of unbalanced small sample anti-breast cancer drugs

The problem of small amount data and sample imbalance exists in the machine learning prediction of the molecular properties of anti breast cancer candidate drugs. Proposing a FL-Lightgbm prediction model based on WGAN-GP data enchance model in order to solve this problem. Firstly, WGAN-GP model is used for data enhancement to increase the sample size of the training data set. Considering the small difference between positive and negative samples, the enhanced data of positive and negative samples are generated respectively, and then combined them according to the original order to ensure that the generated data and the original data maintain the same distribution; Then the Focal Loss function is introduced into the Lightgbm model to increase learning ability for unbalanced samples, the model constructed is called FL-Lightgbm prediction model. After the training of the enhanced data set, the proposed model shows excellent prediction accuracy for 178 randomly selected validation samples in the experiment, and its highest accuracy, AUC and F1 values reach 0.882, 0.851 and 0.7272 respectively. In these three indexes, the proposed model has better prediction ability than the original Lightgbm model with over sampling algorithms such as BorderlineSMOTE and ADASYN.
A Broad Stopband and High Rejection HTS Lowpass Filter for Quantum Computers

This article presents a novel approach for extending the upper stopband of lowpass filters. The proposed technique involves dividing the hairpin unit cells' coupled lines into multiple smaller components, which shifts the harmonics to higher frequencies while maintaining the cut-off frequency. In addition, the stopband is further extended by modifying the tapping position to suppress the second harmonic. For demonstration, an improved dual-hairpin unit cell is devised, which is able to extend the stopband up to 11.3 times the cut-off frequency. Furthermore, a cascaded lowpass filter utilizing multiple improved dual-hairpin unit cells is also designed, which is divided into two subfilters to suppress enclosure resonance. The cascaded filter is fabricated on an high-temperature superconducting thin film deposited on a MgO substrate, demonstrating a cut-off frequency of 483 MHz, extending the stopband to 25.1 GHz (51.9fc), affording a rejection level exceeding 60 dB and insertion loss below 0.04 dB. Notably, the roll-off rate exceeds 569 dB/GHz, and the size measures only 0. 144λg × 0. 030λg.
On the chaotic nature of solar-terrestrial environment: Interplanetary Alfvén intermittency

[1] We present an overview of observational and theoretical evidence of chaos and intermittency in the solar-terrestrial environment including solar dynamo, solar atmosphere, solar wind, and terrestrial magnetosphere-ionosphere-atmosphere. The chaotic nature of space plasmas is studied by a nonlinear model of Alfven waves described by the low-dimensional limit of the derivative nonlinear Schrodinger equation given by its stationary solutions in the frame moving with the driver wave velocity. A periodic window of the bifurcation diagram is constructed to identify two types of Alfven chaos related to type-I intermittency and crisis-induced intermittency. We show that an Alfven chaotic attractor is composed of chaotic saddles and unstable periodic orbits and explain the links between these unstable structures and Alfven intermittency. The role of interplanetary Alfven intermittency in the solar wind driving of intense geomagnetic activities is discussed.
Semantic Role Labeling for Amharic Text Using Multiple Embeddings and Deep Neural Network

Amharic is morphologically complex and under-resourced language, posing difficulties in the development of natural language processing applications. This paper presents the development of semantic role labeler for Amharic text using end-to-end deep neural network architecture. The system implicitly captures morphological, semantic and contextual features of a word at different levels of the architecture, and incorporates the syntactic structure of an input sentence. The proposed neural network architecture has four core layers from bottom to top, namely non-contextual word embedding, contextual word embedding, fully connected and sequence decoding layers. The non-contextual word embedding layer is formed from the concatenation of character-based, word-based and sentence-based word embeddings. This layer captures the morphological and semantic features of a given word by making use of BiLSTM recurrent neural network. At the contextual word embedding layer, a context sensitive embedding of a word is generated by applying a new LSTM layer on the top of the non-contextual concatenated word embedding layer. A fully connected network layer is added on top of contextual word embedding layer to supplement it by extracting dependencies among training samples in the corpus. At the sequence decoding layer, a sequence of semantic role labels is predicted using a linear-chain conditional random field algorithm by capturing the dependency among semantic role labels. In addition to the four core layers, the architecture has dropout layers to prevent overfitting problem. The proposed system achieves 94.96% accuracy and 81.2% F1 score when it is tested using test data.
Theoretical Modeling of Multi-Sleeve Monopole Antennas

Abstract–This article presents a numerical technique based on the modal-expansion method for modeling a multi-sleeve monopole antenna fed through an infinite ground-plane by a coaxial transmission line. The modal-expansion analysis is facilitated by introducing a perfectly conducting boundary at a variable height over the ground-plane of the monopole. The resulting structure is then divided into a number of regions and the electromagnetic field components in each region are expanded into the summation of its modal functions. The current distribution over the monopole and sleeve surfaces as well as the antenna’s input impedance are computed by finding the expansion coefficients through matching the tangential field components across the regional interfaces. Numerical results for the surface current distribution and input impedance are presented and discussed with emphasis laid on singleand double-sleeve monopole antennas.
Choosing Priors for Constrained Analysis of Variance: Methods Based on Training Data

Abstract. This article combines the best of both objective and subjective Bayesian inference in specifying priors for inequality and equality constrained analysis of variance models. Objectivity can be found in the use of training data to specify a prior distribution, subjectivity can be found in restrictions on the prior to formulate models. The aim of this article is to find the best model in a set of models specified using inequality and equality constraints on the model parameters. For the evaluation of the models an encompassing prior approach is used. The advantage of this approach is that only a prior for the unconstrained encompassing model needs to be specified. The priors for all constrained models can be derived from this encompassing prior. Different choices for this encompassing prior will be considered and evaluated.
THE CHARACTERISTICS OF POLYTROPIC MAGNETIC REFRIGERATION CYCLES

The concepts of generalized polytropic processes and polytropic refrigeration cycles, which consist of two isothermal processes and two generalized polytropic processes of paramagnetic salt, are introduced. It is shown that such a class of general magnetic refrigeration cycles, which includes the Carnot, Stirling, and other useful magnetic refrigeration cycles, possesses the conditions of perfect regeneration and can have the same coefficient of performance as the Carnot cycle for the same temperature range. Thus, they have many applications in the research and manufacture of magnetic refrigerators.
Twenty-five well-justified fossil calibrations for primate divergences

Phylogenies with estimates of divergence times are essential for investigating many evolutionary questions. In principle, “tip-dating” is arguably the most appropriate approach, with fossil and extant taxa analysed together in a single analysis, and topology and divergence times estimated simultaneously. However, “node-dating” (as used in many molecular clock analyses), in which fossil evidence is used to calibrate the age of particular nodes a priori, will probably remain the dominant approach, due to various issues with analysing morphological and molecular data together. Here, we provide a list of 25 well-justified node calibrations for primate divergences, following best practices: 16 within Haplorhini, four within Strepsirrhini, one for crown Primates, and four for older divergences within Euarchontoglires. In each case, we provide a hard minimum bound, and for 22 of these we also provide a soft maximum bound and a suggested prior distribution. For each calibrated node, we provide the age of the oldest fossil of each daughter lineage that descends from it, which allows use of the “CladeAge” method for specifying priors on node ages. Dorien de Vries. Ecosystems and Environment Research Centre, School of Science, Engineering and Environment, University of Salford, Manchester, UK. (Corresponding author) d.devries@salford.ac. uk @PaleoDorien Robin M.D. Beck. Ecosystems and Environment Research Centre, School of Science, Engineering and Environment, University of Salford, Manchester, UK. r.m.d.beck@salford.ac. uk @robinmdbeck