Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and synthesis of a class of discrete-time neural networks with nonlinear interconnections

A qualitative analysis and a synthesis procedure for a class of discrete-time synchronous neural networks with nonlinear interconnections (of polynomial form) are presented. Networks generated by this synthesis procedure have, in general, greater memory storage capacity than corresponding networks with linear interconnecting structure. The qualitative results which constitute the basis of the synthesis procedure include a simple stability test for the equilibrium points of the class of networks considered. Conditions under which such networks are globally stable have not been identified at this time. In order to simplify the presentation, the authors confine themselves to second-order polynomial network interconnections; however, the qualitative results and the synthesis procedure developed apply to networks with higher-order polynomial interconnections as well. <<ETX>>
A Study on BFO Algorithm based PID Controller Design for MIMO Process using Various Cost Functions

Background/Objectives: The objective of this paper is to design a decentralised PID controller for MIMO process model using Bacterial Foraging Optimization (BFO) algorithm using three different cost functions. Methods/Statistical analysis: In this work, each decentralised PID controller is separately designed for the top product loop and bottom product loop. The proposed method is tested on Wood and Berry (WB) model and Wardle and Wood (WW) model. A comparative study is presented on the considered cost function using the quality measure values, such as ITSE, ITAE, number of iteration and CPU time taken for the simulation. Findings: The result confirms that, all the cost function based approaches offers similar result. Application/Improvements: In future, this method can be tested using some most successful heuristic algorithms existing in the literature.
The Seismic Response to Injected Carbon Dioxide: Comparing Observations to Estimates Based Upon Fluid Flow Modeling

Time‐lapse seismic amplitude differences and travel time shifts, obtained while monitoring enhanced oil recovery at Cranfield, Mississippi, reveal coherent changes that are associated with the injection of carbon dioxide. Rock physics modeling highlights the importance of the oil, brine, and gas content of pore fluids prior to the injection of carbon dioxide. For example, compressional velocity changes due to the injection of carbon dioxide can drop from 300 m/s to less than 100 m/s as the percentage of oil increases from 1% to 50%. Predictions based upon a new technique for modeling wave propagation in a poroelastic medium containing an arbitrary number of fluids, coupled with multicomponent numerical reservoir modeling at Cranfield, reproduce the general pattern of observed seismic amplitude changes and travel time shifts. In particular, time‐lapse amplitude changes suggest a significant and widespread lowering of compressional velocities due to the injection of CO2 into an aquifer bounding the oil rim of the reservoir. It appears that the large‐scale variations in preexisting pore fluid content have a major influence on seismic velocity changes, even in the highly heterogeneous reservoir at Cranfield.
Downscaling Land Surface Temperature from MODIS Dataset with Random Forest Approach over Alpine Vegetated Areas

In this study, we evaluated three different downscaling approaches to enhance spatial resolution of thermal imagery over Alpine vegetated areas. Due to the topographical and land-cover complexity and to the sparse distribution of meteorological stations in the region, the remotely-sensed land surface temperature (LST) at regional scale is of major area of interest for environmental applications. Even though the Moderate Resolution Imaging Spectroradiometer (MODIS) LST fills the gap regarding high temporal resolution and length of the time-series, its spatial resolution is not adequate for mountainous areas. Given this limitation, random forest algorithm for downscaling LST to 250 m spatial resolution was evaluated. This study exploits daily MODIS LST with a spatial resolution of 1 km to obtain sub-pixel information at 250 m spatial resolution. The nonlinear relationship between coarse resolution MODIS LST (CR) and fine resolution (FR) explanatory variables was performed by building three different models including: (i) all pixels (BM), (ii) only pixels with more than 90% of vegetation content (EM1) and (iii) only pixels with 75% threshold of homogeneity for vegetated land-cover classes (EM2). We considered normalized difference vegetation index (NDVI) and digital elevation model (DEM) as predictors. The performances of the thermal downscaling methods were evaluated by the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE) between the downscaled dataset and Landsat LST. Validation indicated that the error values for vegetation fraction (EM1, EM2) were smaller than for basic modelling (BM). BM model determined averaged RMSE of 2.3 K and MAE of 1.8 K. Enhanced methods (EM1 and EM2) gave slightly better results yielding 2.2 K and 1.7 K for RMSE and MAE, respectively. In contrast to the EMs, BM showed a reduction of 22% and 18% of RMSE and MAE respectively with regard to Landsat and the original MODIS LST. Despite some limitations, mainly due to cloud contamination effect and coarse resolution pixel heterogeneity, random forest downscaling exhibits a large potential for producing improved LST maps.
Blue-collar workers, career success and innovation in manufacturing

Purpose The purpose of this paper is to contribute to the understanding of the relationship between employees’ knowledge and organisational performance. Design/methodology/approach Using a structural equation model, feedback received from 237 blue-collar workers from multinational high-tech manufacturing enterprises in Italy was studied to understand, from a dynamic capabilities perspective, the role of soft skills in the career success of production workers. Findings The results of the analysis indicate a positive relationship between workers’ commitment to develop their soft skills and their career success, as well as a positive relationship between an organisation’s approach to both knowledge exploration and knowledge exploitation and the prospects for career success of blue-collar workers. Research limitations/implications The research has both theoretical and practical implications, as any efforts by researchers and practitioners to find effective ways to motivate the workforce will be likely to lead to a positive attitude towards learning and, ultimately, to improved business performance. Originality/value The originality of the paper is the focus on the personality and interpersonal attributes of workforce – blue-collar workers – and how they can affect business performance in highly innovative contexts.
Digital Music Piece Identification using Local Maxima

BitTorrent is one of the most common P2P protocols for distributing large files over the Internet. Internet users can easily share their movie and music files using BitTorrent. The file is shared by dividing into pieces and BitTorrent seed file has the hash values of each pieces for identifying each piece. It means the piece is not identified without seed file. In this paper we proposed an improved identification method for music pieces using local maxima and general chromatic algorithm without seed file. The method improved the identification ratio up to 31% more than that using general chromatic algorithm.
The Fields of Flow and Temperatures in the Chambers of Radiation of Tube Furnaces with Multi-tier Wall Burners of Two Types

In the article, the differential method of thermal calculation of a furnace is used to determine the aerodynamic and thermal characteristics in the chambers of radiation of tube furnaces with wall burners of two types located on several tiers. In the methane steam reforming furnace, the acoustic burners of the near-wall flame gas fuel are arranged in three tiers on the side walls of the radiation chamber. In the primary reforming furnace for the production of ammonium nitrate, wall-mounted burners are located on six tiers. The method implies joint numerical solution of 2D radiation transfer equations using the S 2 -approximation of the discrete ordinate method, of energy equations, flow equations, k-e turbulence model, and two stage modeling of gas fuel combustion. Is it given a brief description of the boundary conditions for differential equations and the method of their numerical solution. The results of the calculation of the temperature fields and the flow of combustion products in the radiation chamber of the furnace obtained with the help of a computer program that implements the described method are given.
Elasticity of Phases in Fe-Al-Ti Superalloys: Impact of Atomic Order and Anti-Phase Boundaries

We combine theoretical and experimental tools to study elastic properties of Fe-Al-Ti superalloys. Focusing on samples with chemical composition Fe71Al22Ti7, we use transmission electron microscopy (TEM) to detect their two-phase superalloy nano-structure (consisting of cuboids embedded into a matrix). The chemical composition of both phases, Fe66.2Al23. 3Ti10.5 for cuboids and Fe81Al19 (with about 1% or less of Ti) for the matrix, was determined from an Energy-Dispersive X-ray Spectroscopy (EDS) analysis. The phase of cuboids is found to be a rather strongly off-stoichiometric (Fe-rich and Ti-poor) variant of Heusler Fe2TiAl intermetallic compound with the L21 structure. The phase of the matrix is a solid solution of Al atoms in a ferromagnetic body-centered cubic (bcc) Fe. Quantum-mechanical calculations were employed to obtain an insight into elastic properties of the two phases. Three distributions of chemical species were simulated for the phase of cuboids (A2, B2 and L21) in order to determine a sublattice preference of the excess Fe atoms. The lowest formation energy was obtained when the excess Fe atoms form a solid solution with the Ti atoms at the Ti-sublattice within the Heusler L21 phase (L21 variant). Similarly, three configurations of Al atoms in the phase of the matrix with different level of order (A2, B2 and D03) were simulated. The computed formation energy is the lowest when all the 1st and 2nd nearest-neighbor Al-Al pairs are eliminated (the D03 variant). Next, the elastic tensors of all phases were calculated. The maximum Young’s modulus is found to increase with increasing chemical order. Further we simulated an anti-phase boundary (APB) in the L21 phase of cuboids and observed an elastic softening (as another effect of the APB, we also predict a significant increase of the total magnetic moment by 140% when compared with the APB-free material). Finally, to validate these predicted trends, a nano-scale dynamical mechanical analysis (nanoDMA) was used to probe elasticity of phases. Consistent with the prediction, the cuboids were found stiffer.
Handling Selfishness in MANETs A Survey

A mobile ad hoc network (MANET) is an infrastructure-less network with self-configuring capability of mobile nodes connected wirelessly. In mobile ad hoc network, some nodes may selfishly decide only to cooperate partially, or not at all, with other nodes. These selfish nodes could then reduce the overall data accessibility in the network along with an increase in query delay. In the past, many people have worked on this selfish node problem, and proposed several methods to detect these selfish nodes. This paper provides a survey on different methods used to detect selfish nodes in MANETs. It also provides an overview on data replication in a mobile adhoc network, andcertain methods to handle selfishness occurring in this replica allocation process. It is being proposed to use a combined credit risk and collaborative watchdog method to improve the network performance by detecting such selfish nodes within a reduced time period.
Understanding the volume-diffusion governed shape-instabilities in metallic systems

The reliability of any day-to-day material is critically dictated by its properties. One factor which governs the behaviour of a material, under a given condition, is the microstructure. Despite the absence of any phase transformation, a change in the microstructure would significantly alter the properties. Therefore, a substantial understanding on the stability of the microstructure is vital to avert any unexpected catastrophic change in the material properties. In the present work, one such numerical approach called phase-field modelling in employed to analyse the stability of two- and three-dimensional finite structures, which dictate the curvature-driven evolution of the microstructure. A characteristic feature of this numerical approach is the introduction of a scalar variable, called the phase field, in addition to the other thermodynamic variables. While the inclusion of the phase field obviates the need for the interface tracking, which is a strenuous aspect of the other conventional techniques, it replaces the sharp interface with a finite diffuse region. Therefore, before adopting and extending the phase-field technique, it is shown that the model recovers the governing law, i.e, Gibbs-Thomson relation, despite the introduction of the diffuse interface. Subsequently, the numerical treatment is employed to investigate the volume-diffusion governed curvature-induced transformation.
Speech recognition using connectionist networks

The use of connectionist networks for speech recognition is assessed using a set of representative phonetic discrimination problems. The problems are chosen with respect to the physiological theory of phonetics in order to give broad coverage to the space of articulatory phonetics. Separate network solutions are sought to each phonetic discrimination problem. A connectionist network model called the Temporal Flow Model is defined which consists of simple processing units with single valued outputs interconnected by links of variable weight. The model represents temporal relationships using delay links and permits general patterns of connectivity including feedback. It is argued that the model has properties appropriate for time varying signals such as speech. Methods for selecting network architectures for different recognition problems are presented. The architectures discussed include random networks, minimally structured networks, hand crafted networks and networks automatically generated based on samples of speech data. Networks are trained by modifying their weight parameters so as to minimize the mean squared error between the actual and the desired response of the output units. The desired output unit response is specified by a target function. Training is accomplished by a second order method of iterative nonlinear optimization by gradient descent which incorporates a method for computing the complete gradient of recurrent networks. Network solutions are demonstrated for all eight phonetic discrimination problems for one male speaker. The network solutions are analyzed carefully and are shown in every case to make use of known acoustic phonetic cues. The network solutions vary in the degree to which they make use of context dependent cues to achieve phoneme recognition. The network solutions were tested on data not used for training and achieved an average accuracy of 99.5 $\pm$ 0.4%. Methods for extending these results to a single network for recognizing the complete phoneme set from continuous speech obtained from different speakers are outlined. It is concluded that acoustic phonetic speech recognition can be accomplished using connectionist networks.
Testing Temporal Data Validity in Oracle 12c using Valid Time Temporal Dimension and Queries

The time aspect of data can be easily represented by Temporal Database. Temporal Database allows you to associate time element with data through temporal validity support. Temporal Validity allows you to associate one or more valid time dimensions with a table and have data be visible depending on its time-based validity, as determined by the start and end dates or time stamps of the period for which a given record is considered to be a valid record. This work aims at testing temporal data with valid time dimensions of temporal database. By using the capabilities of Oracle 12c this work highlights sequence for adding a valid time dimension to a table, and various methods for querying the table and retrieving temporal data based on a specified valid time value or range.
Barriers to Hospital Food Waste: A Pilot Exploratory Study

Food waste is an ever-growing problem in this country and hospitals are large producers of food waste. Food is something that is beneficial to everyone on the planet, but when wasted, it creates added methane gas production which contributes to the greenhouse gas effect. There is a paucity in the literature concerning industry specific food waste disposal processes. To add knowledge about food waste in Maine, a 24question survey was used to ask healthcare organizations nutritional and environmental personnel about, food disposal, reuse, and environmental sustainability efforts. The data was analyzed using descriptive statistics. The response rate was low, however the data provided some insight into food waste in healthcare institutions. With a better understanding, new efforts can focus to food waste reduction, circular economy support, and environmental sustainability.
A hierarchical clustering methodology based on genetic programming for the solution of simple cell-formation problems

The problem of identifying machine cells and corresponding part families in cellular manufacturing has been extensively researched over the last thirty years. However, the complexity of the problem and the considerable number of issues involved in its solution create the need for increasingly efficient algorithms. In this paper the use of genetic programming for the solution of a simple version of the problem is investigated. The methodology is tested on a number of problems taken from the literature and comparative results are presented.
Structure of Lark Sparrow Song in California

We studied the song of the lark Sparrow (Chondestes grammacus) in recordings of 15 individuals from a variety of locations in California. lark Sparrow song is delivered as variable sequences structured in a hierarchy of four levels: elements, syllables, strophes, and themes. at the simplest level, elements can be distinguished by their appearance on a spectrogram. Birds vary the number of repetitions of each element to produce a syllable and string together several syllables to produce a strophe (mean 5.9 syllables per strophe). Strophes are delivered at an average rate of 5.4 per minute. Strophes can be further classified as belonging to one of a few themes in a male’s repertoire, where strophes in different themes are composed of almost entirely distinct elements and syllables. in <6% of strophes did we find elements from one theme mixed with elements from a different theme. Each individual sang one to three themes. The size of the repertoire of strophes is large but we could not quantify it because within a continuous bout of singing any particular sequence of syllables was repeated in only 5% of strophes. Each theme comprised roughly 20–40 distinct syllables. Thus an individual singing three themes could have a repertoire of 60–120 syllables. The number of unique elements per theme ranged from 11 in birds revealing just one theme up to 39 in birds revealing three themes, but longer recordings may have yielded more elements per bird. if our observations for single-themed birds may be extrapolated, birds with three themes might have repertoires of 33–51 elements. in the two comparisons possible, we detected almost no sharing of elements among neighboring birds. one of the most fascinating aspects of bird behavior is the remarkable range in size of the song repertoire among different species of songbirds (Kroodsma 2005, Catchpole and Slater 2008, Pieplow 2017). individuals of many species, such as the Chipping Sparrow (Spizella passerina; Borror 1959), ovenbird (Seiurus aurocapilla; lein 1981), and Zebra finch (Taeniopygia guttata; Catchpole and Slater 2008), get by with a single simple primary song that varies little. others, such as the White-crowned Sparrow
The role of facilitation and social processes in collaborative learning: Implications for the design of an applied systems science curriculum

ix List of Tables . xi List of Figures . xii List of Appendices . xiii List of Abbreviations . xiv Preface . xv Background . xv Facilitating collaborative learning . xviii Overview of the chapters . xix Chapter 1: Introduction . 1 1.1. Chapter overview . 1 1.2. John Warfield and applied systems science . 1 1.3. Philosophical and theoretical underpinnings of collaborative learning . 14 1.4. Advancing Learning Sciences approaches to collaborative learning: a focus on learning processes and orchestration . 27 1.5. Designing CSCL environments: Applied systems science education . 39 Chapter 2: Collaborative learning processes and outcomes . 42 2.1. Chapter overview . 42 2.2. An overview of collaborative learning outcomes . 42 2.3. Process-oriented research in collaborative learning . 44 2.4. Argumentation and collaborative learning . 46 2.5. Peer learning . 65 2.6. From instructional processes to social processes social psychological factors in collaborative learning . 69 2.7. Rationale for the current research . 88
A Chirped Pulse Fourier Transform Millimeter WaveSpectrometer for Room Temperature, Gas Mixture Analysis

A new arbitrary waveform generator based, chirped pulse spectrometer for high- resolution, millimeter wave rotational spectroscopy of gas mixtures is presented. The spectrometer band covers the frequency range from 260 – 295 GHz, a favorable spectral window for room temperature analysis of small molecules with a molecular mass of less than 150 amu. The design leverages the state of the art in solid-state millimeter light sources and high-speed digital electronics to introduce significant advances for millimeter/submillimeter spectroscopy, which is conventionally addressed by direct absorption techniques. By efficient use of a high power millimeter wave light source, the chirped pulse spectrometer is 10,000 times faster than modern direct absorption counterparts. In addition to speed, the time resolved emission spectroscopy approach enables analytical tools that can be used to speed spectral assignment in unknown samples. Results of sensitivity, dynamic range, and chemical selectivity are presented using compressed gases as an initial benchmark followed by extensions to real gas mixtures. The results have implications to a broad set of basic science research applications and make a strong case for wider application to analytical challenges as a new commercial platform.
A Adaptive Dorsal Hand Vein Recognition Algorithm Based on Optimized HMM

As a kind of biometric feature authentication method, vein recognition has more merits than others. In this paper, a new vein recognition algorithm based on adaptive hidden Markov model (HMM), where the parameters of HMM are optimized by using stepper increasing method according to different vein databases, and in the database every vein object can be represented as a HMM. Because the main features of vein image are reflected in direction and location, and the direction and location information of image can be obtained through Radon Transform, Radon Transform is applied to the thinned vein image which was obtained after pre-processing; Different sets of HMM parameters are used in different databases, in the proposed algorithm the parameters, which include the number of states, the number of distinct observable symbols and the number of observations in the sequence, are adjusted by stepper increasing. Experimental results show that the proposed recognition method outperforms two other methods which are based on feature points and image fusion respectively in terms of correct identification rate, and the recognition time 0.850s is sufficient to meet the requirement of real-time.