Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of theoretical and experimental methods of Raman spectroscopy in the determination of unsaturated fatty acids in vegetable oils

The Raman spectra of five samples of sunflower seed oil and five samples of cold-pressed olive oil of various brands are recorded in the range of 500–2000 cm–1. Within the framework of the B3LYP/631G(d)/6-31G(d,p)/6-31+G(d,p)/6- 311G(d)/6-311G(d, p)/6-311+G(d,p) methods, the structural models of eight fatty acids (oleic, linoleic, palmitic, stearic, α-linolenic, arachidonic, eicosapentaenoic, and docosahexaenoic) are constructed, and also within the framework of the B3LYP/6-31G(d) method, the structural models of triglycerides of the first four of the above acids are obtained. The vibrational wavenumbers and intensities in the IR and Raman spectra are calculated. The Raman spectra of olive oil and sunflower seed oil were simulated by using the supermolecular approach. We investigated the dependence of the relative intensity of the vibrational bands νexp = 1660 and 1445 cm–1 on the concentration of triglycerides in oils of oleic and linoleic acids and the dependence of the intensity of these bands on the degree of saturation of fatty acids. Experimental and empirical dependences are constructed to estimate the relative concentration of triglycerides of oleic and linoleic acids in a mixture of olive oil and sunflower seed oil. The applicability of the density functional theory together with the vibrational spectroscopy for the identification of mixtures of vegetable oils is discussed.
Scanner-Based Minirhizotrons Help to Highlight Relations between Deep Roots and Yield in Various Wheat Cultivars under Combined Water and Nitrogen Deficit Conditions

Breeding for crops in the context of climate change necessitates phenotyping tools for roots in field conditions. Such in-field phenotyping requires the development of rapid and non-destructive measurement techniques for the screening of relevant root traits under sub-optimal conditions. In this study, we used scanner-based minirhizotrons to measure in situ the root length and surface/volume densities of roots for four wheat varieties, under four different growth conditions: irrigated and rainfed coupled with optimal and sub-optimal N fertilization under a Mediterranean climate. For all the treatments, grain yield correlates with minirhizotron-based root surface density measured at anthesis (r2 = 0.48). Irrigated and rainfed conditions led to contrasted relations between roots and grain yield: no correlation was found in irrigated plots, while under rainfed conditions and sub-optimal fertilization, the higher yields are related to a higher root colonization of the deeper soil layers (r2 = 0.40). Shoot biomass was correlated to grain yield in irrigated conditions, but not in rainfed conditions. However, for the latter, the total root weight, the proportion of which being mainly located in the top soil, is not related to the grain yield. In this way, we show the relationship between these higher grain yields and a stress avoidance mechanism of the root system characterized by a higher root density in the deep soil layers. Thus, unlike shoot biomass measurements, scanner-based minirhizotron allows the direct detection of such a stress-related root development, and therefore opens the door to a better prediction of grain yield.
Standardization and Industrialized Construction of Special Purpose Buildings

Purpose The aim of the present study is to look into the potential of standardization of special purpose buildings, with the example of the Norwegian Directorate of Public Construction and Property Management (Statsbygg). Design/Methodology/Approach The present study uses results from a group workshop on the topic of standardization, suggesting building types suitable for standardization or modular construction. In addition, data from Statsbygg’s project database is used. Findings There is a broad specter of special purpose buildings with potential for standardization, such as customs facilities, courthouses, university buildings and buildings with a high share of office functions. Even buildings with an individualized character, such as museums or government buildings, have a certain potential for standardization of functional or constructional elements. Modular construction can be used where and when appropriate. Research Limitations/Implications Being on a brainstorming level and limited to Statsbygg, the study provides a starting point for further research looking at other building commissioners working with special purpose buildings, or quantifying the potential for cost reduction. Practical Implications On the basis of the findings from this study, Statsbygg considers further standardization of their special purpose buildings, not only within building types but also across the portfolio or within a project, for example rooms or functional elements. Originality/Value Research on standardization of special purpose buildings is limited. The article presents the results of a workshop with project managers, contributing to the topic based on their experience from the construction of special purpose buildings. Although on a brainstorming level, the research is a starting point for further research into this topic.
A method to estimate baseline and platform altitude for SAR interferometry

A method to estimate baseline parameters for SAR interferometry is described in the paper. The proposed method uses three interferograms by three observations. This method is applied to ERS-1 SAR data. The result shows that baseline parameters are estimated with residual phase difference RMS error of less than 20/spl deg/ (about one-twentieth of a cycle), while initial phase difference error calculated by using orbit information is more than 2100/spl deg/ (several cycles).
Single Stage Matrix Vector Multiplication via Hadoop Map-Reduce

This report explores an algorithm to perform Power method iterations in the cloud via Hadoop Map-Reduce. With the inclusion of a preprocessing procedure, only a single Map-Reduce stage is required per iteration. Several Optimizations were considered that improved the speed of the algorithm. The proposed approach can also be altered such that under certain conditions, the preprocessing is incorporated into the first multiplication step. It can also be extended to perform Jacobi method iterations.
Improving Learning Effectiveness for a Third Year Materials Unit

Background: Our recent teaching practice for a third year materials unit is presented in this paper. Because of the large enrolment number ( 180) and limited teaching staff, no assignment was given during the whole semester, and full solutions were directly given in the tutorials, which resulted in the problems of low motivation of study and poor performance. In this year's teaching, we attempted a new strategy incorporating active learning techniques, peer learning and statistical analysis. Purpose: The purpose of this study was testing if the learning effectiveness could be improved by applying active learning, peer learning and statistical analysis. Design/Method: In the teaching for the tutorials of this unit, active learning techniques were attempted. Handouts with gaps were given in the tutorial classes to promote active thinking. Since solving these questions requires consulting engineering charts and tables, there will be differences from person to person. The students were asked to attempt the questions and send the result by email. They were also encouraged to form groups and learn from peers. The results being received were analysed statistically and the distribution was released to the students. There are potentially two benefits: 1) this approach helps the students to derive the correct answer; and 2) this approach gives the students a direct sense about the typical variations of the answers to an exam question, and helps them understand the variations in engineering. Results: It is shown from our study that the students were more actively engaged with the learning process and became active thinkers, compared to the previous years. The learning outcomes were significantly improved, which was evidenced by the exam results and the student evaluations. Conclusions: Active learning can significantly improve the learning effectiveness of engineering units. By utilising peer learning and statistical analysis, students can also learn the variations in the real engineering practice, and team work skills. Thus, they will be more prepared to become professional engineers.
Experiences using the Cray Multi-Threaded Architecture (MTA-2)

The Naval Research Laboratory has recently installed and is operating a 40-processor Cray Multithreaded Architecture (MTA-2) computer. The MTA-2 with its hardware support for multithreading and large uniformly accessible memory offers a promising new paradigm in parallel computing, especially for large problems. In order to evaluate the machine, four typical applications whose structures would lend themselves to the MTA were selected and evaluated in terms of the level of effort and reprogramming required in contrast to the benefits in running in an MTA environment. The amount of changes required to port the code ranged from very little to a substantial rewrite of portions of the code. Performance improvements ranging from a factor of two to more than 10 over the previous implementations were noted.
Coastline detection in SAR images using texture analysis in textural or geometrical multi-resolution

A new method is proposed in this paper for coastline extraction which uses the SAR amplitude images, or if available, the interferometric coherence images. This method uses texture analysis based on textural multi-resolution (TMR) or geometrical multi-resolution (GMR), for a fine analysis of coastline. First order texture measures (TM) have been used. In TMR, a series of TM are generated at various textural scales from the original image. In GMR case, a wavelet transform produces a low-resolution approximation of the original image. Consequently, TM are also generated at a suitable low-resolution approximation. A selection of the suitable TM in one or another multi-resolution approach, leads to a good separation of sea and coastal area and reveals coastline. A detection of discontinuities allows then easy extraction of coastline. The obtained results are promising and show a good detection, and a good continuity of coastline. A proposed method has been tested on ERS SAR amplitude and coherence coastal region images of Cameroon, Mauritania and Guyana.
Background Modeling and Foreground Detection for Video Surveillance

Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction. The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the books website. A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and humancomputer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.
Type synthesis and kinematics analysis of a family of three translational and one rotational pick-and-place parallel mechanisms with high rotational capability

This article proposes a family of spatial three translational and one rotational parallel mechanisms (PMs) for pick-and-place operation. Their features are one independent rotation of the mechanism with four identical limbs, which are provided by the four revolute joints on the moving platform. The rotational capability of the PMs has a range of at least 180°. This article focuses on the synthesis of the PMs and kinematics analysis of the 4-P(2-SS)R parallel mechanism. First, based on the Lie group theory, three parallelograms are used in designing the PMs. The limbs are listed and two types of three translational and one rotational PMs are synthesized. Then, a typical 4-P(2-SS)R PM is selected, the 6 × 6 Jacobian matrix and the 6 × 6 × 6 Hessian matrix of the mechanism are derived for solving the displacement, velocity, and acceleration of the mechanism. Finally, singularity configurations are disclosed from the 6 × 6 Jacobian matrix, and the workspace of the mechanism is provided to illustrate the high rotational capability.
Parallel Branch and Bound Algorithm - A comparison between serial, OpenMP and MPI implementations

This paper presents a comparison of an extended version of the regular Branch and Bound algorithm previously implemented in serial with a new parallel implementation, using both MPI (distributed memory parallel model) and OpenMP (shared memory parallel model). The branch-and-bound algorithm is an enumerative optimization technique, where finding a solution to a mixed integer programming (MIP) problem is based on the construction of a tree where nodes represent candidate problems and branches represent the new restrictions to be considered. Through this tree all integer solutions of the feasible region of the problem are listed explicitly or implicitly ensuring that all the optimal solutions will be found. A common approach to solve such problems is to convert sub-problems of the mixed integer problem to linear programming problems, thereby eliminating some of the integer constraints, and then trying to solve that problem using an existing linear program approach. The paper describes the general branch and bound algorithm used and provides details on the implementation and the results of the comparison.
The high performance storage system (HPSS)

Ever more powerful computers and rapidly enlarging data sets require unprecedented levels of data storage and access capabilities. To help meet these requirements, the scalable, network-centered, parallel storage system HPSS was designed and is now being developed. The parallel 1/0 architecture, mechanisms, strategies and capabilities are described. The current development status and the broad applicability are illustrated through a discussion of the sites at which HPSS is now being implemented, representing a spectrum of computing environments. Planned capabilities and time scales will be provided. Some of the remarkable developments in storage media data density looming on the horizon will also be noted.
Hyperspectral Image Resolution EnhancementUsing Object Tagging OLHE Technique

Resolution plays an important role in hyperspectral images like satellite images. The discrete wavelet transform based (DWT) resolution enhancement scheme generates artifacts due to a shift-variant property. Resolution enhancement based on dual-tree complex wavelet transform (DT-CWT) and nonlocal means (NLM) suffers from high latency. In this paper a new method based on oriented local histogram equalization (OLHE) is proposed for resolution enhancement of hyper spectral images. Satellite Images acquired by satellite is affected by impulse noise. This impulse noise distorts the edge pixels in the satellite image, which degrades the segmentation process. Hence, this impulse noise should be removed before enhancing satellite images. Optimum Edge preserving impulse noise removing algorithm is proposed in this paper to remove the impulse noise present in the satellite image. OLHE technique which is similar to local histogram equalization is proposed to capture the orientation of edges in the image that enhances the resolution. Performance analysis is made by calculating PSNR and MSE value which reveals superiority of the proposed technique over the conventional and state-of-the-art RE techniques.
A New Signal Processing Approach to Study Action Potential Content in Sympathetic Neural Signals

Sympathetic nerve activity plays an essential role in the normal regulation of blood pressure in humans and in the etiology and progression of many chronic diseases. Sympathetic nerve recordings associated with blood pressure regulation can be recorded directly using microneurography. A general characteristic of this signal is spontaneous burst activity of spikes (action potentials) separated by silent periods against a background of considerable gaussian noise. During measurement with electrodes, the raw muscle sympathetic nerve activity (MSNA) signal is amplified, band-pass filtered, rectified and integrated. This integration process removes important information regarding action potential content and their discharge properties. The first objective of this thesis was to propose a new method for detecting action potentials from the raw MSNA signal to enable investigation of post-ganglionic neural discharge properties. The new method is based on the design of a mother wavelet that is matched to an actual mean action potential template extracted from a raw MSNA signal and applying it to the raw MSNA signal using a continues wavelet transform (CWT) for spike detection. The performance of the proposed method versus two previous wavelet-based approaches was evaluated using 1) MSNA recorded from seven healthy participants and, 2)simulated MSNA. The results show that the new matched wavelet performs better than the previous wavelet-based methods that use a non-matched wavelet in detecting action potentials in the MSNA signal. The second objective of this thesis was to employ the proposed action potential detection and classification technique to study the relationship between the recruitment of sympathetic action potentials (i.e., neurons) and the size of integrated sympathetic bursts in human MSNA signal. While in other neural systems (e.g. the skeletal motor system) there is a well understood pattern of neural recruitment during activation, our understanding of how sympathetic neurons are coordinated during baseline and baroreceptor unloading are very limited. We demonstrate that there exists a hierarchical pattern of recruitment of additional faster conducting neurons of larger amplitude as the sympathetic bursts become stronger. This information has important implications for how blood pressure is controlled, and the malleability of sympathetic activa-
Interferometric point target analysis for deformation mapping

Interferometric Point Target Analysis (IPTA) is a method to exploit the temporal and spatial characteristics of interferometric signatures collected from point targets to accurately map surface deformation histories, terrain heights, and relative atmospheric path delays. In this contribution the IPTA concept is introduced, including the point selection criteria, the phase model and the iterative improvement of the model parameters. Intermediate and final results of an IPTA example using a stack of ERS-1 and ERS-2 data, confirm the validity of the concept and indicate a high accuracy of the resulting products.
Investigation of JPEG2000 image transmission over next generation wireless networks

The JPEG2000 standard was introduced for image compression. An analytical model is proposed for accurately predicting the resulting quality of JPEG2000-encoded images, if the bit-stream is transmitted over error-prone wireless channels. The estimation accuracy of the analytical model is validated by simulation results. Such an analytical model can be utilized by the base station to design efficient unequal error protection scheme for transmitting JPEG2000-encoded images over next generation wireless networks.
Multi-task Learning

Multi-task learning can leverage information learned by one task to benefit the training of other tasks. Despite this capacity, naı̈ve formulations often degrade performance and in particular, identifying the tasks that would benefit from cotraining remains a challenging design question. In this paper, we analyze the dynamics of information transfer, or transference, across tasks throughout training. Specifically, we develop a similarity measure that can quantify transference among tasks and use this quantity to both better understand the optimization dynamics of multi-task learning as well as improve overall learning performance. In the latter case, we propose two methods to leverage our transference metric. The first operates at a macro-level by selecting which tasks should train together while the second functions at a micro-level by determining how to combine task gradients at each training step. We find these methods can lead to significant improvement over prior work on three supervised multi-task learning benchmarks and one multi-task reinforcement learning paradigm.
Control algorithms for a vertically-constrained one-legged hopping machine

A physical prototype of a vertically-constrained, one-legged hopping machine is presented. The machine consists of an elevated body supported by a single springy leg and a leg actuator used to manipulate the leg's length. The body of the machine is a DC motor. The leg and leg actuator are a system of tubes and a mechanical spring that allow smooth and repeatable hopping. Three control algorithms that regulate the machine's hopping height are presented and tested experimentally. These are: (i) a tabular control scheme that selects the control input on the basis of the desired steady-state hopping height; (ii) a near-inverse controller based on a discrete, hop-to-hop model of the plant dynamics; and (iii) a near-inverse controller with integral error feedback. The machine's transient and steady-state behavior is evaluated for each controller. The effectiveness of the algorithms is further assessed by subjecting the controlled system to abrupt changes in the body mass. Experimental data indicate that the near-inverse controller with integral height-error feedback gives the best results in compensating for parameter variations. <<ETX>>