Miracle-dz/UniFAR-FTUs huggingface dataset:
Circularly Polarized Wearable Antennas

By employing circularly polarized antennas, it is possible to prevent polarization mismatch losses which in turn increases the connection reliability between communication devices. This chapter focuses on circularly polarized wearable antennas. The Introduction section presents the motives behind this particular antenna type and discusses the advantages of circular polarization in wearable applications, not forgetting the challenges involved in the implementation of such antennas. To understand the nature of circular polarization, and to avoid design errors, a brief theory section follows. The next section is dedicated to survey the scientific publications related to this vital topic, providing a review of the latest developments. Finally, a case study of a dual-band circularly polarized wearable antenna for personal satellite communication and navigation at L1 and Iridium frequency bands is presented. The section goes through the design procedure from material selection to antenna performance evaluation by means of return loss and radiation measurements.
Virtual Time-Inverse OFDM Underwater Acoustic Channel Estimation Algorithm Based on Compressed Sensing

The severe multipath delay of the underwater acoustic channel, the Doppler shift, the severe time-varying characteristics, and sparsity make it difficult to obtain the channel state information in the channel estimation of the virtual time-reverse mirror OFDM, which makes the virtual time mirror subcarrier orthogonality easy to suffer damage; the focusing effect is not obvious. Therefore, this paper proposes a virtual time-inverse OFDM underwater acoustic channel estimation algorithm based on compressed sensing. The algorithm extracts the detection signal, constructs a sparse signal model of the delay-Doppler shift, and then performs preestimation of the underwater acoustic channel based on the compressed sensing theory. Then, by predicting the timing of the underwater acoustic channel and convolving with the received signal, the algorithm improves the focusing effect better. Experimental simulations show that compared with LS and OMP algorithms, the algorithm can accurately recover channel information from a small number of observations, reduce the bit error rate by 10%, and improve the accuracy of channel estimation and the time-inverse OFDM performance of virtual time.
Screening of Chinese brassica species for anti-cancer sulforaphane and erucin

Natural sulforaphane and erucin have been of increasing interest for nutraceutical and pharmaceutical industries due to their anti-cancer effect. The sulforaphane and/or erucin contents in seeds of 43 different Chinese Brassica oleracea L. varieties were analyzed by HPLC and GC-MS. Among them, 21 cultivars seed meal (in 5 species, including Chinese kale, cabbage, kohlrabi, kale and broccoli) yielded sulforaphane and/or erucin. The results indicated that erucin was found mainly in cabbage and kohlrabi, and sulforaphane was found mainly in broccoli. The highest content of sulforaphane (1575.5 mg/kg) and erucin (2528.1 mg/kg) were found in Green Dragon I (broccoli) and Dongchunbao (cabbage), respectively. Crude sulforaphane and erucin were extracted in gram-scale; 1.266 g sulforaphane (purity: 78.2%) and 0.972 g erucin (purity: 65.6%) were obtained.
Grain yield responses of faba bean (Vicia faba L.) to applications of fertiliser phosphorus and zinc.

Seed (grain) yield responses of faba bean (Vicia faba L. cv. Fiord) to applications of fertiliser phosphorus (0, 5, 10, 20 and 40 kg P/ha as triple superphosphate) and zinc (0, 0.5, 1 and 2 kg Zn/ha as zinc oxide) were measured in 3 field experiments conducted in 1997 and 1998 on neutral to alkaline soils in south-western Australia. Additions of fertiliser phosphorus significantly (P 0.05). Increases in grain yields due to zinc fertiliser were small (<10%) and were only significant (P<0.05) in 1 experiment. This suggests the 3 sites chosen had adequate soil zinc for grain production of faba bean. In 1 experiment the increase in grain yield due to addition of phosphorus fertiliser was due to an increase in the number of pods per plant; numbers of seed per pod and mean seed weight were unaffected by additions of phosphorus and zinc fertiliser. Adding phosphorus and zinc fertiliser increased concentrations of both elements in grain, but had no effect on the concentrations of other nutrient elements (N, K, S, Ca, Mg, Na, Cu, Mn, Fe) measured in grain. These findings support results of a previous study in Western Australia indicating that phosphorus is the major nutrient element deficiency for grain production of faba bean in neutral to alkaline soils.
TOWARDS FAULT DIAGNOSIS WITH ATTENTION

Monitoring industrial processes are typical tasks for human maintenance experts. Unfortunately, this kind of expert needs a high amount of domain knowledge and is thus very rare. This leads to circumstances in which a frequent monitoring of high dimensional sensor data is desired but cannot be implemented in the long run. In the past, multiple approaches based on signal similarity or prediction models, have been proposed. Within this contribution we try to transfer knowledge from Recurrent Neural Network (RNN)-based speech translation techniques onto bearing fault diagnosis. Therefore, we use a Long-Short-Term Memory (LSTM)-Autoencoder-based system to extract features from raw time series data and receive information about the systems current health state. We also evaluate the learned representations for different bearing damages and propose an extention to our model based on an Attention-LSTM approach which let the network decide which parts of the sequence are relevant to look at. These methods could lead to new insights of neural networks analysing industrial machine data in general.
A DETECTION OF POOR CONTACT FAULT LOCATION IN THE LOW-VOLTAGE POWER CABLE USING STDR/SSTDR

This poor contact fault location of low-voltage power cable was performed by using reflectometry for research. This paper describes a cable accidents and importance, and Chapter 2, inform the principles and characteristics of a typical reflectometry, Chapter 3, we describe the applied removal reference signal technique for the detection performance of sequence and reflected signal used in the reflectometry. And Chapter 4 describes the experimental conditions and the environment, the cable fault detection test was performed. Compare the result was confirmed by the measurement using the cable fault detection.
Dual-Mandate Patrols: Bandit-Based Learning in Green Security Domains

Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i.e., patrollers), who must patrol vast areas to protect from attackers (e.g., poachers or illegal loggers). Past work in these domains mostly focuses on exploiting historical data to build predictive models of attacker behavior and plan patrols based on these models. However, this approach ignores the potential to use patrols to improve the predictive model and maximize future reward. The few exceptions that follow a no-regret learning paradigm neglect characteristics of the reward function such as decompos-ability and smoothness in patrolling effort and target feature space. We (i) formulate the problem as a multi-armed bandit with Lipschitz continuity to exploit smoothness, where each arm represents a patrol strategy; (ii) present a no-regret approach for arm selection that uses an integer program to exploit decomposability; and (iii) demonstrate that our algorithm, LIZARD, improves performance on real-world poaching data from Cambodia.
Bismuth Trioxide Modified Carbon Nanotubes as Negative Electrode Catalysts for all Vanadium Redox Flow Batteries

Bismuth trioxide modified carbon nanotubes (Bi2O3/CNTs) composite was fabricated by liquid phase deposition-calcinating method and used as electrocatalyst for V/V redox couple of all vanadium redox flow batteries (VRFBs). The modification of Bi species at the surface of CNTs can significantly inhibit the hydrogen evolution reaction and enhance the electrochemical activity to the V/V redox reaction. The VRFB single cell with Bi2O3/CNTs modified graphite felt as negative electrode exhibits excellent energy storage performances, such as higher charge/discharge capacity and energy efficiency, indicating that the V/V redox reaction can be facilitated significantly by Bi2O3/MWCNTs composite.
Prototype Development of a Smart Voice-Controlled Audio System B9ased on the Raspberry Pi Platform

We report a prototype audio system that can be controlled by means of voice commands. The operations of this audio player – such as song playback and volume control – can be effectively controlled by verbal commands alone without requiring any button-press or dial-turn, enabling a user to operate it with full hands. This feature could be particularly useful in situations when the user’s view and attention are pre-occupied, as in the case of driving or cycling. A voice-command device also has the advantage of a smaller form factor and simpler product casing, due to fewer dials and buttons. While there are a wide variety of commercial audio systems, only very limited few allow voice-control operations. This voice-controlled audio system is low-cost, open-source, and capable of “smart” features that include notifying weather forecasts, automatic volume control, and automatic shutdown. Its platform is the single-board computer Raspberry Pi, which runs speech-to-text processes that record and transcribe a given voice command, such as “Play music” and “Volume up. ” The Raspberry Pi also connects to cloud-based services – and upon voice requests – can check and tell real-time information such as date, time, and weather. The system’s average response time to a given voice command was measured to be about 5 seconds. A simple circuit of LED indicators was also designed to prompt users to give voice commands at the right window of time, therefore improving system responsiveness and overall user experience. This prototype can be extended to voice-control other appliances in an integrated smart home environment.
An Accelerated Accuracy-enhanced Randomized Singular Value Decomposition for Factorizing Matrices with Low-rank Structure

Big data has in recent years gained ground in many scientific and engineering problems. It seems to some extent prohibitive for traditional matrix decomposition methods (i.e. QR, SVD, EVD, etc.) to handle such large-scale problems involving data matrix. Many researchers have developed several algorithms to decompose such big data matrices. An accuracy-enhanced randomized singular value decomposition method (referred to as AE-RSVDM) with orthonormalization recently becomes the state-of-the-art to factorize large data matrices with satisfactory speed and accuracy. In our paper, low-rank matrix approximations based on randomization are studied, with emphasis on accelerating the computational efficiency on large data matrices. By this, we accelerate the AE-RSVDM with modified normalized power iteration to result in an accelerated version. The accelerated version is grounded on a two-stage scheme. The first stage seeks to find the range of a sketch matrix which involves a Gaussian random matrix. A low-dimensional space is then created from the high-dimensional data matrix via power iteration. Numerical experiments on matrices of different sizes demonstrate that our accelerated variant achieves speedups while attaining the same reconstruction error as the AE-RSVDM with orthonormalization. And with data from Google art project, we have made known the computational speed-up of the accelerated variant over the AE-RSVDM algorithm for decomposing large data matrices with low-rank form.
Advanced steady-state modelling and optimisation of LNG production

The main goal of the work was the development of a mathematical model of a typical liquefied natural gas (LNG) cycle, and to demonstrate the use of the model for steady-state optimisation. The liquefaction of the natural gas (NG) is a common procedure that allows a volume reduction by a factor of 600, resulting in several advantages in terms of transportation and storage. A typical LNG liquefaction process consists in series of refrigeration cycles, using both pure and mixed refrigerants. Two advanced modelling approaches (simple and complex) were taken for the following LNG processes: (i) C3/MR, (ii) AP-XTM and (iii) AP-XTM alternative, using both Européen de Recherches Gaziéres (GERG) and Peng-Robinson (PR) property methods. Both property packages affect the results in a negligible difference of less than 0.1%. The optimisation improved the total cost of the AP-XTM process in 58%, ending up with a value of around 83 M$/year and a specific power consumption (SPC) of 15.8 [kW-day/tonne LNG], fitting up the standard industrial values.
The diet of urban Magpies Pica Pica

This paper describes the diet of Magpies in the Manchester urban environment, based on analysis of stomach contents, pellets and faecal material. The diet comprised a selection of typical grassland fauna, the majority of which were surface-dwelling invertebrates. Weevils, click beetles, ground beetles, flies, caterpillars and spiders were common. However, soil-dwelling animals such as leatherjackets and worms were estimated to form a significant proportion of the weight of food. Vertebrate remains, such as those of the field vole Microtus agrestis and the House Sparrow Passer domesticus, were present at a low frequency. The most common constituents of the nestling diet were invertebrate groups that attained their peak seasonal abundance during the nestling period, which suggests that food resources may be utilized in proportion to their availability. During the winter when invertebrate material is scarce, the diet is largely composed of plant material; Magpies may experience a food shortage at this time of year. The summer diet of the adult is similar to that of nestling Magpies; neither include many eggs or nestlings.
Spatial patterns of kangaroo density across the South Australian pastoral zone over 26 years: aggregation during drought and suggestions of long distance movement

1. Wildlife surveys usually focus on estimating population size, and management actions such as commercial harvesting, culling and poison baiting are referenced commonly to population size alone, without taking into account the way in which those animals are distributed. This paper outlines how point-based aerial survey data can be converted to continuous density surfaces using spatial analysis techniques. Using this approach, we describe and explore the spatial patterns of density of two species of kangaroos in an area exceeding 200 000 km2 in South Australia over a 26-year period. 2. Densities of red and western grey kangaroos were estimated in 2 km_2 segments along aerial survey transect lines, yielding point density estimates. Universal kriging provided an unbiased interpolation of these data using the spatial autocorrelation structure described by the semi-variogram. The Getis statistic identified clusters of high and low kangaroo density. 3. Considerable year-to-year variation in the spatial patterns of kangaroo density was observed. In many cases, annual rates of increase over large areas were too high to be explained by vital rates alone, implying immigration from surrounding areas. These large shifts in distribution were occasionally to areas that had received better rainfall than the surrounding areas. For both species, there was no obvious local spatial autocorrelation pattern or clustering of kangaroo density beyond that described by average density and the present set of management regions, suggesting the latter are appropriate divisions for harvest management. 4. Data for both species fitted the power law relationship extremely well. During dry times, red kangaroos, but not western grey kangaroos, were more aggregated, supporting past ground observations at a fine spatial scale. 5. Synthesis and applications. Kriged density surfaces enable estimation of kangaroo density on individual properties, which are the management units at which harvest quotas or culling approvals are allocated. These estimates will be marked improvements over systematic sampling estimates when sampling intensity is low. Predictions of shifts in kangaroo distribution using rainfall or satellite imagery will allow more accurate allocation of harvest quotas. Similarly, predictions of more even kangaroo dispersion following high rainfall will allow managers to anticipate downturns in harvest rate.
Salmon lice infection of wild sea trout and Arctic char in marine and freshwaters: the effects of salmon farms

The abundance of salmon lice and the physiological effects of infection were examined in two stocks of sympatric sea trout and anadromous Arctic char in northern Norway. One stock feed in a coastal area with extensive salmon farming (exposed locality), while the other feed in a region with little farming activity (unexposed locality). The results showed that the lice infection was significantly higher at the exposed locality, at which the mean intensity of infection peaked in June and July at over 100 and 200 lice larvae per fish respectively. At the exposed locality we also observed a premature return to freshwater of the most heavily infected fish. Such behaviour has previously been interpreted as a response by the fish to reduce the stress caused by the infection and/or to enhance survival. Blood samples taken from sea trout at sea at the exposed locality showed a positive correlation between intensity of parasite infection and an increase in the plasma cortisol, chloride and blood glucose concentrations, while the correlations from sea trout in freshwater were more casual. Several indices pointed towards an excessive mortality of the heaviest infected fish, and 47% of the fish caught in freshwater and 32% of those captured at sea carried lice at intensities above the level that has been shown to induce mortality in laboratory experiments. Furthermore, almost half of all fish from the exposed locality had lice intensities that would probably cause osmoregulatory imbalance. High salmon lice infections may therefore have profound negative effects upon wild populations of sea trout. At the unexposed location, the infection intensities were low, and few fish carried more than 10 lice. These are probably within the normal range of natural infection and such intensities are not expected to affect the stock negatively.
Driver Modeling Based on Vehicular Sensing Data

In the past few years, the automotive electronics and sensing technologies have developed rapidly. Today, the status of most of the sub-systems in a running vehicle can be accurately monitored. This process produces a huge amount of data. Extracting the potential value of such data, to for instance support developing advanced vehicle diagnosis and active safety applications, has attracted tremendous attentions in both academia and industry. Considering that the sensing data, if sampled with sufficiently high frequency, can accurately represent how a driver maneuvers a vehicle, this paper investigates using the vehicular sensing data to exploit drivers’ behaviors in different traffic scenarios. We apply machine learning techniques to construct driving behavior models, and discuss their applications in driver identification. Keywords-driving behavior models; vehicular sensing data; machine learning; driver identification
Modelling Procedure for the Selection of Steel Pipes Supplier by Applying Fuzzy AHP Method

The aim of this research is the evaluation and selection of suppliers by applying the fuzzy multi-criteria analysis. The study used fuzzy Analytic Hierarchy Process (FAHP) to choose the optimal supplier for the purchase of materials necessary for the production of pre-insulated pipes. Decision-makers selected among five suppliers based on nine criteria: material cost, pipe length, delivery time, type of payment, transport distance, quality, reliability, flexibility and relationship with customers. Effective execution of procurement, in this case, the procurement of material needed for the production logistics subsystem, influences the overall efficiency of the business. It is vital to make the right decision when selecting a supplier, because the optimal choice ensures lower cost and higher quality of the product itself, and therefore more competitiveness in the market.
Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Smart grid (SG) networks are newly upgraded networks of connected objects that greatly improve reliability, efficiency, and sustainability of the traditional energy infrastructure. In this respect, the smart metering infrastructure (SMI) plays an important role in controlling, monitoring, and managing multiple domains in the SG. Despite the salient features of SMI, security, and privacy issues have been under debate because of the large number of heterogeneous devices that are anticipated to be coordinated through public communication networks. This survey paper shows a brief overview of real cyber attack incidents in traditional energy networks and those targeting the smart metering network. Specifically, we present a threat taxonomy considering: 1) threats in system-level security; 2) threats and/or theft of services; and 3) threats to privacy. Based on the presented threats, we derive a set of security and privacy requirements for SG metering networks. Furthermore, we discuss various schemes that have been proposed to address these threats, considering the pros and cons of each. Finally, we investigate the open research issues to shed new light on future research directions in SG metering networks.
Reflective agile interative design

In Sacks’ account of new technology adoption, new technologies do not transform the world, but rather they are “made at home in the world that has whatever organization it already has”. In this process of being made at home, use emerges and design understandings arise. A Reflective Agile Iterative Design (RAID)framework was employed to iteratively design a mobile social group communication technology which harnessed existing mundane technology such as instant messaging and SMS, and study its emergent use. The technology was “made at home” in peoples’ lives over time and led to small shifts in their communication and coordination patterns. RAID-style approaches are often glimpsed behind Web 2.0 sites and academia, although the style itself has received little direct attention in the academic literature. The approach is summed up as ‘learning about technology through living with it’ and is well suited to understanding and designing mundane technology with its fusion of the action research and agile development philosophies. The characteristics and challenges of designing using this approach are described.