Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Covariance Models for Collaborative Integrity Monitoring

This thesis introduced a method for modeling non-stationary random errors to enable Collaboration-Enhanced Receiver Integrity Monitoring (CERIM). CollaborationEnhanced Receiver Integrity Monitoring is a relative new method of GPS integrity monitoring which has multiple advantages compared to conventional Receiver Autonomous Integrity Monitoring (RAIM). The idea is to use information from multiple collaborative receivers to compute a statistic which can be used to monitor system health. CERIM performance depends strongly on the noise covariance model used for the collaborating receivers, but it is not trivial to estimate the noise covariance for receiver teams, particularly for teams operating in an urban environment. This thesis proposes and evaluates a method for estimating a noise covariance model without any external infrastructure or ground truth system. The method is designed to process data even for data sets where the dimension of the CERIM residual vector changes continually (e.g. due to satellites suddenly appearing or disappearing in an urban canyon).
Nest colonies of Baya Weaver Ploceus philippinus (Linnaeus, 1766) on overhead power transmission cables in the agricultural landscape of Cuddalore and Villupuram districts (Tamil Nadu) and Puducherry, India

Nesting habits of Baya Weaver Ploceus philippinus with specific reference to overhead power transmission cables was studied between April and November 2021 in the agrarian landscape of 10 villages covering Cuddalore and Villupuram districts (Tamil Nadu), and Puducherry. A total of 408 nests of various stages (wad stage-35, ring stage-21, helmet stage-227, egg-chamber closed stage-49, complete nests-22, and abnormal nests-54) and 411 birds were enumerated on 25 nest colonies. The number of nests in each colony ranged from 1 to 82. Baya Weavers had selected power cables as nesting sites despite the availability of three nest-supporting trees (n= 2,255), such as Cocos nucifera, Borassus flabellifer, and Phoenix sylvestris within 500 m of nesting cables. Birds used leaves of sugarcane Saccharum officinarum, Indian Date Palm Phoenix sylvestris, and Narrow-leaf Cattail Typha angustifolia as a source of fibres for the construction of nests. Twenty-three out of 25 nest colonies were found on power cables running over sugarcane crops. Abnormal nests constituted 13.23% (n= 54) of the total nests and 92.91% (n= 223) helmet stage nests had clay deposits on the inner walls. A total of 285 fallen nests in various stages of development were scattered on the ground. There were opportunistic sightings of avian predators, such as House Crow Corvus splendens, Large-billed Crow Corvus macrorhynchos, Rufous Treepie Dendrocitta vagabunda, and Shikra Accipiter badius found perched on power cables bearing nests and caused damages to eight nests.
An Approach for Structuring Heterogeneous Automotive Software Systems by use of Multicore Architectures

The significance of software within modern cars increases continuously. A manufacturer’s competitive advantage relies more and more on compelling functionalities provided to the passengers. This raises the pressure on software architects of electronic automotive components. The successful integration of different software becomes a major challenge. This paper presents an approach to give support on that issue by the use of multicore hardware architectures. By reflecting the internal structure of the software in the underlying hardware, the scheduling of tasks performed in parallel can be determined based on the internal architecture rather than on performance aspects only.
Leadership of schools as research-led organisations in the English educational environment

This article examines the conditions for the growth and expansion of research-engaged schools in England. The current policy climate is seeing a rapid growth of autonomous schools coupled with the continuing tendency to hold schools to account for overall student educational attainment indicators. Within this context, the article begins by considering some of the benefits of developing a research-led school culture and gives a brief account of the research-engaged school movement. Using a biological analogy, the article argues for an understanding of the growth of a school research culture as occurring within an interconnected ecosystem. Four ‘nourishing’ factors are explained in detail: systemic connectedness; leadership for knowledge creation; teaching as a research-informed practice; and the school as a learning organisation. School leaders are urged to consider developing a culture of research engagement as a long-term, sustainable improvement strategy.
Sensitivity Identification of Low-Frequency Cantilever Fibre Bragg Grating Accelerometer using Cascade-Forward Backpropagation Neural Network

The frequency-dependent issues and instrumentation requirement for FBG sensors necessitate the identification of the sensitivity of the cantilever FBG accelerometer using machine learning. As result, this article presents a cascade-forward backpropagation (CFB) neural network with an orthogonally-phase chirp signal with a range of constant forcing frequency and steadily increasing base acceleration amplitude as its input. This input/output data set was numerically calculated by integrating modal model and Euler-Bernoulli beam approach (FBG-MM). The maximum amplitude of the base acceleration was 200 m/s2 and the forcing frequencies and location of the FBG sensor mounted on the beam measured from the fixed end were 1 to 90 Hz and 0.03 m, respectively. The trained CFB predicted the wavelength shift very well, but it was restricted to one-half of the forcing frequencies of those used in the CFB training process, whereas the base acceleration is not an important element in determining the sensitivity of the FBG accelerometer. In terms of the FBG sensor’s location on the beam, considering a few positions will greatly expand the CFB’s capabilities. Future work will include the use of the trained CFB as “black-box sensitivity” for actual acceleration measurement, as well as the use of empirical data to replace the numerical FBG-MM as the input/output training data set.
Ghosting and breadcrumbing: prevalence and association with online dating behavior among young adults Ghosting y breadcrumbing: prevalencia y relaciones con los comportamientos vinculadas a las citas online entre jóvenes adultos

The present study is part of a large study analyzing the prevalence of ghosting and breadcrumbing in sample of Spanish adults aged between 18 and 40 years. The study was split into different papers to better organize and understand the data obtained. The present paper investigated the prevalence of ghosting and breadcrumbing and associations between ghosting and breadcrumbing behavior and online dating practices. The results showed that half the participants were unfamiliar with the terms ghosting and breadcrumbing. However, approximately two in every 10 participants reported having experienced and initiated ghosting, and slightly more than three in every 10 participants had experienced or initiated breadcrumbing in the last 12 months. Regression analyses showed that the use of online dating sites/apps, more short-term relationships, and practicing online surveillance increase the likelihood of experiencing, as well as initiating, ghosting and breadcrumbing.
A Polynomial Inversion-Based Fast Time-Delay Estimation Method for Wideband Large-Scale Antenna Systems

This paper proposes a new fast time-delay estimation (TDE) method based on polynomial inversion which addresses the challenges arising from the requirements for high-precision, low-computational-complexity synchronization error estimation in wideband large-scale antenna systems (LSASs). In this work, we use the convex parabolic extreme point equation as the timing error detector (TED), and develop a polynomial inversion-based function to characterize the one-to-one mapping relationship between true time delay (TTD) and TED estimates using the least square (LS) method, then obtain the time-delay difference with a high accuracy and high computational efficiency. The results of the performance analysis indicate that the Mean Square Error (MSE) of the proposed algorithm is less than 1 dB away from the Cramer–Rao lower bound (CRLB), which is produced in this paper, while adding a few multipliers compared to the convex parabolic interpolation method. Finally, a further example illustrates that the proposed algorithm can achieve a synchronization error of less than 5 ps between channels based on the NI PXI broadband multichannel acquisition platform.
Energy reduction in domestic homes using smart control systems

The aim this work was to investigate the effect smart heating control systems have on the energy performance in domestic homes in the UK. An experimental investigation was conducted of three case study buildings which were selected with different constructions and occupancy patterns to represent a cross section of the typical UK housing stock. Temperature data loggers were deployed in each home from 1 February until 31 April 2014 and these logged the internal temperature of the living room, kitchen and master bedroom at 5 minute intervals. A numerical analysis using IES VE (Integrated Environmental Systems Virtual Environment) dynamic thermal modelling software was undertaken of these three case study buildings with the results from the experimental investigation used to provide validation that the thermal performance of the dynamic thermal models was the same as the case study buildings, within experimental tolerances. The thermal performance for each case study building was compared to the CIBSE (Chartered Institute of Building Service Engineers) recommended guidelines for internal thermal comfort temperatures and consistent underheating in each case study building was identified. One dynamic thermal model was selected and taken forward for modifications to be made to the heating control system, with the single zone thermostatic control system being replaced by a 2 zone thermostatic control system and finally a multi zone thermostatic control system. Three thermostat schedules were investigated for the zoned control systems, the first being a 9-5 working schedule assuming the occupants are out of the house between those hours, an always occupied schedule assuming some level of occupation through the day and a nightshift schedule assuming a shift workers pattern not following a traditional Monday to Friday 9 – 5 working week. The study found that increasing the zoning of the control systems did not yield energy savings in every case but did increase the comfort conditions for the occupants and the degree of control the occupants had in their building. The occupancy pattern was found to affect the performance of the zonal heating strategy.
A Novel Fault Diagnosis Method for TE Process Based on Optimal Extreme Learning Machine

Chemical processes usually exhibit complex, high-dimensional and non-Gaussian characteristics, and the diagnosis of faults in chemical processes is particularly important. To address this problem, this paper proposes a novel fault diagnosis method based on the Bernoulli shift coyote optimization algorithm (BCOA) to optimize the kernel extreme learning machine classifier (KELM). Firstly, the random forest treebagger (RFtb) is used to select the features, and the data set is optimized. Secondly, a new optimization algorithm BCOA is proposed to automatically adjust the network hyperparameters of KELM and improve the classifier performance. Finally, the optimized feature sequence is input into the proposed classifier to obtain the final diagnosis results. The Tennessee Eastman (TE) chemical process have been collected and used to verify the effectiveness of the proposed method. A comprehensive comparison and analysis with widely used algorithms is also performed. The results demonstrate that the proposed method outperforms other methods in terms of classification accuracy. The average diagnosis rate of 21 faults is found to be 89.32%.
Classification and Advantage of Software Fault Prediction

: Software testing is tedious, resource consuming but important process in the software development lifecycle. Ideally, a large portion of software development resources is allotted to the software testing and software quality assurances activities [1]. Modern day software systems are growing complex and larger in size, thus making the task of software testing and quality assurance more difficult. The ultimate goal of the software testing process is to deliver the software system that is free from any bug and meeting the requirements of the stakeholders. However, ensuring that a software system is free from all faults is required an exhaustive and thorough testing, which is an expensive, almost impossible goal to achieve [2]. In real-world software projects, typically, a small amount of budget is left for the testing.
Ginseng Malva Verticillata Tea (GMVT) Improve Glucose and Lipid Metabolism in Overweight Rats

Hyperglycemia plays a main role in the pathogenesis of cardiovascular diseases, fatty liver disease and insulin resistance in Diabetes mellitus type 2 (T2DM). Excess adipose tissue is the main risk factor for developing T2DM. Numerous drugs have been approved to reduce body weight and these medicines act by increasing lipolysis, decreasing satiety level, and increasing thermogenesis. But due to their adverse effects they are withdraw from the market. People are interested in using herbs and herbal drugs to achieve the best effect with fewer side effects. Traditionally in Asia, cinnamon (Cinnamomum verum), bitter gourd (Momordica charantia), dill (Anethum graveolens), black cumin (Nigella sativa). Turmeric, Ginger, green cardamom, Fenugreek and Ginseng use to improve hyperlipidemic and hypoglycemic conditions. In the current study, we treated overweight rats to ginseng tea. Results demonstrated a significant decrease in glucose, LDL-C, and cholesterol while increase in the HDL-C and leptin levels. Leptin is belonging to cytokine release from adipose tissue exhibit decrease satiety, increase energy expenditure and reduce fat by inhibiting lipogenesis and increasing lipolysis. Thus, it was concluded Ginseng Malva Verticillata tea (GMVT) can be suggested as a possible alternative treatment to improve lipid profile, hyperglycemia and related pathogeneses.
Supplementary Material of MOOCad

Summarizing progression stages in event sequences is an important step towards analyzing learning sequences, which helps in understanding variation within different but similarly evolving learning behaviors. MOOcad implements an unsupervised stage analysis algorithm [1] that segments learning sequences into stages with semantic meaning through three critical steps: (1) Estimation of event representation, which converts each event of a sequence into a vector representation by employing a word embedding model [5]. In our application, a learning event/activity is represented by H-code. For example, if the event means a learner watching lecture video in module 1 => section 2 => lecture 3, then we encode the H-code as “V1-2.3”. (2) Alignment of event sequences, in which a Dynamic Time Warping (DTW) algorithm [2] is used to align and group event sequences with variable lengths and event orders. (3) Segmentation of sequence, as shown in Fig. 1(b), where aligned learning sequences are segmented into latent stages using an optimization-based algorithm. In our application, there is a coherence score within each segment. The greedy algorithm is used to maximize the total coherence score of all the segments in each iteration. We set a threshold value th for the optimization such that the algorithm will stop automatically when total score increase that is smaller than the threshold.
Edinburgh Research Explorer Cambrian-Eocene pre-rift, pulsed rift, passive margin and emplacement processes along the northern margin of the Southern Neotethys: evidence from the Antalya Complex in the Alanya Window (S Turkey)

coalescence in volcanological material. With the integration of a rheometer, information on bubble deformation could also be gained. In the near future, upgrades of most large-scale synchrotron radiation facilities to diffraction-limited storage rings will create new opportunities, for instance through sub-second tomographic imaging capabilities at sub-micron length scales. evidence the behavior of phenomena in 3D at unprecedented spatio-temporal resolution. This newly unlocked of and numerical models in diﬀerent Earth Sciences key
Clinical Outcomes of Chronic Kidney Disease Patients with STEMI Treated with Percutaneous Coronary Intervention: A Single Centre Study

Background: Patients with advanced chronic kidney disease sustain extremely high mortality rates following acute myocardial infarction. Nauta et al. evaluated temporal trends in 12,087 patients with acute myocardial infarction from a single institution over 24 years and report a reduction in 30-day mortality in the most recent decade for all patients, including patients with chronic kidney disease. This trend is optimistic, but understanding contributory factors would be critical in future studies to further improve survival. Patients with renal impairment were often left out from most major clinical trials assessing the optimal treatment for ST-elevation myocardial infarction (STEMI). We aim to analyze the outcomes of STEMI patients with renal impairment treated with coronary angioplasty. Methods: STEMI patients treated with percutaneous coronary intervention (PCI) were stratified into presence (GFR < 60 ml/min/1.73m2 ) or absence (GFR ≥ 60 ml/min/1.73m2 ) of chronic kidney disease (CKD). Patient’s demographics, extent of coronary artery disease, procedural data, discharge medications, short (in-hospital) and long (1 year) term outcomes were critically assessed. Results: A total of 840 patients were included in the final analysis. STEMI CKD cohort was predominantly male (91%) with a mean age of 62.05 ± 10.75 years. They had higher cardiovascular risk factors namely diabetes mellitus (64%), hypertension (93%) and dyslipidemia (74%) in contrast to those without CKD. There were notably higher percentage of CKD patients presented with Killip class 3 and 4; 28 vs 8.75%. Thrombolytic therapy remained the most commonly instituted treatment regardless the status of kidney function. Furthermore, our STEMI CKD cohort also was more likely to receive less of evidence-based treatment upon discharge. In terms of outcomes, patients with CKD were more likely to develop in-hospital death (OR: 4.15, 95% CI 3.02–6.79), MACE (OR: 3.44, 95% CI 2.09–4.78) and vascular complications (OR: 1.79, 95% CI 0.89–4.2) compared to the non-CKD patients. The risk of death at 1-year post PCI in STEMI CKD patients was also reported to be high (HR: 3.88, 95% CI 2.81–5.18). Conclusion: STEMI and CKD is a deadly combination, proven in our cohort, adding on to the current evidence in the literature. We noted that our STEMI CKD patients tend to be younger with extremely high prevalence of diabetes mellitus. The poor outcome mainly driven by immediate or short termperiprocedural adverse events, therefore suggests that a more efficient treatment in this special group is imperative.
Seal monitoring and evaluation for the Luchterduinen offshore wind farm: 2. Tconstruction - 2014 report

Two seal species live in Dutch waters: the harbour seal (Phoca vitulina) and the grey seal (Halichoerus grypus). They occupy land-based sites (haul-outs) in both the Wadden Sea and the Delta region, and move between these regions along the North Sea coastal zone. Human activities, such as construction of a wind farm in this zone, may influence movement and use of the zone by the seals. Monitoring of potential impacts on seals to Luchterduinen construction was required in the permit to construct. The Luchterduinen offshore wind farm is the third wind farm development in the Dutch North Sea coastal zone (between Den Helder and Rotterdam). Pile-driving of the turbine towers occurred between 31 July and 16 October, 2014. Seals exposed to pile-driving, even at close distances of
Distraction Detection by Eye Tracking using Raspberry-Pi for Driver Safety

—Passively monitoring driver’s eyes can help in detecting state of mind and alertness of driver and thus can reduce risk of accidents. Proposed system includes three main parts 1) Facial feature tracking 2) Eye gaze 3) Eyes off the road and fatigue detection. Video feed from camera installed on car dashboard tracks features of driver in real time (25FPS). Image processing algorithm is developed in OpenCV and implemented on Raspberry Pi board to make a compact embedded system. Different gaze zones are defined, few of which are eyes off the road points. SVM is used to train and classify different combinations of gaze and head pose angles to determine exact point of gaze. Based on algorithm output, if driver’s eyes are off the road or eyes are closed due to fatigue then accordingly audio and steering vibration warnings are given to driver.
Unsupervised Machine Learning Techniques for Detecting PLC Process Control Anomalies

The security of programmable logic controllers (PLCs) that control industrial systems is becoming increasingly critical due to the ubiquity of the Internet of Things technologies and increasingly nefarious cyber-attack activity. Conventional techniques for safeguarding PLCs are difficult due to their unique architectures. This work proposes a one-class support vector machine, one-class neural network interconnected in a feed-forward manner, and isolation forest approaches for verifying PLC process integrity by monitoring PLC memory addresses. A comprehensive experiment is conducted using an open-source PLC subjected to multiple attack scenarios. A new histogram-based approach is introduced to visualize anomaly detection algorithm performance and prediction confidence. Comparative performance analyses of the proposed algorithms using decision scores and prediction confidence are presented. Results show that isolation forest outperforms one-class neural network, one-class support vector machine, and previous work, in terms of accuracy, precision, recall, and F1-score on seven attack scenarios considered. Statistical hypotheses tests involving analysis of variance and Tukey’s range test were used to validate the presented results.
Differences in Songs and Calls, their Production and Biological Significance

Communication is an integral part of animal behaviour. Birds communicate with each other primarily by means of visual and vocal signals. Elaborate or cryptic plumage, brightly coloured bare skin, wattles, tail, beak and feet are used in communication, with or without accompanying acoustic signals. Sound is an ideal method for communication over long distances. Acoustic signals seem to be produced only when required, and sound can be used to transmit a large amount of information efficiently.
Interference suppression techniques for millimeter-wave integrated receiver front ends

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