Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple-Mode Orthogonal Frequency Division Multiplexing With Index Modulation

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) performs transmission by considering two modes over OFDM subcarriers, which are the null and the conventional $M$ -ary signal constellation. The spectral efficiency (SE) of the system, however, is limited, since the null mode itself does not carry any information and the number of subcarrier activation patterns increases combinatorially. In this paper, a novel IM scheme, called multiple-mode OFDM-IM (MM-OFDM-IM), is proposed for OFDM systems to improve the SE by conveying information through multiple distinguishable modes and their full permutations. A practical and efficient mode selection strategy, which is constrained on the phase shift keying/quadrature amplitude modulation constellations, is designed. Two efficient detectors that provide different tradeoffs between the error performance and detection complexity are also proposed. The principle of MM-OFDM-IM is further extended to the in-phase and quadrature components of OFDM signals, and the method of generating multiple modes from the $M$ -ary pulse amplitude modulation constellation for this modified scheme is also introduced. Bit error rate (BER) analyses are provided for the proposed schemes. Monte Carlo simulations on BER corroborate the analyses and show that the proposed schemes appear as promising multi-carrier transmission alternatives by outperforming the existing OFDM-IM counterparts.
Incremental Data Converters at Low Oversampling Ratios

In this paper the use of incremental A/D converters with low oversampling ratios is investigated. Incremental A/D converters are able to achieve a higher SQNR than delta-sigma modulators at oversampling ratios below 4, allowing them to operate as higher bandwidth converters with medium resolution. The impact of removing the input S/H, as well as analyzing their behaviour at an OSR as low as 1 is explored. An eighth-order cascaded incremental A/D converter is analyzed and shown as an example.
A Transaction Model for Improving Data Availability in Mobile Computing

We incorporate a prewrite operation before a write operation in a mobile transaction to improve data availability. A prewrite operation does not update the state of a data object but only makes visible the future value that the data object will have after the final commit of the transaction. Once a transaction reads all the values and declares all the prewrites, it can pre-commit at mobile host (MH) (computer connected to unreliable mobile communication network). The remaining transaction’s execution (writes on database) is shifted to the mobile service station (MSS) (computer connected to the reliable fixed network). Writes on database consume time and resources and are therefore shifted to MSS and delayed. This reduces wireless network traffic congestion. Since the responsibility of expensive part of the transaction’s execution is shifted to the MSS, it also reduces the computing expenses at mobile host. A pre-committed transaction’s prewrite values are made visible both at mobile and at fixed database servers before the final commit of the transaction. Thus, it increases data availability during frequent disconnection common in mobile computing. Since a pre-committed transaction does not abort, no undo recovery needs to be performed in our model. A mobile host needs to cache only prewrite values of the data objects which take less memory, transmission time, energy and can be transmitted over low bandwidth. We have analysed various possible schedules of running transactions concurrently both at mobile and fixed database servers. We have discussed the concurrency control algorithm for our transaction model and proved that the concurrent execution of our transaction processing model produces only serializable schedules. Our performance study shows that our model increases throughput and decreases transaction-abort-ratio in comparison to other lock based schemes. We have briefly discussed the recovery issues and implementation of our model.
An exemplar-based NMF approach to audio event detection

We present a novel, exemplar-based method for audio event detection based on non-negative matrix factorisation. Building on recent work in noise robust automatic speech recognition, we model events as a linear combination of dictionary atoms, and mixtures as a linear combination of overlapping events. The weights of activated atoms in an observation serve directly as evidence for the underlying event classes. The atoms in the dictionary span multiple frames and are created by extracting all possible fixed-length exemplars from the training data. To combat data scarcity of small training datasets, we propose to artificially augment the amount of training data by linear time warping in the feature domain at multiple rates. The method is evaluated on the Office Live and Office Synthetic datasets released by the AASP Challenge on Detection and Classification of Acoustic Scenes and Events.
Regularized Complete Cycle Consistent GAN for Anomaly Detection

This study presents an adversarial method for anomaly detection in real-world applications, leveraging the power of generative adversarial neural networks (GANs) through cycle consistency in reconstruction error. Previous methods suﬀer from the high variance between class-wise accuracy which leads to not being applicable for all types of anomalies. The proposed method named RCALAD tries to solve this problem by introducing a novel discriminator to the structure, which results in a more eﬃcient training process. Additionally, RCALAD employs a supplementary distribution in the input space to steer reconstructions toward the normal data distribution, eﬀectively separating anomalous samples from their reconstructions and facilitating more accurate anomaly detection. To further enhance the performance of the model, two novel anomaly scores are introduced. The proposed model has been thoroughly evaluated through extensive experiments on six various datasets, yielding results that demonstrate its superiority over existing state-of-the-art models. The code is readily available to the research community at https://github.com/zahraDehghanian97/RCALAD.
TensorTextures

TensorTextures is a new image-based texture mapping technique. It is a generative model that, from a sparse set of example images, learns the interaction between viewpoint, illumination, and geometry, which determines surface appearance, including complex details such as self-occlusion and self-shadowing. As Fig. 1 illustrates, although the coins appear to have considerable 3D relief under continuously varying viewpoint and illumination, the collection of coins in the box is actually a synthesized TensorTexture mapped onto a planar surface. TensorTextures stems from a recently proposed multilinear (i.e., tensor) algebra approach to the analysis of image ensembles [Vasilescu and Terzopoulos 2002]. Here, we apply the approach to ensembles of images of textured surfaces. Given such an ensemble, our algorithm learns an approximation to the bidirectional texture function (BTF) [Dana et al. 1999], which describes the appearance of the textured surface under various viewpoints and illuminations. A generalization of the well-known BRDF, the BTF is a function of six variables , where are pixel coordinates, is the viewpoint direction, and is the illumination direction. Unlike the method of [Malzbender et al. 2001] our technique estimates the complete BTF, including variations not only in illumination, but also in viewpoint. Unlike the BTF synthesis method of [Tong et al. 2002], our technique is purely image based—it avoids the nontrivial problem of 3D geometric microstructure estimation.
SSCBench: A Large-Scale 3D Semantic Scene Completion Benchmark for Autonomous Driving

Semantic scene completion (SSC) is crucial for holistic 3D scene understanding by jointly estimating semantics and geometry from sparse observations. However, progress in SSC, particularly in autonomous driving scenarios, is hindered by the scarcity of high-quality datasets. To overcome this challenge, we introduce SSCBench, a comprehensive benchmark that integrates scenes from widely-used automotive datasets (e.g., KITTI-360, nuScenes, and Waymo). SSCBench follows an established setup and format in the community, facilitating the easy exploration of the camera-and LiDAR-based SSC across various real-world scenarios. We present quantitative and qualitative evaluations of state-of-the-art algorithms on SSCBench and commit to continuously incorporating novel automotive datasets and SSC algorithms to drive further advancements in this field. Our resources are released on https://github.com/ai4ce/SSCBench .
Quasi-Static FDTD Method for Dosimetry in Human due to Contact Current

The present study proposes a quasi-static finite-difference time-domain (FDTD) method for dosimetry in humans due to contact current at low frequencies (∼10kHz). Our attention focused on wave sources which can reduce computational time. The computational time was found to be reduced using a voltage source of a step function with smooth start. The computational time required for the proposed method was smaller than a quasi-static FDTD method proposed in a previous study. Comparison between our computational results and those in a previous study suggested the effectiveness of our proposal. The difference in in-situ electric field due to different human models was a factor of 2 or so.
Efficient shape mapping through dense touch and vision

—Knowledge of 3-D object shape is of great importance to robot manipulation tasks, but may not be readily available in unstructured environments. While vision is often occluded during robot-object interaction, high-resolution tactile sensors can give a dense local perspective of the object. However, tactile sensors have limited sensing area and the shape representation must faithfully approximate non-contact areas. In addition, a key challenge is efﬁciently incorporating these dense tactile measurements into a 3-D mapping framework. In this work, we propose an incremental shape mapping method using a GelSight tactile sensor and a depth camera. Local shape is recovered from tactile images via a learned model trained in simulation. Through efﬁcient inference on a spatial factor graph informed by a Gaussian process, we build an implicit surface representation of the object. We demonstrate visuo-tactile mapping in both simulated and real-world experiments, to incrementally build 3-D reconstructions of household objects.
Pleistocene sandur rhythms, cycles and megacycles: Interpretation of depositional scenarios and palaeoenvironmental conditions

The Drawa sandur, which is the largest, coarse‐grained sandur in Poland, dates from the Pomeranian phase of the Weichselian glaciation (c. 16 ka BP). Using Markov chain analysis we infer that five cycles and five rhythms occur in its proximal part. The cycles dominated by Gt and St lithofacies in the lower part of the sandur succession and by a GDm lithofacies in the upper part, are fining‐upward cycles deposited in braided channels during large ablation floods. Three groups of cycles are distinguished based on their genesis: (i) cycles due to channel‐sheet evolution during large floods; (ii) cycles due to braid‐bar development during initial and advanced diminishing of floods; and (iii) cycles developed in the thalweg or interbar channels. The succession as a whole forms a large‐scale coarsening‐up megacycle (‘sandur megacycle’) which corresponds to a phase of ice‐sheet advance. Because the cyclicity was evident from Markov chain analysis of the sedimentary succession, we suggest that this statistical tool is valuable for reconstruction of glacifluvial sedimentary conditions, particularly as it can shed new light on the palaeogeographical development of sandar.
Quantifying errors in discontinuous permafrost plateau change from optical data, Northwest Territories, Canada: 1947–2008

The discontinuous permafrost zone has been subject to increased air temperatures over recent decades. Permafrost thaw can cause changes to topography, hydrology, vegetation, and trace gas fluxes, and thus it is important to monitor changes in permafrost area through time. Optical imagery can be used to generate time-series databases of near-surface spectra that may be related to permafrost area. This provides a spatial perspective on area permafrost change that is not easily obtained from field data alone. This study examines the cumulative maximum and minimum errors of aerial and satellite imagery used for change detection within the Scotty Creek watershed, Fort Simpson, NWT, Canada. The results illustrate that, unless unchanging linear features are found throughout every image used (e.g., to be used as multitemporal tie points) and radiometric normalization can be applied (problematic for film images), direct image to image comparisons (e.g., subtraction) are not appropriate. Further, measureable cumulative errors are often produced by misclassification of edges, resolution limitations, and increased landscape fragmentation. At Scotty Creek, increased fragmentation of permafrost plateaus occurred from 1947 to 2008. Cumulative maximum and minimum errors result in an approximate 8%–26% error in permafrost area when compared with the total area of the site. Rates of permafrost area reduction within the study area were approximately 0.5% every year, determined from linear correlation (r2 = 0.91, n = 5). Therefore, based on the maximum cumulative error (a worst-case scenario), approximately 21–32 years (for resolutions of 0.18–1.10 m) is required between images to approximate change within this particular site. Increased (decreased) rates of change at other sites will decrease (increase) the timing required to identify change between images beyond error bounds.
Eternal—a component‐based framework for transparent fault‐tolerant CORBA

Enterprises are increasingly involved in worldwide round‐the‐clock e‐commerce and e‐business, which requires them to be operational 24 hours per day, 7 days per week. With outages leading to loss of revenue, reputation and customers, fault tolerance becomes increasingly important. By mixing the fault tolerance logic into the application logic, existing fault tolerance practices render applications more complex, more prone to errors, and more difficult to maintain and build. The Eternal system is a component‐based middleware framework that provides transparent fault tolerance for enterprise applications, and that ensures continuous $24\times7$ operation without requiring special skills of the application programmers. The Eternal system implements the new Fault‐Tolerant CORBA standard. Copyright © 2002 John Wiley & Sons, Ltd.
How Does Enterprise Architecture Add Value to Organisations?

Enterprise architecture (EA) is the definition and representation of a high-level view of an enterprise's business processes and IT systems, their interrelationships, and the extent to which these processes and systems are shared by different parts of the enterprise. EA aims to define a suitable operating platform to support an organisation's future goals and the roadmap for moving towards this vision. Despite significant practitioner interest in the domain, understanding the value of EA remains a challenge. Although many studies make EA benefit claims, the explanations of why and how EA leads to these benefits are fragmented, incomplete, and not grounded in theory. This article aims to address this knowledge gap by focusing on the question: How does EA lead to organisational benefits? Through a careful review of EA literature, the paper consolidates the fragmented knowledge on EA benefits and presents the EA Benefits Model (EABM). The EABM proposes that EA leads to organisational benefits through its impact on four benefit enablers: Organisational Alignment, Information Availability, Resource Portfolio Optimisation, and Resource Complementarity. The article concludes with a discussion of a number of potential avenues for future research, which could build on the findings of this study.
A Web Tool for the Semantic Integration of Heterogeneous and Complex Spreadsheet Tables

The acquisition and integration of data contained in spreadsheet tables is a complex task because they do not impose any regular structure on the organization of the data, or constraints on valid values. Moreover, mistakes can occur due to the passage from a format to another one or misspelled words in the original sources. The automatic extraction of their content, interpretation and integration is thus a complex task. In this paper, we outline the characteristics of a semi-automatic, interactive tool conceived for creating a knowledge base by extracting semantic information from heterogeneous spreadsheets.
Climate change and on-farm conservation of crop landraces in centres of diversity

Global climate change will have important eff ects on the ways in which humanity feeds itself (Fischer et al., 2005; Lobell et al., 2008). Increasing temperatures, changing rainfall patterns and increases in frequency of extreme events, such as droughts, storms, fl oods and weather extremes, will present important challenges to agricultural and food systems (Ortiz, 2011; Vermeulen et al., 2012). Agricultural biodiversity in general, and plant genetic resources for food and agriculture in particular, will play a fundamental role in the capacity of agricultural and food systems to adapt and respond to climate change (Jarvis et al., 2010; Ortiz, 2011). Th e fundamental role of these resources still remains, however, relatively unacknowledged (Ortiz, 2011). Th is is changing, however, and there is increasing attention to the complex relationships between climate change and the use and conservation of agricultural biodiversity, of which this volume is a good example. Th e conservation of crop genetic diversity has been a worldwide concern for many decades, particularly owing to the worry that much of this diversity would disappear with agricultural and economic development, i.e. gen etic erosion (Hawkes, 1983; Harlan, 1992). Although this has happened for certain crops and certain areas, considerable diversity is still grown in developing countries by smallholder farmers, particularly in centres of crop domestication and diversity (Brush, 2004; Jarvis et al., 2008). Eff orts to conserve crop diversity by the scientifi c community have led to the collection and conservation of seeds in ex situ genebanks (Plucknett et al., 1987). In the past two decades, there has been a growing interest in on-farm conservation of landraces in centres of crop diversity (Bellon et al., 1997; Bretting and Duvick, 1997; Brush, 2004; Gepts, 2006). It refers to the management of landraces in farmers’ fi elds and orchards where they originated, and aims at maintaining the processes of crop evolution (Brush, 1995). Landraces have been defi ned as dynamic populations of a cultivated plant with a historical origin, distinct identity, often genetically diverse and locally adapted, and associated with a set of farmers’ practices of seed selection and fi eld management as well as with a knowledge base (Camacho Villa et al., 2005). To function, on-farm conservation depends then on farmers’ preferences, knowledge, management, practices and social organization. It contrasts with ex situ conservation, where the aim is to maintain the genes and genotypes contained in samples of seeds or planting material representative of the diversity of a particular crop without change over a long time. Th ese two strategies are aimed at conserving diff erent things. On-farm conservation is about maintaining processes, whereas ex situ conservation is about maintaining specifi c results of these processes (specifi c genes and genotypes sampled at a particular point in time). Both 8 Climate Change and On-farm Conservation of Crop Landraces in Centres of Diversity
Stress‐induced borehole elongation: A comparison between the four‐arm dipmeter and the borehole televiewer in the Auburn Geothermal Well

The nature and origin of borehole elongation recorded by the four-arm dipmeter calipers is studied utilizing information obtained from hydraulic fracturing stress measurements and borehole televiewer data taken in a well located in Auburn, New York. A preferred orientation N10°W-S10°E, ±10° and a less prominant E-W orientation of borehole elongation, was observed on two runs of the dipmeter. Comparisons of borehole geometry determined using the televiewer and the dipmeter show that both tools give the same orientation of borehole elongtion provided that the zone of elongation is longer than 30 cm. Comparisons of dipmeter caliper data with orientation of in situ stress and natural fractures, obtained from hydrofracturing tests and televiewer data show that the N10°W-S10°E borehole elongations (1) are axisymmetric, (2) are aligned with the minimum horizontal stress Sh, and (3) are not associated with natural fractures intersecting the well. These elongations are interpreted as stress-induced well bore breakouts. The E-W elongation direction is characterized by an asymmetric borehole cross section in thinly bedded rocks and is not caused by breakouts. This asymmetric geometry can be discriminated from breakouts using the oriented electric measurements provided by the dipmeter. This study demonstrates that the dipmeter can be used to determine the orientation of Sh (by mapping breakouts), confirming the results of earlier less detailed studies, and provides a firm basis for mapping regional stress patterns using existing dipmeter data.
Finding Protein Family Similarities in Real Time through Multiple 3D and 2D Representations, Indexing and Exhaustive Searching

Research suggests that the complex geometric shapes of amino-acid sequence folds often determine their functions. In order to aid domain experts to classify new protein structures, and to be able to identify the functions of such new discoveries, accurate shape-related algorithms for locating similar protein structures are thus needed. To this end, we present our Content-based Analysis of Protein Structure for Retrieval and Indexing system, which locates protein families, and identifies similarities between families, based on the 2D and 3D signatures of protein structures. Our approach is novel in that we utilize five different representations, using a query by prototype approach. These diverse representations provide us with the ability to view a particular protein structure, and the family it belongs to, focusing on (1) the C-α chain, (2) the atomic position, (3) the secondary structure, based on (4) residue type or (5) residue name. Our experimental results indicate that our method is able to accurately locate protein families, when evaluated against the 53.000 entries located within the Protein Data Bank performing an exhaustive search in less than a fraction of a second.