Miracle-dz/UniFAR-FTUs huggingface dataset:
Under Consideration for Publication in Theory and Practice of Logic Programming the Witness Properties and the Semantics of the Prolog Cut

The semantics of the Prolog " cut " construct is explored in the context of some desirable properties of logic programming systems, referred to as the witness properties. The witness properties concern the operational consistency of responses to queries. A generalization of Prolog with negation as failure and cut is described, and shown not to have the witness properties. A restriction of the system is then described, which preserves the choice and first-solution behaviour of cut but allows the system to have the witness properties. The notion of cut in the restricted system is more restricted than the Prolog hard cut, but retains the useful first-solution behaviour of hard cut, not retained by other proposed cuts such as the " soft cut ". It is argued that the restricted system achieves a good compromise between the power and utility of the Prolog cut and the need for internal consistency in logic programming systems. The restricted system is given an abstract semantics, which depends on the witness properties; this semantics suggests that the restricted system has a deeper connection to logic than simply permitting some computations which are logical.
Embedded DRAM (eDRAM) power-energy estimation for system-on-a-chip (SoC) applications

Embedded DRAM (eDRAM) power-energy estimation is presented for system-on-a-chip (SOC) applications. The main feature is the signal swing based analytic (SSBA) model, which improves the accuracy of the conventional SRAM power-energy models. The SSBA model combined with the high-level memory access statistics provides a fast and accurate system level power-energy estimation of eDRAM. The power-energy estimation using SSBA model shows 95% accuracy compared with the transistor level power simulation results for three fabricated eDRAMs.
Evolution of biped locomotion using linear genetic programming

Gait generation for bipedal robots is a very complex problem. The basic cycle of a bipedal gait, called a stride, consists of two main phases, namely the single-support phase and the double-support phase, which take place in sequence. During the single-support phase, one foot is in contact with the ground and the other foot is in swing motion, being transferred from back to front position. In the double-support phase, both feet simultaneously touch the ground, and the weight of the robot is shifted from one foot to the other. During the completion of a stride, the stability of the robot changes dynamically, and there is always a risk of tipping over. Thus it is crucial to actively maintain the stability and walking balance of the robot at all times. In the conventional engineering approach, there are two main methods for bipedal gait synthesis: Off-line trajectory generation, and on-line motion planning (Wahde and Pettersson, 2002; Katic and Vukobratovic, 2003). Both these methods rely on the calculation of reference trajectories, such as e.g. trajectories of joint angles, for the robot to follow. An off-line controller assumes that there exists an adequate dynamic model of the robot and its environment, which can be used to derive a body motion that adheres to a stability criterion, such as e.g. the zero-moment point (ZMP) criterion (Li et al., 1992; Huang et al., 2001; Huang and Nakamura, 2005; Hirai et al., 1998; Yamaguchi et al., 1999; Takanishi et al., 1985) that requires the ZMP to stay within an allowable region, namely the convex hull of the support region defined by the feet. An on-line motion controller, on the other hand, uses limited knowledge of the kinematics and dynamics of the robot and its environment (Furusho and Sano, 1990; Fujimoto et al., 1998; Kajita and Tani, 1996; Park and Cho, 2000; Zheng and Shen, 1990). Instead, simplified models are used to describe the relationship between input and output. This method also relies much on real-time feedback information. Control policies based on classical control theory, like the ones outlined above, have been successfully implemented on bipedal robots in a number of cases, see e.g. the references mentioned in the previous paragraph. When the robot is operating in a well-known, structured environment, the abovementioned control methods normally work well. However, the success of these methods relies on the calculation of reference trajectories for the robot to follow. When the robot is moving in a realistic, dynamically changing environment such reference trajectories can rarely be specified, since the events that might
kEFCM: kNN-Based Dynamic Evolving Fuzzy Clustering Method

Despite the recent emergence of research, creating an evolving fuzzy clustering method that intelligently copes with huge amount of data streams in the present high-speed networks involves a lot of difficulties. Several efforts have been devoted to enhance traditional clustering techniques into on-line evolving fuzzy able to learn and develop continuously. In line with these efforts, we propose kEFCM, kNN-based evolving fuzzy clustering method. kEFCM overcomes the problems of computational cost, dynamic fuzzy evolving, and clustering complexity of traditional kNN. It employs the least-squares method in determining the cluster center and influential area, as well as the Euclidean distance in identifying the membership degree. It enhances the traditional kNN algorithm by involving only cluster centers in making classification decisions and evolving on-line the clusters when a new data arrives. For evaluation purpose, the experimental results on a collection of benchmark datasets are compared against other well-known clustering methods. The evaluation results approve a good competitive level of kEFCM.
Adaptive model order reduction for structures fed by dispersive waveguide modes

This paper presents a self-adaptive reduced-basis method for driven microwave problems which incorporates the frequency-dependent mode patterns and dispersive propagation coefficients of inhomogeneous waveguides. A reduced-order model provides a low-dimensional subspace for approximating the relevant waveguide modes over the considered frequency range. That information is exploited to establish affine parameter-dependence in the three-dimensional driven model, which hereby becomes accessible to projection-based model-order reduction.
A case for wireless 3D NoCs for CMPs

Inductive-coupling is yet another 3D integration technique that can be used to stack more than three known-good-dies in a SiP without wire connections. We present a topology-agnostic 3D CMP architecture using inductive-coupling that offers great flexibility in customizing the number of processor chips, SRAM chips, and DRAM chips in a SiP after chips have been fabricated. In this paper, first, we propose a routing protocol that exchanges the network information between all chips in a given SiP to establish efficient deadlock-free routing paths. Second, we propose its optimization technique that analyzes the application traffic patterns and selects different spanning tree roots so as to minimize the average hop counts and improve the application performance.
Tensor networks and the enumeration of regular subgraphs

We propose a universal approach to a range of enumeration problems in graphs. The key point is in contracting suitably chosen symmetric tensors placed at the vertices of a graph along the edges. In particular, this leads to an algorithm that counts the number of d-regular subgraphs of an arbitrary graph including the number of d-factors (previously we considered the case d=2 with a special emphasis on the enumeration of Hamiltonian cycles; cf. math.CO/0403339). We briefly discuss the problem of the computational complexity of this algorithm.
Expression of CD99 in Multiple Myeloma: A Clinicopathologic and Immunohistochemical Study of 170 Cases

Background Multiple myeloma (MM) is a heterogeneous and ultimately fatal disease. Risk stratification using prognostic biomarkers is crucial to individualize treatments. We sought to investigate the role of CD99, a transmembrane protein highly expressed in many hematopoietic cells including subpopulations of normal and neoplastic plasma cells, for MM risk stratification. Methods CD99 expression was measured in paraffin samples of bone marrow and extramedullary biopsies of 170 patients with MM. Patients were divided into those with high score (moderately and strongly positive) and low score (negative and weakly positive), with all staining being cytoplasmic and/or membranous. Results High anti-CD99 immunostaining was observed in 72 of 136 (52.9%) bone marrow biopsies and 24 of 87 (27.6%) extramedullary biopsies in MM. High CD99 expression of extramedullary specimens was associated with significantly longer overall survival (OS; p=.016). High CD99 expression of extramedullary specimens was also associated with better prognosis in the nonautologous stem cell transplantation group of MM patients (p=.044). In multivariate analysis, International Staging System stage was an independent prognostic factor, whereas CD99 expression was no longer statistically significant. Conclusions Expression of CD99 in extramedullary specimens was correlated with longer OS, suggesting that CD99 may be a helpful immunohistochemical marker for risk stratification.
Learning Robust Low-Rank Representations

In this paper we present a comprehensive framework for learning robust low-rank representations by combining and extending recent ideas for learning fast sparse coding regressors with structured non-convex optimization techniques. This approach connects robust principal component analysis (RPCA) with dictionary learning techniques and allows its approximation via trainable encoders. We propose an efficient feed-forward architecture derived from an optimization algorithm designed to exactly solve robust low dimensional projections. This architecture, in combination with different training objective functions, allows the regressors to be used as online approximants of the exact offline RPCA problem or as RPCA-based neural networks. Simple modifications of these encoders can handle challenging extensions, such as the inclusion of geometric data transformations. We present several examples with real data from image, audio, and video processing. When used to approximate RPCA, our basic implementation shows several orders of magnitude speedup compared to the exact solvers with almost no performance degradation. We show the strength of the inclusion of learning to the RPCA approach on a music source separation application, where the encoders outperform the exact RPCA algorithms, which are already reported to produce state-of-the-art results on a benchmark database. Our preliminary implementation on an iPad shows faster-than-real-time performance with minimal latency.
The Impact of Off-task and Gaming Behaviors on Learning: Immediate or Aggregate?

Both gaming the system (taking advantage of the system's feedback and help to succeed in the tutor without learning the material) and being off-task (engaging in behavior that does not involve the system or the learning task) have been previously shown to be associated with poorer learning. In this paper we investigate two hypotheses about the mechanisms that lead to this reduced learning: (a) less learning within individual steps (immediate harmful impact) and (b) overall learning loss due to fewer opportunities to practice (aggregate harmful impact). We show that gaming tends to have immediate harmful impact while off-task tends to have aggregated harmful impact on learning.
Fine mapping of a major quantitative trait locus mediating multiple opioid addiction behaviors

Opioid addiction is a growing epidemic with no known genetic basis. Mice represent a valuable tool that can be used to better understand the genetic components of opioid addiction by studying opioid induced behaviors such as locomotor activity. The two closely related C57BL/6 substrains, C57BL/6J (B6J) and C57BL/6NJ (B6NJ), exhibit limited genetic diversity, yet display phenotypic differences when under the influence of oxycodone. Quantitative trait locus (QTL) mapping, a discovery based approach to identifying genomic regions underlying statistical variation in complex traits, was used to identify a locus on distal chromosome 1 for oxycodone-induced locomotor activity and withdrawal. F2 offspring from a cross utilizing these substrains that are homozygous B6J across the chromosome 1 QTL compared to offspring that are heterozygous display the same phenotypic differences as the parental strains, namely oxycodone-induced locomotor activity. F2 mice were selected based on distal chromosome 1 genotypes and backcrossed to parental strain C57BL/6J to fine map the QTL interval. Through family analysis, regions proximal to 167 Mb and distal to 187 Mb have been ruled out as containing the QTL mediating oxycodone-induced locomotor activity. Future studies should employ this same technique to fine map the QTL
Perceptual Steganography Based on Adaptive Quantization-Embedder

A steganographic scheme based on adaptive quantization-embedder is proposed in this paper. The scheme uses the new constructed contrast-correlation distortion metric to optimally choose quantization steps for image blocks to guarantee more data being embedded in busy areas. Different form existing methods, our scheme embeds the AQE parameters together with message bits into the cover image. Simulation experiments show the proposed scheme can provide a good trade-off between the perceptibility and the capacity.
Gold-Plated Micromachined Millimeter-Wave Resonators Based on Rectangular Coaxial Transmission Lines

Resonators based on microfabricated rectangular coaxial (recta-coax) transmission lines are presented. The resonators were fabricated using a multilayered nickel electroplating process that enables the fabrication of three-dimensional structures. As a method to improve performance, gold was plated on the resonators using an electroless process. A model for predicting the effect of the plating on a resonator quality (Q) factor is presented and verified by measurements. Measured resonators show that the plating can increase the Q factor of nickel resonators by over 50% at frequencies above 44 GHz. Utilizing gold plating, 50-Omega resonators are demonstrated at 44 and 60 GHz with unloaded Q factors of 213.1 and 242.3, respectively
Target Acquisition vs. Expressive Motion

The purpose of pitch correction is to assist a musician in playing notes with accuracy and precision, without preventing expressive pitch variations. This study presents and examines a new method for automatic pitch correction: Dynamic Pitch Warping (DPW). The analytic formulation of the warping function is derived. In the context of live playing of continuous pitch trajectories, the dynamics of pitch correction must be considered. Methods for triggering and releasing the correction are discussed, and a performance test is conducted. DPW is evaluated in the context of digital musical instruments that are controlled by a stylus on a graphic tablet. The results show significant improvement in note accuracy and precision with the addition of the correction method. Analyses of various types of modulations (including vibrato, portamento, and glissando) demonstrate that expressive pitch variations are preserved by the DPW correction. Perceptual tests show that the effects of DPW correction are well perceived and positively assessed by listeners. The proposed method allows for accurate pitch target acquisition together with preservation of expressive motion, a result that could be extended to other situations that require dynamic trajectory correction.
Efficiently Scaling Out-of-Order Cores for Simultaneous Multithreading

Simultaneous multithreading (SMT) out-of-order cores waste a significant portion of structural out-of-order core resources on instructions that do not need them. These resources eliminate false ordering dependences. However, because thread interleaving spreads dependent instructions, nearly half of instructions dynamically issue in program order after all false dependences have resolved. These in-sequence instructions interleave with other reordered instructions at a fine granularity within the instruction window. We develop a technique to efficiently scale in-flight instructions through a hybrid out-of-order/in-order microarchitecture, which can dispatch instructions to efficient in-order scheduling mechanisms -- using a FIFO issue queue called the shelf -- on an instruction-by-instruction basis. Instructions dispatched to the shelf do not allocate out-of-order core resources in the reorder buffer, issue queue, physical registers, or load-store queues. We measure opportunity for such hybrid microarchitectures and design and evaluate a practical dispatch mechanism targeted at 4-threaded cores. Adding a shelf to a baseline 4-thread system with 64- entry ROB improves normalized system throughput by 11.5% (up to 19.2% at best) and energy-delay product by 10.9% (up to 17.5% at best).
Towards a Reliable Evaluation of Mixed-Initiative Systems

Mixed-Initiative approaches are being applied in different real world domains and many systems have been developed to address specific problems. Though several successful examples of such tools encourage the use of this solving paradigm, it is worth highlighting that research in mixed-initiative interaction is still at an early stage and many important issues ne ed to be addressed. In particular, while some work has been devoted to the design of working prototypes and to identify relevant features of the mixed-initiative interaction, littl e attention has been given to the problem of evaluating the approach as a whole and the diverse aspects involved. This work aims at highlighting the need for effective evaluation studies f or this class of tools and provides a methodological contribution in this direction. In particular it uses an experimental met hodology well known in psychology and human-computer interaction for the problem of understanding users’ attitude wit h respect to mixed-initiative problem solving and investigates the importance of explanation services as a means to foster users’ involvement in the problem solving.
Protection Strategies for Direct Access to Virtualized I/O Devices

Commodity virtual machine monitors forbid direct access to I/O devices by untrusted guest operating systems in order to provide protection and sharing. However, both I/O memory management units (IOMMUs) and recently proposed software-based methods can be used to reduce the overhead of I/O virtualization by providing untrusted guest operating systems with safe, direct access to I/O devices. This paper explores the performance and safety tradeoffs of strategies for using these mechanisms. The protection strategies presented in this paper provide equivalent inter-guest protection among operating system instances. However, they provide varying levels of intra-guest protection from driver software and incur varying levels of overhead. A simple direct-map strategy incurs the least overhead, providing native-level performance but offering no enhanced protection from misbehaving device drivers within the guest operating system. Additional protection against guest drivers can be achieved by limiting IOMMU page-table mappings to memory buffers that are actually used in I/O transfers. Furthermore, the cost incurred by this limitation can be minimized by aggressively reusing these mappings. Surprisingly, a software-only strategy that does not use an IOMMU at all performs competitively, and sometimes better than, hardware-based strategies while maintaining strict inter-guest isolation.
Assessment of long-term WRF-CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States

Abstract. Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO2 and NOx over the past 16 years (1995–2010) across the United States (US), their impacts on anthropogenic aerosol loading over North America, and subsequent impacts on regional radiation budgets. In particular, this study attempts to determine the consequences of the changes in tropospheric aerosol burden arising from substantial reductions in emissions of SO2 and NOx associated with control measures under the Clean Air Act (CAA) especially on trends in solar radiation. Extensive analyses conducted by Gan et al. (2014a) utilizing observations (e.g., SURFRAD, CASTNET, IMPROVE, and ARM) over the past 16 years (1995–2010) indicate a shortwave (SW) radiation (both all-sky and clear-sky) "brightening" in the US. The relationship of the radiation brightening trend with decreases in the aerosol burden is less apparent in the western US. One of the main reasons for this is that the emission controls under the CAA were aimed primarily at reducing pollutants in areas violating national air quality standards, most of which were located in the eastern US, while the relatively less populated areas in the western US were less polluted at the beginning of this study period. Comparisons of model results with observations of aerosol optical depth (AOD), aerosol concentration, and radiation demonstrate that the coupled WRF–CMAQ model is capable of replicating the trends well even though it tends to underestimate the AOD. In particular, the sulfate concentration predictions were well matched with the observations. The discrepancies found in the clear-sky diffuse SW radiation are likely due to several factors such as the potential increase of ice particles associated with increasing air traffic, the definition of "clear-sky" in the radiation retrieval methodology, and aerosol semi-direct and/or indirect effects which cannot be readily isolated from the observed data.
Social media celebrity and the institutionalization of YouTube

This study explores the industrial underpinning and the cultural logic of social media celebrity. Social media visibility may be considered as an alternative way to fame as it bypasses the gatekeeper role played by the entertainment and mass media industries. However, the institutionalization of social media platforms like YouTube and the professionalization of amateur content creation may lead to social media becoming a new locale for industrialized celebrity manufacturing. Taking YouTube beauty vloggers as an example, this study shows that being a celebrity on social media is economically embedded in an industrial structure constituted by the platform’s business model, technical affordances, the advertising market, and commercial cultural intermediaries. Social media celebrity’s status is achieved not only through a set of affiliative, representational, and celebrification techniques, but also by engaging in meticulous entrepreneurial calculation considering the abovementioned industrial factors. This emerging industrial structure is associated with a new cultural logic of celebrity that distinguishes the fame native to social media from that on the silver screen and television. This study shows that social media celebrity is characterized by staged authenticity, managed connectedness with audience, the abundance of celebrity figures, and the cultural preoccupation with self-sufficient uniqueness.
Automatic Speaker Recognition: Current Approaches and Future Trends •1

In this paper we provide a brief overview of the area of speaker recognition, defining terminology, discussing applications, describing underlying techniques and providing some indications of performance. Following this overview we compare speaker verification to other biometrics and discuss some of the strengths and weaknesses of speaker verification technology. Finally we outline some potential future trends in research and development.