Miracle-dz/UniFAR-FTUs huggingface dataset:
DDA: Cross-Session Throughput Prediction with Applications to Video Bitrate Selection

User experience of video streaming could be greatly improved by selecting a high-yet-sustainable initial video bitrate, and it is therefore critical to accurately predict throughput before a video session starts. Inspired by previous studies that show similarity among throughput of similar sessions (e.g., those sharing same bottleneck link), we argue for a cross-session prediction approach, where throughput measured on other sessions is used to predict the throughput of a new session. In this paper, we study the challenges of cross-session throughput prediction, develop an accurate throughput predictor called DDA, and evaluate the performance of the predictor with real-world datasets. We show that DDA can predict throughput more accurately than simple predictors and conventional machine learning algorithms; e.g., DDA's 80%ile prediction error of DDA is > 50% lower than other algorithms. We also show that this improved accuracy enables video players to select a higher sustainable initial bitrate; e.g., compared to initial bitrate without prediction, DDA leads to 4x higher average bitrate.
A Safety Certification Strategy for IEC-61508 Compliant Industrial Mixed-Criticality Systems Based on Multicore Partitioning

The development of mixed-criticality systems that integrate applications of different criticality levels (safety, security, real-time and non real-time) can provide multiple benefits such as product cost-size-weight reduction, reliability increase and scalability. However, the integration of applications with different criticality levels leads to several challenges with respect to safety certification standards. This paper defines a safety certification strategy for IEC-61508 compliant industrial mixed-criticality systems based on multicore partitioning. This approach is illustrated with a safety concept of a simplified IEC-61508 compliant wind-turbine mixed-criticality system, reviewed and approved by a certification authority.
Steady-State and Transient Operation of IPMSMs Under Maximum-Torque-per-Ampere Control

This paper analyzes different aspects of the maximum-torque-per-ampere (MTPA) vector control of interior permanent-magnet synchronous motors at steady state and transient. Two different implementations are considered: a nonlinear-model-based MTPA profile including saturation and cross-saturation effects and a technique based on the maximization of the motor input power versus stator current. Furthermore, this paper analyzes the torque evolution during a transient under an MTPA control strategy on motors with different characteristics. Useful modifications of the current loop are suggested to improve the drive performance. The effects of the torque transient on the sensorless rotor position estimation are also taken into consideration, in case a sensorless MTPA implementation is required. Experimental results confirm the theoretical analysis, showing the benefits of the new control schemes.
Gradient estimates for a nonlinear parabolic equation under Ricci flow

Let $(M,g(t))$, $0\le t\le T$, be a n-dimensional complete noncompact manifold, $n\ge 2$, with bounded curvatures and metric $g(t)$ evolving by the Ricci flow $\frac{\partial g_{ij}}{\partial t}=-2R_{ij}$. We will extend the result of L. Ma and Y. Yang and prove a local gradient estimate for positive solutions of the nonlinear parabolic equation $\frac{\1 u}{\1 t}=\Delta u-au\log u-qu$ where $a\in\R$ is a constant and $q$ is a smooth function on $M\times [0,T]$.
IDENTIFYING REDUNDANT TEST CASESFOR TESTING PARALLEL LANGUAGE CONSTRUCTS

Based on the successes of others in utilizing parallelism to enhance the performance of communication protocol implementations, we have been investigating various approaches to exploiting parallelism to improve the performance of implementations of the MIL-STD 188-220A protocol standard. Simultaneously, we have been investigating ways of providing automatic testing of the parallel aspects of the parallelized protocol implementations. This paper describes some of our research eeorts towards building a software tool for automatic , program-based testing of the resulting multithreaded software.
Research on Multi-objective Parameter Optimization Based on the Experimental Design and ANN-GA in the Digital Environment

Aiming at the multi-objective parameter optimization problem of black box system in the digital design/simulation environment, a multi-objective parameter optimization model based on the orthogonal design/uniform design and Artificial Neural Network- Genetic Algorithms ANN-GA is established. In this method, the principle of experimental design is used to arrange a test or virtual test project. The data modifying and data collecting in the virtual test are accomplished applying the characteristic of parameterization in the environment of digital simulation. At last, the neural network and Pareto genetic algorithm are adopted to optimize multi-objective parameters. A Pareto-optimal set of digital model can be found in specified region.
Alterations of pulmonary function in patients with inflammatory bowel diseases

Aim: The aim of this study was to investigate the alterations of pulmonary function tests (PFTs) and their relationship with disease activity in inflammatory bowel diseases (IBDs). Methods: Sixty-four IBD patients (31 Crohn's disease [CD] and 33 ulcerative colitis [UC]) and thirty healthy individuals (controls) were studied with regard to the following parameters of PFTs: Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio, mid-forced expiratory flow of 25–75% (FEF 25–75), residual volume, total lung capacity, and diffusing capacity of the lung for carbon monoxide (DLCO). The disease activity was calculated using the Crohn's Disease Activity Index for CD and Mayo Clinic Score for UC. Correlation analysis was performed between disease activity and sputum cytology and PFTs. Results: Nineteen of the 31 CD patients (61.29%) and 17 of the 33 UC patients (51.52%) but none of the controls showed at least one abnormal PFTs (P < 0.05). Compared with controls, both CD and UC patients exhibited a significant reduction in FEV1 (P < 0.05), FVC (P < 0.05), FEF 25–75 (P < 0.05), and DLCO (P < 0.05). The majority with decreased measurements of PFTs were in the active phase of diseases (P < 0.05). IBD activity scores correlated negatively with some parameters of PFTs and positively with lymphocytosis and eosinophilia of sputum (P < 0.05). Conclusions: Pulmonary function disorders are significantly common in IBD patients. The impairment in active disease is significantly greater than in remission.
Apparent display resolution enhancement for moving images

Limited spatial resolution of current displays makes the depiction of very fine spatial details difficult. This work proposes a novel method applied to moving images that takes into account the human visual system and leads to an improved perception of such details. To this end, we display images rapidly varying over time along a given trajectory on a high refresh rate display. Due to the retinal integration time the information is fused and yields apparent super-resolution pixels on a conventional-resolution display. We discuss how to find optimal temporal pixel variations based on linear eye-movement and image content and extend our solution to arbitrary trajectories. This step involves an efficient method to predict and successfully treat potentially visible flickering. Finally, we evaluate the resolution enhancement in a perceptual study that shows that significant improvements can be achieved both for computer generated images and photographs.
Adaptive Narrowband Level Set Model of Underwater Objects Detection

According to the nonlinear characteristics of original sonar image with big data, adaptive narrowband level set model to detect sonar image is proposed in this paper. In order to estimate the approximate position of the underwater objects after smoothing the original image, initial segmentation is processed with the block mode k-means clustering algorithm. On this basis, zero level set function is adaptively initialized using the approximate position of the underwater objects, which can not only reduce human intervention but also improve the detection speed. To further improve the robustness and detection accuracy, new adaptive narrowband level set model are provided to complete local optimization by minimizing each new energy function. Detection experiments demonstrate that the proposed method improves the detection speed and accuracy, and it has certain adaptability.
Vector Perturbation Based on Symbol Scaling for Limited Feedback MISO Downlinks

We propose a low-complexity vector precoding (VP) scheme for the downlink of multi-user multiple input single output (MU-MISO) systems with limited feedback. Conventional VP requires the use of modulo operation and knowledge of the scaling factor used at the transmitter in order to remove the perturbation quantity at the receiver. The latter may be problematic in certain limited feedback scenarios where only quantized versions of the scaling factor can be made available at the receiver. To circumvent this shortcoming, we propose a modified VP technique where the search of perturbing vectors is limited to the area in the symbol constellation which is constrictive to the information symbols, i.e., the area where the distances from the decision thresholds are increased with respect to a distance threshold. By doing this, the perturbation quantities can only enhance detection and need not be removed at the receiver. Successful detection can therefore be done without the use of the modulo operation and the scaling factor, which makes the proposed VP scheme applicable to limited feedback scenarios. Analytical and simulation results show that the performance of the proposed scheme is free of the error floor typically encountered with conventional VP in the presence of limited feedback.
Publish-time data integration for open data platforms

Platforms for publication and collaborative management of data, such as Data.gov or Google Fusion Tables, are a new trend on the web. They manage very large corpora of datasets, but often lack an integrated schema, ontology, or even just common publication standards. This results in inconsistent names for attributes of the same meaning, which constrains the discovery of relationships between datasets as well as their reusability. Existing data integration techniques focus on reuse-time, i.e., they are applied when a user wants to combine a specific set of datasets or integrate them with an existing database. In contrast, this paper investigates a novel method of data integration at publish-time, where the publisher is provided with suggestions on how to integrate the new dataset with the corpus as a whole, without resorting to a manually created mediated schema or ontology for the platform. We propose data-driven algorithms that propose alternative attribute names for a newly published dataset based on attribute- and instance statistics maintained on the corpus. We evaluate the proposed algorithms using real-world corpora based on the Open Data Platform opendata.socrata. com and relational data extracted from Wikipedia. We report on the system's response time, and on the results of an extensive crowdsourcing-based evaluation of the quality of the generated attribute names alternatives.
Activation of AMPKα2 Is Not Crucial for Mitochondrial Uncoupling-Induced Metabolic Effects but Required to Maintain Skeletal Muscle Integrity

Transgenic (UCP1-TG) mice with ectopic expression of UCP1 in skeletal muscle (SM) show a phenotype of increased energy expenditure, improved glucose tolerance and increase substrate metabolism in SM. To investigate the potential role of skeletal muscle AMPKα2 activation in the metabolic phenotype of UCP1-TG mice we generated double transgenic (DTG) mice, by crossing of UCP1-TG mice with DN-AMPKα2 mice overexpressing a dominant negative α2 subunit of AMPK in SM which resulted in an impaired AMPKα2 activity by 90±9% in SM of DTG mice. Biometric analysis of young male mice showed decreased body weight, lean and fat mass for both UCP1-TG and DTG compared to WT and DN-AMPKα2 mice. Energy intake and weight-specific total energy expenditure were increased, both in UCP1-TG and DTG mice. Moreover, glucose tolerance, insulin sensitivity and fatty acid oxidation were not altered in DTG compared to UCP1-TG. Also uncoupling induced induction and secretion of fibroblast growth factor 21 (FGF21) from SM was preserved in DTG mice. However, voluntary physical cage activity as well as ad libitum running wheel access during night uncovered a severe activity intolerance of DTG mice. Histological analysis showed a progressive degenerative morphology in SM of DTG mice which was not observed in SM of UCP1-TG mice. Moreover, ATP-depletion related cellular stress response via heat shock protein 70 was highly induced, whereas capillarization regulator VEGF was suppressed in DTG muscle. In addition, AMPKα2-mediated induction of mitophagy regulator ULK1 was suppressed in DTG mice, as well as mitochondrial respiratory capacity and content. In conclusion, we demonstrate that AMPKα2 is dispensable for SM mitochondrial uncoupling induced metabolic effects on whole body energy balance, glucose homeostasis and insulin sensitivity. But strikingly, activation of AMPKα2 seems crucial for maintaining SM function, integrity and the ability to compensate chronic metabolic stress induced by SM mitochondrial uncoupling.
Sources of Business Cycles in a Low Income Country

We examine the role of global and domestic shocks in driving macroeconomic fluctuations for Ghana. We are able to study the impact of exogenous shocks including productivity, credit supply, and commodity price shocks. We identify the shocks with a combination of sign and recursive restrictions within Bayesian VAR models. As a benchmark we provide results for South Africa to document the difference between two economies with similar structures but different levels of development. We find that global shocks play a more dominant role in South Africa than in Ghana. These shocks operate through three channels: trade, credit and commodity prices.
16.6- and 28-GHz Fully Integrated CMOS RF Switches With Improved Body Floating

This paper presents two fully integrated CMOS transmit/receive (T/R) switches with improved body-floating operations. The first design exploits an improved transistor layout with asymmetric drain-source region, which reduces the drain-source feed-through for body-floated RF switches. In the second design, a switched body-floating technique is proposed, which reconfigures the body-floating condition of a switch transistor in the ON and OFF states. Both designs are fabricated in a standard 0.13-mum triple-well CMOS process. With regard to 2-dB insertion loss, the switch with asymmetric drain-source achieves 28-GHz bandwidth, which is among the highest reported frequencies for CMOS T/R switches. The bandwidth of the switched body-floating design is 16.6 GHz. There is approximately 5 dB better isolation obtained in the switched body-floating design. With the resistive double-well body-floating technique, 26.5- and 25.5-dBm input 1-dB compression point (P1dB) are obtained, respectively. Both designs consume only 150 mum times 100 mum die area. The demonstrated T/R switches are suitable for high-frequency and wideband transceivers.
Irradiation-Induced Deinococcus radiodurans Genome Fragmentation Triggers Transposition of a Single Resident Insertion Sequence

Stress-induced transposition is an attractive notion since it is potentially important in creating diversity to facilitate adaptation of the host to severe environmental conditions. One common major stress is radiation-induced DNA damage. Deinococcus radiodurans has an exceptional ability to withstand the lethal effects of DNA–damaging agents (ionizing radiation, UV light, and desiccation). High radiation levels result in genome fragmentation and reassembly in a process which generates significant amounts of single-stranded DNA. This capacity of D. radiodurans to withstand irradiation raises important questions concerning its response to radiation-induced mutagenic lesions. A recent study analyzed the mutational profile in the thyA gene following irradiation. The majority of thyA mutants resulted from transposition of one particular Insertion Sequence (IS), ISDra2, of the many different ISs in the D. radiodurans genome. ISDra2 is a member of a newly recognised class of ISs, the IS200/IS605 family of insertion sequences.
Broadband Source Process of the 1998 Iwate Prefecture, Japan, Earthquake as Revealed from Inversion Analyses of Seismic Waveforms and Envelopes

An earthquake of M 6.1 occurred on 3 September 1998, along an active fault at the southwestern foot of Mt. Iwate, a volcano in northeastern Japan. Acceleration records of this earthquake were obtained at seven stations within 40 km of the epicenter. In order to investigate the source process of this earthquake in a broad frequency range, we simultaneously conducted inversion analyses of low-frequency seismic waveforms and high-frequency seismogram envelopes. First, executing the envelope inversion by using the envelope Green function derived from the radiative-transfer theory in the high-frequency band of 2-16 Hz, we estimated the spatial distribution of seismic-wave energy radiation on the fault plane of 10 km × 10 km. We found that seismic-wave energy was strongly radiated from the southwestern deeper part of the fault plane. By using data from the same stations and using the same fault geometry as the high-frequency analysis, we applied a waveform-inversion method to three-component displacement records in the low-frequency band of 0.1-0.33 Hz. This result showed that seismic moment was mainly released at the shallow part of the fault. Comparing these results, we found that high-frequency energy was strongly radiated from the deepest periphery of the region, where seismic moment was mainly released. This result implies that the radiation of high-frequency energy was associated with the arrest of rupture for this earthquake. Manuscript received 21 April 2001.
Detection of overlapping protein complexes using a protein ranking algorithm

The detection of protein complexes is evidently a cornerstone of understanding various biological processes and identifying key genes causing different diseases. Accordingly, many methods aiming at detecting protein complexes were developed. Recently, a novel method called ProRank was introduced. This method uses a ranking algorithm to detect protein complexes by ordering proteins based on their importance in the interaction network and by accounting for the evolutionary relationships among them. The experimental results showed that ProRank outperformed several well-known methods in terms of the number of detected complexes with high accuracy, precision and recall levels. In this paper, we overcome a drawback of the ProRank algorithm and further improve its performance by allowing detected protein complexes to overlap; a supposition that was not considered in the original version of the method.
Departure Time and Route Choice

Early studies of peak-period traffic congestion generally ignored the departure time decision of road users. Vickrey (1969) and Kocur (1981) remedied this oversight by deriving the departure rate along a single route subject to queuing congestion as the outcome of individual utility maximization. Arnott et al (1985) extend their work, examining alternative toll schemes and deriving rules for optimal capacity. This paper extends these analyses to a simple network of routes in parallel.
Classification Loss Function for Parameter Ensembles in Bayesian Hierarchical Models

Parameter ensembles or sets of point estimates constitute one of the cornerstones of modern statistical practice. This is especially the case in Bayesian hierarchical models, where different decision-theoretic frameworks can be deployed to summarize such parameter ensembles. The estimation of these parameter ensembles may thus substantially vary depending on which inferential goals are prioritised by the modeller. In this note, we consider the problem of classifying the elements of a parameter ensemble above or below a given threshold. Two threshold classification losses (TCLs) --weighted and unweighted-- are formulated. The weighted TCL can be used to emphasize the estimation of false positives over false negatives or the converse. We prove that the weighted and unweighted TCLs are optimized by the ensembles of unit-specific posterior quantiles and posterior medians, respectively. In addition, we relate these classification loss functions on parameter ensembles to the concepts of posterior sensitivity and specificity. Finally, we find some relationships between the unweighted TCL and the absolute value loss, which explain why both functions are minimized by posterior medians.
On the classification of 2-extendable Cayley graphs on dihedral groups

A graph X with at least two independent edges is 2-extendable if any two independent edges of X are contained in a perfect matching of X. In this paper, we prove that a connected Cayley graph of even order on a dihedral group is 2-extendable if and only if it is not isomorphic to anyone of the following circulant graphs: (I) Z2n(1, 2n 1), n ~ 3; (II) Z2n(1,2,2n-l,2n-2), n~3; (III) Z4n(1,4n -1,2n), n ~ 2; (IV) Z4n+2(2,4n, 2n + 1), n ~ 1; and (V) Z4n+2(1,4n+l,2n,2n+2), n ~ 1.
On the limited potential of buffers to improve quality of experience

This paper investigates the potential of improving the Quality of Experience (QoE) of pervasive video delivery by buffering. It reveals the importance of delivering video without freezes to the end user. It then introduces a fluid flow model that leads to a closed formula for the freeze probability, and matches measured distributions of on- and off-times to this model's exponential distributions in order to underline its feasibility. The closed formula for the freeze probability is then used to investigate the impact of two buffer size adaptation policies, one additive and one multiplicative with regards to the deviation of the average off-time from its nominal value. It is proven that, besides of some specific conditions in the additive case, the freeze probability grows with the disturbance, which means that even an increased buffer size implies worse performance and thus QoE. It also points out a way out of this dilemma, which is to try to reduce off times by reducing the utilization of the mobile link.
Reference frame selection algorithm of HEVC encoder for low power video device

Modern video applications on mobile devices use higher resolutions and frame rates in order to offer better visual quality. Therefore, the power consumption reduction of the decoder in the mobile device is more challenging. In this paper, the reference frames selection algorithm of HEVC encoder for power consumption reduction on the decoder side is proposed. In particular, the power consumption of decoder for random access mode is significant compared with other coding mode. Firstly, the evaluation result show that when the number of group of picture and reference frames are varied on some conditions in random access mode. Next, based on the evaluation results, the proposed algorithm adaptively select the optimal number of reference frames in terms of the relationship of the prediction mode, coding unit size. The proposed algorithm is evaluated by the reference software of HEVC. The simulation results show that the proposed algorithm can reduce over 40% of the reference frames comparing to the original HEVC algorithm.