Miracle-dz/UniFAR-FTUs huggingface dataset:
A black-box approach to energy-aware scheduling on integrated CPU-GPU systems

Energy efficiency is now a top design goal for all computing systems, from fitness trackers and tablets, where it affects battery life, to cloud computing centers, where it directly impacts operational cost, maintainability, and environmental impact. Today's widespread integrated CPU-GPU processors combine a CPU and a GPU compute device with different powerperformance characteristics. For these integrated processors, hardware vendors implement automatic power management policies that are typically not exposed to the end-user. Furthermore, these policies often vary between different processor generations and SKUs. As a result, it is challenging to design a generally-applicable energy-aware runtime to schedule work onto both the CPU and GPU of such integrated CPU-GPU processors to optimize energy consumption. We propose a new black-box scheduling technique to reduce energy use by effectively partitioning work across the CPU and GPU cores of integrated CPU-GPU processors. Our energy-aware scheduler combines a power model with information about the runtime behavior of a specific workload. This power model is computed once for each processor to characterize its power consumption for different kinds of workloads. On two widely different platforms, a high-end desktop system and a low-power tablet, our energy-aware runtime yields an energy-delay product that is 96% and 93%, respectively, of the near-ideal Oracle energy-delay product on a diverse set of workloads.
Relationships between Trait Empathy and Psychological Well-Being in Japanese University Students

The Interpersonal Reactivity Index (IRI) is a commonly used instrument for measuring individual differences in trait empathy. It is composed of the following four subscales: Perspective taking; fantasy; empathic concern; and personal distress. Previous studies have reported finding a positive relationship between psychological well-being and perspective taking, but little remains known about the association between psychological well-being and the other IRI subscales. Therefore in this study, we investigated the degree to which each IRI subscale could predict psychological well-being, which was measured using Ryff’s Psychological Well-Being Scales, in 119 Japanese undergraduate and graduate students (43 females, 76 males; mean age: 22 years; age range: 19 - 25 years). Regression analysis revealed that perspective taking positively predicted personal growth, purpose in life, and environmental mastery, while personal distress negatively predicted autonomy, environmental mastery, and self-acceptance. Neither fantasy nor empathic concern predicted psychological well-being. These results support those found in previous studies, and suggest that perspective taking, a cognitive component of empathy, plays an important role in the improvement of psychological well-being.
Don’t Mention the Shoe! A Learning to Rank Approach to Content Selection for Image Description Generation

We tackle the sub-task of content selection as part of the broader challenge of automatically generating image descriptions. More specifically, we explore how decisions can be made to select what object instances should be mentioned in an image description, given an image and labelled bounding boxes. We propose casting the content selection problem as a learning to rank problem, where object instances that are most likely to be mentioned by humans when describing an image are ranked higher than those that are less likely to be mentioned. Several features are explored: those derived from bounding box localisations, from concept labels, and from image regions. Object instances are then selected based on the ranked list, where we investigate several methods for choosing a stopping criterion as the ‘cut-off’ point for objects in the ranked list. Our best-performing method achieves state-of-the-art performance on the ImageCLEF2015 sentence generation challenge.
Establishing the NP-hardness of maximally permissive RAS-based approaches to multi-vehicle system safety

The safety problem in multi-vehicle systems seeks to establish collision-free and live vehicle motion, and it is a prominent problem for many configurations of these environments. Past work studying this problem in the context of free-range vehicular systems through abstractions based on Resource Allocation System (RAS) theory, has implicitly assumed that its resolution through maximally permissive supervision is NP-hard, and therefore, it has typically pursued suboptimal (i.e., more restrictive) solutions. The work presented in this paper offers formal proof to this implicit assumption, closing the apparent gap in the existing literature.
Homecare kit platform supporting multiple bio-signals acquisition and analysis in daily-life

In the ageing society, medical service has changed from the “cure-service” for patients to the “care-service” for semi-healthy or healthy people. The care service for healthy people in daily-life requires using a homecare kit to measure and analyze their personal bio-signal in daily activities. The acquisition signal in daily-life can help detect early symptoms of disease and enable their cure. In this paper, we propose a homecare kit based cloud platform for the acquisition, analysis and management of the multiple bio-signals from daily-life activity, and for sending alerts to another user (guardian) or doctor when a dangerous situation occurs. In the proposed platform, the homecare kit consists of wearable devices with embedded biosensors: ACC, PPG/SpO2, Breathing, ECG, and the user can easily wear and use the homecare kit for measuring the bio-signal in daily life or while sleeping. If the user is a patient with a disease such as arrhythmias, during a dangerous situation such as breaking down or a stop in breathing, the alert messaging service can alert the asynchronous push message to the registered guardian or doctor. In the hospital, healthcare professional staff can also analyze the stacked bio-signal from a user's daily life and can prescribe for personal living. For the verification of the implemented homecare kit, a sleep apnea patient actually wore our homecare kit and polysomnography equipment simultaneously in the hospital. We evaluated the equipment equivalence based on the analysis result and acquisition bio-signal.
Meaning and Credibility in Cheap-Talk Games - eScholarship

UNIVERSITY OF CALIFORNIA, BERKELEY Department of Economics Berkeley, California Working Paper 8609 MEANING AND CREDIBILITY IN CHEAP-TALK GAMES Joseph Farrell September 26, 1986 Key words: Communication, signaling, refinement of equilibrium, language, cheap talk, game theory. There have been many previous and more technical versions of this paper; the most recent is listed in the references. For helpful comment s and encouragement, I thank Vincent Crawford, Robert Gibbons, Jerry Green, Eric Maskin, Andrew McLennan, Roger Myerson, Suzanne Scotchier, and especially Joel Sobel. I also thank two helpful referees, one of whom suggested the essay format. JEL Classification:
Detecting atomic-set serializability violations in multithreaded programs through active randomized testing

Concurrency bugs are notoriously difficult to detect because there can be vast combinations of interleavings among concurrent threads, yet only a small fraction can reveal them. Atomic-set serializability characterizes a wide range of concurrency bugs, including data races and atomicity violations. In this paper, we propose a two-phase testing technique that can effectively detect atomic-set serializability violations. In Phase I, our technique infers potential violations that do not appear in a concrete execution and prunes those interleavings that are violation-free. In Phase II, our technique actively controls a thread scheduler to enumerate these potential scenarios identified in Phase I to look for real violations. We have implemented our technique as a prototype system AssetFuzzer and applied it to a number of subject programs for evaluating concurrency defect analysis techniques. The experimental results show that AssetFuzzer can identify more concurrency bugs than two recent testing tools RaceFuzzer and AtomFuzzer.
Parameter calibration for synthesizing realistic-looking variability in offline handwriting

Motivated by the widely accepted principle that the more training data, the better a recognition system performs, we conducted experiments asking human subjects to do evaluate a mixture of real English handwritten text lines and text lines altered from existing handwriting with various distortion degrees. The idea of generating synthetic handwriting is based on a perturbation method by T. Varga and H. Bunke that distorts an entire text line. There are two purposes of our experiments. First, we want to calibrate distortion parameter settings for Varga and Bunke's perturbation model. Second, we intend to compare the effects of parameter settings on different writing styles: block, cursive and mixed. From the preliminary experimental results, we determined appropriate ranges for parameter amplitude, and found that parameter settings should be altered for different handwriting styles. With the proper parameter settings, it should be possible to generate large amount of training and testing data for building better off-line handwriting recognition systems.
ABSOLUTE PROPERTIES OF THE ECLIPSING BINARY STAR V501 HERCULIS

V501 Her is a well detached G3 eclipsing binary star with a period of 8.597687 days for which we have determined very accurate light and radial-velocity curves using robotic telescopes. Results of these data indicate that the component stars have masses of 1.269 ± 0.004 and 1.211 ± 0.003 solar masses, radii of 2.001 ± 0.003 and 1.511 ± 0.003 solar radii, and temperatures of 5683 ± 100 K and 5720 ± 100 K, respectively. Comparison with the Yonsei–Yale series of evolutionary models results in good agreement at an age of about 5.1 Gyr for a somewhat metal-rich composition. Those models indicate that the more massive, larger, slightly cooler star is just beyond core hydrogen exhaustion while the less massive, smaller, slightly hotter star has not quite reached core hydrogen exhaustion. The orbit is not yet circularized, and the components are rotating at or near their pseudosynchronous velocities. The distance to the system is 420 ± 30 pc.
Efficient Data Communication Using Dynamic Switching of Compression Method

As a means for high-speed communication on the network with limited communication bandwidth such as WAN or wireless LAN environment, we can use the online high-speed data compression/decompression method. Since it is necessary to reduce the transfer time including the time of the data compression process, it is difficult to adopt the advanced but time-consuming compression algorithm. However, it is possible to mitigate this constraint, if we take advantage of the multiple cores of multi-core processor that is significantly spread in recent years. By performing data transfer and compression on different processor cores in parallel, it is possible to use the advanced algorithm for higher compression ratio than conventional online algorithm, as long as the compression process catches up with the process of data transmission to network. Thus, it is possible to transfer the data faster, by transferring the more compressed data than conventional. In this paper, we investigate the method of highly efficient data transfer in the network of limited communication bandwidth. The method tries to select the highest compression algorithm dynamically as long as it catches up with the actual speed of sending data, in order to fully utilize the network bandwidth. Our evaluation result shows that the proposed method can select the nearly best compression method, and achieve up to 3 times speed-up maximum in various situations where both communication bandwidth and input data vary with time.
Rapid Screening of the Epidermal Growth Factor Receptor Phosphosignaling Pathway via Microplate-Based Dot Blot Assays

Expression profiling on a large scale, as is the case in drug discovery, is often accomplished through use of sophisticated solid-phase protein microarrays or multiplex bead technologies. While offering both high-throughput and high-content analysis, these platforms are often too cost prohibitive or technically challenging for many research settings. Capitalizing on the favorable attributes of the standard ELISA and slot blotting techniques, we developed a modified dot blot assay that provides a simple cost-effective alternative for semiquantitative expression analysis of multiple proteins across multiple samples. Similar in protocol to an ELISA, but based in a membrane bound 96-well microplate, the assay takes advantage of vacuum filtration to expedite the tedious process of washing in between binding steps. We report on the optimization of the assay and demonstrate its use in profiling temporal changes in phosphorylation events in the well-characterized EGF-induced signaling cascade of A431 cells.
Optimal Newton-type methods for nonconvex smooth optimization problems

We consider a general class of second-order iterations for unconstrained optimization that includes regularization and trust-region variants of Newton’s method. For each method in this class, we exhibit a smooth, bounded-below objective function, whose gradient is globally Lipschitz continuous within an open convex set containing any iterates encountered and whose Hessian is α−Holder continuous (for given α ∈ [0, 1]) on the path of the iterates, for which the method in question takes at least ⌊ǫ⌋ function-evaluations to generate a first iterate whose gradient is smaller than ǫ in norm. This provides a lower bound on the evaluation complexity of second-order methods in our class when applied to smooth problems satisfying our assumptions. Furthermore, for α = 1, this lower bound is of the same order in ǫ as the upper bound on the evaluation complexity of cubic regularization, thus implying cubic regularization has optimal worst-case evaluation complexity within our class of second-order methods.
Parameter control in Differential Evolution for constrained optimization

In this paper we present the addition of parameter control in a Differential Evolution algorithm for constrained optimization. Three parameters are self-adapted by encoding them within each individual and a fourth parameter is controlled by a deterministic approach. A set of experiments are performed in order (1) to determine the performance of the modified algorithm with respect to its original version, (2) to analyze the behavior of the self-adaptive parameter values and (3) to compare it with respect to state-of-the-art approaches. Based on the obtained results, some findings regarding the values for the DE parameters as well as for the parameters related with the constraint-handling mechanism are discussed.
Beyond the byzantine generals: unexpected behavior and bridging fault diagnosis

Physical defects cause behaviors unmodeled by even the best fault simulators, which complicates predictive diagnosis. This paper reports on a diagnosis procedure that uses modified composite signatures constructed from single stuck-at information combined with a lexicographic matching and ranking algorithm. The diagnosis procedure is used to perform high-quality bridging fault diagnosis for more than 400,000 diagnostic experiments involving dropping or adding behaviors from the simulations of faulty circuits.
Ieee Transactions on Information Forensics and Security This Is a Pre-print Only 1

—This paper proposes a method for the extraction of biometric features from the spatial patterns formed by eye movements during an inspection of dynamic visual stimulus. In the suggested framework each eye movement signal is transformed into a time-constrained decomposition by using a proba-bilistic representation of spatial and temporal features related to eye fixations and called Fixation Density Map (FDM). The results for a large collection of eye movements recorded from 200 individuals indicate the best equal error rate (EER) of 10.8% and Rank-1 identification rate (Rank-1 IR) as high as 51%, which is a significant improvement over existing eye movement-driven bio-metric methods. In addition, our experiments reveal that a person recognition approach based on the FDM performs well even in cases when eye movement data are captured at lower than optimum sampling frequencies. This property is very important for the future ocular biometric systems where existing iris recognition devices could be employed to combine eye movement traits with iris information for increased security and accuracy. Considering that commercial iris recognition devices are able to implement eye image sampling usually at a relatively low rate, the ability to perform eye movement-driven biometrics at such rates is of great significance.
GLOBAL STABILITY OF THE ENDEMIC EQUILIBRIUM OF MULTIGROUP SIR EPIDEMIC MODELS

ABSTRACT. For a class of multigroup SIR epidemic models with varying subpopulation sizes, we establish that the global dynamics are completely determined by the basic reproduction number R0. More specifically, we prove that, if R0 ≤ 1, then the disease-free equilibrium is globally asymptotically stable; if R0 > 1, then there exists a unique endemic equilibrium and it is globally asymptotically stable in the interior of the feasible region. Our proof of global stability utilizes the method of global Lyapunov functions and results from graph theory.
On the transfer of evolutionary couplings to industry

In this paper, we describe a case study at Philips Healthcare MRI focusing on evolutionary couplings, i.e., a technique to infer relationships among modules by analyzing their history of changes in the source code archive. In this case study, we failed to transfer CouplingViewer, a tool implementing the current state-of-art in evolutionary couplings, to industry. According to the industrial experts an important industrial requirement was not met: the signal-to-noise ratio was too low.
A Logic of Emotions for Intelligent Agents

This paper formalizes a well-known psychological model of emotions in an agent specification language. This is done by introducing a logical language and its semantics that are used to specify an agent model in terms of mental attitudes including emotions. We show that our formalization renders a number of intuitive and plausible properties of emotions. We also show how this formalization can be used to specify the effect of emotions on an agent's decision making process. Ultimately, the emotions in this model function as heuristics as they constrain an agent's model.
Privacy-preserving Classification of Data Streams

Data mining is the information technology that extracts valuable knowledge from large amounts of data. Due to the emergence of data streams as a new type of data, data streams mining has recently become a very important and popular research issue. There have been many studies proposing efficient mining algorithms for data streams. On the other hand, data mining can cause a great threat to data privacy. Privacy-preserving data mining hence has also been studied. In this paper, we propose a method for privacy-preserving classification of data streams, called the PCDS method, which extends the process of data streams classification to achieve privacy preservation. The PCDS method is divided into two stages, which are data streams preprocessing and data streams mining, respectively. The stage of data streams preprocessing uses the data splitting and perturbation algorithm to perturb confidential data. Users can flexibly adjust the data attributes to be perturbed according to the security need. Therefore, threats and risks from releasing data can be effectively reduced. The stage of data streams mining uses the weighted average sliding window algorithm to mine perturbed data streams. When the classification error rate exceeds a predetermined threshold value, the classification model is reconstructed to maintain classification accuracy. Experimental results show that the PCDS method not only can preserve data privacy but also can mine data streams accurately.
Operational amplifiers with flexible noise power balance scheme for SOC application

Advances in integrated circuit technology have led to the birth and proliferation of a wide variety of integrated circuits, including but not limited to application specific integrated circuits(ASIC), various types of microcontrollers and processors. Many applications such as communication devices (VoIP, MoIP, wireless) require chip speeds that may be unattainable with separate IC products. Creating portable analog modules requires the system to capture not only the sized schematic of the circuit but also the objectives that circuit is trying to achieved. This paper applies the embedding knowledge into pure simulation based methodology to perform automatic analog intergraded circuit design, synthesis and optimization in order to reduce development time of this kind of circuits. A practical platform independent computer aided design methodology for synthesis of (analog circuits) Operational Amplifier with flexible noise --power balance is presented in this paper. In order to evaluate the fitness of the circuit specifications in any iteration of SA, NGSPICE simulation is used. The simulation results confirm the efficiency of presented methodology in determining the device sizes in analog circuits.
The Effects of Deleterious Mutations on Evolution at Linked Sites

The process of evolution at a given site in the genome can be influenced by the action of selection at other sites, especially when these are closely linked to it. Such selection reduces the effective population size experienced by the site in question (the Hill–Robertson effect), reducing the level of variability and the efficacy of selection. In particular, deleterious variants are continually being produced by mutation and then eliminated by selection at sites throughout the genome. The resulting reduction in variability at linked neutral or nearly neutral sites can be predicted from the theory of background selection, which assumes that deleterious mutations have such large effects that their behavior in the population is effectively deterministic. More weakly selected mutations can accumulate by Muller’s ratchet after a shutdown of recombination, as in an evolving Y chromosome. Many functionally significant sites are probably so weakly selected that Hill–Robertson interference undermines the effective strength of selection upon them, when recombination is rare or absent. This leads to large departures from deterministic equilibrium and smaller effects on linked neutral sites than under background selection or Muller’s ratchet. Evidence is discussed that is consistent with the action of these processes in shaping genome-wide patterns of variation and evolution.
Optimising the combined source and channel coding of a discrete communication system

The problem of optimising the structure of the encoder/decoder pair in a discrete communication system, with an additive distortion measure, is formulated in terms of a quadratic programming (QP) problem. This new formulation benefits from the following special features: it optimises the joint effects of the source/channel coding on the end-to-end distortion; and the encoder and the decoder structures are not restricted to being the inverse of each other. A method which obtains an e-minimiser approximation of an optimum point of a general QP problem is discussed. Some simulation results based on this method are also given.