Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary and Alternative Algorithms : Reliable Cost Predictions for Finding Optimal Solutions to the LABS Problem ∗

The low-autocorrelation binary sequence (LABS) problem represents a major challenge to all search algorithms, with the evolutionary algorithms claiming the best results so far. However, the termination criteria for these types of stochastic algorithms are not well-defined and no reliable claims have been made about optimality. Our approach to find the optima of the LABS problem is based on combining three principles into a single method: (1) solver performance experiments with problem sizes for which optimal solutions are known, (2) an asymptotic statistical analysis of such experiments, (3) reliable predictions of the computational cost required to find optimal solutions for larger problem sizes. The proposed methodology provides a well-defined termination criterion for evolutionary and alternative search algorithms alike. keywords: fundamental combinatorial algorithms, performance predictions and evaluations, low-autocorrelation binary sequence, evolutionary algorithms ∗Ready-to-execute software environment, data sets, and the results reported in the experiments have been archived on the LABS problem home page www.cbl. ncsu.edu/OpenExperiments/LABS/ Email adddresses: brglez@cs.ncsu.edu, xyli@unity.ncsu.edu, stallmann@cs.ncsu.edu, militzer@gl.ciw. edu Corresponding author.
On Feature Orientation and Requirements Encapsulation

Naive feature orientation runs into problems with large software systems, such as telephone switching systems. With naive feature orientation, a feature extends a base system by an arbitrary increment of functionality. Information hiding helps to structure a large software system design into modules such that it can be maintained. We focus on the requirements of a software system. Requirements can be structured analogously to design modules. Naive feature orientation can violate requirements encapsulation. We survey approaches with improved encapsulation, and we show how and when families of requirements can help.
Recursive Strategies for Answering Recursive Queries - The RQA/FQI Strategy

In this paper we will discuss several methods for recursive query processing using a recursive control structure. We will describe the QSQR method, introduced in [Vie861 and show that it fails to produce all answers in certain cases. After analyzing the causes of this failure we propose an improved algorithm the RQA/FQI Strategy which is complete over the domain of function-free Horn clauses. The new method uses a two step approach recursive expansion + an efficient variant of LFP iteration to evaluate recursive queries. A short comparison of these methods shows the efficiency of RQA/FQI.
Label-free Semiquantitative Peptide Feature Profiling of Human Breast Cancer and Breast Disease Sera via Two-dimensional Liquid Chromatography-Mass Spectrometry*S

A label-free semiquantitative peptide feature profiling method was developed in response to challenges associated with analysis of two-dimensional liquid chromatography-tandem mass spectrometry data. One hundred twenty human sera (49 from invasive breast carcinoma patients, 26 from non-invasive breast carcinoma patients, 35 from benign breast disease patients, and 10 from normal controls) were repeatedly analyzed using a standardized two-dimensional liquid chromatography-mass spectrometry method. Data were extracted using the novel semiquantitative peptide feature profiling method, which is based on comparisons of normalized relative ion intensities. Hierarchical cluster analyses and principle component analyses were used to evaluate the predicative capability of the extracted data, and results were promising. Extracted data were also randomly assigned to either a training group (65%) or to a test group (35%) for artificial neural network modeling. Models best identified invasive breast carcinomas (212 predictions, 94% accurate) and benign non-neoplastic breast disease (96 predictions, 81.3% accurate). These results suggest that, after further development, the novel method may be useful for large scale clinical proteomic profiling.
Training sequence design for adaptive equalization of multi-user systems

Preliminary work on training sequence design for block adaptive channel estimation methods for multi-user direct-sequence/code-division multiple-access (DS/CDMA) systems is provided. The focus is on linear minimum-mean squared error estimation methods. First, a joint channel estimation scheme is considered for hybrid quasi-synchronous CDMA/time-division multiple-access systems. For the CDMA/TDMA hybrid optimal training sequences are designed. The second scenario considers a completely asynchronous classical DS/CDMA system. Bayesian channel estimation is considered for a single user of interest. Based on estimated interference statistics, an optimal training sequence is designed. Numerical results are provided which indicate that significant improvements in performance can be achieved when employing optimized training sequences.
Health-related quality-of-life outcome measures in paediatric palliative care: A systematic review of psychometric properties and feasibility of use

Background: The number of children worldwide requiring palliative care services is increasing due to advances in medical care and technology. The use of outcome measures is important to improve the quality and effectiveness of care. Aim: To systematically identify health-related quality-of-life outcome measures that could be used in paediatric palliative care and examine their feasibility of use and psychometric properties. Design: A systematic literature review and analysis of psychometric properties. Data sources: PsychInfo, Medline and EMBASE were searched from 1 January 1990 to 10 December 2014. Hand searches of the reference list of included studies and relevant reviews were also performed. Results: From 3460 articles, 125 papers were selected for full-text assessment. A total of 41 articles met the eligibility criteria and examined the psychometric properties of 22 health-related quality-of-life measures. Evidence was limited as at least half of the information on psychometric properties per instrument was missing. Measurement error was not analysed in any of the included articles and responsiveness was only analysed in one study. The methodological quality of included studies varied greatly. Conclusion: There is currently no ‘ideal’ outcome assessment measure for use in paediatric palliative care. The domains of generic health-related quality-of-life measures are not relevant to all children receiving palliative care and some domains within disease-specific measures are only relevant for that specific population. Potential solutions include adapting an existing measure or developing more individualized patient-centred outcome and experience measures. Either way, it is important to continue work on outcome measurement in this field.
Romano: autonomous storage management using performance prediction in multi-tenant datacenters

Workload consolidation is a key technique in reducing costs in virtualized datacenters. When considering storage consolidation, a key problem is the unpredictable performance behavior of consolidated workloads on a given storage system. In practice, this often forces system administrators to grossly overprovision storage to meet application demands. In this paper, we show that existing modeling techniques are inaccurate and ineffective in the face of heterogenous devices. We introduce Romano, a storage performance management system designed to optimize truly heterogeneous virtualized datacenters. At its core, Romano constructs and adapts approximate workload-specific performance models of storage devices automatically, along with prediction intervals. It then applies these models to allow highly efficient IO load balancing. End-to-end experiments demonstrate that Romano reduces prediction error by 80% on average compared with existing techniques. The result is improved load balancing with lowered variance by 82% and reduced average and maximum latency observed across the storage systems by 52% and 78%, respectively.
Rollin' Justin - Design considerations and realization of a mobile platform for a humanoid upper body

Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With Rollin' Justin a mobile robotic system and research platform is presented that allows the implementation and demonstration of sophisticated control algorithms and dexterous manipulation. Important problems of service robotics such as mobile manipulation and strategies for using the increased workspace and redundancy in manipulation task can be studied in detail. This paper gives an overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system Justin into Rollin' Justin, a fully self-sustaining mobile research platform.
Feminism: Failed or Functioning? A Study of Women’s Views on the Movement

From The Women’s March in January 2017 to the current Me Too movement, women’s rights have appeared to come to the forefront of America. Discussion of abortion rights have reemerged, gender norms are questioned more and more, and sexual assault is becoming a visible, important topic. To some, this is seen as a revolution that has been necessary for decades. However, others may not see it this way for a variety of reasons. Feminism tends to be a very taboo word that carries baggage of all sorts. What may cause some women to label themselves as feminists, and what may cause others to turn away from it? Which elements of the feminist movement may be at play in this? Do women today perceive themselves as possessing a marginalized status, and do any small benefits that come along with being a woman connect to women’s perception of having a marginalized status? Through interviewing twelve women at a public college in upstate New York, this study finds that many women do see the need for the movement and believe that women are still marginalized. However, they also largely believe that feminism continues to not include all identities, still privileging white, straight, middle-class women over other identities. Advantages of being a woman did not tend to play a role in a woman’s support of the feminist movement.
TNF receptor secretion after ex vivo adenoviral gene transfer to cornea and effect on in vivo graft survival.

PURPOSE To explore the potential for adenovirus-mediated ex vivo gene transfer of a soluble tumor necrosis factor (TNF) receptor and evaluate the effect of transplanting the adenovirally transplanted corneas in vivo. METHODS Rabbit corneal segments were transfected with replication-deficient adenovirus (AdTNFR) encoding a soluble TNF receptor fusion protein (TNFR-Ig). Production of TNFR-Ig was measured by using ELISA and bioassay. Corneas were transfected ex vivo with AdTNFR and then transplanted in vivo. Survival of AdTNFR-transfected corneas was compared with that of those treated either with a null vector control adenovirus (Ad0) or nontransfected control corneas. RESULTS Ex vivo production of a molecule with TNF blocking bioactivity from AdTNFR-transfected corneas was demonstrated over a period of 4 weeks. Transplanted AdTNFR-transfected corneas showed a marginally increased survival time in vivo over nontransfected control corneas, but a significantly increased survival time over Ad0-treated control corneas. Ad0 treatment of corneal allografts before transplantation had a proinflammatory effect and accelerated the onset of corneal endothelial rejection. CONCLUSIONS Adenoviral gene transfer is an effective means of transferring a gene encoding soluble TNFR-Ig to corneal endothelium, and ex vivo production of a biologically active secreted molecule was demonstrated for 4 weeks. However, in vivo, only a marginally increased survival was seen compared with control corneas. The introduction of this transgene using a less immunogenic vector may demonstrate prolongation of corneal allograft survival.
> Replace This Line with Your Paper Identification Number (double-click Here to Edit) < Datafed: an Architecture for Federating Atmospheric Data for Geoss

—DataFed is a distributed web-services-based computing environment for accessing, processing and rendering environmental data in support of air quality management and science. The flexible, adoptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing value chains. The approach of DataFed is mediation between users and data providers. DataFed assumes the autonomous and spontaneous emergence of distributed data sources. It non-intrusively wraps datasets for access by web services. The mediator software, composed of web services, provides homogeneous data views (e.g. geospatial, time views) using a global multi-dimensional data model. Application software written using web services consists of data browsers and analysis tools for distributed AQ data. Currently DataFed serves as data gateway for user programs; web pages, GIS, science tools as well as for loosely coupled Service Oriented Architecture Applications. Its federated data pool consists of over 50 datasets and the tools have been applied in several air pollution projects Index Terms—Earth environment, terrestrial atmosphere, information system.
Smart-DJ: Context-Aware Personalization for Music Recommendation on Smartphones

Providing personalized content on smartphones is significant in ensuring user experience and making mobile applications profitable. The existing approaches mostly ignore the rich personalized information from user interaction with smartphones. In this paper, we address the issue of recommending personalized music to smartphone users and propose Smart-DJ. Smart-DJ incorporates an evolutionary model called Incremental Regression Tree, which incrementally collects contextual data, music data and user feedback to characterize his/her personal taste of music. An efficient recommending algorithm is designed to make accurate recommendations within bounded latency. We implement Smart-DJ and evaluate its performance through analysis and real-world experiments. The results demonstrate that Smart-DJ outperforms the state-of-arts approaches in terms of recommendation accuracy and overhead.
Resilience and Sustainable Development: Theory of resilience, systems thinking and adaptive governance

This ESDN Quarterly Report (QR) provides a condensed overview of the concept of resilience. Despite the complexity of the theory behind resilience, this QR tries to communicate the main notions behind this concept in a way that is understandable and not overly technical. The intention of this QR is to serve as a guide through the concept of resilience. The report does not aim at being exhaustive but intends to provide an overview on the links which are particularly relevant for sustainable development (SD) in general and SD governance in particular. A multitude of diverse sources have been used, mainly from the academic literature. It has to be mentioned the significant and decisive role that the Resilience Alliance has in providing extensive knowledge: the website that they are running, is an exceptionally good source of information for those who are interested and want to deepen their knowledge of resilience. Additionally, among all the scientific publications cited throughout the report, a special mention goes to the book by Walker and Salt (2006) entitled “Resilience thinking: sustaining ecosystems and people in a changing world”, which is very much suggested as a practical source of information on resilience. As notions provide guidance, understand the linkages the concept resilience sustainable policy-makers relationships among production, drought, variable rainfall, tropical storms, pine beetle infestation, drought/flood/disease incidence, water quality and supply, coastal change, fluctuating lake levels.
A Fan-type condition for Hamiltonian graphs

For two non-adjacent vertices u: v in a graph G, we use a(u~ v) to denote the ma. "\. imum cardinality of an independent vertex set of G containing both u and v. In this paper, we prove that if G is a 2-connected graph of order n and max{d{u),d(v}} ~ ~ for each pair of nonadjacent vertices Lt. v of G with 1 ::; IN( u) nN( v) I < a(u, v) -1, then either G is Hamiltonian or else G belongs to a family of exceptional graphs.
Parameterization of γ, epm, and Neutrino Spectra Produced by p-p Interaction in Astronomical Environments

We present the yield and spectra of stable secondary particles (γ, e±, νe, e, νμ, and μ) of p-p interaction in parameterized formulae to facilitate calculations involving them in astronomical environments. The formulae are derived from the up-to-date p-p interaction model by Kamae et al. (2005), which incorporates the logarithmically rising inelastic cross section, the diffraction dissociation process, and the Feynman scaling violation. To improve fidelity to experimental data in lower energies, two baryon resonance contributions have been added: one representing Δ(1232) and the other representing multiple resonances around 1600 MeV/c-2. The parameterized formulae predict that all secondary particle spectra be harder by about 0.05 in power-law indices than that of the incident proton and their inclusive cross sections be larger than those predicted by p-p interaction models based on the Feynman scaling.
Using singularity exponent in distance based classifier

The paper deals with using so called singularity exponent in a classifier that is based on ordered distances of patterns to a given (classified) pattern. The approximation of probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in a form of a suitable power (exponent) of a distance is presented together with a way how to state it. A classifier utilizing knowledge about explored data distribution in a space and a suggested expression of the exponent is presented. Experimental results on both synthetic and real-life data show interesting behavior (classification accuracy) of the classifier in comparison with other well-known classifiers.
Improving Text Classification by Using Encyclopedia Knowledge

The exponential growth of text documents available on the Internet has created an urgent need for accurate, fast, and general purpose text classification algorithms. However, the "bag of words" representation used for these classification methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. In order to deal with this problem, we integrate background knowledge - in our application: Wikipedia - into the process of classifying text documents. The experimental evaluation on Reuters newsfeeds and several other corpus shows that our classification results with encyclopedia knowledge are much better than the baseline "bag of words " methods.
A high-sensitivity 135GHz millimeter-wave imager by differential transmission-line loaded split-ring-resonator in 65nm CMOS

A high-sensitivity 135GHz millimeter-wave (mm-wave) imager is demonstrated in 65nm CMOS by on-chip metamaterial resonator: a differential transmission-line (T-line) loaded with split-ring-resonator (DTL-SRR). Due to sharp stop-band introduced by metamaterial load, high-Q oscillatory amplification can be achieved with high sensitivity when utilizing DTL-SRR as quench-controlled oscillator to provide regenerative detection. The developed mm-wave imager pixel has a compact core chip area of 0.0085mm2 with measured power consumption of 6.2mW, sensitivity of -76.8dBm, noise figure of 9.7dB, and noise equivalent power of 0.9fW/√Hz with demonstrated mm-wave images.
Job Assignments Under Moral Hazard: The Peter Principle Revisited

We show that inefficient job assignments arise in organizations even if there is full information about employees’ types and complete contracts are possible. Our model also provides a new perspective on the Peter Principle: the output of an employee who is promoted into a job for which he is not well suited need not decline postpromotion, because he is pushed to exert more effort. Although promotions are desirable for most employees, they make the least able in a hierarchy level worse off: for them earnings increase only because they work harder to compensate for their “incompetence. ”
An Algebraic Approach to Modeling Analogical Projection in Pattern Perception

In this paper we propose an algebraic method for solving proportional analogy problems involving sequential patterns. In this approach, sequential patterns are considered as elements of an algebra. The gestalt that is assigned to a pattern is represented by the term of the algebra that denotes it. Most patterns are ambiguous: there are diierent terms that correspond to a pattern, representing diierent gestalts of it. When a pattern is perceived as part of a proportional analogy, it may assume a diierent gestalt than when it is viewed in isolation. We consider analogical relations as mappings between algebras and give a formal deenition of the preferred gestalts for an analogy in terms of the simplicity of algebraic terms that denote the patterns involved in the proportional analogy. We conjecture that these terms correspond to the gestalts that are perceived by a human who solves the proportional analogy problem. Finally, we describe an algorithm to solve the proportional analogy problems, which computes the simplest gestalts for the three given terms | taking into account the mutual context eeect | on the basis of which the fourth term of the proportional analogy is determined. Creativity consists in the generation of ideas that are experienced as new | that is, not implied by systematic or routine cognitive processes; ideas that require a leap of imagination. Some approaches to modeling creativity have been presented in Hofstadter (1995) and Indurkhya (1992), where it is observed that new ideas and perspectives are often created when one realm of experience is interpreted using structures from a diierent realm: this mechanism is often referred to as analogical or metaphorical projection. We conjecture that the cognitive mechanism of metaphorical projection is essentially the same as analogical projection between perceptual structures.
Answer Set Programming and Bounded Model Checking

In this paper bounded model checking of asynchronous concurrent systems is introduced as a promising application area for answer set programming. This is an extension of earlier work where bounded model checking has been used for verification of sequential digital circuits. As the model of asynchronous systems a generalization of communicating automata, 1-safe Petri nets, are used. A mapping from bounded reachability and deadlock detection problems of 1-safe Petri nets to stable model computation is devised. Some experimental results on solving deadlock detection problems using the mapping and the Smodels system are presented. They indicate that the approach is quite competitive when searching for short executions of the system leading to deadlock.
Prediction of Users' Response Time in Q&A Communities

Social media and online Question and Answer (Q&A) communities in particular have become a successful solution for finding answers on diverse topics. However, not all questions are answered by these communities. Also, many questions are not answered quickly enough. In this paper, we propose a framework for predicting users' response time. The framework uses a diverse set of features including information on users, the content they generate while communicating, question tags, spatial and temporal features. Then these features are used as input for training predictive models by various machine learning algorithms. As a case study, three diverse Q&A communities from Stack Exchange are selected to test the framework. We demonstrate that Deep Belief Networks outperform Logistic Regression (LR), k-nearest neighbors (k-NN), and Decision Trees (DT) in the accuracy of the prediction across the three diverse Q&A communities.