Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting synchronous and asynchronous DVS for feedback EDF scheduling on an embedded platform

Contemporary processors support dynamic voltage scaling (DVS) to reduce power consumption by varying processor voltage/frequency dynamically. We develop power-aware feedback--DVS algorithms for hard real-time systems that adapt to dynamically changing workloads. The algorithms lower execution speed while guaranteeing timing constraints. We study energy consumption for synchronous and asynchronous DVS switching on a PowerPC board. Energy, measured via data acquisition, is reduced up to 70% over naïve DVS for our feedback scheme with 24% peak savings over previous algorithms. These results, albeit differing in quantity, confirm trends observed under simulation. They are the first of their kind on an embedded board.
A Dynamic Labeling Scheme for XML Document

Efficient evaluation of XML queries requires the determination of whether a relationship exists between two elements. A number of labeling schemes have been designed to meet the need. However, most of them have poor updating performance. In this paper, a new dynamic region-based labeling scheme is proposed which uses real numbers instead of integers to represent the region. Moreover, the scheme can adjust the codes of some nodes in some parts of the document tree according to the condition of updates. Our analysis shows this new labeling scheme provides efficient support for updates.
Prevention and Reversal of Diabetic Nephropathy in db/db Mice Treated with Alagebrium (ALT-711)

Background: Alagebrium (ALT-711) has been shown to improve renal dysfunction in animal models of diabetes. Methods: To test its effects in diabetic nephropathy (DN), ALT-711 was administered (1 mg/kg daily i.p.) to 9-week-old female db/db mice (n = 15, group A1) for 3 weeks and to 3-month-old (n = 15, group A2), 7-month-old (n = 7, group A3), and 12-month-old (n = 5, group A4) female db/db mice for 12 weeks, while a similar number of diabetic and nondiabetic mice were used as controls. The ΕN-carboxymethyllysine (CML) levels in serum, urine, skin, and kidney tissue were measured by enzyme-linked immunosorbent assay. The renal morphometric parameters were assessed by electron and light microscopy. Results: By the 3rd week of treatment, the serum CML level decreased by 41%, and the urinary CML concentration increased by 138% from baseline, while the urinary albumin/creatinine ratio was lower (p < 0.05) in diabetic and nondiabetic group A1 mice. After 3 months of treatment, serum, skin, and kidney CML levels and urinary albumin/creatinine ratio were lower (p < 0.05) and the urinary CML levels higher (p < 0.05) in treated group A2, A3, and A4 animals compared with groups which received phosphate-buffered saline, with a similar pattern observed in nondiabetic mice. The renal morphological parameters characteristic of DN decreased in treated compared with untreated mice. Conclusion: Alagebrium may prevent, delay, and/or reverse established DN in db/db mice by reducing the systemic advanced glycation end product pools and facilitating the urinary excretion of advanced glycation end products.
Association between contextual dependence and replicability in psychology may be spurious

The Reproducibility Project: Psychology (RP:P) attempted to replicate 100 cognitive and social-personality psychology studies (1). Van Bavel et al. (2) report an association (r = −0.23, P = 0.024) between a study’s rated “contextual dependence” and whether the study was successfully replicated by the RP:P. However, this association is entirely the result of an omitted third variable: whether the study was in cognitive or social-personality psychology. Within each subdiscipline there is no relationship between context dependence and replicability: r = −0.08, P = 0.54 for social-personality psychology; r = −0.04, P = 0.79 for cognitive psychology (point-biserial correlations).
Timing and schedulability analysis for distributed automotive control applications

High-end cars today consist of more than 100 electronic control units (ECUs) that are connected to a set of sensors and actuators and run multiple distributed control applications. The design flow of such architectures consists of specifying control applications as Simulink/Stateflow models, followed by generating code from them and finally mapping such code onto multiple ECUs. In addition, the scheduling policies and parameters on both the ECUs and the communication buses over which they communicate also need to be specified. These policies and parameters are computed from high-level timing and control performance constraints. The proposed tutorial will cover different aspects of this design flow, with a focus on timing and schedulability problems. After reviewing the basic concepts of worst-case execution time analysis and schedulability analysis, we will discuss the differences between meeting timing constraints (as in classical real-time systems) and meeting control performance constraints (e.g., stability, steady and transient state performance). We will then describe various control performance related schedulability analysis techniques and how they may be tied to model-based software development. Finally, we will discuss various schedule synthesis techniques, both for ECUs as well as for communication protocols like FlexRay, so that control performance constraints specified at the model-level may be satisfied. Throughout the tutorial different commercial as well as academic tools will be discussed and demonstrated.
Book Reviews: The Proper Treatment of Events, by Michiel van Lambalgen and Fritz Hamm

Figures.Preface. Part I: Time, events and cognition.Chapter 1: Time.Psychology of time.Why do we have the experience of time at all? Chapter 2: Events and time.The analogy between events and objects.The Russell-Kamp construction of time from events.Walker's construction.Richer languages for events.Some linguistic applications.Continuous time from events.Conclusion. Chapter 3: Language, time and planning.Part II: The formal apparatus.Chapter 4: Events formalized.A calculus of events.The axiom system EC.Scenarios. Minimal models.Chapter 5: Computing with time and events.Logic programming with constraints.Minimal models revisited.How to get to the other side of a street.When do causes take effect? Exercises for chapters 4 and 5.Da capo, with feeling.Chapter 6: Finishing touches.Coding VPs as fluents and events.Consistency, truth and partiality.Part III: A marriage made in heaven - linguistics and robotics.Chapter 7: Aktionsart.Eventualities. Formal definition of Aktionsarten.Perfective and imperfective eventualities.Chapter 8: Tense.Reichenbach's reference time R.Event time and the sentence.Present tense.Past tense.Future tense.Exercises.Chapter 9: Tense in French: Passe Simple and Imparfait.Introduction. Data.Formalizing the Passe Simple and Imparfait.Coda. Exercises.Chapter 10: Grammatical aspect.The perfect.The progressive.A computational proof.Comments on the literature.Exercises.Chapter 11: Coercion.Additive coercion.Subtractive coercion.Cross-coercion.Temporal adverbials: 'in' and 'for'. Coercion and intensionality.Exercises.Chapter 12: Nominalization.Two types of English Gerunds.History of the English gerundive system.Nominalizations formalized I: Denotation types.Nominalizations formalized II: Lexical meaning.Chapter 13: Appendix: the basics of logic programming.Logic programming for propositional logic.Logic programming for predicate logic.References. Index.
Underdetermined DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Array

Quasi-stationary signals have been widely found in practical applications, which have time-varying second-order statistics while staying static within local time frames. In this paper, we develop a robust direction-of-arrival (DOA) estimation algorithm for quasi-stationary signals based on the Khatri–Rao (KR) subspace approach. A partly-calibrated array is considered, in which some of the sensors have an inaccurate knowledge of the gain and phase. In detail, we first develop a closed-form solution to estimate the unknown sensor gains and phases. The array is then calibrated using the estimated sensor gains and phases which enables the improved DOA estimation. To reduce the computational complexity, we also proposed a reduced-dimensional method for DOA estimation. The exploitation of the KR subspace approach enables the proposed method to achieve a larger number of degrees-of-freedom, i.e., more sources than sensors can be estimated. The unique identification condition for the proposed method is also derived. Simulation results demonstrate the effectiveness of the proposed underdetermined DOA estimation algorithm for quasi-stationary signals.
Scalable, synthetic, sensor network data generation

Sensor networks are a new class of distributed systems composed of a large number of densely deployed sensors, actuators, low power computation, and wireless communication devices. Sensor network research is still in its infancy. There is a large volume of exploratory research; however, few real systems are deployed and little experimental data from sensor networks is available to test proposed protocol design. Due to lack of experimental data and sophisticated models derived from such data, most data processing algorithms from the sensor network literature are evaluated with data generated from simple models. Through statistical performance analysis and algorithm evaluation using experimental data, we demonstrate the need to evaluate algorithms using realistic data corresponding to a wide range of parameter values and irregular topology input. Motivated out of a concern for data sensitivity and a lack of experimental data, we propose a scalable synthetic data generation framework to support systematic algorithm evaluation and robust algorithm design. We have two strategies to achieve scalable synthetic data generation. First, using case studies of concrete sensor network algorithms we identify a small number of parameters to manipulate in our synthetic data generation. This significantly reduces the search space from exponential to a manageable number. Second, we use empirical models derived from experimental data to guide simulation towards those portions of the space that represent real world scenarios. Guided by these two strategies, we implement algorithms to generate synthetic data either with similar characteristics as the experimental data, or exhibiting a wide range of data characteristics. In addition to the irregular topology data generation toolbox, we also provide ready-to-use test suites to encourage people to utilize more realistic data when evaluating their algorithms. Moreover, the sensor data replay addition to EmStar enhances EmStar simulation/emulation with more realistic sensor data traces.
Bid optimization for broad match ad auctions

Ad auctions in sponsored search support "broad match" that allows an advertiser to target a large number of queries while bidding only on a limited number. While giving more expressiveness to advertisers, this feature makes it challenging to optimize bids to maximize their returns: choosing to bid on a query as a broad match because it provides high profit results in one bidding for related queries which may yield low or even negative profits. We abstract and study the complexity of the {\em bid optimization problem} which is to determine an advertiser's bids on a subset of keywords (possibly using broad match) so that her profit is maximized. In the query language model when the advertiser is allowed to bid on all queries as broad match, we present a linear programming (LP)-based polynomial-time algorithm that gets the optimal profit. In the model in which an advertiser can only bid on keywords, ie. , a subset of keywords as an exact or broad match, we show that this problem is not approximable within any reasonable approximation factor unless P=NP. To deal with this hardness result, we present a constant-factor approximation when the optimal profit significantly exceeds the cost. This algorithm is based on rounding a natural LP formulation of the problem. Finally, we study a budgeted variant of the problem, and show that in the query language model, one can find two budget constrained ad campaigns in polynomial time that implement the optimal bidding strategy. Our results are the first to address bid optimization under the broad match feature which is common in ad auctions.
A Hybrid Approach for Joint Simulation of Geometallurgical Variables with Inequality Constraint

Geometallurgical variables have a significant impact on downstream activities of mining projects. Reliable 3D spatial modelling of these variables plays an important role in mine planning and mineral processing, in which it can improve the overall viability of the mining projects. This interdisciplinary paradigm involves geology, geostatistics, mineral processing and metallurgy that creates a need for enhanced techniques of modelling. In some circumstances, the geometallurgical responses demonstrate a decent intrinsic correlation that motivates one to use co-estimation or co-simulation approaches rather than independent estimation or simulation. The latter approach allows us to reproduce that dependency characteristic in the final model. In this paper, two problems have been addressed, one is concerning the inequality constraint that might exist among geometallurgical variables, and the second is dealing with difficulty in variogram analysis. To alleviate the first problem, the variables can be converted to new variables free of inequality constraint. The second problem can also be solved by taking into account the minimum/maximum autocorrelation factors (MAF) transformation technique which allows defining a hybrid approach of joint simulation rather than conventional method of co-simulation. A case study was carried out for the total and acid soluble copper grades obtained from an oxide copper deposit. Firstly, these two geometallurgical variables are transferred to the new variables without inequality constraint and then MAF analysis is used for joint simulation and modelling. After back transformation of the results, they are compared with traditional approaches of co-simulation, for which they showed that the MAF methodology is able to reproduce the spatial correlation between the variables without loss of generality while the inequality constraint is honored. The results are then post processed to support probabilistic domaining of geometallurgical zones.
Temporal Semantics Extraction for Improving Web Search

Current Web-search engines can be improved through techniques that consider a temporal dimension in both query formulation and information extraction processes. An accurate recognition of temporal expressions in data sources is required, as well as extracting semantic embedded meta-information concerning time in a standard format that allows reasoning without ambiguity. Temporal Web searching entails an interesting advance on the way to the Semantic Web. We propose a temporal expressions recognition and normalization (TERN) system for contents in Spanish, which has been integrated into a Web-search engine prototype. The contribution of this system lies in its capability of taking into account the semantics of time in the user queries as well as in the search collections, independently of its representation. Evaluation figures show that the inclusion of temporal information management aptitudes to Web searching means considerable improvements in its performance.
Bone morphogenetic proteins: The anomalous molecules

Bone is unique of all the tissues in the vertebrate organism. When injured, it heals by formation of new bone. Bone morphogenetic proteins (BMPs) are powerful inductors of the osteogenic activity during the embryologic bone formation phase and in cases of bone healing. They have proliferative effects on different cellular types, showing chemotactic properties and are able to induce mesenchymal cells differentiation into osteoblastic and chondroblastic line cells. Both primary cells and cell lines have been shown to respond to BMPs. Further the ability of embryonic cells to respond to BMPs by differentiating into cartilage and bone cells suggests that they are involved in the development of embryonic skeletal system. In addition, these proteins can also promote the angiogenesis, regulate the activity of some growth factors, and affect the production of these growth factors, which is helpful for the osteogenesis. BMPs have been considered as the most potent growth factors that can promote the bone regeneration. Thus, the aim of this review is to emphasize on the unique nature of the BMP molecules regarding their structure, classification, signaling mechanism, etc., as BMPs are the only molecules which show such deviation from the normal order, type. This will further help in understanding the role of BMPs and their potential advances which are necessary to facilitate the process of regeneration in periodontics.
Alternative Livelihood Options for Gich Local Community a Perspective on Sustainable Tourism Development:The Case of Newly Resettle Site of Debark/Semin Mountain National Park, Ethiopia

The study area being a resettled site for the people does not have adequate information to survive in such a different geographical conditions and lack of knowledge towards new form of businesses limit them to work out for the alternative sources of livelihood. These communities were previously depending upon agricultural for food, income and for their day today survival. The factors that were prevalent in a resettled site compelled the community to involve in unsustainable practices. So, the objective of the study is to look out for an alternative livelihood options for Gich local community of Semin Mountain National Parks (Newly resettle site of Debark). The study is descriptive in its nature and qualitativeaquantitative research methodology was adopted. Data collection was done on the basis of personal interviews, through questionnaire survey and Focus Group Discussions. Frequency, percentage, average mean, one way ANOVA, independent t-test, one sample test and paired correlation were employed. Local communities those are settled near and around the park have best possible livelihood opportunities such as off farm activities (carpenter, masonry, house painting, timber house, mill , bakery etc.), small scale agro based practices like (poultry, livestock rearing, dairy, fruit orchards etc.), tourism product development (handy crafts, traditional coffee, local beer, honey beer, traditional restaurants, traditional music house or "Azmari", and tourism sector related employment (souvenir shops, chefs, tour guides, guards of hotel, cleaners, housekeepers, porters and raw material suppliers to local restaurants). As stake holders were not able to solve the resettlement issues of the residents, they were unable to have community associations, there were lacking electricity and transportation facilitiesin an around the site and that makes local inhabitants dissatisfied about their resettlement.
Partitioning unstructured meshes for homogeneous and heterogeneous parallel computing environments

Partitioning meshes is a preprocessing step for parallel scientific simulation. The quality of a partitioning is measured by load balance and communication overhead. The effectiveness of a partitioning significantly influences the performance of parallel computation. In this paper, we propose a quadtree spatial-based domain decomposition method for partitioning unstructured meshes. The background quadtree, which is originally used to represent the density distribution among elements within the computing domain, can be used to obtain an initial partitioning and to do multi-level refinement. As the quadtree implicitly defines hierarchical relationship, which is a natural way to define coarsening and uncoarsening phases, we can repeatedly apply coarsening, partitioning, and uncoarsening multilevel refinement phases, until no improvement can be made. Thus, for most cases, the partitioning results by our method are better than those produced by other graph-based partitioning methods. Experimental studies for the NACA0012 airfoil, the NASA EET wing, and an artillery shell within a shock tube are reported.
Mean-square stabilization for discrete-time networked control system with random delay

This paper presents a small gain theorem in the mean square sense for a class of networked systems with one-step random delay. This delay is model by a Kronecker δ function of a random variable which obeys Bernoulli distribution. The small gain theorem is proposed explicitly in terms of the ℋ2 norm of a involved transfer function determined by parameters of the networked system and the communication channel.
Spam detection using web page content: a new battleground

Traditional content-based e-mail spam filtering takes into account content of e-mail messages and apply machine learning techniques to infer patterns that discriminate spams from hams. In particular, the use of content-based spam filtering unleashed an unending arms race between spammers and filter developers, given the spammers' ability to continuously change spam message content in ways that might circumvent the current filters. In this paper, we propose to expand the horizons of content-based filters by taking into consideration the content of the Web pages linked by e-mail messages. We describe a methodology for extracting pages linked by URLs in spam messages and we characterize the relationship between those pages and the messages. We then use a machine learning technique (a lazy associative classifier) to extract classification rules from the web pages that are relevant to spam detection. We demonstrate that the use of information from linked pages can nicely complement current spam classification techniques, as portrayed by SpamAssassin. Our study shows that the pages linked by spams are a very promising battleground.