Miracle-dz/UniFAR-FTUs huggingface dataset:
AUTONOMOUS ROCK ACQUISITION

In order to perform efficient, robust planetary exp loration with robotic systems that use manipulation during s cience experiments, we will be increasingly reliant on veh iclebased autonomous and semi-autonomous control modali ties. Planned lander and rover missions to Mars will requ ire manipulative capabilities for placing science equip ment and acquiring geological samples. As an Earth-based op erator can only communicate with the system periodically a nd therefore is limited to making only high level comm ands, we must rely on local autonomies in the system to intelligently carry out the desired actions. This p aper describes an experimental system and ongoing resear ch for developing strategies for autonomous behavior media t by humans at a great distance. This paper is not inte nded to present any one aspect of our work in a highly theo retical or rigorous way; rather we give an overview of our wor k and communicate insights into the challenges we have fa c d over the past few years.
Optimization of ECG Classification by Means of Feature Selection

This study tackles the ECG classification problem by means of a methodology, which is able to enhance classification performance while simultaneously reducing the computational resources, making it specially adequate for its application in the improvement of ambulatory settings. For this purpose, the sequential forward floating search (SFFS) algorithm is applied with a new criterion function index based on linear discriminants. This criterion has been devised specifically to be a quality indicator in ECG arrhythmia classification. Based on this measure, a comprehensive feature set is analyzed with the SFFS algorithm, and the most suitable subset returned is additionally evaluated with a multilayer perceptron (MLP) to assess the robustness of the model. Aiming at obtaining meaningful estimates of the real-world performance and facilitating comparison with similar studies, the present contribution follows the Association for the Advancement of Medical Instrumentation standard EC57:1998 and the same interpatient division scheme used in several previous studies. Results show that by applying the proposed methods, the performance obtained in similar studies under the same constraints can be exceeded, while keeping the requirements suitable for ambulatory monitoring.
New Approximate Graph Matching andMaximum cut ?

For a graph G with e edges and n vertices, and w(E) as a total edge weight, a maximum cardinality matching (MCM) (resp. maximum weighted matching (MWM)) of G is a maximum subset M of edges (resp. a subset M of edges with a maximum edge weight) such that no two edges of M are incident at a common vertex. The best known algorithm for solving the MCM problem in general graphs (resp. the MWM problem in bipartite graphs) requires O(n 5=2) time (resp. O(n(e + n log n)) time). We rst propose an approximate MCM algorithm that runs in O(e + n) sequential time yielding a matching of size at least e n? 1. Next, the proposed MCM algorithm is extended to the weighted case running in O(e + n) time, yielding the size of at least w(E) n? 1 , when n is even. When n is odd, the lower bound obtained is w(E)? w(Iv) n? 2 , where w(Iv) is the weight on edges incident to vertex v which is minimum over considering all vertices. The results improve the bound known before. The proposed algorithms are extremely simple, and the derived lowerbounds are existentially tight. Based on the approximate MCM technique, we nd an O(e + n) time approximation algorithm for the maximum cut (MAXCUT) problem which nds a cut of size at least b en 2(n? 1) c for general graphs (when n is even). The problem of approximate MWM has a number of applications, as well as MAXCUT problem, for example in, Vertex Cover and TSP. Both approximate maximum matching and MAXCUT has an important application in VLSI designs that require very fast estimation (or near-optimal solution) in early design stages.
1 Major Research Results 1 . 1 Polynomial Factorization

In the following the EKbib and BASE URL is https:// users.cs. duke.edu/~elk27/bibliography/. The COURSEBASE URL is https://kaltofen.math.ncsu. edu/courses/. Many of my publications are accessible through links in the Reference section of both the web BASE/index.html and this pdf document. In general, the URLs of the pdf or gzipped postscript files of my papers are EKbib/y/l.pdf or EKbib/y/l.ps. gz, where y is the year of publication (last two digits) and l is the citation key in the BASE/kaltofen.bib file (replacing colons with underscores for compatibilty with Microsoft Windows). The items thus retrieved are copyrighted by the publishers or by E. Kaltofen.
Arabic Interface Analysis Based on Cultural Markers

This study examines the Arabic interface design elements that are largely influenced by the cultural values. Cultural markers are examined in websites from educational, business, and media. Cultural values analysis is based on Geert Hofstede’s cultural dimensions. The findings show that there are cultural markers which are largely influenced by the culture and that the Hofstede’s score for Arab countries is partially supported by the website design components examined in this study. Moderate support was also found for the long term orientation, for which Hoftsede has no score.
Multiscale Entropy Analysis of Different Spontaneous Motor Unit Discharge Patterns

This study explores a novel application of multiscale entropy (MSE) analysis for characterizing different patterns of spontaneous electromyogram (EMG) signals including sporadic, tonic and repetitive spontaneous motor unit discharges, and normal surface EMG baseline. Two algorithms for MSE analysis, namely, the standard MSE and the intrinsic mode entropy (IMEn) (based on the recently developed multivariate empirical mode decomposition method), were applied to different patterns of spontaneous EMG. Significant differences were observed in multiple scales of the standard MSE and IMEn analyses (<;i>p<;/i> <; 0.001) for any two of the spontaneous EMG patterns, while such significance may not be observed from the single-scale entropy analysis. Compared to the standard MSE, the IMEn analysis facilitates usage of a relatively low scale number to discern entropy difference among various patterns of spontaneous EMG signals. The findings from this study contribute to our understanding of the nonlinear dynamic properties of different spontaneous EMG patterns, which may be related to spinal motoneuron or motor unit health.
Metabolic Syndrome Augments the Risk of Early Neurological Deterioration in Acute Ischemic Stroke Patients Independent of Inflammatory Mediators: A Hospital-Based Prospective Study

Background and Aims. Metabolic syndrome (MetS) has been associated with occurrence and prognosis of ischemic stroke. This study aimed to evaluate whether an association exists between MetS and early neurological deterioration (END) following acute ischemic stroke and the possible role inflammatory biomarkers play. Methods and Results. We conducted a prospective cohort investigation that involved 208 stroke patients within 48 hours from symptom onset. MetS was determined by the modified National Cholesterol Education Program/Adult Treatment Panel III criteria. END was defined as an increase of ⩾1 point in motor power or ⩾2 points in the total National Institutes of Health Stroke Scale (NIHSS) score within 7 days. Univariate logistic regression analysis showed that patients with MetS had a 125% increased risk of END (OR 2.25; 95% CI 1.71–4.86, P = 0.005). After adjustment for fibrinogen and high-sensitivity C-reactive protein, MetS remained significantly correlated to END (OR 2.20; 95% CI 1.10–4.04, P = 0.026) with a 77% elevated risk per additional MetS trait (OR 1.77; 95% CI 1.23–2.58, P = 0.002). Conclusions. This study demonstrated that MetS may be a potential predictor for END after ischemic stroke, which was independent of raised inflammatory mediators.
Eliciting evaluative comments from users in web 2.0 scenarios

In recent years, we've seen a huge growth in the level of user-supplied reviews posted online. These reviews range from feedback on eBay or comments on sites such as YouTube, to social bookmarking sites like StumbleUpon that allow users to comment on almost any page on the web. I'm interested in how these comments are incorporated into evaluative judgements by the users that read them, and how we can improve them through better user interfaces in order to maximise their value to other users. The work draws on psychology and neurology, as well as ideas around credibility from information science, to design and test the impact of intelligent interface changes and behaviour on review composition and ascertain how the composition of a review can make it more or less useful.
Plasma Proteome Profiles Associated with Diet-Induced Metabolic Syndrome and the Early Onset of Metabolic Syndrome in a Pig Model

Obesity and related diabetes are important health threatening multifactorial metabolic diseases and it has been suggested that 25% of all diabetic patients are unaware of their patho-physiological condition. Biomarkers for monitoring and control are available, but early stage predictive biomarkers enabling prevention of these diseases are still lacking. We used the pig as a model to study metabolic disease because humans and pigs share a multitude of metabolic similarities. Diabetes was chemically induced and control and diabetic pigs were either fed a high unsaturated fat (Mediterranean) diet or a high saturated fat/cholesterol/sugar (cafeteria) diet. Physiological parameters related to fat metabolism and diabetes were measured. Diabetic pigs' plasma proteome profiles differed more between the two diets than control pigs plasma proteome profiles. The expression levels of several proteins correlated well with (patho)physiological parameters related to the fat metabolism (cholesterol, VLDL, LDL, NEFA) and diabetes (Glucose) and to the diet fed to the animals. Studying only the control pigs as a model for metabolic syndrome when fed the two diets showed correlations to the same parameters but now more focused on insulin, glucose and abdominal fat depot parameters. We conclude that proteomic profiles can be used as a biomarker to identify pigs with developing metabolic syndrome (prediabetes) and diabetes when fed a cafeteria diet. It could be developed into a potential biomarkers for the early recognition of metabolic diseases.
Developing a learner-centered criteria to assessing group activities in blended learning environments

Since the appearance of learning management systems, establishing a fair and precise mechanism to assess learning activities has been a challenging issue. Evaluation of group's work in blended learning environments which these systems are used can be a more complicated task due to implicit factors affecting result of final group's work, like degree of members' enthusiasm or their social relations (namely, communication or negotiation between group's members known as group's dynamics). The aim of this paper is to define comprehensive criteria for assessing group learning activities, considering standard learning progress taxonomy, during blended educational courses. We proposed a framework for assessment of online learning groups with respect to three major activities namely, forums, wikis and messaging. We measured correlation between performing these activities and enhancing learning skills with respect to Blooms taxonomy. We considered different parts of course exams' grades to evaluate performance of students in groups considering this taxonomy. Our promising results led us to believe that applying these criteria in blended educational courses may enhance the quality of collaborative learning activities and help student to perform better in learning groups through formative assessment of groups' work.
Practical Multicast Security Architecture Using Sleep State

Multicast security researches have been going on for a decades. In representative, some standard documents have been submitted by IETF Working Group (WG) MSEC. The reason that multicast group security is more difficult than one-to-one security is because all group members must share single group key at the same time. Whenever members join and leave, the group key must be updated and distributed to all members to keep forward and backward secrecy. At this time, '1 affects n' problem occurs. For a practical multicast security service in an actual world, it is not sufficient that membership state is divided into only two parts: join and leave. This paper describes different features between multicast and multicast security, and suggests the SLEEP state for the practical multicast security service.
The Stream-based Service-Centered Calculus : a Foundation for Service-Oriented Programming

We give a formal account of SSCC, a calculus for modeling service-based systems, suitable to describe both service composition (orchestration) and the protocols that services follow when invoked (conversation). The calculus includes primitives for defining and invoking services, for isolating conversations (called sessions) among clients and servers, and for orchestrating services. The calculus is equipped with a reduction and a labeled transition semantics related by an equivalence result. SSCC provides a good trade-off between expressive power for modeling and simplicity for analysis. We assess the expressive power by modeling van der Aalst workflow patterns and an automotive case study from the European project Sensoria. For analysis, we present a simple type system ensuring compatibility of client and service protocols. We also study the behavioral theory of the calculus, highlighting some axioms that capture the behavior of the different primitives. As a final application of the theory, we define and prove correct some program transformations. These allow to start modeling a system from a typical UML Sequence Diagram, and then transform the specification to match the service-oriented programming style, thus simplifying its implementation using web services technology.
Plant Translation Factors and Virus Resistance

Plant viruses recruit cellular translation factors not only to translate their viral RNAs but also to regulate their replication and potentiate their local and systemic movement. Because of the virus dependence on cellular translation factors, it is perhaps not surprising that many natural plant recessive resistance genes have been mapped to mutations of translation initiation factors eIF4E and eIF4G or their isoforms, eIFiso4E and eIFiso4G. The partial functional redundancy of these isoforms allows specific mutation or knock-down of one isoform to provide virus resistance without hindering the general health of the plant. New possible targets for antiviral strategies have also been identified following the characterization of other plant translation factors (eIF4A-like helicases, eIF3, eEF1A and eEF1B) that specifically interact with viral RNAs and proteins and regulate various aspects of the infection cycle. Emerging evidence that translation repression operates as an alternative antiviral RNA silencing mechanism is also discussed. Understanding the mechanisms that control the development of natural viral resistance and the emergence of virulent isolates in response to these plant defense responses will provide the basis for the selection of new sources of resistance and for the intelligent design of engineered resistance that is broad-spectrum and durable.
A Review of Workflow Scheduling in Cloud Computing Environment

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. The advent of Cloud computing as a new model of service provisioning in distributed systems, encourages researchers to investigate its benefits and drawbacks in executing scientific applications such as workflows. There are a mass of researches on the issue of scheduling in cloud computing, most of them, however, are bout workflow and job scheduling. A cloud workflow system is a type of platform service which facilitates the automation of distributed applications based on the novel cloud infrastructure. The scheduling of the workflows is typically performed manually by the IT staff. The scheduling entails the selection of the services and the appropriate start time for each workflow. In this paper we have reviewed different types of workflow scheduling algorithms. The main aim of this work is to study various problems, issues and types of scheduling algorithms for cloud workflows.
New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results

Statistical selection procedures can identify the best of a finite set of alternatives, where "best" is defined in terms of the unknown expected value of each alternative's simulation output. One effective Bayesian approach allocates samples sequentially to maximize an approximation to the expected value of information (EVI) from those samples. That existing approach uses both asymptotic and probabilistic approximations. This paper presents new EVI sampling allocations that avoid most of those approximations, but that entail sequential myopic sampling from a single alternative per stage of sampling. We compare the new and old approaches empirically. In some scenarios (a small, fixed total number of samples, few systems to be compared), the new greedy myopic procedures are better than the original asymptotic variants. In other scenarios (with adaptive stopping rules, medium or large number of systems, high required probability of correct selection), the original asymptotic allocations perform better.
A New Method for Recognizing Pulse Repetition Interval Modulation

In a dense modern electronic warfare environment, there are a lot of radar signals. The identification of these radar signals is the main task of the electronic support measures systems. Pulse repetition intervals of signals received from radars can have various PRI modulations and levels. In this paper, a new method of recognizing PRI modulation type and its levels is proposed for ESM systems. The proposed method is based not only on the properties of the biased autocorrelation function of the PRI sequences but also on the development of a hierarchical clustering method for both classifying PRI modulation types and clustering the PRI levels. The performance of the proposed method has also been evaluated in a simulation scenario.
A scala-based actor-entity architecture for intelligent interactive simulations

Simulator X is a software research platform for intelligent Real-time Interactive Systems. Based on the actor model, it supports fine grained concurrency and parallelism. The architecture uses actors to realize a distributed application state and execution model which is mapped to an object-centered global and coherent world view based on entities. The architecture pays specific attention to the minimize coupling and maximize cohesion software engineering principle. Entities are associated with specific properties. These properties are realized by so called state variables. State variable access is implicitly relayed to individual actors guarding access to them. The underlying asynchronous event mechanism is based on the actors' message passing facility to provide intra- and interprocess communication. It supports typical read/write access as well as change notification and snapshot services. An extensible world interface uses a semantic annotation layer grounded into an ontology to provide a coherent world view of the distributed world state and execution model. The world interface greatly simplifies configurability and the semantic layer provides a solid foundation for incorporation of different Artificial Intelligence components. The system is implemented in Scala using the Java virtual machine. This choice additionally fosters low-level scalability, portability, and reusability. The platform is targeted at Virtual Reality, Augmented Reality, Mixed Reality, and computer games.
Guarded models for intrusion detection

Host-based intrusion detection systems that monitor an application execution and report any deviation from its statically built model have seen tremendous progress in recent years. However, the weakness of these systems is that they often rely on overly abstracted models that reflect only the control flow structure of programs, and therefore are subject to so-called â mimicry attacksâ . Authors of these models have argued that capturing more of the data flow characteristics of a program is necessary to prevent a large class of attacks, in particular, non-control-data attacks. In this paper, we present the guarded model, a novel model that addresses the various deficiencies of the state-of-the-art intrusion detection systems. Our model is a generalization of previous models that offers no false alarms, a very low monitoring overhead, and is automatically generated. Our model detects mimicry attacks by combining control flow and data flow analysis, but can also tackle the ever increasingly threatening non-control-data flow attacks. Our model is the first model built automatically by combining control flow and data flow analysis using state-of-the-art tools for automatic generation and propagation of invariants. Our model not only prevents intrusions, but allows in some cases the detection of application logic bugs. Such bugs are beyond the reach of current intrusion detection systems
Induction of Heme Oxygenase-1 Can Halt and Even Reverse Renal Tubule-Interstitial Fibrosis

Background The tubule-interstitial fibrosis is the hallmark of progressive renal disease and is strongly associated with inflammation of this compartment. Heme-oxygenase-1 (HO-1) is a cytoprotective molecule that has been shown to be beneficial in various models of renal injury. However, the role of HO-1 in reversing an established renal scar has not yet been addressed. Aim We explored the ability of HO-1 to halt and reverse the establishment of fibrosis in an experimental model of chronic renal disease. Methods Sprague-Dawley male rats were subjected to unilateral ureteral obstruction (UUO) and divided into two groups: non-treated and Hemin-treated. To study the prevention of fibrosis, animals were pre-treated with Hemin at days -2 and -1 prior to UUO. To investigate whether HO-1 could reverse established fibrosis, Hemin therapy was given at days 6 and 7 post-surgery. After 7 and/or 14 days, animals were sacrificed and blood, urine and kidney tissue samples were collected for analyses. Renal function was determined by assessing the serum creatinine, inulin clearance, proteinuria/creatininuria ratio and extent of albuminuria. Arterial blood pressure was measured and fibrosis was quantified by Picrosirius staining. Gene and protein expression of pro-inflammatory and pro-fibrotic molecules, as well as HO-1 were performed. Results Pre-treatment with Hemin upregulated HO-1 expression and significantly reduced proteinuria, albuminuria, inflammation and pro-fibrotic protein and gene expressions in animals subjected to UUO. Interestingly, the delayed treatment with Hemin was also able to reduce renal dysfunction and to decrease the expression of pro-inflammatory molecules, all in association with significantly reduced levels of fibrosis-related molecules and collagen deposition. Finally, TGF-β protein production was significantly lower in Hemin-treated animals. Conclusion Treatment with Hemin was able both to prevent the progression of fibrosis and to reverse an established renal scar. Modulation of inflammation appears to be the major mechanism behind HO-1 cytoprotection.