Miracle-dz/UniFAR-FTUs huggingface dataset:
Lazy Evaluation for Concurrent OLTP and Bulk Transactions

Existing concurrency control systems cannot execute transactions with overlapping updates concurrently. This is especially problematic for bulk updates, which usually overlap with all concurrent transactions. To solve this, we have developed a concurrency control mechanism based on lazy evaluation, which moves evaluation of operations from the writer to the reader. This allows readers to prioritize evaluation of those operations in which they are interested, without loss of atomicity of transactions. To handle bulk operations, we dynamically split large transactions into transactions on smaller parts of the data. In this paper we present an abstract lazy index structure for lazy transactions, and show how transactions can be encoded to effectively use this data structure. Moreover, we discuss evaluation strategies for lazy transactions, where trade-offs can be made between latency and throughput. To evaluate our approach, we have implemented a concurrent lazy trie, on which we performed a number of micro benchmarks.
What Makes a Good Pervasive Middleware ?

We present 3D Evaluation Model for pervasive middlewares with dimensions of Pervasive Environment specific, Quantitative and Qualitative metrics. We expect our approach is viable to evaluate pervasive middleware since it attempts to cover diverse aspects of ubiquitous computing. In this short paper, we have briefly introduced our 3D Evaluation Model and put forth this issue for open discussion in the poster session.
Autonomous Agent for DDoS Attack Detection and Defense in an Experimental Testbed

Distributed Denial of Service (DDoS) attacks impinge on the availability of critical resources in the Internet domain. The objective of this paper is to develop an autonomous agent based DDoS defense in real time without human intervention. A mathematical model based on Lanchester law has been designed to examine the strength of DDoS attack and defense group. Once attack strength is formulated efficient defense mechanism is deployed at the victim to block malicious flows. The proposed framework is validated in an experimental testbed with geographically distributed testbed nodes. From the experimental results, the strength of attack group is observed as 49%. The defense strength of Hop Count Filtering mechanism is obtained as 31.3% whereas the proposed Hybrid Model defense effectiveness is computed as 48.7%. Also, Adaptive Bandwidth Management (ABM) using fuzzy inference system provides sustainable bandwidth to legitimate users by providing low bandwidth share for attackers. The proposed autonomous agent based model defends against DDoS attack in various aspects like prevention of IP spoofing, effective bandwidth management, improvement of Quality of Service provisioning, availability of services to legitimate clients and protecting critical infrastructure points. The defense mechanism paves way to Critical Information Infrastructure Protection.
A Modelling and Optimization Framework for Real-World Vehicle Routing Problems

The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limited commodities and transportation resources, high planning complexity and the increasing cost pressure through the strong competition between logistics service providers make it essential to use computer-aided systems for the planning of the transports. An important subtask in this context is the operational planning of trucks or other specialized transportation vehicles. These optimization tasks are called Vehicle Routing Problems (VRP). Over 1000 papers about a huge variety of Vehicle Routing Problems indicate the practical and theoretical importance of this NP-hard optimization problem. Therefore, many specific solvers for different Vehicle Routing Problems can be found in the literature. The drawback is that most of these solvers are high specialized and inflexible and it needs a lot of effort to adapt them to modified problems. Additionally, most real world problems are often much more complex than the idealized problems out of literature and they also change over time. To face this issue, we present an integrated modelling and optimization framework for solving complex and practical relevant Vehicle Routing Problems. The modular structure of the framework, a script based modelling language, a library of VRP related algorithms and a graphical user interface give the user both reusable components and high flexibility for rapid prototyping of complex Vehicle Routing Problems.
Practical Experiences in Trading Off Ontology Usability and Reusability

This paper describes the practical application of ontologies in designing knowledge-based systems. We built a common ontology to allow knowledge sharing among several applications in the domain of air campaign planning. In trying to reuse this shared ontology, we confirmed previous findings in the knowledge acquisition literature: it is difficult to simultaneously obtain high usability (i.e., adequacy for a specific use) and reusability (i.e., adequacy for several uses). In this article, we discuss some of the reasons for this trade-off, and present some lessons learned about the limitations of current tools for ontology construction in practical applications.
An evaluation of the most important competitive analysis methods applied by global mining firms to determine the future intent of a competitive force : research article

Global mining firms make an important contribution to employment opportunities, the gross domestic product and export earnings in the South African economy. Various macro-environmental influences have created a dynamic and turbulent competitive environment for the global mining industry. The complex nature of this environment requires increased strategic flexibility, speed and innovation to manage environmental discontinuities and unpredictable changes for the creation or maintenance of any competitive advantage. Remaining informed about events in the external environment becomes an absolute imperative. A purposeful, continuous analysis of the competitive environment is imperative in order to make strategic decisions for survival and growth in the turbulent mining industry. The question is what methods of competitive analysis are applied by mining firms and whether these methods offer sufficient insight into the competitive environment to make sound strategic decisions. In an empirical study, global mining firms indicated that they mostly apply financial analysis, competitor analysis, scenario analysis and SWOT analysis as competitive analysis techniques. In this article, these four methods are qualitatively evaluated for their appropriateness as competitive advantage techniques. It was found that competitor analysis is one of the best methods of competitive analysis. Financial analysis, scenario analysis and SWOT analysis have value if they are used as part of a wider analysis. It can therefore be concluded that global mining firms, to some extent, apply useful techniques in the analysis of a competitive force.
An adaptive redundancy technique for wireless indoor multicasting

We present an adaptive technique that combines forward error correction (FEC) with channel state estimation (CSE) and automatic repeat request (ARQ) for packet loss recovery in wireless indoor multicast systems. The novel aspect of the technique is its ability to achieve significant packet throughput with high data reliability, to avoid feedback acknowledgement (ACK) implosion, as well as to reduce and flexibly to limit delay for real-time applications. We suggest a set of criteria to measure the multicast performance and simulate a simple two-state indoor channel model. The simulation results show that the proposed technique significantly improves the communication quality and channel efficiency, to compare with traditional FEC and ARQ techniques.
Topological Changes in Scale Space as a Function of Image Transformations Comparing Diierent Stability Criteria

To provide a basis for the registration of medical images we search for reliable feature points using a scale-space approach. The features are deened by diierential invariants at increasing scales and their extraction is based on iso-surface techniques. We investigate some topological changes of orbits which can be observed as a result of image transformations. We also examine whether features, stable at multiple scales, are also stable with respect to various types of transformations. Thus we can compare the usefulness of diierent stability criteria for registration. We present statistical results showing the dependency on the type and strength of the transformation and also on the scale parameters.
Using the Natural Gradient for training Restricted Boltzmann Machines

Restricted Boltzmann Machines are difficult to train: Only an approximation of the gradient of the objective function is available. The objective function itself is intractable. Therefore most of the efficient convex optimisation techniques such as conjugate gradient descent or line search methods cannot be used. Using second order information is also not easy: evaluating the Hessian or an approximation of the Hessian is hard, and even if the Hessian is available, the dimensionality is usually too high to allow for inversion of the Hessian. Therefore RBMs are usually trained by stochastic gradient ascent, using a rough approximation of the gradient obtained by Gibbs sampling. It is known that learning by stochastic gradient ascent can be improved by including the covariance between stochastic gradients. However, this requires inverting a covariance matrix of size proportional to the dimensionality of the gradient. Recently, a new efficient approximate natural gradient method has been proposed. This method has shown to signi cantly improve training of ANNs, but hasn’t been tried on RBMs yet. In this report I will show that natural learning can indeed improve the training of RBMs during the convergence phase. However, natural learning methods can lead to instabilities and very slow initial learning. If natural learning is to be used, it should not be used for the initial training phase. I will also describe how estimating the partition function by Annealed Importance Sampling (AIS) can lead to overly optimistic estimations of the data log-likelihood and develop some ideas how the estimation error may be kept small.
Dose‐ and time‐dependent oval cell reaction in acetaminophen‐induced murine liver injury

We examined the response of murine oval cells, that is, the putative liver progenitor cells, to acetaminophen. Female C57BL/6J mice were injected intraperitoneally with varying doses of N‐acetyl‐paraaminophen (APAP) (250, 500, 750, and 1,000 mg/kg of weight) and sacrificed at 3, 6, 9, 24, and 48 hours. In preliminary studies, we showed that anticytokeratin antibodies detected A6‐positive cells with a sensitivity and specificity of greater than 99%. The oval cell reaction was quantified, on immunostaining for biliary‐type cytokeratins, as both number and density of oval cells per portal tract, analyzed by size of portal tract. Acetaminophen injury was followed by periportal oval cell accumulation displaying a moderate degree of morphological homogeneity. Oval cell response was biphasic, not temporally correlating with the single wave of injury seen histologically. Increases in oval cells were largely confined to the smallest portal tracts, in keeping with their primary derivation from the canals of Hering, and increased in a dose‐dependent fashion. The timing of the two peaks of the oval cell reaction also changed with increasing dose, the first becoming earlier and the second later. In conclusion, our studies indicate a marked oval cell activation during the height of hepatic injury. Oval cells appear to be resistant to acetaminophen injury. The close fidelity of mechanism and histology of acetaminophen injury between mouse and human livers makes it a useful model for investigating liver regeneration and the participation of stem/progenitor cells in that process. (HEPATOLOGY 2005.)
Sampling and Reconstruction of Periodic Piecewise Polynomials Using Sinc Kernel

We address a problem of sampling and reconstructing periodic piecewise polynomials based on the theory for signals with a finite rate of innovation (FRI signals) from samples acquired by a sinc kernel. This problem was discussed in a previous paper. There was, however, an error in a condition about the sinc kernel. Further, even though the signal is represented by parameters, these explicit values are not obtained. Hence, in this paper, we provide a correct condition for the sinc kernel and show the procedure. The point is that, though a periodic piecewise polynomial of degree R is defined as a signal mapped to a periodic stream of differentiated Diracs by R+1 time differentiation, the mapping is not one-to-one. Therefore, to recover the stream is not sufficient to reconstruct the original signal. To solve this problem, we use the average of the target signal, which is available because of the sinc sampling. Simulation results show the correctness of our reconstruction procedure. We also show a sampling theorem for FRI signals with derivatives of a generic known function.
Multi-Level Service Composition in Supervised Cloud Computing

T he role of AN agent system in an exceedingly cloud network is to spot the simplest obtainable resources and share them through a service created accessible over the net. Hence they act as inter-mediator for providing cloud services to varied users. The cloud service customers determine numerous service compositions through service discovery channels and move with service suppliers on numerous parameters to finish up with a negotiation. Our projected system focuses on planning such a supervised cloud computing design between cloud service customers and cloud service suppliers, with the service negotiation supported multiple factors together with service avails, turnout (capability of process multiple shopper requests in parallel), service delay, error, rate and value.
Minimum-Cost Multicast over Coded Packet Networks

Streaming data to di↵erent receivers from a single source is a very common scenario. In general this would be achieved by using single source multicast, for which finding the most cost-ecient paths is very hard as it has to be computed in a centralized manner and is only a↵ordable for little networks since it is not solvable in polynomial time. Although today’s networks use e.g. heuristics to quickly find sub-optimal solutions to transmit data from one source to multiple receivers, it would be nice to find even better solutions in less time. However, changing the problem a little bit might help. Although routers are currently only able to forward and copy packets, there is no reason to limit them to only those functionalities. Having a network of routers capable of network coding ‐ meaning being able to apply an arbitrary causal function on multiple incoming packets, resulting in one outgoing packet ‐ can change this. This work gives an introduction to finding optimal cost solutions for multicast in a coded packet network, and shows that finding these solutions is possible in a decentralized manner resulting in only polynomial e↵ort to calculate.
Modeling Data Correspondence in Multidatabase Systems

An essential part of a multidatabase system is a model which is able to incorporate diier-ent database schemas. This model must be capable of relating the concepts within the shared local data. The relationships which may be included may be as straightforward as a syntax conversion or as complex as conditional attribute equivalence. Moreover, the model should allow queries to be done at the local level while still being guided at the global level. This paper presents an object oriented graph as one such model. The local database concepts and the object oriented graph concepts are re-lated/linked by annotated edges which are used to algorithmically transform one local query into a series of other local subqueries. Thus, this integration method provides a method for model-ing data correspondences across a variety of data models.
Constraining the Lifetime of Circumstellar Disks in the Terrestrial Planet Zone: A Mid-Infrared Survey of the 30 Myr old Tucana-Horologium Association

We have conducted an N-band survey of 14 young stars in the ~30 Myr old Tucana-Horologium association to search for evidence of warm, circumstellar dust disks. Using the MIRAC-BLINC camera on the Magellan I (Baade) 6.5 m telescope, we find that none of the stars have a statistically significant N-band excess compared to the predicted stellar photospheric flux. Using three different sets of assumptions, this null result rules out the existence of the following around these post-T Tauri stars: (1) optically thick disks with inner hole radii of ≲0.1 AU, (2) optically thin disks with masses of less than 10-6 M⊕ (in ~1 μm sized grains) within ≲10 AU of these stars, and (3) scaled-up analogs of the solar system zodiacal dust cloud with more than 4000 times the emitting area. Our survey was sensitive to dust disks in the terrestrial planet zone with fractional luminosity of log(Ldust/L*) ~ 10-2.9, yet none were found. Combined with results from previous surveys, these data suggest that circumstellar dust disks become so optically thin as to be undetectable at N band before age ~20 Myr. We also present N-band photometry for several members of other young associations and a subsample of targets that will be observed with the Spitzer Space Telescope by the Formation and Evolution of Planetary Systems Legacy Science Program. Finally, we present an absolute calibration of MIRAC-BLINC for four filters (L, N, 11.6, and Qs) on the Cohen-Walker-Witteborn system.
Emergence of Virtual Reality as a Tool for Upper Limb Rehabilitation: Incorporation of Motor Control and Motor Learning Principles

The primary focus of rehabilitation for individuals with loss of upper limb movement as a result of acquired brain injury is the relearning of specific motor skills and daily tasks. This relearning is essential because the loss of upper limb movement often results in a reduced quality of life. Although rehabilitation strives to take advantage of neuroplastic processes during recovery, results of traditional approaches to upper limb rehabilitation have not entirely met this goal. In contrast, enriched training tasks, simulated with a wide range of low- to high-end virtual reality–based simulations, can be used to provide meaningful, repetitive practice together with salient feedback, thereby maximizing neuroplastic processes via motor learning and motor recovery. Such enriched virtual environments have the potential to optimize motor learning by manipulating practice conditions that explicitly engage motivational, cognitive, motor control, and sensory feedback–based learning mechanisms. The objectives of this article are to review motor control and motor learning principles, to discuss how they can be exploited by virtual reality training environments, and to provide evidence concerning current applications for upper limb motor recovery. The limitations of the current technologies with respect to their effectiveness and transfer of learning to daily life tasks also are discussed.
Multi-level Europeans. The Influence of Territorial Attachments on Political Trust and Welfare Attitudes

This study explores if the multi-level system in Europe can be seen as challenging both traditional state roles and the European integration process, since territorial identity by some is expected to be important for legitimacy and solidarity. The author argues the relevance of taking into account all levels of the multi-level system and shifting the focus from the level of the system to the individuals who live in it, and therefore investigates the influence of individuals’ territorial attachments on political trust and welfare attitudes. Incorporating theoretical insights from various research disciplines, three challenges are put forward concerning 1) multi-level territorial attachments, 2) their effect on political trust, and 3) the effect on welfare attitudes. Moreover, these relationships may be influenced by different institutional contexts. Empirically, these challenges are investigated by analyzing two different types of data sets, combining comparative opinion data from all the EU member states with more detailed data from Sweden. The results indicate that neither the territorial attachments themselves, nor their impact on political trust, constitute a challenge to the role of the state (or to the continuation of European integration). Rather, the European multi-level system seems to have enhanced both attachment to and trust in a number of territorial levels, including the states and the EU. However, the relationship between multi-level territorial attachments and welfare attitudes is of more concern, with possible difficulties to sustain support for the welfare state if the majority of people would have strong attachments to territorial levels other than the state. Moreover, there is no indication of a demand for a “social Europe”. In this regard, the European multi-level system may challenge the traditional role of the (welfare) state, but without offering any immediate alternative at the European level. Finally, the results indicate the relevance of taking into account the institutional context, not least regarding the variation of EU member states’ experience of the multi-level system.
MoViTo: a Generic Visualization Tool for Mobility Analysis

This paper describes the design and implementation of MoViTo (mobility visualization tool) a generic visualization tool developed mainly to facilitate the observation and the understanding of mobility patterns in wireless networks. As an example, a WiFi environment has been chosen to display the usage of this tool but other context (such as ad-hoc networks) can be studied by adapting its generic entities (nodes, links, and graphics) and input data trace (e.g. signal strength instead of event log) to each situation. The starting point of our study is an overview of the literature on the field of mobility analysis in mobile telecommunication systems. These researches show the importance of understanding wireless usage and provide some related measurements. However, the interpretation of the results of purely statistical nature still remains difficult. For this reason we think that a visualization tool may be a fast and efficient way for characterizing the usage in such environment. Among our goals, we wish to develop an open tool, capable to be adapted to several contexts and to produce an easy interpretable dashboard. The monitoring can be focused on several parameters. For example it is possible to examine nodes moves over a given period and/or a specific geographical area. The preliminary analysis given at the end of this article relate to 21 week trace of a WiFi corporate network used by more than 240 employees carrying various kinds of wireless devices (laptops, PDA.) and communicating (Mail, Internet, IM, etc) via 17 WiFi access points