Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical optimization of linear constraint processing

We consider the problem of solving a large number of simple systems of constraints. This problem occurs in the context of databases with very large collections of data while the constraints are over a small number of variables. The methodology we develop is based on a hierarchical evaluation of the constraints which are rst simpliied, and replaced by constraints approximating the initial ones. We focus on systems of linear constraints over the reals, which model spatial objects, and consider both geometric and topological approximations, deened with very simple constraints. We show that these constraints can be used either to solve the initial systems, or at least to lter out unsatissable systems. More generally, we consider the manipulation of the spatial objects with rst-order queries. We show how the queries can be evaluated by taking advantage of the approximations. In general, it is undecidable if a query can be completely answered on approximated data. The main contribution of the paper is the development of a set of rewriting rules, that allow the transformation of queries into equivalent ones that make use of the approximation. As usual with optimization problems, an optimal solution is out of reach, but the rules are optimal for individual operations of relational algebra. The eeciency of the technique is important for the range of applications considered, where the probability of ltering from the approximated data is very high. The technique is illustrated on a practical example.
Political Warfare in Sub-Saharan Africa: U.S. Capabilities and Chinese Operations in Ethiopia, Kenya, Nigeria, and South Africa

Abstract : Today, as in the past, the People's Republic of China (PRC) exerts influence on the African continent. Unlike the United States, which also attempts to sway African nations and people, the PRC uses an instrument of grand strategy called political warfare as its primary means of influence. What is political warfare, and how is it being employed in Africa today? How do U.S. capabilities compare to PRC operations and capabilities in Africa? This monograph answers these and other questions to inform the current national security debate among U.S. policy and decision makers. For while the struggle against international terrorism will continue indefinitely, the U.S. Government must not overlook other grand strategic challenges currently taking place around the world. The monograph explains political warfare in its historic context and offers a current definition. Simply, political warfare is a nonviolent instrument of grand strategy, involves coordinated activities, and results in tangible effects on intended targets. In operational terms, political warfare includes economic aid and development assistance, as well as training, equipping, and arming military and security forces. Exchange visits and public pronouncements are secondary political warfare operations, supporting and facilitating primary operations. Political warfare offers distinct advantages over other instruments of grand strategy, making it a desirable means of exerting influence. Vis-a-vis other instruments -- particularly military power -- political warfare is economical. Moreover, political warfare may potentially garner its wielder prestige and a positive reputation around the world. Ethiopia, Kenya, Nigeria, and South Africa are considered regional "anchor" states according to U.S. national security policy. Since 2000, the PRC has expanded political warfare operations in these four countries. This monograph presents case studies of PRC political warfare operations in these nations.
Development of Transactions Authorization Protocol for Ubiquitous Commerce Systems

Transparency in transactions can only be achieved through a controlled coordination of the real and cyber worlds. The success of Ubiquitous Commerce Systems (UCS) relies on the convergence of both worlds. The mobile devices are ubiquitous; they can be used anytime and anywhere. This poses a lot of security challenges in a ubiquitous society where business transactions will be involved. With the emergence of electronic payment and other business transaction solutions, ubiquity has the potential to make commerce freer and the transaction flows easier. However, privacy, security and mutual trust are critical to its development and use. Hence, for users of UCS services to have full confidence in the system, most especially while operating in a cashless society, absolute security must be put in place by stakeholders. This paper presents a Transactions Authorization Protocol (TAP) for the UCS. TAP is conceptualized to enhance security for UCS users. This protocol is less intrusive and it allows stage by stage authentication before final authorization of the users’ requests.
An Investigation of Machine Translation Evaluation Metrics in Cross-lingual Question Answering

Through using knowledge bases, question answering (QA) systems have come to be able to answer questions accurately over a variety of topics. However, knowledge bases are limited to only a few major languages, and thus it is often necessary to build QA systems that answer questions in one language based on an information source in another (cross-lingual QA: CLQA). Machine translation (MT) is one tool to achieve CLQA, and it is intuitively clear that a better MT system improves QA accuracy. However, it is not clear whether an MT system that is better for human consumption is also better for CLQA. In this paper, we investigate the relationship between manual and automatic translation evaluation metrics and CLQA accuracy by creating a data set using both manual and machine translations and perform CLQA using this created data set. 1 As a result, we find that QA accuracy is closely related with a metric that considers frequency of words, and as a result of manual analysis, we identify 3 factors of translation results that affect CLQA accuracy.
Autonomic Allocation of Communicating Virtual Machines in Hierarchical Cloud Data Centers

Cloud providers are typically hierarchically organized into interconnected data centers, each with a collection of racks of servers organized into clusters. The communication cost between two servers is a function of their relative location in the cloud infrastructure. Cloud consumers submit allocation requests for virtual machines, of different types and capacities, and provide an indication of the communication strength between all pairs of requested virtual machines. There is therefore a need for autonomic provisioning of virtual machines in a cloud environment. This paper formalizes the problem of finding an optimal allocation for the requested virtual machines that maximizes the cloud provider's revenue, which depends on how close the requested machines are allocated. This paper presents efficient heuristic algorithms for this NP-hard problem. Experiments show the heuristics to significantly outperform an allocation strategy that is oblivious to the communication strength between virtual machines. The proposed heuristics were also shown to generate between 80% and 90% of the optimal revenue.
Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form

The dynamic surface control (DSC) technique was developed recently by Swaroop et al. This technique simplified the backstepping design for the control of nonlinear systems in strict-feedback form by overcoming the problem of "explosion of complexity. " It was later extended to adaptive backstepping design for nonlinear systems with linearly parameterized uncertainty. In this paper, by incorporating this design technique into a neural network based adaptive control design framework, we have developed a backstepping based control design for a class of nonlinear systems in strict-feedback form with arbitrary uncertainty. Our development is able to eliminate the problem of "explosion of complexity" inherent in the existing method. In addition, a stability analysis is given which shows that our control law can guarantee the uniformly ultimate boundedness of the solution of the closed-loop system, and make the tracking error arbitrarily small.
VIRE: Sailing a Blue Ocean with Value-Innovative Requirements

Value-innovative requirements engineering guides software development organizations in creating new markets based on new product values for potential customers. Most requirements-engineering techniques and practices focus on eliciting requirements from existing, known customers. However, these techniques and practices aren't sufficient for surviving in current highly competitive markets. In particular, small organizations typically lack sufficient resources to compete effectively with large companies. W. Chan Kim and Renee Mauborgne proposed the blue-ocean strategy to create new marketplace value and so make competition irrelevant. A "blue ocean" is a potential market where competition doesn't yet exist.
Co-manipulation with multiple probabilistic virtual guides

In co-manipulation, humans and robots solve manipulation tasks together. Virtual guides are important tools for co-manipulation, as they constrain the movement of the robot to avoid undesirable effects, such as collisions with the environment. Defining virtual guides is often a laborious task requiring expert knowledge. This restricts the usefulness of virtual guides in environments where new tasks may need to be solved, or where multiple tasks need to be solved sequentially, but in an unknown order. To this end, we propose a framework for multiple probabilistic virtual guides, and demonstrate a concrete implementation of such guides using kinesthetic teaching and Gaussian mixture models. Our approach enables non-expert users to design virtual guides through demonstration. Also, they may demonstrate novel guides, even if already known guides are active. Finally, users are able to intuitively select the appropriate guide from a set of guides through physical interaction with the robot. We evaluate our approach in a pick-and-place task, where users are to place objects at one of several positions in a cupboard.
Data quality of 5 years of central norovirus outbreak reporting in the European Network for food-borne viruses.

BACKGROUND The food-borne viruses in Europe (FBVE) network database was established in 1999 to monitor trends in outbreaks of gastroenteritis due to noroviruses (NoVs), to identify major transmission routes of NoV infections within and between participating countries and to detect diffuse international food-borne outbreaks. METHODS We reviewed the total of 9430 NoV outbreak reports from 13 countries with date of onset between 1 January 2002 and 1 January 2007 for representativeness, completeness and timeliness against these objectives. RESULTS Rates of reporting ranged from a yearly average of 1.8 in 2003 to 11.6 in 2006. Completeness of reporting of an agreed minimum dataset improved over the years, both for epidemiological and virological data. For the 10 countries that provided integrated (epidemiological AND virological) reporting over the 5-year period, the completeness of the minimum dataset rose from 15% in 2003 to 48% in 2006. Two countries have not been able to combine both data types due to the structure of the national surveillance system (England and Wales and Germany). Timeliness of reporting (median days between the onset of an outbreak and the date of reporting to the FBVE database) differed greatly between countries, but gradually improved to 47 days in 2006. CONCLUSION The outbreaks reported to the FBVE reflect the lack of standardization of surveillance systems across Europe, making direct comparison of data between countries difficult. However, trends in reported outbreaks per country, distribution of NoV genotypes, and detection of diffuse international outbreaks were used as background data in acute questions about NoV illness and the changing genotype distribution during the 5-year period, shown to be of added value. Integrated reporting is essential for these objectives, but could be limited to sentinel countries with surveillance systems that allow this integration. For successful intervention in case of diffuse international outbreaks, completeness and timeliness of reporting would need to be improved and expanded to countries that presently do not participate.
A unifying framework for non-linear registration of 3D objects

An extension of our earlier work is proposed to find a non-linear aligning transformation between a pair of deformable 3D objects. The basic idea is to set up a system of nonlinear equations whose solution directly provides the parameters of the aligning transformation. Each equation is generated by integrating a nonlinear function over the object's domains. Thus the number of equations is determined by the number of adopted nonlinear functions yielding a flexible mechanism to generate sufficiently many equations. While classical approaches would establish correspondences between the shapes, our method works without landmarks. Experiments with 3D polynomial and thin plate spline deformations confirm the performance of the framework.
Mobbing and Chaotic Reflections in International Politics Documents

Mobbing is a phenomenon which has treatments of personal and economical sequels. This chapter aims to present traditional legal reflections of mobbing and educational responsibilities in this situation. Mobbing, which has been a subject of study in education, organizational treatment, the world of business and management, psychology, nursing and more, found its way in international legal documents especially after the 1990s. Mentioned laws foresee employers to have more responsibilites in terms of work conditions. It is also imperative to mention that national level of interferences has started lately. Some assumptions of Chaos Theory such as loyalty for beginning conditions and turbulance call it ambiguity to mobbing attitude, unpredictability and making a point of small situations are also discussed in this chapter.
Macropinosome maturation and fusion with tubular lysosomes in macrophages

Macropinosomes formed by addition of recombinant macrophage colony- stimulating factor (rM-CSF) to mouse macrophages migrate centripetally and shrink, remaining detectable by phase microscopy for up to 15 min. This longevity allowed us to study how macropinosomes age. Macropinosomes were pulse labeled for 1 min with fixable fluorescein dextran (FDx10f), a probe for fluid phase pinocytosis, and chased for various times. To quantify changes in their antigenic profile, pulse- labeled macropinosomes of different ages were fixed and stained for immunofluorescence with a panel of antibodies specific for the transferrin receptor (TfR), the late endosome-specific, GTP-binding protein rab 7 or lysosomal glycoprotein A (lgp-A), and the percentage of antibody positive, FDx10f-labeled macropinosomes was scored. Some newly formed macropinosomes were positive for TfR, but few were rab 7 or lgp-A-positive. With intermediate chase times (2-4 min), staining for rab 7 and lgp-A increased to > 60%, while TfR staining declined. After a long chase (9-12 min), rab 7 staining returned to low levels while lgp-A staining remained at a high level. Thus, macropinosomes matured by progressive acquisition and loss of characteristic endocytic vesicle markers. However, unlike a maturation process, their merger with the tubular lysosomal compartment more nearly resembled the incorporation of a transient vesicle into a pre-existing, stable compartment. Shortly after their formation, FDx10f-labeled macropinosomes contacted and merged with Texas red dextran (TRDx10)- labeled tubular lysosomes. This occurred in two steps: macropinosomes acquired lgp-A first, and then several minutes later the cation- independent mannose-6-phosphate receptor (CI-MPR) and markers of lysosomal content (cathepsin L or pre-loaded TRDx10), all apparently derived from tubular lysosomes. Thus, macropinosome progress through macrophages showed features of both the maturation and vesicle shuttle models of endocytosis, beginning with a maturation process and ending by merger into a stable, resident lysosomal compartment.
Towards Automatic Content-Based Separation of DJ Mixes into Single Tracks

DJ mixes and radio show recordings constitute an important and underexploited music and data source. In this paper we try to approach the problem of separation of a continuous DJ mix into single tracks or timestamping a mix. Sharing some aspects with the task of structural segmentation, this problem has a number of distinctive features that make difficulties for structural segmentation algorithms designed to work with a single track. We use the information derived from spectrum data to separate tracks from each other. We show that the metadata that usually comes with DJ mixes can be exploited to improve the separation. An iterative algorithm that can consider both content-based data and user provided metadata is proposed and evaluated on a collection of freely available timestamped DJ mix recordings of various styles.
Discrete differential operators in multidimensional Haar wavelet spaces

We consider a class of discrete differential operators acting on multidimensional Haar wavelet basis with the aim of finding wavelet approximate solutions of partial differential problems. Although these operators depend on the interpolating method used for the Haar wavelets regularization and the scale dimension space, they can be easily used to define the space of approximate wavelet solutions.
Corpus-Based Extraction of Collocations in Chinese

Collocation, i.e. the sequences of certain words which habitually co-occur, plays an essential part in human language. The present study is intending to identify the detailed classification and typical features of collocations in Chinese language, and explore a new computer-assistant way for extraction and representation of Chinese collocations. The investigation is based on the largest and only Singapore Chinese corpus (SCC), of which 20 million words have been analysed. The central novel idea of this research is the combination of dictionary, language rules and statistic data in automatic collocation extraction. So far, this method has not been proposed.
An Improved Mass-Spring Model to Simulate Draping Cloth

This paper describes a fast technique for cloth simulation based on a mass spring model. The difference is one animation process is divided to two segments which are numerical integrated together and a virtual force is added to get the rebounded animation segment. A local refinement is used to avoid the overlap of the two segments. Experiments show that this method can simulate the draping cloth efficiently and effectively.
Improving the automatic detection of design flaws in object-oriented software systems Petru

In order to increase the flexibility and extensibility of an object-oriented software system, its structural flaws have to be detected. The practice shows that the automatic approach for design flaw detection based on metrics is not very accurate. While the choice of the used metrics can be easily argued, the values for their thresholds are usually chosen based only upon the designers experience. In this paper we present a method for tuning the values of the thresholds. Experimental results are also shown in order to prove the efficiency of our method.
Transcription Factor Binding Site Detection Algorithm Using Distance Metrics Based on a Position Frequency Matrix Concept

Regulatory sequence detection is a fundamental challenge in computational biology. The transcription process in protein synthesis starts with the binding of the transcription factor (TF) to its binding site. These binding sites are short DNA segments that are called motifs. Different sites can bind to the same factor. This variability in binding sequences besides their low information content and low specificity increases the difficulty of their detection using computational algorithms. This paper proposes a novel algorithm for transcription factor binding sites (TFBSs) detection in the entire genomic structure and allow discovery of new motif sequences. This is achieved by using distance metrics based on a position frequency matrix (PFM) concept that quantify the similitude between the set of conserved sequences belonging to a particular TF and the entire DNA sequence under study. Hence, the PFM in this context can be thought of as a consensus sequence as it provides a representative measure of the said set of binding sites belonging to a particular TF. The algorithm then quantifies the correlation between the PFM and each binding site belonging to a given TF. Same scenario is then applied to the genome sequence under study. The obtained distance metrics are then utilized to discover new potential TFBSs based on their similitude of the set of binding sites investigated. Analysis is applied to Escherichia coli (E. coli) bacterial genomes. Simulation results verify the correctness and the biological relevance of the proposed algorithm.
Angle Measurement for Meter-Wave Radar Based on Mainlobe Multipath Jamming Suppression

When detecting low-attitude targets, the angular accuracy of the meter-wave radar will descend because of the multipath reflecting from ground. Since the multipath signal can be regarded as a multipath jamming coming from the mainlobe, we propose an angle measurement based on the mainlobe multipath jamming suppression. The weight of the new approach is obtained through certain constraints on the sum-difference beams, which can suppress the jamming and keep the curve of the monopulse ratio unchanged. Then form sum-difference beams and calculate the ratio of the monopulse ratio of the target. Finally, obtain the angle of the target through the determination of the smallest difference between the monopulse ratio of the target and the quiescent monopulse ratio. The method proposed in this paper can preserve good precision of the measurement angle. The result is verified by computer simulation.
A neuro-dynamic programming approach to admission control in ATM networks: the single link case

We are interested in solving large-scale Markov decision problems. The classical method of dynamic programming provides a mathematical framework for finding optimal solutions for a given Markov decision problem. However, dynamic programming algorithms become computationally infeasible when the underlying Markov decision problem evolves over a large state space. In recent years, a new methodology, called neuro-dynamic programming, has emerged which tries to overcome this "curse of dimensionality". We show how neuro-dynamic programming can be applied to the admission control problem for a single link in an ATM environment. Based on results obtained through neuro-dynamic programming, we derive a heuristic "threshold" policy. Performances of the policies obtained through neuro-dynamic programming are compared with a policy which always accepts a customer when the required resources are available.
Substrate Integrated Waveguide Cavity Resonators for Complex Permittivity Characterization of Materials

A novel planar substrate integrated waveguide cavity resonator technique for measurement of complex permittivity is described, which has applications for dielectric measurement systems in the pharmaceutical industry. The high-Q resonant structure is a modernization of well-known measurement cells where the dielectric constant is deduced by cavity perturbation from the shift in resonant frequency and the change in the Q factor. The method uses extremely small amounts of a broad range of materials for accurate characterization. The ease of fabrication, low cost, and potential for integration with many other components on the same substrate allows it to be used in a disposable manner.