Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Internet services in IP over ATM networks

This paper presents a trace-driven analysis of IP over ATM services from a user-perceived quality of service standpoint. QoS parameters such as the sustained throughput for transactional services and other ATM layer parameters such as the burstiness (MBS) per connection are derived. On the other hand, a macroscopic analysis that comprises percentage of flows and bytes per service, TCP transaction duration and mean bytes transferred in both directions is also presented. The traffic trace is obtained with novel measurement equipment that combines header extraction hardware and a high-end UNIX workstation capable of providing a timestamp accuracy in the order of microseconds. The ATM link under analysis concentrates traffic from a large population of 1500 hosts from the Public University of Navarra campus network, that produced 1700000 TCP connections approximately in the measurement period of one week. The results obtained from such a wealth of data suggest that QoS is primarily determined by transport protocols and not by ATM bandwidth. The sustained throughput of TCP connections never grows beyond 80 Kbit/s with 70% probability in the data transfer phase (i.e., in the ESTABLISHED state) and we observe a strong influence of the connection establishment phase in the user-perceived throughput. On the other hand, the burstiness of individual TCP connections is rather small, namely TCP connections do not produce bursts according to the geometric law given by slow start and commonly assumed in previously published studies.
Grit, Growth Mindset, and Deliberate Practice in Online Learning.

Online education continues to grow in popularity and is an attractive option for individuals of all ages, but particularly for adults who must balance work, family, and school responsibilities. Attrition rates in online courses are high for a variety of personal and institutional reasons. Some of the personal reasons attributed to retention in online courses and degree programs focus on non-cognitive factors related to persistence, a growth mindset, and grit. Prior research has demonstrated that higher grit scores could equate to higher achievement in multiple areas of a person’s life–professionally and personally, and in academic settings. However, to mindfully improve retention of online learners, faculty need training and should implement strategies such as deliberate practice, which requires full engagement, repeated that grit, a growth mindset, and deliberate practice strategies may improve retention of online students. Identifying reasons for high attrition rates in online courses and non-cognitive traits that lead to academic success will offer a foundation for more research to identify ways to increase student persistence in online
DECOR: A Method for the Specification and Detection of Code and Design Smells

Code and design smells are poor solutions to recurring implementation and design problems. They may hinder the evolution of a system by making it hard for software engineers to carry out changes. We propose three contributions to the research field related to code and design smells: (1) DECOR, a method that embodies and defines all the steps necessary for the specification and detection of code and design smells, (2) DETEX, a detection technique that instantiates this method, and (3) an empirical validation in terms of precision and recall of DETEX. The originality of DETEX stems from the ability for software engineers to specify smells at a high level of abstraction using a consistent vocabulary and domain-specific language for automatically generating detection algorithms. Using DETEX, we specify four well-known design smells: the antipatterns Blob, Functional Decomposition, Spaghetti Code, and Swiss Army Knife, and their 15 underlying code smells, and we automatically generate their detection algorithms. We apply and validate the detection algorithms in terms of precision and recall on XERCES v2.7. 0, and discuss the precision of these algorithms on 11 open-source systems.
The Ruzsa divergence for random elements in locally compact abelian groups

Over the past few years, a family of interesting new inequali ties for the entropies of sums and differences of random variables has emerged, motivated by analogous resul ts in additive combinatorics. These inequalities were developed by Marcus, Ruzsa, Tao, Tetali and the first-named a uthor in the discrete case, and by the authors in the case of continuous random variables. The present work exten ds these earlier results to the case of random vectors taking values inR or, more generally, in arbitrary (locally compact and Polis h) abelian groups. We isolate and study a key quantity, the Ruzsa divergence between two probability distributions, and we show that its properties can be used to extend the earlier inequalities to the present gen eral setting. The new results established include several variations on the theme that the entropies of the sum and the d ifference of two independent random variables severely constrain each other. Although the setting is quite general , the result are already of interest (and new) for random vectors inR. In that special case, quantitative bounds are provided for the stability of the equality conditions in the entropy power inequality; a reverse entropy power ine quality for log-concave random vectors is proved; an information-theoretic analog of the Rogers-Shephard ineq uality for convex bodies is established; and it is observed that some of these results lead to new inequalities for the de t rminants of positive-definite matrices.
Making active-probing-based network intrusion detection in Wireless Multihop Networks practical: A Bayesian inference approach to probe selection

Practical intrusion detection in Wireless Multihop Networks (WMNs) is a hard challenge. The distributed nature of the network makes centralized intrusion detection difficult, while resource constraints of the nodes and the characteristics of the wireless medium often render decentralized, node-based approaches impractical. We demonstrate that an active-probing-based network intrusion detection system (AP-NIDS) is practical for WMNs. The key contribution of this paper is to optimize the active probing process: we introduce a general Bayesian model and design a probe selection algorithm that reduces the number of probes while maximizing the insights gathered by the AP-NIDS. We validate our model by means of testbed experimentation. We integrate it to our open source AP-NIDS DogoIDS and run it in an indoor wireless mesh testbed utilizing the IEEE 802.11s protocol. For the example of a selective packet dropping attack, we develop the detection states for our Bayes model, and show its feasibility. We demonstrate that our approach does not need to execute the complete set of probes, yet we obtain good detection rates.
Cooperative friendship networks through SLAC with Newscast

The effective cooperation and coordination of nodes is necessary for performance improvement in the P2P network. In this paper, we focus on the problem of maintaining considerable amount of cooperation and friendship in P2P networks of selfish peers. For this purpose we will analyze the performance of SLAC. It is a simple algorithm that maintains excessive levels of cooperation and friendship in a network while performing tasks. A simulation model “Prisoners' Dilemma” is presented that puts this algorithm to work in a Peersim environment. For providing random sampling, an existing protocol called “NEWSCAST” has been used. The extensive computer simulations show that the technique is scalable, robust and decentralized.
Model Checking Games for CTL

We define model checking games for the temporal logic CTL∗ and prove their correctness. They provide a technique for using model checking interactively in a verification/specification process. Their main feature is to construct paths in a transition system stepwise. That enables them to be the basis for a local model checking algorithm with a natural notion of justification. However, this requires configurations of a game to contain sets of formulas. Moreover, an additional structure on these sets, called focus, has to be used to guarantee correctness.
The Leishmania infantum Acidic Ribosomal Protein P0 Administered as a DNA Vaccine Confers Protective Immunity to Leishmania major Infection in BALB/c Mice

ABSTRACT In this study, we examined the immunogenic properties of the Leishmania infantum acidic ribosomal protein P0 (LiP0) in the BALB/c mouse model. The humoral and cellular responses induced by the administration of the LiP0 antigen, either as soluble recombinant LiP0 (rLiP0) or as a plasmid DNA formulation (pcDNA3-LiP0), were determined. Also, the immunological response associated with a prime-boost strategy, consisting of immunization with pcDNA3-LiP0 followed by a boost with rLiP0, was assayed. Immunization with rLiP0 induced a predominant Th2-like humoral response, but no anti-LiP0 antibodies were induced after immunization with pcDNA3-LiP0, whereas a strong humoral response consisting of a mixed immunoglobulin G2a (IgG2a)-IgG1 isotype profile was induced in mice immunized with the prime-boost regime. For all three immunization protocols, rLiP0-stimulated production of gamma interferon (IFN-γ) in both splenocytes and lymph node cells from immunized mice was observed. However, it was only when mice were immunized with pcDNA3-LiP0 that noticeable protection against L. major infection was achieved, as determined by both lesion development and parasite burden. Immunization of mice with LiP0-DNA primes both CD4+ and CD8+ T cells, which, with the L. major challenge, were boosted to produce significant levels of IL-12-dependent, antigen-specific IFN-γ. Taken together, these data indicate that genetic vaccination with LiP0 induces protective immunological effector mechanisms, yet the immunological response elicited by LiP0 is not sufficient to keep the infection from progressing.
Goal-directed elaboration of requirements for a meeting scheduler: problems and lessons learnt

Recently a number of requirements engineering languages and methods have flourished that not only address 'what' questions but also 'why', 'who' and 'when' questions. The objective of the paper is twofold: to assess the strengths and weaknesses of one of these methodologies on a nontrivial benchmark; and to illustrate and discuss a number of challenging issues that need to be addressed for such methodologies to become effective in supporting real, complex requirements engineering tasks. The problem considered here is that of a distributed meeting scheduler system; the methodology considered is the KAOS goal directed language and method. The issues raised from this case study include goal identification, the "deidelization" of unachievable goals, the handling of interfering goals, the impact of early formal reasoning, the merits of early reuse of abstract descriptions and categories, requirements traceability and the need to link requirements to retractable assumptions, and the potential benefits of hybrid acquisition strategies.
Humanoid and Human Inertia Parameter Identification Using Hierarchical Optimization

We propose a method for estimation of humanoid and human links' inertial parameters. Our approach formulates the problem as a hierarchical quadratic program by exploiting the linear properties of rigid body dynamics with respect to the inertia parameters. In order to assess our algorithm, we conducted experiments with a humanoid robot and a human subject. We compared ground reaction forces and moments estimated from force measurements with those computed using identified inertia parameters and movement information. Our method is able to accurately reconstruct ground reaction forces and force moments. Moreover, our method is able to estimate correctly masses of the robots links and to accurately detect additional masses placed on the human subject during the experiments.
Minkowski vacuum transitions in (nongeometric) flux compactifications

In this work we study the generalization of twisted homology to geometric and nongeometric backgrounds. In the process, we describe the necessary conditions to wrap a network of D-branes on twisted cycles. If the cycle is localized in time, we show how by an instantonic brane mediation, some D-branes transform into fluxes on different backgrounds, including nongeometric fluxes. As a consequence, we show that in the case of a IIB six-dimensional torus compactification on a simple orientifold, the flux superpotential is not invariant by this brane-flux transition, allowing the connection among different Minkowski vacuum solutions. For the case in which nongeometric fluxes are turned on, we also discuss some topological restrictions for the transition to occur. In this context, we show that there are some vacuum solutions protected to change by a brane-flux transition.
Application of New Theory in Entrepreneurship: Social Cognition

The introduction of Social Cognition Theory (SCT) widens our understanding of how individual differences may affect the individual “thinker. ” SCT states that individuals are reliant on large amounts of stored knowledge (Fiske & Taylor, 1984). SCT is appropriate for the study of entrepreneurship because it links “thinking” from within an individual to the act of “doing” (Fiske & Taylor, 1984). The basic premise of entrepreneurship is action or doing (McMullen & Shepherd, 2006b). Our perspective paper contributes to entrepreneurship literature by building upon insights gained through prior studies related to cognition and by introducing and making a compelling case about of the value of social cognition theory for deepening our understanding of entrepreneurship.
Scalable Distributed Image Transcoding Using Python-WorkQueue

Transcoding large amounts of digital media from one format to another is a common data intensive workflow. In this paper, we present a scalable image transcoding system based on Python-WorkQueue that significantly reduces the amount of time required to convert images from one format to another by mapping transcoding tasks across a distributed pool of remote workers. We test our system using a Condor cluster and varying amounts of files and number of workers. Our results show that we are able to achieve speed increases up until a certain limit.
Deeper Machine Translation and Evaluation for German

This paper describes a hybrid Machine Translation (MT) system built for translating from English to German in the domain of technical documentation. The system is based on three different MT engines (phrase-based SMT, RBMT, neural) that are joined by a selection mechanism that uses deep linguistic features within a machine learning process. It also presents a detailed source-driven manual error analysis we have performed using a dedicated “test suite” that contains selected examples of relevant phenomena. While automatic scores show huge differences between the engines, the overall average number or errors they (do not) make is very similar for all systems. However, the detailed error breakdown shows that the systems behave very differently concerning the various phenomena
Silencing Near tRNA Genes Requires Nucleolar Localization*

Transcription by RNA polymerase II is antagonized by the presence of a nearby tRNA gene in Saccharomyces cerevisiae. To test hypotheses concerning the mechanism of this tRNA gene-mediated (tgm) silencing, the effects of specific gene deletions were determined. The results show that the mechanism of silencing near tRNA genes is fundamentally different from other forms of transcriptional silencing in yeast. Rather, tgm silencing is dependent on the ability to cluster the dispersed tRNA genes in or near the nucleolus, constituting a form of three-dimensional gene control.
Bibliography of Godel ’ s Theorem Universal Turing Machine

RAID must work. After years of essential research into massive multiplayer online role-playing games, we verify t he significant unification of I/O automata and neural networks. Our focus in this position paper is not on whether the lookasi de buffer can be made pervasive, stable, and encrypted, but rat her on proposing new extensible algorithms (Taha).
A kind of generalized fuzzy C-means clustering model and its applications in mining steel strip flatness signal

In this paper, the intelligent techniques are utilized to enhance the quality control precision in the steel strip cold rolling production. Firstly, a new control scheme is proposed, establishing the classifier of the steel strip flatness signal is the basis of the scheme. The fuzzy clustering method is used to establish the classifier. Getting the high quality clustering prototypes is one of the key tasks. Secondly, a kind of new fuzzy clustering model, generalized fuzzy C-means clustering (GeFCM) model, is proposed and used as the mining tools in the real applications. The results, under the comparisons with the results obtained by the basic fuzzy clustering model, show the GeFCM is robust and efficient and it not only can get much better clustering prototypes, which are used as the classifier, but also can easily and effectively mine the outliers. It is very helpful in the steel strip flatness quality control system in one real cold rolling line. Finally, it is pointed out that the new model's efficiency is mainly due to the introduction of a set of adaptive degrees wj (j=1.n, and n is the number the data objects) and an adaptive exponent p which jointly affect the clustering operations. In nature, the proposed GeFCM model is the generalized version of the existing fuzzy clustering models.
Serpentine robots: A study of design philosophy

A number of serpentine robotic systems have been developed at various research laboratories. The ones notable among these are studied and discussed, which will provide a reasonably good insight into the various aspects of research and development in serpentine robots. The robotic systems have been studied from the point of view of their design philosophy and gait implementation techniques. Salient features of these robots are presented. Effort has been made to identify the robots that have articulation or series of rigid links connected with joints. Irrespective of their intended purpose, special attention was given to physical construction and effort has been made to classify the robots based on their locomotion mechanism, joint types and degree of freedom.
Synthesis of Facial Caricatures Using Eigenspaces and Its Applications to Humanlike Animated Agents

This paper first summarizes our unique method to synthesize facial caricatures using eigenspaces. This method can handle shape features of each facial part and arrangement features of facial parts independently. Then, in order to provide a dynamic lifelike agent based on a synthesized facial caricature, a method to represent mouth shape changes corresponding to speech and a method to give facial expressions are proposed. Here, the fact that facial features are exaggerated in facial caricatures is considered to synthesize an appropriate animation of facial caricature automatically. Experimental results show the usefulness of the proposed methods.
Adapting protocol characteristics of CoAP using sensed indication for vehicular analytics

In this paper we present a unique approach to make use of CoAP (Constrained Application Protocol) [1] from IETF (Internet Engineering Task Force) in a situation aware mode. The protocol adapts its characteristic for resource optimization depending on the indication inferred from sensed data. We consider a use-case for vehicular telemetry using a constrained in-vehicle sensor gateway which posts the vehicular information (accelerometer, GPS, device-identifier, time). In this use-case bandwidth usage is the main concern for the sensor gateway whereas usage of power which is directly impacted by overall bandwidth consumption is a key factor in case of mobile phone used as sensor gateway. We have reduced communication cost and optimized resource usage in terms of energy and bandwidth which are essential for any constrained sensor gateway by adapting characteristics of CoAP as mentioned above. The improvements are established by analyzing the data captured in real field.
Limits Laws for Geometric Means of Free Random Variables

Let $\{T_{k}\}_{k=1}^{\infty}$ be a family of *--free identically distributed operators in a finite von Neumann algebra. In this work we prove a multiplicative version of the free central limit Theorem. More precisely, let $B_{n}=T_{1}^{*}T_{2}^{*}. T_{n}^{*}T_{n}. T_{2}T_{1}$ then $B_{n}$ is a positive operator and $B_{n}^{1/2n}$ converges in distribution to an operator $\Lambda$. We completely determine the probability distribution $\nu$ of $\Lambda$ from the distribution $\mu$ of $|T|^{2}$. This gives us a natural map $\mathcal{G}:\mathcal{M_{+}}\to \mathcal{M_{+}}$ with $\mu\mapsto \mathcal{G}(\mu)=\nu. $ We study how this map behaves with respect to additive and multiplicative free convolution. As an interesting consequence of our results, we illustrate the relation between the probability distribution $\nu$ and the distribution of the Lyapunov exponents for the sequence $\{T_{k}\}_{k=1}^{\infty}$ introduced in \cite{LyaV}.
GPUDet: a deterministic GPU architecture

Nondeterminism is a key challenge in developing multithreaded applications. Even with the same input, each execution of a multithreaded program may produce a different output. This behavior complicates debugging and limits one's ability to test for correctness. This non-reproducibility situation is aggravated on massively parallel architectures like graphics processing units (GPUs) with thousands of concurrent threads. We believe providing a deterministic environment to ease debugging and testing of GPU applications is essential to enable a broader class of software to use GPUs. Many hardware and software techniques have been proposed for providing determinism on general-purpose multi-core processors. However, these techniques are designed for small numbers of threads. Scaling them to thousands of threads on a GPU is a major challenge. This paper proposes a scalable hardware mechanism, GPUDet, to provide determinism in GPU architectures. In this paper we characterize the existing deterministic and nondeterministic aspects of current GPU execution models, and we use these observations to inform GPUDet's design. For example, GPUDet leverages the inherent determinism of the SIMD hardware in GPUs to provide determinism within a wavefront at no cost. GPUDet also exploits the Z-Buffer Unit, an existing GPU hardware unit for graphics rendering, to allow parallel out-of-order memory writes to produce a deterministic output. Other optimizations in GPUDet include deterministic parallel execution of atomic operations and a workgroup-aware algorithm that eliminates unnecessary global synchronizations. Our simulation results indicate that GPUDet incurs only 2X slowdown on average over a baseline nondeterministic architecture, with runtime overheads as low as 4% for compute-bound applications, despite running GPU kernels with thousands of threads. We also characterize the sources of overhead for deterministic execution on GPUs to provide insights for further optimizations.
The construction and use of a general purpose synthetic program for an interactive benchmark on demand paged systems

A general purpose synthetic program may be used to good advantage in configuring a workload for use in benchmarking several machines. A good general purpose synthetic program should be able to do a variety of types of CPU and I/O processing in a variety of source languages, should be able to simulate interactive processing, and should be able to exercise the core management routines of a demand paged (virtual) system. The construction and use of a general purpose FORTRAN synthetic program is outlined, and the results of a benchmark in which it was used are given. The development of the workload used in the benchmark is also described.