Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimentations for QoS Evaluation of Publish/Subscribe Systems Deployed on Ad-hoc Network

Publish/subscribe (P/S) systems have been widely studied and applied in wired networks. However, their deployment on mobile ad hoc networks still presents a lot of challenges especially when there are quality of service (QoS) requirements. In this paper, we approach these challenges by looking first at network routing protocols. We present experimentations that allow to study the reaction of these protocols against QoS degradation that occur at the middleware layer. Based on an empirical study, we show that the routing layer is generally not aware about QoS degradations and so it does not react when they occur. Thus, a reaction in the middleware layer have to be developed in order to achieve a reasonable performance.
Prices, Liquidity, and the Information Content of Trades

We investigate the effect of asymmetric information on prices and liquidity by analyzing trades, quotes, spreads and depths. Information content should increase with trade size and the degree of information asymmetry of the trading period. Results show that price and liquidity effects are significantly associated with information content as measured by both trade size and the timing of the trade relative to information events. Results are stronger for purchases than sales. Quoted prices are better measures of information effects than transaction prices, because they control for bid-ask bounce. Finally, trades that are known a priori not to contain information have no impact on prices and liquidity, even when they are very large in size.
UTILISING SIGNAL MEASUREMENT IN BANDWIDTH RESERVATION SCHEME FOR QOS PROVISIONING IN MULTIMEDIA WIRELESS NETWORKS

Next generation multimedia wireless networks require guaranteed quality of service (QoS) over the duration of mobile connections, and also require efficient use of network resources. In this paper, bandwidth reservation scheme is proposed for QoS provisioning in multimedia wireless networks. The proposed scheme integrates user mobility information obtained by measuring Received Signal Strength (RSS) for determining the next cell the mobile user is likely to move to. Simulation results demonstrate that the proposed scheme can guarantee the required QoS requirements in terms of handoff call dropping probability and new call blocking probability while maintaining efficient use of network resources.
Requiring Multiplicity for Nondeterministic Automata

This paper is the second in a series of papers to formalize the proof presented in [1] that the set difference between NP and P is not the empty set . The critical difference between the proof presented in [1] and previous attempts at this problem is that the proof in [1] focuses on the nature of the answers to our set of problems belonging to P and NP instead of the set of problem directly. In a previous work [2] we presented a formalization of deterministic automata in terms of [1]. Here, we will begin the formalization of nondeterministic automata in terms of the structures required by [1]. Specifically, we will demonstrate that, for nondeterministic automata, at least one of the stage games for our Bayesian/Markov game will need to be noncooperative.
An Inexact Energy System Optimization Model including Environmental Constraints for Beijing, China

Planning of energy systems is confronted with dual pressures from economic development and environmental protection, and associated with various uncertainties. In this paper, an inexact energy system optimization model (IESOM) was developed, through integrating interval-parameter and mixed integer programming (IMILP) within an energy systems management framework. IESOM would minimize the total cost subject to environmental and economic constraints, and optimizes the development of the energy producing and conversion under given fuel prices, and useful energy demand,over a pre-defined time horizon. IESOM was applied to a case study of Beijing’s energy system. The results indicate that IESOM would establish an economically logical energy supply system, supporting Beijing’s rapid economic grow and get the best environmental benefits through relatively low economic costs.
Non-Interference Preserving Compilation of Android Bytecode

Android is an operating system that has been used in a majority of mobile devices. Each application in Android runs in an instance of the Dalvik virtual machine, which is a register-based virtual machine (VM). Most applications for Android are developed using Java, compiled to Java bytecode and then translated to DEX bytecode using the dx tool in the Android SDK. In this work, we aim to develop a typebased method for certifying non-interference properties of DEX bytecode, following a methodology that has been developed for Java bytecode certification by Barthe et al. To this end, we develop a formal operational semantics of the Dalvik VM, a type system for DEX bytecode, and prove the soundness of the type system with respect to a notion of non-interference. We then study the translation process from Java bytecode to DEX bytecode, as implemented in the dx tool in the Android SDK. We show that an abstracted version of the translation from Java bytecode to DEX bytecode preserves the non-interference property. More precisely, we show that if the Java bytecode is typable in Barthe et al’s type system (which guarantees non-interference) then its translation is typable in our type system. This result opens up the possibility to leverage existing bytecode verifiers for Java to certify non-interference properties of Android bytecode.
Smile detection in unconstrained scenarios using self-similarity of gradients features

Smile detection in unconstrained scenarios is a hot research topic with many real-world applications. This paper presents a new approach to practical smile detection and the primary contributions are three-fold. (1) In the image registration procedure, an eyes-mouth alignment strategy is found to be more efficient than popular eyes alignment. (2) In the feature extraction procedure, a novel feature descriptor, Self-Similarity of Gradients (GSS), is proposed and achieved good performance in comparison with baseline approaches. (3) Feature combination and multi-classifier combination strategies are adopted in experiments and excellent results are obtained. Experimental results show that the combined features (HOG+GSS) using AdaBoost+SVM achieve improved performance over state-of-the-art in the GENKI4K benchmark.
EEIA: Energy Efficient Indexed Aggregation in Smart Wireless Sensor Networks

The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network's operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach "Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.
Vectorization and Parallelization of the Adaptive Mesh Refinement N-Body Code

We describe our vectorized and parallelized adaptive mesh refinement (AMR) N-body code with shared time steps, and report its performance on a Fujitsu VPP5000 vector-parallel supercomputer. Our AMR N-body code puts hierarchical meshes recursively where higher resolution is required and the time step of all particles are the same. The parts that are the most difficult to vectorize are loops that access the mesh data and particle data. We vectorized such parts by changing the loop structure, so that the innermost loop steps through the cells instead of the particles in each cell, in other words, by changing the loop order from the depth-first order to the breadth-first order. We also parallelized our code for distributed memory machines. The important part of parallelization is data decomposition. We sorted the hierarchical mesh data by the Morton order, or the recursive N-shaped order, level by level and split and allocated the mesh data to the processors. Particles are allocated to the processor to which the finest refined cells including the particles are also assigned. Our timing analysis using Λ-dominated cold dark matter simulations shows that our parallel code speeds up almost ideally up to 32 processors, the largest number of processors in our test.
Service-Centric Networking with SCAFFOLD

Abstract : Online services are typically replicated on multiple servers in different datacenters, and have (at best) a loose association with specific end-hosts or locations. To meet the needs of these online services, we introduce SCAFFOLD--an architecture that provides flow-based anycast with (possibly moving) service instances. SCAFFOLD allows addresses to change as end-points move, in order to retain the scalability advantages of hierarchical addressing. Successive refinement in resolving service names limits the scope of churn to ensure scalability while in-band signaling of new addresses supports seamless communication as end-points move. We design, build, and evaluate a SCAFFOLD prototype that includes an end-host network stack (built as extensions to Linux and the BSD socket API) and a network infrastructure (built on top of OpenFlow and NOX). We demonstrate several applications, including a cluster of web servers, partitioned memcached servers, and migrating virtual machines, running on SCAFFOLD.
Multi-scale kernels for short utterance speaker recognition

Short utterance is a great challenge for speaker recognition, for there is very limited data can be used for training and testing. To give a robust estimation, the amount of model parameters for the short utterance should be less than that for the long utterance; however, this may impede the models descriptive capability. In this paper, we propose a multi-scale kernel (MSK) approach to solve this problem. We construct a series of kernels with different scales, and combine them through multiple kernel learning (MKL) optimization. In this way, the robustness and scalability of the model will be both enhanced. The experimental results on NIST SRE 2010 10sec- 10sec dataset show that the proposed MSK method outperforms the traditional Gaussian mixture model supervector (GSV) followed by support vector machine (SVM) method.
The location and function of NMDA receptors in cat and kitten visual cortex

The role of N-methyl-D-aspartate (NMDA) receptors in cat visual cortex was studied as a function of both layer and age by iontophoresis of the NMDA antagonist (D)-2-amino-5-phosphonovaleric acid (APV). Effects on both visual responses and spontaneous activity were observed. In superficial layers (II and III), D-APV reduced visual responses substantially at all ages. Iontophoresis of D-APV with 10 nA of ejecting current for 2–3 min was sufficient to reduce the response to approximately one third of control levels. The magnitude of the reduction did not vary with age. In granular and deep layers (IV, V, and VI), D-APV affected the visual response in young animals but only spontaneous activity in older animals. On average, visual responses were reduced to about half at 20–23 days of age and to about 75% at 4 weeks of age but in most cases were not significantly affected in adults. The rapid change in the functional effect of NMDA receptors over the third and fourth week in granular and deep layers suggests a role in development. There was a reasonable age correlation between the change in effect and the period of geniculocortical afferent segregation. Further experiments will be necessary to determine whether NMDA receptors are necessary for segregation to occur. The presence of an NMDA component to the visual response in the adult in layers II and III argues either that these layers retain some form of plasticity in the adult or that NMDA receptors play a role in the transmission of normal visual input to these layers.
A Protocol for Privacy Preserving Neural Network Learning on Horizontally Partitioned Data

This article presents a new approach for privacy preserving neural network training. Several studies have been devoted to privacy preserving supervised model learning, but little work has been done to extend neural network learning with a privacy preserving protocol. Neural networks are popular for many applications, among else those calling for a robust learning algorithm. In this study, we elaborate on privacy preserving classification as well as regression with neural networks on horizontally partitioned data. We consider a scenario of more than two parties that are semi-honest but curious. We extend the neural network classification algorithm presented by Rumelhart et al. with protocols for secure sum and secure matrix addition. The extended algorithm does not fully guarantee privacy in the sense defined by Goldreich, but we show that the information revealed is not associated to a specific party and could also be derived by juxtaposing the local data and the final model.
Processor-memory interconnections for multiprocessors

A new class of interconnection networks is proposed for processor to memory communication in multiprocessing systems. These networks allow a direct link between any processor to any memory module. The cost of these networks is considerably less than that of full crossbars. Moreover, the design and control of these networks is simple. The proposed networks and the full crossbars are analyzed with respect to the bandwidth and the cost.
Large scale geolocalization and routing experimentation with the SensLAB testbed

SensLAB's goal is to provide a very large scale open wireless sensor network testbed, by deploying 1024 nodes over 4 interconnected sites, and to offer a reference tool for the wireless sensor network community. Our demonstration purpose is to illustrate what the SensLAB1 platform offers through a case study: an animal tracking application needing routing and mobile node geolocalization. Through this example, we will show how to run an application in the large scale testbed SensLAB and some of the tools it provides to help in developing, tuning and monitoring such a large scale application.
A Novel Elastic Window for Face Detection and Recognition from Video

Since the past several years, face recognition from video has received significant attention due to wide range of commercial and law enforcement applications, such as surveillance systems, closed circuit TV (CCTV) monitoring, etc. Human face detection is the first and important task in a dynamic environment, such as video, where noise conditions, illuminations, locations of subjects and pose can vary significantly from one frame to another frame. In this paper, a novel elastic window, which does not make any assumption about the pose, expression or prior localization of a face in a video frame is presented for finding boundary of face region. The window locates the possible face boundaries by elastically expanding its size using local image gradients. Prior to this, a video-frame undergoes in several pre-processing tasks in order to remove noise, background, etc. And producing thin binary image representing only possible face boundaries and scattered noises. After detecting faces from video frames, we extract discriminant facial features from these cropped face images. A multi-class SVM is used as a classifier for face recognition based on these facial features. The proposed method was evaluated on Honda/UCSD video database and the experimental results show that the proposed method outperforms several existing video-based face recognition methods in terms of face recognition.
A ubiquitous message passing interface implementation in Java:jmpi

jmpi is a 100% Java-based implementation of the message-passing interface (MPI-1) standard jmpi comes with an efficient and effective MPI implementation in Java and supports a user-friendly Java application programming interface (API) for MPI. We present the implementation details and give some early communication benchmark performance results on a cluster of SUN UltraSparc workstations.
Model Predictive Control of Polymer Electrolyte Membrane fuel cell with dead-end anode and periodic purging

This paper proposes a model predictive control structure to attain performance requirements and to meet with actuator constraints. The goal is to maintain the differential pressure between the anode and cathode sides of a polymer electrolyte membrane fuel cell (PEMFC), at the inlet side of the stack, known as fuel overpressure, in a desired region. The effects of dynamic purging, nitrogen crossover, and load are included as disturbances. A proportional control valve is used as an actuator. Applying the pneumatic modeling technique, the behavior of a Ballard 3kW test station in a dead-end anode configuration is replicated and experimentally validated. To achieve a linear model, a nonlinear transformation is used to decompose the valve dynamic behavior. To evaluate the controller performance, numerical simulation is conducted using data from the experimental model. The results show the ability of the controller to compensate for all disturbances.
Supporting reflective practice in creativity education

In this study, we design a learning environment to foster participants' creative attitude and evaluate its effectiveness in a university class. Our educational program consists of the following three phases: (1) introduction (studying the basics of Mindstorms used as a tool), (2) creative activities (producing playground equipment using Mindstorms), and (3) self-reflective activities on the creative processes (each group constructing a diagram describing their own creative processes and discussing the processes). We evaluate the effectiveness based on comparisons of pre- and post-tests and the contents of the participants' discussions. In particular, we confirm the following three learning activities: (1) the participants discussed their creative activities from various viewpoints, (2) they also discussed the viewpoints considered to be important for creative activities, and (3) they realized the importance of idea generation, idea embodiment, and collaboration in creative activities.
Propagation of high-energy cosmic rays in extragalactic turbulent magnetic fields: resulting energy spectrum and composition

We extend previous studies of mixed-composition extragalactic cosmic-ray source models, investigating the influence of a nonnegligible extragalactic magnetic field on the propagated cosmic-ray spectrum and composition. We study the transport of charged particles in turbulent fields and the transition from a ballistic to a diffusive propagation regime. We introduce a method allowing a fast integration of the particle trajectories, which allows us to calculate extragalactic cosmic-ray spectra in the general case, without using either the diffusive or the rectilinear approximation. We find that the main features of the mixed-composition models – regarding the interpretation of the ankle and the non-monotonous evolution of the average cosmic-ray mass – remain essentially unchanged as long as the magnetic field intensity does not exceed a few nG.
Visual programming for robot control

The primary advantage of visual programming languages is that they directly represent the structure of algorithms and data, thereby enhancing the programmer's ability to build and comprehend programs. If the programming domain consists of physical objects with observable behaviour, such as a robot and its environment, then incorporating the obvious visual representations of these objects directly into the programming process may further increase the programmer's effectiveness and accuracy. We propose a robot programming system consisting of two parts; a definition module with which to describe the structure, function and visual representation of a specific robot, and a programming module that uses this description to enable programming by direct manipulation. We describe the visual editors that constitute the first of these modules, discuss the underlying structure generated by it, and briefly show how this structure can be used in the second module.
Concomitant stress potentiates the preference for, and consumption of, ethanol induced by chronic pre-exposure to ethanol

Ethanol abuse is linked to several acute and chronic injuries that can lead to health problems. Ethanol addiction is one of the most severe diseases linked to the abuse of this drug. Symptoms of ethanol addiction include compulsive substance intake and withdrawal syndrome. Stress exposure has an important role in addictive behavior for many drugs of abuse (including ethanol), but the consequences of stress and ethanol in the organism when these factors are concomitant results in a complex interaction. We investigated the effects of concomitant, chronic administration of ethanol and stress exposure on the withdrawal and consumption of, as well as the preference for, ethanol in mice. Male Swiss mice (30–35 g, 8-10 per group) were exposed to an ethanol liquid diet as the only source of food for 15 days. In the final 5 days, they were exposed to forced swimming stress. Twelve hours after removal of the ethanol liquid diet, animals were evaluated for ethanol withdrawal by measuring anxiety-related behaviors and locomotor activity. Twenty-four hours after evaluation of ethanol withdrawal, they were evaluated for voluntary consumption of ethanol in a “three-bottle choice” paradigm. Mice exposed to chronic consumption of ethanol had decreased locomotor activity during withdrawal. Contrary to our expectations, a concomitant forced swimming stress did not aggravate ethanol withdrawal. Nevertheless, simultaneous ethanol administration and stress exposure increased voluntary consumption of ethanol, mainly solutions containing high concentrations of ethanol. These results showed that stressful situations during ethanol intake may aggravate specific addiction-related behaviors.
Innate immune recognition of breast tumor cells mediates CCL22 secretion favoring Treg recruitment within tumor environment

Regulatory T cells (Treg) have been reported of poor prognosis for overall survival in primary breast tumors (BT). As CCL22 plays a major role in Treg recruitment within primary BT we deciphered the mechanisms involved in the CCL22 production by breast epithelial tumor cells and propose herein the major role of their innate immune recognition in this production.
" Placer " " Shooter " " Blocker " " Defender " Active behavior Passive behavior

The multi-agent paradigm is widely used to provide solutions to a variety of organizational problems related to the collective achievement of one or more tasks. All these problems share a common difficulty of design: how to proceed from a global specification of the collective task to the specification of the local behaviors, which are to be provided to the agents? We have defined the Cassiopeia method whose specificity is to articulate the design of a multi-agent system around the notion of organization. This paper reports the use of this method for designing and implementing the organization of a soccer robot team. We show why we chose this application and how we designed it, we discuss its interest and inherent difficulties, in order to clearly express the needs for a design methodology dedicated to DAI.