Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated License Management and Economic Resource Allocation Model for Cloud Computing

Cloud computing is a recent trend in IT that moves computing and data away from desktop and portable PCs into large data centers. Cloud computing is on-demand computing in which the computing resources are owned and managed by a service provider and the users access the resources via the Internet. But cloud computing potential doesn't begin and end with the personal computer's transformation into a thin client. License management and economic resource allocation is a major issue faced by cloud computing paradigm. In this paper we propose MobiLim, a framework which addresses major problems related to license management and economic resource allocation in cloud computing. This framework named MobiLim is managed by independent software vendor (ISVs), who controls access to the resource provider resources. MobiLim provides a secure and robust license management solution as well as allocate resources economically to the customers.
Towards Adaptive Resource Allocation for Database Workloads

Modern computer systems provide hardware resources that allow database systems to execute a large number of tasks in parallel. However, no software system is perfectly scalable, and allocating more resources does not necessarily result in better performance. For commensurate resource allocation and increased efficiency, it is desirable to dynamically allocate hardware resources according to workload demands and conduct hardware consolidation. Given the complexity of database systems and their workloads, it is challenging to design such an adaptive algorithm. This paper addresses this problem using a simple feedback mechanism. The contributions of this work are twofold. First, an application-agnostic performance metric based on hardware performance counters is proposed to measure system performance online. This fine-grained metric enables agile feedback even for long running analytical workloads. Second, an allocation algorithm is presented that is designed based on fuzzy control techniques. The controller does not need a system model or prior training. Evaluation results show that a good correlation exists between the system-level metric and application-specific performance metrics. Further, a database system with our controller can achieve performance comparable to that obtained with manual tuning.
Adaptive Video Streaming in MU-MIMO Networks

We consider extensions and improvements on our previous work on dynamic adaptive video streaming in a multi-cell multiuser ``small cell'' wireless network. Previously, we treated the case of single-antenna base stations and, starting from a network utility maximization (NUM) formulation, we devised a ``push'' scheduling policy, where users place requests to sequential video chunks to possibly different base stations with adaptive video quality, and base stations schedule their downlink transmissions in order to stabilize their transmission queues. In this paper we consider a ``pull'' strategy, where every user maintains a request queue, such that users keep track of the video chunks that are effectively delivered. The pull scheme allows to download the chunks in the playback order without skipping or missing them. In addition, motivated by the recent/forthcoming progress in small cell networks (e.g., in wave-2 of the recent IEEE 802.11ac standard), we extend our dynamic streaming approach to the case of base stations capable of multiuser MIMO downlink, i.e., serving multiple users on the same time-frequency slot by spatial multiplexing. By exploiting the ``channel hardening'' effect of high dimensional MIMO channels, we devise a low complexity user selection scheme to solve the underlying max-weighted rate scheduling, which can be easily implemented and runs independently at each base station. Through simulations, we show MIMO gains in terms of video streaming QoE metrics like the pre-buffering and re-buffering times.
Topology-Independent Link Activation Scheduling Schemes for Mobile CDMA Ad Hoc Networks

In this paper, we study medium access control (MAC) protocols with quality-of-service (QoS) support, that is, topology-independent link activation transmission scheduling, for mobile code-division multiple-access (CDMA) ad hoc networks. QoS provisioning for each communication link is guaranteed without the need to adopt transmission schedules in mobile environments. An interference model, which captures the difference between transmission and interference ranges, is considered. Under this interference model, an approach to guaranteeing conflict-free transmission slots in each frame (QoS provisioning) for each communication link is proposed. Compared with the previously known method, superior performance is obtained. We then present a topology-independent link activation scheduling framework based on the theory of group-divisible (GD) designs. By the mathematical properties of GD designs, the proposed framework guarantees conflict-free transmission slots in each frame for each communication link, without the overhead due to the recomputation of transmission schedules when the network topology changes. With the proposed framework, we study and evaluate one series of GD design constructions. Based on the results derived, topology-independent link activation scheduling algorithms are then presented. The proposed schemes are designed for different objectives: maximizing the minimum system throughput and/or minimizing the schedule frame length. Numerical results show that the proposed algorithms outperform previously known schemes. The average performance of the proposed schemes is also derived.
Multimodal knowledge-based analysis in multimedia event detection

Multimedia Event Detection (MED) is a multimedia retrieval task with the goal of finding videos of a particular event in a large-scale Internet video archive, given example videos and text descriptions. We focus on the multimodal knowledge-based analysis in MED where we utilize meaningful and semantic features such as Automatic Speech Recognition (ASR) transcripts, acoustic concept indexing (i.e. 42 acoustic concepts) and visual semantic indexing (i.e. 346 visual concepts) to characterize videos in archive. We study two scenarios where we either do or do not use the provided example videos. In the former, we propose a novel Adaptive Semantic Similarity (ASS) to measure textual similarity between ASR transcripts of videos. We also incorporate acoustic concept indexing and classification to retrieve test videos, specially with too few spoken words. In the latter 'ad-hoc' scenario where we do not have any example video, we use only the event kit description to retrieve test videos ASR transcripts and visual semantics. We also propose an event-specific fusion scheme to combine textual and visual retrieval outputs. Our results show the effectiveness of the proposed ASS and acoustic concept indexing methods and their complimentary role. We also conduct a set of experiments to assess the proposed framework for the 'ad-hoc' scenario.
The Mixed Boundary Problem in L p and Hardy spaces for Laplace ’ s Equation on a Lipschitz Domain

We study the boundary regularity of solutions of the mixed problem for Laplace’s equation in a Lipschitz graph domain Ω whose boundary is decomposed as ∂Ω = N ∪ D, where N ∩ D = ∅. For a subclass of these domains, we show that if the Neumann data g is in Lp(N) and if the Dirichlet data f is in the Sobolev space L(D), for 1 < p < 2, then the mixed boundary problem has a unique solution u for which N(∇u) ∈ Lp(∂Ω), where N(∇u) is the non-tangential maximal function of the gradient of u.
Rigorously assessing software reliability and safety

This paper summarises the state of the art in the assessment of software reliability and safety ("dependability"), and describes some promising developments. A sound demonstration of very high dependability is still impossible before operation of the software; but research is finding ways to make rigorous assessment increasingly feasible. While refined mathematical techniques cannot take the place of factual knowledge, they can allow the decision-maker to draw more accurate conclusions from the knowledge that is available
Design and Deployment of a Peer-to-Peer Based IPTV System over Global Internet

IPTV is highly advocated in recent years. Today, the growth of the residential users makes it possible to broadcast live video content through global Internet to a great population of end users. In this paper, we mainly describe the design and deployment experiences of a peer-to-peer (P2P) based IPTV system called Gridmedia since P2P is universally recognized as a scalable and cost-effective means for group communication. In order to reduce the playback latency at end users as well as offer resilience to high churn rate in peer community, Gridmedia organizes end users into an unstructured overlay while proposes an efficient push-pull streaming mechanism to distribute video segments among partner nodes. To further verify the prototype, on one hand we conduct extensive experiments over PlanetLab to confirm the overlay architecture and streaming mechanism in Gridmedia can greatly reduce the average playback latency as compared to previous works; on the other hand the practical deployment of Gridmedia system over global Internet also demonstrated it could reliably support large number of users without need of network infrastructure. We also discuss, in a practical way, the issues when perfecting a prototype to a publicly released platform and system performance during live broadcasting CCTV Spring Festival Gala 2006.
Client-Centered, Energy-Efficient Wireless Communication on IEEE 802.11b Networks

In mobile devices, the wireless network interface card (WNIC) consumes a significant portion of overall system energy. One way to reduce energy consumed by a device is to transition its WNIC to a lower-power steep mode when data is not being received or transmitted. In this paper, we investigate client-centered techniques for energy efficient communication, using IEEE 802.11b, within the network layer. The basic idea is to conserve energy by keeping the WNIC in high-power mode only when necessary. We track each connection, which allows us to determine inactive intervals during which to transition the WNIC to sleep mode. Whenever necessary, we also shape the traffic from the client side to maximize sleep intervals-convincing the server to send data in bursts. This trades lower WNIC energy consumption for an increase in transmission time. Our techniques are compatible with standard TCP and do not rely on any assistance from the server or network infrastructure. Results show that during Web browsing, our client-centered technique saved 21 percent energy compared to PSM and incurred less than a 1 percent increase in transmission time compared to regular TCP. For a large file download, our scheme saved 27 percent energy on average with a transmission time increase of only 20 percent
The economics of altruism: The old, the rich, the female

ABSTRACT This study examines whether people of different observed characteristics exhibit different degree of altruism. The article utilizes a National Mental Health Survey that gathered questions about respondents’ self-reported altruism along with their demographic, labor force, and income information. The empirical results revealed the following: (1) Older people are more altruistic. This could potentially be explained by the Socioemotional Selectivity Theory (SST) that the older people shift towards emotion-related goals that can be internally rewarding in the present. (2) Higher-income people are more altruistic. This could potentially be explained by the fact that higher-income people could better afford to be more altruistic compared to lower-income people. (3) Women are more altruistic. This could potentially be explained by either biological evolution or social imposition. The main results are robust once the potential endogeneity problem of the income variable is mitigated by the use of the instrumental variable estimation method.
Exploring Heritage through time and space supporting community reflection on the highland clearances

On the two hundredth anniversary of the Kildonan clearances, when people were forcibly removed from their homes, the Timespan Heritage centre has created a program of community centred work aimed at challenging pre conceptions and encouraging reflection on this important historical process. This paper explores the innovative ways in which virtual world technology has facilitated community engagement, enhanced visualisation and encouraged reflection as part of this program. An installation where users navigate through a reconstruction of pre clearance Caen township is controlled through natural gestures and presented on a 300 inch six megapixel screen. This environment allows users to experience the past in new ways. The platform has value as an effective way for an educator, artist or hobbyist to create large scale virtual environments using off the shelf hardware and open source software. The result is an exhibit that also serves as a platform for experimentation into innovative ways of community co-creation and co-curation.
Novel closed-form ML position estimator for hyperbolic location

Geolocation of mobile terminals has become in the last decades an important issue in mobile networks. In the literature, there have been presented several closed-form position estimators based on time-difference-of-arrival (TDOA) measurements. Only Fang's estimator can be considered optimum in the maximum likelihood (ML) sense. Unfortunately, it can only be applied to the particular case of two TDOA measurements for the two dimensional (2D) location case. This paper presents an extension of this closed-form estimator to be applied to an arbitrary number of TDOA measurements by means of a transformation in the maximum likelihood function. This allows the ML function minimization to be split in several partial ML minimizations which only consider a subset of the available measurements, where the original Fang's estimator can be applied. Numerical simulations show that the proposed algorithm, that can be considered asymptotically the ML-estimator, attains the theoretical limits for all range of reasonable SNR values and has a low implementation complexity.
Entropy Based Clustering of Data Streams with Mixed Numeric and Categorical Values

In is paper, a novel algorithm for clustering data streams with mixed numeric and categorical attributes (CNC-Stream)is proposed. A new similarity measure based on entropy determining the similarity between the objects(data points in the stream or the micro- clusters in memory) is also presented here, which makes CNC-Stream work, the experiments conducted on the real data sets and synthetic data sets show that the proposed method is of high quality.
Personalizing a Universal Recurrent Neural Network Language Model with User Characteristic Features by Crowdsouring over Social Networks

With the popularity of mobile devices, personalized speech recognizer becomes more realizable today and highly attractive. Each mobile device is primarily used by a single user, so it's possible to have a personalized recognizer well matching to the characteristics of individual user. Although acoustic model personalization has been investigated for decades, much less work have been reported on personalizing language model, probably because of the difficulties in collecting enough personalized corpora. Previous work used the corpora collected from social networks to solve the problem, but constructing a personalized model for each user is troublesome. In this paper, we propose a universal recurrent neural network language model with user characteristic features, so all users share the same model, except each with different user characteristic features. These user characteristic features can be obtained by crowdsouring over social networks, which include huge quantity of texts posted by users with known friend relationships, who may share some subject topics and wording patterns. The preliminary experiments on Facebook corpus showed that this proposed approach not only drastically reduced the model perplexity, but offered very good improvement in recognition accuracy in n-best rescoring tests. This approach also mitigated the data sparseness problem for personalized language models.
Through the Looking Glass: Taking Stock of Offender Reentry

Offender reentry has been part of the fabric of the criminal justice system since the first prison opened its doors and people who went in the front door were, at some point, released. Traditionally, the research on offender reentry has either supported best practice by determining what specific individual-level programming “works” or “doesn’t work” or it has assessed the success of programs in terms of their ability to reduce recidivism. And while we may have moved the dial in the last 50 years with respect to what we know about individual-level offender reentry attributes, there is no effective overarching narrative to explain the offender reentry phenomenon. Overwhelmingly, practitioners and academics in the criminal justice system operate within a paradigm that assesses and evaluates everything using risk. Unfortunately, a risk- or deficit-focused approach to viewing offender reentry severely limits our ability to think differently about the problem. However, if we employ a paradigm for offender reentry that focuses less on problems and more on strengths, different outcomes are possible. Work done in social work that promotes “strengths-based, solution-focused, capacity building, asset creating, motivation enhancing” empowerment models that accentuate the positive serves as an exemplar for us to use in criminal justice when discussing offender reentry. The three strengths-based principles adapted to offender reentry and discussed here are as follows: Officer–offender relationships that emphasize collaboration will promote law-abiding, prosocial behavior; offenders who are empowered will be more likely to seek to change; and cooperation from the community is key to successful offender reentry. Fiscal, political, and common sense reasons for using a strengths-based approach to offender reentry are discussed.
A compiler-based infrastructure for software-protection

Not long after the introduction of stored-program computing machines, the first high-level language compilers appeared. The need for automatically and efficiently mapping abstract concepts from high-level languages onto low-level assembly languages has been recognized ever since. A compiler has a unique ability to gather and analyze large amounts of data in a manner that would be an unwieldy manual endeavor. It is this property that makes known compiler techniques and technology ideally suited for the purposes of software protection against reverse engineering and tampering attacks. In this paper, we present a code transformation infrastructure combined with build-time security techniques that are used to integrate protection into otherwise vulnerable machine programs. We show the applicability of known compiler techniques such as aliasanalysis, whole program analysis, data-flow analysis, and control-flow analysis and how these capabilities provide the basis for program transformations that provide comprehensive software protection. These methods are incorporated in an extensible framework allowing efficient development of new code transformations, as part of a larger suite of security tools for the creation of robust applications. We describe a number of successful applications of these tools.
Performance analysis of TCP in VANETs by using 802.11e

Communication in VANETS needs consideration of high mobility, congestion, collision and reliability factors. The successful delivery of important messages needs high reliability in case of TCP traffic during high congestion. Reliability and performance of priority based traffic is better than for same priority traffic and produces different results. In this paper we have analyzed the performance of TCP traffic in VANETs by using 802.11e and compared it with 802.11. Using NS2 we show that remarkable increase in the performance of TCP traffic is observed in case of 802.11e.
Signal Shaping Using Non-Unique Symbol Mappings

We obtain a shaping gain with a non-uniform probability distribution of the signal points in a high order signal constellation. To obtain non-equiprobable signal points, we assign a non-uniform amount of distinct bit labels to the signal points. The proposed method is integrated in a bit interleaved coded modulation scheme with iterative demapping and decoding (so called BICM-ID scheme). This iterative process resolves the ambiguities that arise when several bit labels are assigned to one signal point. We derive a greedy algorithm to get a close to optimum probability distribution of the signal points and we use a binary switching algorithm to optimize the bit-mapping. At a rate of 3 bits per channel use, we obtain shaping gains over 1dB for a 16ASK signal constellation. In combination with irregular convolutional codes, we achieve an iterative decoding threshold at 0.7dB below the capacity of the uniform distribution.
Profile of delamanid for the treatment of multidrug-resistant tuberculosis

New approaches to the treatment of multidrug-resistant and extensively drug-resistant tuberculosis (TB) are badly needed. Not only is the success rate of current treatment regimens suboptimal but existing regimens require multiple drugs and lengthy courses and may lead to significant toxicities. The treatment landscape is beginning to shift, however, with the recent approvals of the new TB drugs bedaquiline and delamanid. Delamanid, a dihydro-imidazooxazole, has been shown to have excellent activity against Mycobacterium tuberculosis in both in vitro and in murine TB models. It has also recently been reported to improve rates of sputum culture conversion in patients with multidrug-resistant TB when added to an optimized background regimen. Although generally well tolerated, delamanid has been associated with QT prolongation, which may be of particular clinical concern when paired with other TB drugs that may also have this effect, most notably the fluoroquinolones. Ongoing studies will help to clarify delamanid’s role in the treatment of drug-resistant TB.
Development of a Nanoelectronic 3-D (NEMO 3-D ) Simulator for Multimillion Atom Simulations and Its Application to Alloyed Quantum Dots

Material layers with a thickness of a few nanometers are common-place in today's semiconduc- tor devices. Before long, device fabrication methods will reach a point at which the other two device dimensions are scaled down to few tens of nanometers. The total atom count in such deca-nano devices is reduced to a few million. Only a small finite number of "free" electrons will operate such nano-scale devices due to quantized electron energies and electron charge. This work demon- strates that the simulation of electronic structure and electron transport on these length scales must not only be fundamentally quantum mechanical, but it must also include the atomic granularity of the device. Various el- ements of the theoretical, numerical, and software foun- dation of the prototype development of a Nanoelectronic Modeling tool (NEMO 3-D) which enables this class of device simulation on Beowulf cluster computers are pre- sented. The electronic system is represented in a sparse complex Hamiltonian matrix of the order of hundreds of millions. A custom parallel matrix vector multiply al- gorithm that is coupled to a Lanczos and/or Rayleigh- Ritz eigenvalue solver has been developed. Benchmarks of the parallel electronic structure and the parallel strain calculation performed on various Beowulf cluster com- puters and a SGI Origin 2000 are presented. The Be- owulf cluster benchmarks show that the competition for memory access on dual CPU PC boards renders the util- ity of one of the CPUs useless, if the memory usage per node is about 1-2 GB. A new strain treatment for the