3,744 research outputs found

    A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

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    For the past ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore and compare the performance of two very well known routing paradigms, directed diffusion and Energy- Aware Routing, with our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

    The Project Scheduling Problem with Non-Deterministic Activities Duration: A Literature Review

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    Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration. Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved. Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends. Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.Peer Reviewe

    Human-centered Electric Prosthetic (HELP) Hand

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    Through a partnership with Indian non-profit Bhagwan Mahaveer Viklang Sahayata Samiti, we designed a functional, robust, and and low cost electrically powered prosthetic hand that communicates with unilateral, transradial, urban Indian amputees through a biointerface. The device uses compliant tendon actuation, a small linear servo, and a wearable garment outfitted with flex sensors to produce a device that, once placed inside a prosthetic glove, is anthropomorphic in both look and feel. The prosthesis was developed such that future groups can design for manufacturing and distribution in India

    GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU

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    High-performance implementations of graph algorithms are challenging to implement on new parallel hardware such as GPUs because of three challenges: (1) the difficulty of coming up with graph building blocks, (2) load imbalance on parallel hardware, and (3) graph problems having low arithmetic intensity. To address some of these challenges, GraphBLAS is an innovative, on-going effort by the graph analytics community to propose building blocks based on sparse linear algebra, which will allow graph algorithms to be expressed in a performant, succinct, composable and portable manner. In this paper, we examine the performance challenges of a linear-algebra-based approach to building graph frameworks and describe new design principles for overcoming these bottlenecks. Among the new design principles is exploiting input sparsity, which allows users to write graph algorithms without specifying push and pull direction. Exploiting output sparsity allows users to tell the backend which values of the output in a single vectorized computation they do not want computed. Load-balancing is an important feature for balancing work amongst parallel workers. We describe the important load-balancing features for handling graphs with different characteristics. The design principles described in this paper have been implemented in "GraphBLAST", the first high-performance linear algebra-based graph framework on NVIDIA GPUs that is open-source. The results show that on a single GPU, GraphBLAST has on average at least an order of magnitude speedup over previous GraphBLAS implementations SuiteSparse and GBTL, comparable performance to the fastest GPU hardwired primitives and shared-memory graph frameworks Ligra and Gunrock, and better performance than any other GPU graph framework, while offering a simpler and more concise programming model.Comment: 50 pages, 14 figures, 14 table

    Optimal crew routing for linear repetitive projects using graph theory and entropy maximization metric

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    Construction projects that contain several identical or similar units are usually known as repetitive or linear projects. Repetitive projects are regarded as a wide umbrella that includes various categories of construction projects and represents a considerable portion of the construction industry, and contain uniform repetition of work. CPM has been proved to be inefficient in scheduling linear projects because CPM does not address two key aspects, which are maintaining crew work continuity, and achieving a constant rate of progress to meet a given deadline. Line-of-balance (LOB) is a linear scheduling methodology that produces a work schedule in which resource allocation is automatically performed to provide a continuous and uninterrupted use of resource. The fundamental principles of LOB have several shortfalls that raise many concerns about LOB, which need to be attuned and improved in order to suit the nature of construction projects. Hence, this thesis proposes a hybrid approach for scheduling linear projects that stresses on the limitation of LOB scheduling technique. To meet the physical limitation of resources in linear projects, this study presents a flexible optimization model for resolving resource constraint dilemma in linear scheduling problems .The proposed model utilizes a MATLAB code as the searching algorithm to automate the model formulation. The novelty of this model is supplementing a new optimization engine and a decision supporting system that formulate the optimal crews routing between different activities in different units and guarantee the optimal crew distribution for cost efficiency. This model investigates the mechanics of allocating a multi- task skilled workforce between different activities in different units that can lead to increased productivity, flexibility, and work continuity; besides, this model has the capability of accurately identifying the critical path in linear projects. Furthermore, to avoid day-to-day fluctuation in resource demands, this study encompasses a simulation model for handling the resource leveling in linear construction projects. The proposed model was implemented using crystal ball ribbon based on an entropy maximization metric. The entropy-maximization method accounts for such possibility of allowing activity duration to be stretched or crunched relying on activity type without affecting total completion date of a project and provides more optimized resource allocation solutions. A case study for a 4-km sewage pipeline is used to demonstrate the capability of the proposed models, which illustrates the implementation of the proposed models in construction projects

    Aeronautical Engineering: A special bibliography, supplement 60

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    This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1975

    Scheduling Strategies for Construction Project Managers Toward On Time Delivery

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    Construction management projects involve complex, dynamic environments resulting in uncertainty and risk, compounded by demanding time constraints. Research indicated project managers have struggled to identify best practices for scheduling construction projects via critical path methodologies while searching for tools to increase timely job completions and budget profits. The purpose of this single case study was to explore the strategies that construction project managers used to manage scheduled construction project delivery on time. The constructivist philosophical worldview was used as the framework for this study. Data were collected from semistructured interviews from 7 project managers from 5 different construction companies selected via purposive sampling throughout Florida. All project managers had at least 15 years of experience and multiple construction projects with managing scheduled project deliveries. Three themes emerged through thematic analysis: project, time delay, and cost. A construction project can have many variables that project managers cannot control such as the issue of on-time scheduling. Project managers identified that a project could be within the budget or cost set for the project and still be on time and go over budget or be within budget and not meet schedule. No broad support was found for agile project management, and no confirmation could be made that principles of philosophical theories were critical for project success. Implications for a positive social change result in creating new jobs during and after construction, bringing new individuals to neighborhoods, schools, and area businesses

    Analysis of Buffer Starvation with Application to Objective QoE Optimization of Streaming Services

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    Our purpose in this paper is to characterize buffer starvations for streaming services. The buffer is modeled as an M/M/1 queue, plus the consideration of bursty arrivals. When the buffer is empty, the service restarts after a certain amount of packets are \emph{prefetched}. With this goal, we propose two approaches to obtain the \emph{exact distribution} of the number of buffer starvations, one of which is based on \emph{Ballot theorem}, and the other uses recursive equations. The Ballot theorem approach gives an explicit result. We extend this approach to the scenario with a constant playback rate using T\`{a}kacs Ballot theorem. The recursive approach, though not offering an explicit result, can obtain the distribution of starvations with non-independent and identically distributed (i.i.d.) arrival process in which an ON/OFF bursty arrival process is considered in this work. We further compute the starvation probability as a function of the amount of prefetched packets for a large number of files via a fluid analysis. Among many potential applications of starvation analysis, we show how to apply it to optimize the objective quality of experience (QoE) of media streaming, by exploiting the tradeoff between startup/rebuffering delay and starvations.Comment: 9 pages, 7 figures; IEEE Infocom 201
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