Reducing Congestion Effects by Multipath Routing in Wireless Networks

We propose a solution to improve fairness and increasethroughput in wireless networks with location information.Our approach consists of a multipath routing protocol, BiasedGeographical Routing (BGR), and two congestion controlalgorithms, In-Network Packet Scatter (IPS) and End-to-EndPacket Scatter (EPS), which leverage BGR to avoid the congestedareas of the network. BGR achieves good performancewhile incurring a communication overhead of just 1 byte perdata packet, and has a computational complexity similar togreedy geographic routing. IPS alleviates transient congestion bysplitting traffic immediately before the congested areas. In contrast,EPS alleviates long term congestion by splitting the flow atthe source, and performing rate control. EPS selects the pathsdynamically, and uses a less aggressive congestion controlmechanism on non-greedy paths to improve energy efficiency.Simulation and experimental results show that our solutionachieves its objectives. Extensive ns-2 simulations show that oursolution improves both fairness and throughput as compared tosingle path greedy routing. Our solution reduces the variance ofthroughput across all flows by 35%, reduction which is mainlyachieved by increasing throughput of long-range flows witharound 70%. Furthermore, overall network throughput increasesby approximately 10%. Experimental results on a 50-node testbed are consistent with our simulation results, suggestingthat BGR is effective in practice

KAJI EKSPERIMENTAL PENGARUH KECEPATAN PUTAR NOSEL TERHADAP LAJU KONDENSASI PADA PROSES FLASHING

Salah satu cara yang dilakukan untuk memperoleh air bersih adalah dengan cara mengubah air laut menjadi air tawar dengan proses flashing. Metode flashing adalah metode penguapan air secara cepat dalam tabung evaporasi pada tekanan rendah melalui proses throttling. Proses throttling yaitu mendesak air laut dengan tekanan dan temperatur tertentu masuk melewati nosel agar terjadi kabut, kemudian kabut tersebut berada didalam tabung yang bertekanan vakum untuk dikondensasi sehingga air yang mengandung garam akan terpisah dengan air tawar. Salah satu cara agar proses flashing memungkinkan untuk terjadinya laju kondensasi lebih banyak yaitu dengan memanfaatkan nosel berputar agar kabut yang keluar dari nosel mengisi ruang tabung epavorasi. Adapun tujuan dari eksperimen ini yaitu mengetahui kecepatan putar nosel yang optimal pada proses flashing untuk menghasilkan air tawar yang maksimal dengan temperatur air umpan, tekanan vakum, dan tekanan air umpan tetap tetapi kecepatan putar nosel yang diubah-ubah. Variabel pengujian kecepatan putar nosel yang dilakukan yaitu 0 rpm, 15 rpm, 20 rpm, 25 rpm, 29 rpm dan 34 rpm. Pada setiap variabel kecepatan putar nosel diambil sebanyak 5 data dengan melakukan dua kali pengujian untuk setiap datanya. Pengujian pertama dilakukan 70 menit dan pengujian kedua dilakukan berdasarkan temperatur kabut dalam tabung pada pengujian pertama sudah mulai dianggap steady atau tetap. Pengambilan data dilakukan dengan mikrokontroler arduino uno menggunakan sensor temperatur LM35, setelah data diperoleh kemudian data diolah menggunakan metode data statistik dengan tingkat kepercayaan 95%. Dari eksperimen yang dilakukan, kecepatan putar nosel yang optimal menghasilkan laju kondensasi terbanyak adalah 15 rpm dengan laju kondensasi 3,66 ml/menit, sedangkan laju kondensasi terendah adalah kecepatan putar nosel 0 rpm atau keadaan nosel diam dengan laju kondensasi 0,85 ml/menit. Kata kunci : Desalinasi, Flashing, Nosel berputar

A Double Sigma Model for Double Field Theory

We define a sigma model with doubled target space and calculate its background field equations. These coincide with generalised metric equation of motion of double field theory, thus the double field theory is the effective field theory for the sigma model.Comment: 26 pages, v1: 37 pages, v2: references added, v3: updated to match published version - background and detail of calculations substantially condensed, motivation expanded, refs added, results unchange

Health in my community: Conducting and evaluating photovoice as a tool to promote environmental health and leadership among Latino/a youth

BackgroundThe PhotoVoice method has shown substantial promise for work with youth in metropolitan areas, yet its potential for use with Latino youth from agricultural areas has not been well documented.ObjectivesThis project was designed to teach environmental health to 15 high school youth while building their individual and community capacity for studying and addressing shared environmental concerns. The project also aimed to test the utility of PhotoVoice with Latino agricultural youth.MethodsFifteen members of the Youth Community Council (YCC), part of a 15-year project with farmworker families in Salinas, CA, took part in a 12-week PhotoVoice project. Their pictures captured the assets and strengths of their community related to environmental health, and were then analyzed by participants. A multi-pronged evaluation was conducted.ResultsYCC members identified concerns such as poor access to affordable, healthy foods and lack of safe physical spaces in which to play, as well as assets, including caring adults and organizations, and open spaces in surrounding areas. Participants presented their findings on radio, television, at local community events, and to key policy makers. The youth also developed two action plans, a successful 5K run/walk and a school recycling project, still in progress. Evaluation results included significant changes in such areas as perceived ability to make presentations, leadership, and self-confidence, as well as challenges including transportation, group dynamics, and gaining access to people in power.ConclusionThe PhotoVoice method shows promise for environmental health education and youth development in farmworker communities

Quantile forecast discrimination ability and value

While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are introduced here, based on quantile forecasts being the base product for the continuous case (hence in a nonparametric framework). The relative user characteristic (RUC) curve and the quantile value plot allow analysing the performance of a forecast for a specific user in a decision-making framework. The RUC curve is designed as a user-based discrimination tool and the quantile value plot translates forecast discrimination ability in terms of economic value. The relationship between the overall value of a quantile forecast and the respective quantile skill score is also discussed. The application of these new verification approaches and tools is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service

Robust Structured Low-Rank Approximation on the Grassmannian

Over the past years Robust PCA has been established as a standard tool for reliable low-rank approximation of matrices in the presence of outliers. Recently, the Robust PCA approach via nuclear norm minimization has been extended to matrices with linear structures which appear in applications such as system identification and data series analysis. At the same time it has been shown how to control the rank of a structured approximation via matrix factorization approaches. The drawbacks of these methods either lie in the lack of robustness against outliers or in their static nature of repeated batch-processing. We present a Robust Structured Low-Rank Approximation method on the Grassmannian that on the one hand allows for fast re-initialization in an online setting due to subspace identification with manifolds, and that is robust against outliers due to a smooth approximation of the $\ell_p$-norm cost function on the other hand. The method is evaluated in online time series forecasting tasks on simulated and real-world data

Somatopia - Creative computing through inclusive design

The overarching aim of our research has been bridge the gap between emotionally compelling, open source technology innovation and disenfranchised groups who could benefit from the opportunity to engage with such technologies “as themselves”1. We have therefore designed a prototype system, Somatopia, which uses the Raspberry Pi2 computer to create video projections that respond to a variety of gross motor interactions. Our earliest iterations of Somatopia evolved during a series of drama-based workshops with adults with a range of cognitive and physical impairments. Adopting methods that address self-awareness and expressive communication through movement enabled us to participate in activities with the group on an equal basis. The paper describes how the techniques provided a predictable framework for collaboration, which, in turn, directly influenced the design of the interactions

On the Riemann Tensor in Double Field Theory

Double field theory provides T-duality covariant generalized tensors that are natural extensions of the scalar and Ricci curvatures of Riemannian geometry. We search for a similar extension of the Riemann curvature tensor by developing a geometry based on the generalized metric and the dilaton. We find a duality covariant Riemann tensor whose contractions give the Ricci and scalar curvatures, but that is not fully determined in terms of the physical fields. This suggests that \alpha' corrections to the effective action require \alpha' corrections to T-duality transformations and/or generalized diffeomorphisms. Further evidence to this effect is found by an additional computation that shows that there is no T-duality invariant four-derivative object built from the generalized metric and the dilaton that reduces to the square of the Riemann tensor.Comment: 36 pages, v2: minor changes, ref. added, v3: appendix on frame formalism added, version to appear in JHE

Global solar irradiation prediction using a multi-gene genetic programming approach

This is the author accepted manuscript. The final version is available from AIP Publishing via the DOI in this record.In this paper, a nonlinear symbolic regression technique using an evolutionary algorithm known as multi-gene genetic programming (MGGP) is applied for a data-driven modelling between the dependent and the independent variables. The technique is applied for modelling the measured global solar irradiation and validated through numerical simulations. The proposed modelling technique shows improved results over the fuzzy logic and artificial neural network (ANN) based approaches as attempted by contemporary researchers. The method proposed here results in nonlinear analytical expressions, unlike those with neural networks which is essentially a black box modelling approach. This additional flexibility is an advantage from the modelling perspective and helps to discern the important variables which affect the prediction. Due to the evolutionary nature of the algorithm, it is able to get out of local minima and converge to a global optimum unlike the back-propagation (BP) algorithm used for training neural networks. This results in a better percentage fit than the ones obtained using neural networks by contemporary researchers. Also a hold-out cross validation is done on the obtained genetic programming (GP) results which show that the results generalize well to new data and do not over-fit the training samples. The multi-gene GP results are compared with those, obtained using its single-gene version and also the same with four classical regression models in order to show the effectiveness of the adopted approach

Application of preventive maintenance planning in a parquet enterprise

In this study, the process of a parquet enterprise’s transition to preventive maintenance which has been implementing maintenance technique in case of breakdown was investigated. During that transition process, follow up forms for maintenance–repair, breakdown and spare parts were prepared and the implementation processes were followed. At the end of the implementation, it was identified that breakdowns have declined, anxiety and turmoil brought about by breakdowns have been prevented, thelife span of the machines soared, labour-borne accidents declined and production quality increased