Analysis of an optimal policy in dynamic bipartite matching models

[EN] A dynamic bipartite matching model is given by a bipartite matching graph which determines the possible matchings between the various types of supply and demand items. Both supply and demand items arrive to the system according to a stochastic process. Matched pairs leave the system and the others wait in the queues, which induces a holding cost. We model this problem as a Markov Decision Process and study the discounted cost and the average cost problem. We assume that the cost function is linear on the queue sizes. We show that for the N-shaped matching graph, an optimal matching control prioritizes the matchings in the pendant edges and is of threshold type for the diagonal edge. In addition, for the average cost problem, we compute the optimal threshold value. We then show how the obtained results can be used to characterize the structure of an optimal matching control for a quasi-complete graph with an arbitrary number of nodes. For arbitrary bipartite graphs, we show that, when the cost of the pendant edges is larger than in the neighbors, an optimal matching policy prioritizes the items in the pendant edges. We also study the W-shaped matching graph and, when the cost of the pendant edges is larger than the cost of the middle edge, we conjecture that an optimal matching policy is also of threshold type with priority to the pendant edges; however, when the cost of the middle edge is larger, we present simulations that show that it is not optimal to prioritize items in the pendant edgesThe work of Josu Doncel has been supported by the Department of Education of the Basque Government, Spain through the Consolidated Research Group MATHMODE (IT1294-19), by the Marie Sklodowska-Curie, Spain grant agreement No 777778 and by the Spanish Ministry of Science and Innovation, Spain with reference PID2019-108111RB-I00 (FEDER/AEI). This work was also funded by the French National Research Agency, France grant ANR-16-CE05-0008

PENGARUH TEKNOLOGI DAN KOMUNIKASI TERHADAP KINERJA KARYAWAN DI KOPERASI SIMPAN PINJAM DAMAI KABUPATEN LOMBOK UTARA

Koperasi Simpan Pinjam Damai merupakan salah satu Koperasi Simpan Pinjam yang ada di Kabupaten Lombok Utara. Tujuan dari Penelitian ini adalah untuk mengetahui Pengaruh Teknologi dan Komunikasi Terhadap Kinerja Karyawan di Koperasi Simpan Pinjam Damai Kabupaten Lombok Utara. Dengan menggunakan Metode Penelitian kuantitatif Analisis Linear Berganda dengan Program SPSS 22. Variabel bebas dalam Penelitian ini yaitu Teknologi sebagai variabel bebas (X1) dan Komunikasi sebagai variabel bebas (X2) dengan variabel terikat Kinerja Karyawan (Y). Data diperoleh dengan menggunakan teknik Kuesioner, Observasi, Studi Pustaka dan Dokumen. Kuesioner dapat berisi pernyataan dan Pertanyaan yang berdasarkan Teori Maflikhah untuk varibel Teknologi, Teori Devito untuk variabel Komunikasi dan Teori Haryanto untuk Kinerja Karyawan dengan Skala yang digunakan yaitu Skala Linkert. Jumlah Responden dalam Penelitian Ini yaitu 65 orang responden yang berangkat dari 184 anggota koperasi yang perhitungannya menggunakan teori Slovin. Berdasarkan Penelitian Teknologi (X1) berpengaruh terhadap Kinerja Karyawan dengan nilai 2,217 begitupun dengan Komunikasi (X2) berpengaruh terhadap Kinerja Karyawan Sebesar 3,619. Dengan nilai Simultan sebesar 21,4%. Berpengaruh positif terhadap kinerja karyawan. Hasil Kinerja yang kurang baik ini diakibatkan oleh kurang dukungan Teknologi dan Komunikasi terhadap Kinerja Karyawan Di Koperasi Simpan Pinjam Damai Kabupaten Lombok Utara

An online disaggregation algorithm and its application to demand control

National audienceThe increase of renewable energy has made the supply-demand balance of power more complex to handle. In [1], the authors designed randomized controllers to obtain ancillary services to the power grid by harnessing inherent flexibility in many loads. However these controllers suppose that we know the consumption of each device that we want to control. This introduce the cost and the social constraint of putting sensors on each device of each house. Therefore, our approach was to use Nonintrusive Appliance Load Monitoring (NALM) methods to solve a disaggregation problem. The latter comes down to estimating the power consumption of each device given the total power consumption of the whole house. We started by looking at the Factorial Hierarchical Dirichlet Process-Hidden Semi-Markov Model (Factorial HDP-HSMM) introduced in [2]. In our application, the total power consumption is considered as the observations of this state-space model and the consumption of each device as the state variables. Each of the latter is modelled by an HDP-HSMM which is an extension of a Hidden Markov Model. However, the inference method used in [2] is based on Gibbs sampling and has a complexity of O(T 2 N +T N 2) where T is the number of observations and N is the number of hidden states. As our goal is to use the randomized controllers with our estimations, we wanted a method that does not scale with T. Therefore, we developed an online algorithm based on particle filters. Because we worked in a Bayesian setting, we had to infer the parameters of our model. To do so, we used a method called Particle Learning which is presented in [3]. The idea is to include the parameters in the state space so that they are tied to the particles. Then, for each (re)sampling step, the parameters are sampled from their posterior distribution with the help of Bayesian sufficient statistics. We applied the method to data from Pecan Street. Using their Dataport, we have collected the power consumption of each device from about a hundred houses. We selected the few devices that consume the most and that are present in most houses. We separated the houses in a training set and a test set. For each device of each house from the training set, we estimated the operating modes with a HDP-HSMM and used these estimations to compute estimators of the priors hyperparameters. Finally we applied the particle filters method to the test houses using the computed priors. The algorithm performs well for the device with the highest power consumption, the air compressor in our case. We will discuss ongoing work where we apply the "Thermo-statically Controlled Loads" example of [1] using our estimations of this air compressor's operating modes

Membrane localization of N-acylphosphatidylethanolamine in central neurons: Studies with exogenous phospholipases

We studied the localization of N-acyl phosphatidylethanolamine (NAPE), a putative cannabinoid precursor, in primary cultures of striatal and cortical neurons from the rat brain. We probed intact neurons with various exogenous phospholipases, including S. chromofuscus phospholipase D (PLD). S. chromofuscus PLD does not penetrate into neurons (as demonstrated by a lack of internalization of 125I-labeled PLD), and does not cause gross damage to the neuronal membrane (as demonstrated by a lack of effect of PLD on [3H]gamma-aminobutyric acid release). When neurons, labeled to isotopic equilibrium with [3H]ethanolamine, were incubated for 10 min with S. chromofuscus PLD, approximately 50% of neuronal NAPE was hydrolysed. This hydrolysis was accompanied by the release of a family of N-acyl ethanolamines (NAE) (assessed by high performance liquid chromatography), which included the cannabinoid receptor agonist, anandamide. Exogenous phospholipase A2 (PLA2) (Apis mellifera) and PLC (B. cereus) mobilized [3H]arachidonate and [3H]diacylglycerol, respectively, but had no effect on NAE formation under these conditions. These experiments indicate that approximately 50% of neuronal NAPE is localized in a compartment that is easily accessible to extracellular PLD, possibly the plasmalemma, where it would also be easily hydrolyzed upon stimulation to produce NAE

Inactivation of anandamide signaling : A continuing Debate

Copyright 2011 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD

Cannabis sativa and the endogenous cannabinoid system: therapeutic potential for appetite regulation

The herb Cannabis sativa (C. sativa) has been used in China and on the Indian subcontinent for thousands of years as a medicine. However, since it was brought to the UK and then the rest of the western world in the late 19th century, its use has been a source of controversy. Indeed, its psychotropic side effects are well reported but only relatively recently has scientific endeavour begun to find valuable uses for either the whole plant or its individual components. Here, we discuss evidence describing the endocannabinoid system, its endogenous and exogenous ligands and their varied effects on feeding cycles and meal patterns. Furthermore we also critically consider the mounting evidence which suggests non‐tetrahydrocannabinol phytocannabinoids play a vital role in C. sativa‐induced feeding pattern changes. Indeed, given the wide range of phytocannabinoids present in C. sativa and their equally wide range of intra‐, inter‐ and extra‐cellular mechanisms of action, we demonstrate that non‐Δ9tetrahydrocannabinol phytocannabinoids retain an important and, as yet, untapped clinical potential