Preemptive Resume Priority Call Center Model with Two Classes of MAP Arrivals

Generally in call centers, voice calls (say Type 1 calls) are given higher priority over e-mails (say Type 2 calls). An arriving Type 1 call has a preemptive priority over a Type 2 call in service, if any, and the preempted Type 2 call enters into a retrial buffer (of finite capacity). Any arriving call not able to get into service immediately will enter into the pool of repeated calls provided the buffer is not full; otherwise, the call is considered lost. The calls in the retrial pool are treated alike (like Type 1) and compete for service after a random amount of time, and can preempt a Type 2 call in service. We assume that the two types of calls arrive according to a Markovian arrival process (MAP) and the services are offered with preemptive priority rule. Under the assumption that the service times are exponentially distributed with possibly different rates, we analyze the model using matrix-analytic methods. Illustrative numerical examples to bring out the qualitative aspects of the model under study are presented

Aggregation of Key with Searchable Encryption for Group Data Sharing

Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set in cloud storage, but the other encrypted files outside the set remain confidential. This compact aggregate key can be conveniently sent to others or be stored in a smart card with very limited secure storage. We provide formal security analysis of our schemes in the standard model. We also describe other application of our schemes. In particular, our schemes give the first public-key patient-controlled encryption for flexible hierarchy, which was yet to be known

Consistent Anisotropic Repulsions for Simple Molecules

We extract atom-atom potentials from the effective spherical potentials that suc cessfully model Hugoniot experiments on molecular fluids, e.g., $O_2$ and $N_2$. In the case of $O_2$ the resulting potentials compare very well with the atom-atom potentials used in studies of solid-state propertie s, while for $N_2$ they are considerably softer at short distances. Ground state (T=0K) and room temperatu re calculations performed with the new $N-N$ potential resolve the previous discrepancy between experimental and theoretical results.Comment: RevTeX, 5 figure

Vertebrobasilar Artery Occlusion

The presentation of vertebrobasilar artery occlusion varies with the cause of occlusion and location of ischemia. This often results in delay in diagnosis. Areas of the brain supplied by the posterior circulation are difficult to visualize and usually require angiography or magnetic resonance imaging. Intravenous thrombolysis and local-intra arterial thrombolysis are the most common treatment approaches used. Recanalization of the occluded vessel significantly improves morbidity and mortality. Here we present a review of the literature and a case of a patient with altered mental status caused by vertebrobasilar artery occlusion

Fuzzy based clustering in CWPSN using machine learning model

90-94Cognitive wireless power sensor network (CWPSN) technology, widely used in almost all fields, has addressed various issues. The researchers have addressed the problems in the lack of radio spectrum availability and enabled the allocation of dynamic spectrum access in specific fields. The main challenge has been to support the radio spectrum allocation using intelligent adaptive learning and decision-making techniques so that various requirements of 5G wireless networks can be encountered. Machine learning (ML) is one of the most promising artificial intelligence tools conceived to support cognitive wireless networks. This paper aims to provide energy optimization and enhance security to cognitive wireless power sensor networks using a novel protocol during resource allocation. In addition to the existing methods, a novel protocol, fuzzy cluster-based greedy algorithms for attack prediction and energy harvesting using a machine-language model based on neural network techniques have been introduced. The simulation has been done using MATLAB software tools which gives efficient results

Pathways to clinical CLARITY: volumetric analysis of irregular, soft, and heterogeneous tissues in development and disease

AbstractThree-dimensional tissue-structural relationships are not well captured by typical thin-section histology, posing challenges for the study of tissue physiology and pathology. Moreover, while recent progress has been made with intact methods for clearing, labeling, and imaging whole organs such as the mature brain, these approaches are generally unsuitable for soft, irregular, and heterogeneous tissues that account for the vast majority of clinical samples and biopsies. Here we develop a biphasic hydrogel methodology, which along with automated analysis, provides for high-throughput quantitative volumetric interrogation of spatially-irregular and friable tissue structures. We validate and apply this approach in the examination of a variety of developing and diseased tissues, with specific focus on the dynamics of normal and pathological pancreatic innervation and development, including in clinical samples. Quantitative advantages of the intact-tissue approach were demonstrated compared to conventional thin-section histology, pointing to broad applications in both research and clinical settings.</jats:p

Heat release rate estimation in laminar premixed flames using laser-induced fluorescence of CH2O and H-atom

The present work demonstrates the feasibility of heat release rate imaging using the laser-induced fluorescence (LIF) of atomic hydrogen (H-atom) and formaldehyde (CH2O) in laminar premixed flames. The product of H-atom LIF and CH2O LIF signals is evaluated on a pixel-by-pixel basis and is compared with that of the OH × CH2O technique. These results for equivalence ratio ranging from 0.8 to 1.1 are compared with computations of one-dimensional freely-propagating flames. The performance of these markers is studied based on the following two aspects: the spatial accuracy of the local heat release rate and the trend in the total heat release rate with equivalence ratio. The measured trend in the spatial distribution of radicals and the deduced heat release rate agree well with the computational values. The variation in the spatially integrated heat release rate as a function of equivalence ratio is also investigated. The results suggest that the trend in the variation of the integrated heat release rate and the spatial location of heat release rate can be evaluated by either of these markers. The OH-based marker showed certain sensitivity to the chemical mechanism as compared to the H-atom based marker. Both the OH-based and H-atom based techniques provide close estimates of heat release rate. The OH based technique has practical advantage when compared to the H-atom based method, primarily due to the fact that the H-atom LIF is a two-photon process

The busy period and the waiting time analysis of a MAP/M/c queue with finite retrial group

We concentrate on the analysis of the busy period and the waiting time distribution of a multi-server retrial queue in which primary arrivals occur according to a Markovian arrival process (MAP). Since the study of a model with an infinite retrial group seems intractable, we deal with a system having a finite buffer for the retrial group. The system is analyzed in steady state by deriving expressions for (a) the Laplace–Stieltjes transforms of the busy period and the waiting time; (b) the probabiliy generating functions for the number of customers served during a busy period and the number of retrials made by a customer; and (c) various moments of quantites of interest. Some illustrative numerical examples are discussed

Early detection of neovascular age-related macular degeneration : an economic evaluation based on data from the EDNA study

Funding: The project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment Programme (grant number: 12/142/07) and will be published in full in Health Technology Assessment. The funder was not involved in the study design; in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication. The Health Services Research Unit (HSRU) and the Health Economics Research Unit (HERU) are core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorate (HSRU/2021-2024, HERU/2021-2024).Peer reviewedPostprin