Sharif Digital Repository

In this paper we provide the correct tight constant to a data-processing inequality claimed by Erkip and Cover. The correct constant turns out to be a particular hypercontractivity parameter of (X,Y), rather than their squared maximal correlation. We also provide alternate geometric characterizations for both maximal correlation as well as the hypercontractivity parameter that characterizes the data-processing inequality  

Many important problems in Computational Geometry needs to perform some kind of angle processing. The Polar Diagram [4] is a locus approach for problems processing angles. Using this structure as preprocessing, one can eliminate exhaustive searches to find objects with smallest angle. Handling data in change is a significant concept in Computer Science. One of the design and analysis tools used in the modeling of moving geometric objects is the kinetic data structure (or KDS) framework Kinetic Data Structure is a framework for maintaining a certain attribute of a set of objects while moving in a continuous manner. In this paper, we use the notion of kinetic data structure to model the... 

Smartphones can be viewed as resource pools capable of communicating with their outside world. Such communication capabilities provide unique opportunity for sharing resources, which would result in new possibilities for end users. In this paper, we present a new framework designed for managing mobile local networks, also referred to as Mobile Clouds. In this framework, mobility of nodes is managed by selecting one leader for each cloud, which is responsible for all cloud-level decisions, as well as processing all incoming data from other users. We also evaluate and discuss our proposed framework under different scenarios  

We focus on two metric clusterings namely r-gather and (r, ?)-gather. The objective of r-gather is to minimize the radius of clustering, such that each cluster has at least r points. (r, ?)-gather is a version of r-gather with the extra condition that at most n? points can be left unclustered (outliers). MapReduce is a model used for processing big data. In each round, it distributes data to multiple servers, then simultaneously processes each server's data. We prove a lower bound 2 on the approximation factor of metric r-gather in the MapReduce model, even if an optimal algorithm for r-gather exists. Then, we give a (4+ δ)-approximation algorithm for r-gather in MapReduce which runs in O(... 

We focus on two metric clusterings namely r-gather and (r, ?)-gather. The objective of r-gather is to minimize the radius of clustering, such that each cluster has at least r points. (r, ?)-gather is a version of r-gather with the extra condition that at most n? points can be left unclustered (outliers). MapReduce is a model used for processing big data. In each round, it distributes data to multiple servers, then simultaneously processes each server's data. We prove a lower bound 2 on the approximation factor of metric r-gather in the MapReduce model, even if an optimal algorithm for r-gather exists. Then, we give a (4+ δ)-approximation algorithm for r-gather in MapReduce which runs in O(... 

Correctly detecting the position where a concept begins to drift is important in mining data streams. In this paper, we propose a new method for detecting concept drift. The proposed method, which can detect different types of drift, is based on processing data chunk by chunk and measuring differences between two consecutive batches, as drift indicator. In order to evaluate the proposed method we measure its performance on a set of artificial datasets with different levels of severity and speed of drift. The experimental results show that the proposed method is capable to detect drifts and can approximately find concept drift locations  

The noninvasive fetal electrocardiogram (ECG) data available from Physionet data bank are suitable for developing fetal heart rate (FHR) detection algorithms. The data have been collected from single subject with a broad range of gestation weeks, and have a total data length of more than 9 hours arranged in 55 data sets. However, there are three additional data features which are currently not directly available from Physionet to facilitate the easy usage of these data: (1) the fetal peak visibility evaluation, (2) the gestation week, and (3) the data length. This article presents an improvement to the data bank by providing the additional features. The required pre-processing of the data is... 

Optical computing has emerged as a promising candidate for real-time and parallel continuous data processing. Motivated by recent progresses in metamaterial-based analog computing [Science 343, 160 (2014)], we theoretically investigate the realization of two-dimensional complex mathematical operations using rotated configurations, recently reported in [Opt. Lett. 39, 1278 (2014)]. Breaking the reflection symmetry, such configurations could realize both even and odd Green's functions associated with spatial operators. Based on such an appealing theory and by using the Brewster effect, we demonstrate realization of a firstorder differentiator. Such an efficient wave-based computation method... 

One of the challenging problems in real-time data-parallel processing applications is to schedule tasks to different servers aiming to increase data locality for higher efficiency or lower delay, and at the same time, doing load balancing to stabilize the system of server-queues. We target this problem, and discuss efficient real-time task scheduling algorithms aimed not only to stabilize the system when the arrival rate is in the capacity region (i.e. throughput optimality condition), but also to minimize the mean delay of all tasks in heavy traffic regime when the arrival rate approaches the capacity boundary (i.e. heavy-traffic optimality condition). In this paper, we point out the data... 

In this paper, we study the problem of simulating a discrete memoryless channel (DMC) from another DMC under an average-case and an exact model. We present several achievability and infeasibility results, with tight characterizations in special cases. In particular, for the exact model, we fully characterize when a binary symmetric channel can be simulated from a binary erasure channel when there is no shared randomness. We also provide infeasibility and achievability results for the simulation of a binary channel from another binary channel in the case of no shared randomness. To do this, we use the properties of Rényi capacity of a given order. We also introduce a notion of 'channel... 

We introduce the blind index coding (BIC) problem, in which a single sender communicates distinct messages to multiple users over a shared channel. Each user has partial knowledge of each message as side information. However, unlike classical index coding, in BIC, the sender is uncertain of what side information is available to each user. In particular, the sender only knows the amount of bits in each user's side information but not its content. This problem can arise naturally in caching and wireless networks. In order to blindly exploit side information in the BIC problem, we develop a hybrid coding scheme that XORs uncoded bits of a subset of messages with random combinations of bits from... 

To limit the peak power consumption of a cluster, a centralized power capping system typically assigns power caps to the individual servers, which are then enforced using local capping controllers. Consequently, the performance and throughput of the servers are affected, and the runtime of jobs is extended as a result. We observe that servers in big data processing clusters often execute big data applications that have different tolerance for approximate results. To mitigate the impact of power capping, we propose a new power-Capping aware resource manager for Approximate Big data processing (CAB) that takes into consideration the minimum Quality-of-Result (QoR) of the jobs. We use... 

Nowadays, a wide range of enterprises are faced with big data processing in different domains such as transaction operations, business calculations and analytical computations. Large-scale computing is an approach for big data processing. Due to the cost of large-scale computing and limitations of enterprise budgets, it is hardly possible to process all the input data and therefore the Quality of Result (QoR) may be affected. SAIR is an approach to improve QoR of big data processing for aggregative usages based on significance variety when there is a budget constraint. In this paper, the most significant data portions have been assigned to the most efficient resources in terms of time and... 

Investigation of the X-ray structure of the newly prepared [Ru(NO)(2,6isopPh2Aceq)Cl3] (2,6isopPh2Aceq = bis(2,6-diisopropylphenylimino)acenaphthenequinone) complex revealed for the first time the π-hole interaction involving the coordinated nitrosyl group with DMSO as the solvent of crystallization in the crystal lattice. Processing of CSD data showed only one reported structure. A significant feature of the structure is the presence of n → π∗, π → σ∗, and n → σ∗ interactions due to the coordinated nitrosyl and chloro groups and DMSO. © 2020 The Royal Society of Chemistry  

In this study, the liquid-liquid phase behavior of aromatic compound. +. aliphatic compound. +. ionic liquid (IL) ternary systems was estimated by using two artificial neural networks (ANN) developed based on back propagation (BP) and hybrid group method of data handling (GMDH). Molar ratio of aliphatic compound, aromatic compound, and IL as well as temperature, molecular weight ratio of aliphatic compound to IL, and molecular weight ratio of aromatic compound to IL were chosen as the inputs to the networks. Additionally, the mole fraction of components in final alkane-rich phase and IL-rich phase was considered as desired outputs. The best topology of the BP-ANN model was found as (6-8-4).... 

Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif... 

Thermal conductivity of nanofluids plays key rol in heat transfer capacity of fluids. adding nanoparticles to a base fluid can lead to enhancement in thermal conductivty ratio. CuO/Ethyle Glycol (EG) is one of the most applicable nanofluids for heat transfer purposes. In the present study, thermal conductivty ratio of CuO/EG nanofluid is modeled by applying Group Method of Data Hnadling and Least Square Support Vector Machine – Gentic Algorithm approaches. Results indicated that the utilized model are very accurate in predicting thermal conductivty ratio of the nanofluid. The R-squared values for the proposed model are equal to 0.994 and 0.991 by applying Group Method of Data Handling and... 

To increase crew efficiency during a long duration space mission, we have developed a Sequence Dependent Structured Matrix (SDSM) which enables designers to quickly derive the shortest paths astronauts (mission specialists) need to perform their daily tasks. This research aims to develop a new efficient tool by combining two or more DSM interpretations which help increase the ability of proper decision makings for complex situations as space travel. The results of this work have been used for arranging crew quarters in the spacecraft suited for Mars mission. In the same approach, we have been able to generalize the concept and construct different specific types of DSM; such as, Astronauts'... 

Data aggregation is an effective technique which is introduced to save energy by reducing packet transmissions in WSNs. However, it extends the delay at the intermediate nodes, so it can complicate the handling of delayconstrained data in event-critical applications. Besides, the structure-based aggregation as the dominant data gathering approach in WSNs suffers from high maintenance overhead in dynamic scenarios for event-based applications. In this paper, to make aggregation more efficient, we design a novel structure-free Real-time Data AGgregation protocol, RDAG, using a Real-time Data-aware Routing policy and a Judiciously Waiting policy for spatial and temporal convergence of packets.... 

As an alternative to adaptive nonlinear schemes for dimensionality reduction, linear random projection has recently proved to be a reliable means for high-dimensional data processing. Widespread application of conventional random projection in the context of image analysis is, however, mainly impeded by excessive computational and memory requirements. In this paper, a two-dimensional random projection scheme is considered as a remedy to this problem, and the associated key notion of concentration of measure is closely studied. It is then applied in the contexts of image classification and sparse image reconstruction. Finally, theoretical results are validated within a comprehensive set of...