John Backus- inventor of FORTRAN

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“CSMA-Based and Optimal link scheduling in Multihop MIMO Networks using SINR Model ”

The development of high-performance distributed scheduling algorithms for multi-hop wireless networks have become a matter of interest in recent years. The problem is challenging when studied under a physical interference model because it requires the SINR to be above a certain threshold at the receiver for decoding success. Under this SINR model, the transmission failure can be caused by interference due to simultaneous transmissions from far away nodes, which intensifies the difficulty in developing a distributed algorithm for link scheduling. In this paper, we are going to propose scheduling algorithm that uses carrier sensing and show that the algorithm is applicable to distributed implementation as well as it results in throughput optimality. This algorithm has a feature called the dual-state approach. It separates the transmission schedules from the system state means control state ans data state are separated hence can be shown to improve delay performance

Imbibition in Double Phase Flow Through Porous Media

In this paper, the phenomenon of Imbibition in two immiscible phase flow through porous media is discussed. The Successive over Relaxation (S.O.R.) method is applied to solve the governing partial differential equation and the numerical results have been represented using graphs

“CSMA-Based Link Scheduling in Multihop MIMO Networks using SINR Model ”

The main aim of this study to resolve the problem of distributed scheduling in multi-hop MIMO networks. We will first develop a “MIMO pipe” model which will provide the required SINR , which gives the rate-reliability tradeoff in MIMO communications.Here we are going to study development of CSMA-based MIMO-pipe scheduling especially under the SINR model.We are going to choose the SINR model over the conventionally studied matching or protocol-based interference models because it has ability to capture the impact of interference in wireless networks. Here each node is equipped with an antenna array. In CSMA based scheduling, nodes will first sense the channel activity before attempting transmissions, whenever the channel is sensed to be idle, the nodes will continue with data transmissions. When the channel is detected to be busy, the nodes have to wait for a random amount of backoff time before reattempting the transmission.We will study that protocol model based throughput-optimal CSMA based scheduling, would not work well under the SINR model because its has dynamic and intrinsic link coupling. To tackle this challenge,CSMA-based MIMO-pipe scheduling is develpoed in both discrete-time system and continuous-time system

A Survey Paper on Ontology-Based Approaches for Semantic Data Mining

Semantic Data Mining alludes to the information mining assignments that deliberately consolidate area learning, particularly formal semantics, into the procedure. Numerous exploration endeavors have validated the advantages of fusing area learning in information mining and in the meantime, the expansion of information building has enhanced the group of space learning, particularly formal semantics and Semantic Web ontology. Ontology is an explicit specification of conceptualization and a formal approach to characterize the semantics of information and data. The formal structure of ontology makes it a nature approach to encode area information for the information mining utilization. Here in Semantic information mining ontology can possibly help semantic information mining and how formal semantics in ontologies can be joined into the data mining procedure. DOI: 10.17762/ijritcc2321-8169.16048

Vehicular Ad-hoc Network with Adaptive Cruise Control

Data fusion is the process of combining data from multiple sources. To improve accuracy of the information it is necessary to collect data from multiple sensors. The intelligent transport system (ITS) is used for vehicles safety applications. It is also used to enhance the non safety applications i.e. road and vehicle efficiency. In vehicular ad-hoc network multiple sensors are available for security measures for driver, and also important for communication between V2V, V2I or I2V. To control the cruising of vehicle Adaptive Cruise Control is required. To broadcast information unscented filter based on recursive Kalman type of estimator is used

Intrusion Detection System by using SVM and Ant Colony

In today’s world, it is very difficult to protect our system from different types of attacks or viruses . Intrusion Detection System (IDS) are basically designed to defend computer system from various types of attacks. In this paper a new approach is proposed for network intrusion detection. This new approach will make the combination of SVM algorithm with Self-Organized Ant Colony Network (CSOACN) algorithm to develop new IDS. It will take advantages of both while avoiding their limitations. The basic task of this approach is to classify network packet as normal or abnormal while minimizing misclassi?cation. For experimental setup we had used standard benchmark NSLKDD dataset which is advanced version of KDDCUP99 dataset. The system shows best result as we compare it with different types of IDS which was developed by using different algorithm

Redshift drift in axially symmetric quasi-spherical Szekeres models

Models of inhomogeneous universes constructed with exact solutions of Einstein's General Relativity have been proposed in the literature with the aim of reproducing the cosmological data without any need for a dark energy component. Besides large scale inhomogeneity models spherically symmetric around the observer, Swiss-cheese models have also been studied. Among them, Swiss-cheeses where the inhomogeneous patches are modeled by different particular Szekeres solutions have been used for reproducing the apparent dimming of the type Ia supernovae (SNIa). However, the problem of fitting such models to the SNIa data is completely degenerate and we need other constraints to fully characterize them. One of the tests which is known to be able to discriminate between different cosmological models is the redshift-drift. This drift has already been calculated by different authors for Lema\^itre-Tolman-Bondi (LTB) models. We compute it here for one particular axially symmetric quasi-spherical Szekeres (QSS) Swiss-cheese which has previously been shown to reproduce to a good accuracy the SNIa data, and we compare the results to the drift in the $\Lambda$CDM model and in some LTB models that can be found in the literature. We show that it is a good discriminator between them. Then, we discuss our model's remaining degrees of freedom and propose a recipe to fully constrain them.Comment: 15 pages, 7 figures, minor changes in title, text, figures and references; conclusions unchanged, this version matches the published versio

Online frequency domain identification method for stable systems

An online estimation method for single-input-single-output (SISO) type stable systems is discussed based on frequency transformation technique. Reported method based on Fast Fourier Transform (FFT) is an offline identification method means the controller is required to remove from the closed-loop at the time of autotuning test. So, the modified method is suggested for online identification and has been tested on several systems to show the effectiveness of the method. A relay with hysteresis in parallel with Proportional-Integral (PI) controller induces stationary oscillation cycle whose frequency and amplitude are used for system identification. We consider the development of a non-iterative approach with less computational efforts and a reasonable amount of data. A simulation study is given to illustrate the potential advantage of the presented method