Searcharxiv⌕ Search

SEARCH · Searcharxiv

Results for “cs.OH”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources
arXiv2010

ICT in Universities of the Western Himalayan Region of India II: A Comparative SWOT Analysis

This study presents a comparative SWOT analysis to comprehend the pattern of development of ICT within six universities of western Himalayan region of India. With the objective of achieving quality and excellence in higher education system in the region, this study provides a basis to decision makers to exploit opportunities and minimize the external threats. The SWOT analysis of different universities, placed under three categories, has been undertaken within the four-tier framework used earlier by the authors. Guided by the initiatives of National Mission on Education through ICT (NMEICT) for SWOT analysis, findings of this paper reveal, relative consistency of these three categories of universities, with the earlier study. A few suggestions, as opportunities, with an emphasis on problem solving orientation in higher education, have been made to strengthen the leadership of universities in the field of ICT.

cs.OH↗
arXiv2010

Modified EESM Based Link Adaptation Algorithm for Multimedia Transmission in Multicarrier Systems

The previous link adaptation algorithms on ofdm based systems use equal modulation order for all sub carrier index within a block. For multimedia transmission using ofdm as the modulation technique, unequal constellation is used within one ofdm subcarrier block, a set of subcarriers for audio and another set for video transmissions. A generic model has been shown for such a transmission and link adaptation algorithm has been proposed using EESM (Effective Exponential SNR mapping) method as basic method. Mathematical model has been derived for the channel based on bivariate Gaussian distribution in which the amplitude varies two dimensionally in the same envelope. From the Moment generating function of bivariate distribution, Probability of error has been theoretically derived. Results have been shown for BER performance of an ofdm system using unequal constellation. BER performances have been shown for different values of correlation parameter and fading figure.

cs.OH↗
arXiv2010

Understanding Formulation of Social Capital in Online Social Network Sites (SNS)

Online communities are the gatherings of like-minded people, brought together in cyberspace by shared interests. The shared interest has hidden social capital aspects and can be of bridging or bonding type. Creating such communities is not a big challenge but sustaining member's participation is. This study examines the formation and maintenance of social capital in social network sites. In addition to assessing bonding and bridging social capital, we explore a dimension of social capital that assesses one's ability to stay connected with members of a previously inhabited community, which we call maintained social capital. Such dimension is enacted here in terms of Hypothesis.

cs.OH↗
arXiv2010

New Insights from an Analysis of Social Influence Networks under the Linear Threshold Model

We study the spread of influence in a social network based on the Linear Threshold model. We derive an analytical expression for evaluating the expected size of the eventual influenced set for a given initial set, using the probability of activation for each node in the social network. We then provide an equivalent interpretation for the influence spread, in terms of acyclic path probabilities in the Markov chain obtained by reversing the edges in the social network influence graph. We use some properties of such acyclic path probabilities to provide an alternate proof for the submodularity of the influence function. We illustrate the usefulness of the analytical expression in estimating the most influential set, in special cases such as the UILT(Uniform Influence Linear Threshold), USLT(Uniform Susceptance Linear Threshold) and node-degree based influence models. We show that the PageRank heuristic is either provably optimal or performs very well in the above models, and explore its limitations in more general cases. Finally, based on the insights obtained from the analytical expressions, we provide an efficient algorithm which approximates the greedy algorithm for the influence maximization problem.

cs.OH↗
arXiv2010

Design of Current Controller for Two Quadrant DC Motor Drive by Using Model Order Reduction Technique

In this paper, design of current controller for a two quadrant DC motor drive was proposed with the help of model order reduction technique. The calculation of current controller gain with some approximations in the conventional design process is replaced by proposed model order reduction method. The model order reduction technique proposed in this paper gives the better controller gain value for the DC motor drive. The proposed model order reduction method is a mixed method, where the numerator polynomial of reduced order model is obtained by using stability equation method and the denominator polynomial is obtained by using some approximation technique preceded in this paper. The designed controllers responses were simulated with the help of MATLAB to show the validity of the proposed method.

cs.OH↗
arXiv2010

An Intelligent System For Effective Forest Fire Detection Using Spatial Data

The explosive growth of spatial data and extensive utilization of spatial databases emphasize the necessity for the automated discovery of spatial knowledge. In modern times, spatial data mining has emerged as an area of voluminous research. Forest fires are a chief environmental concern, causing economical and ecological damage while endangering human lives across the world. The fast or early detection of forest fires is a vital element for controlling such phenomenon. The application of remote sensing is at present a significant method for forest fires monitoring, particularly in vast and remote areas. Different methods have been presented by researchers for forest fire detection. The motivation behind this research is to obtain beneficial information from images in the forest spatial data and use the same in the determination of regions at the risk of fires by utilizing Image Processing and Artificial Intelligence techniques. This paper presents an intelligent system to detect the presence of forest fires in the forest spatial data using Artificial Neural Networks. The digital images in the forest spatial data are converted from RGB to XYZ color space and then segmented by employing anisotropic diffusion to identify the fire regions. Subsequently, Radial Basis Function Neural Network is employed in the design of the intelligent system, which is trained with the color space values of the segmented fire regions. Extensive experimental assessments on publicly available spatial data illustrated the efficiency of the proposed system in effectively detecting forest fires.

cs.OH↗
arXiv2010

IT in Power Sector A KPCL Implementation

In this paper we investigate the extent of Information Technology penetration in Power sector, taking KPCL, Karnataka Power Corporation Ltd., a premier power generating, a state owned public sector organization as an example. Any organization to flourish, adoption of Information Technology is inevitable in the days of fast changing technological advancements. It is not merely the investment on IT which helps but adoption of right IT solutions and the optimum use of the same does matter and becomes most critical. A strong infrastructure coupled with modern technical and management concepts has helped KPCL to meet the challenges of the rising energy demands of Karnataka.

cs.OH↗
arXiv2010

Comparative Results: Group Search Optimizer and Central Force Optimization

This note compares the performance of two multidimensional search and optimization algorithms: Group Search Optimizer and Central Force Optimization. GSO is a new state-of-the-art algorithm that has gained some notoriety, consequently providing an excellent yardstick for measuring the performance of other algorithms. CFO is a novel deterministic metaheuristic that has performed well against GSO in previous tests. The CFO implementation reported here includes architectural improvements in errant probe retrieval and decision space adaptation that result in even better performance. Detailed results are provided for the twenty-three function benchmark suite used to evaluate GSO. CFO performs better than or essentially as well as GSO on twenty functions and nearly as well on one of the remaining three. Includes update 24 February 2010.

cs.OH↗
arXiv2010

Effect of different substrates on Compact stacked square Microstrip Antenna

Selection of the most suitable substrate for a Microstrip antenna is a matter of prime importance. This is because many limitations of the microstrip antenna such as high return loss, low gain and low efficiency can be overcome by selecting an appropriate substrate for fabrication of the antenna, without shifting the resonant frequency significantly. The substate properties such as its dielectric constant, loss tangent have a pronounced effect on the antenna characteristics. Some of the critical properties that are to be taken care of while selecting a dielectric are homogeneity, moisture absorption and adhesion of metal- foil cladding. In this paper a comprehensive study of the effect of variation of substrate material on the antenna properties has been presented.

cs.OH↗
arXiv2010

Limited Memory Prediction for Linear Systems with Different types of Observation

This paper is concerned with distributed limited memory prediction for continuous-time linear stochastic systems with multiple sensors. A distributed fusion with the weighted sum structure is applied to the optimal local limited memory predictors. The distributed prediction algorithm represents the optimal linear fusion by weighting matrices under the minimum mean square criterion. The algorithm has the parallel structure and allows parallel processing of observations making it reliable since the rest faultless sensors can continue to the fusion estimation if some sensors occur faulty. The derivation of equations for error cross-covariances between the local predictors is the key of this paper. Example demonstrates effectiveness of the distributed limited memory predictor.

cs.OH↗
arXiv2010

FPGA Based Sinusoidal Pulse Width Modulated Waveform Generation for Solar (PV) Rural Home Power Inverter

With the increasing concern about global environmental protection and energy demand due to rapid growth of population in developing countries and the diminishing trend of resources of conventional grid supply, the need to produce freely available pollution free natural energy such as solar/wind energy has been drawing increasing interest in every corner of the world. In an effort to utilize these energies effectively through Power converter, a great deal of research is being carried out by different researchers / scientist and engineers at different places in the world to meet the increasing demand of load. The study presents methodology to integrate solar (PV) energy (which is freely available in every corner of the world) with grid source and supplement the existing grid power in rural houses during its cut off or restricted supply period. In order to get consistency in supply a DG is also added as a standby source in the proposed integration of network. The software using novel Direct PWM modulation strategy and its soft control features extend the flexibility to control converter (inverter) parameters like voltage, frequency, number of samples of PWM pulses constituting sine-wave without changing any hardware configuration in the circuit. The system simulation of PWM Pulse generation has been done on a XILINX based FPGA Spartan 3E board using VHDL code. The test on simulation of PWM generation program after synthesis and compilation were recorded and verified on a prototype sample.

cs.OH↗
arXiv2010

SVM Model for Identification of human GPCRs

G-protein coupled receptors (GPCRs) constitute a broad class of cell-surface receptors in eukaryotes and they possess seven transmembrane a-helical domains. GPCRs are usually classified into several functionally distinct families that play a key role in cellular signalling and regulation of basic physiological processes. We can develop statistical models based on these common features that can be used to classify proteins, to predict new members, and to study the sequence-function relationship of this protein function group. In this study, SVM based classification model has been developed for the identification of human gpcr sequences. Sequences of Level 1 subfamilies of Class A rhodopsin is considered as case study. In the present study, an attempt has been made to classify GPCRs on the basis of species. The present study classifies human gpcr sequences with rest of the species available in GPCRDB. Classification is based on specific information derived from the n-terminal and extracellular loops of the sequences, some physicochemical properties and amino acid composition of corresponding gpcr sequences. Our method classifies Level 1 subfamilies of GPCRs with 94% accuracy.

cs.OH↗
arXiv2010

Optimized reversible BCD adder using new reversible logic gates

Reversible logic has received great attention in the recent years due to their ability to reduce the power dissipation which is the main requirement in low power digital design. It has wide applications advanced computing, low power CMOS design, Optical information processing, DNA computing, bio information, quantum computation and nanotechnology. This paper presents an optimized reversible BCD adder using a new reversible gate. A comparative result is presented which shows that the proposed design is more optimized in terms of number of gates, number of garbage outputs and quantum cost than the existing designs.

cs.OH↗
arXiv2010

Determining the quality evaluation procedures using the expert systems

At this time, quality is a strategic instrument of the entities' global management, but it is also a determining element of their competitive spirit. The importance given to quality is abundantly found in the preoccupations of the European Union's Minister Board, by elaborating documents with a high impact over the quality of products/ services in special, and organizations in general. We live in an era, when the evolution of the social life puts the accent more and more on quality, resulted from various processes, at the level of various domains of the economical and social development.

cs.OH↗
arXiv2010

The Role of the XBRL Standard in Optimizing the Financial Reporting

When the financial information is difficult to produce, interpret, compare and analyze, we are put in the situation to face inconvenient consequences with negative repercussions, such as: the investor can give up the investment (with negative consequences on the risk equity market), the banks may not give loans, an auditor may not consider the financial statements as being credible etc. These facts allow the introduction of this paper's main objective, the eXtensible Business Reporting Language (XBRL) which is an open standard, independent and international for the treatments, opportunity, correctness, efficiency and minor costs of the financial and economical information. The XBRL will be analyzed in the second part of the paper, the history of this electronic communication language will be described, as there will also be described the promoting organizations, the base technology (the WEB and XML architecture which will be the next stage of the internet programming), and the role it has within the chain of reporting between the XBRL consortium and the international accounting organizations IASB-CI. This taxonomy serves clearly every accounting and extra- accounting information made by the company. This information which is treated in present by resorting to various formats or structures (most times incompatible between them and the owners) will be standardized with the XBRL.

cs.OH↗
arXiv2010

Equal Power Distribution and Dynamic Subcarrier Assignment in OFDM Using Minimum Channel Gain Flow with Robust Optimization Uncertain Demand

In this paper, the minimum channel gain flow with uncertainty in the demand vector is examined. The approach is based on a transformation of uncertainty in the demand vector to uncertainty in the gain vector. OFDM systems are known to overcome the impairment of the wireless channel by splitting the given system bandwidth into parallel sub-carriers, on which data-symbols can be transmitted simultaneously. This enables the possibility of enhancing the system's performance by deploying adaptive mechanisms, namely power distribution and dynamic sub-carrier assignments. The performances of maximizing the minimum throughput have been analyzed by MATLAB codes.

cs.OH↗
arXiv2010

Low-complexity Fusion Filtering for Continuous-Discrete Systems

In this paper, low-complexity distributed fusion filtering algorithm for mixed continuous-discrete multisensory dynamic systems is proposed. To implement the algorithm a new recursive equations for local cross-covariances are derived. To achieve an effective fusion filtering the covariance intersection (CI) algorithm is used. The CI algorithm is useful due to its low-computational complexity for calculation of a big number of cross-covariances between local estimates and matrix weights. Theoretical and numerical examples demonstrate the effectiveness of the covariance intersection algorithm in distributed fusion filtering.

cs.OH↗