A probabilistic multidimensional data model and its applications in business management

This dissertation develops a conceptual data model that can efficiently handle huge volumes of data containing uncertainty and are subject to frequent changes. This model can be used to build Decision Support Systems to improve decision-making process. Business intelligence and decision-making in today\u27s business world require extensive use of huge volumes of data. Real world data contain uncertainty and change over time. Business leaders should have access to Decision Support Systems that can efficiently handle voluminous data, uncertainty, and modifications to uncertain data. Database product vendors provide several extensions and features to support these requirements; however, these extensions lack support of standard conceptual models. Standardization generally creates more competition and leads to lower prices and improved standards of living. Results from this study could become a data model standard in the area of applied decisions sciences. The conceptual data model developed in this dissertation uses a mathematical concept based on set theory, probability axioms, and the Bayesian framework. Conceptual data model, algebra to manipulate data, a framework and an algorithm to modify the data are presented. The data modification algorithm is analyzed for time and space efficiency. Formal mathematical proof is provided to support identified properties of model, algebra, and the modification framework. Decision-making ability of this model was investigated using sample data. Advantages of this model and improvements in inventory management through its application are described. Comparison and contrast between this model and Bayesian belief networks are presented. Finally, scope and topics for further research are described

Body Area Networks

Recent technological advances in integrated circuits, wireless networks, and physiological sensing have enabled miniature, lightweight, low power, intelligent monitoring devices to be integrated into a Body Area Network (BAN). This new type of technology hold much promise for future patient health monitoring. BANs promise inexpensive, unobtrusive, and unsupervised ambulatory monitoring during normal daily activities for long periods of time. However, in order for BANs to become ubiquitous and affordable, a number of challenging issues must be resolved, such as integration, standardisation, system design, customisation, security and privacy, and social issues. This paper presents an overview of many of these issues and indeed the background and rationale of body area networks

Perception of Groundnuts Leaf Disease by Neural Network with Progressive Re-Sizing

India is the world's second-largest groundnut producer after Brazil. An major crop of oilseeds is groundnuts. Because of this, the crop's quality and yield have declined, which has had a detrimental effect on the agricultural economy. This is partly because the crop is more susceptible to various diseases. It is required to create more precise and reliable automated approaches to address this problem and improve the identification of groundnut leaf diseases. This article proposes a deep learning-driven approach based on a progressive scaling technique for the accurate classification and identification of groundnut leaf diseases. The five main groundnut leaf diseases that are the subject of this study are leaf spot, armyworm effect, wilts, yellow leaf, and healthy leaf. The proposed model is trained using both progressive resizing and conventional techniques, and its performance is assessed using cross-entropy loss. A fresh dataset is meticulously curated in Gujarat state, India's Saurashtra region, for training and validation. Due to the dataset's uneven sample distribution across disease categories, an extended focus loss function was used to correct this class imbalance. In order to evaluate the performance of the suggested model, a number of performance metrics are utilized, including accuracy, sensitivity, F1-score, precision, and sensitivity. Notably, the suggested model has a 96.12% success rate, which signifies a considerable increase in the disease identification accuracy. It's important to note that the model incorporating progressive resizing beats the basic neural network-based model based on cross-entropy loss, highlighting the potency of the recommended approach

Hall Effects on MHD Flow Through a Porous Straight Channel

The effect of Hall currents on the flow of a viscous incompressible slightly conducting fluid through a porous straight channel under a uniform transverse magnetic field is considered. The pressure gradient is taken as constant quantity and the case of steady flow is obtained by taking the time since the start of the motion to be infinite. Skin friction, temperature distribution and coefficients of heat transfer at both the plates have been evaluated. The effects of Hall parameter, magnetic parameter and Reynolds number on the above physical quantities have been investigated. Velocity distribution when the pressure gradient (i) varies linearly with time, and (ii) decreases exponentially with time has also been evaluated

Analysis of the Different Medicinal Leaf with Fractal Dimension

Fractal analysis has been applied to describe various aspects connected with the complexity of plant morphology. In this work we determined the fractal dimension of leaves from various species of Peepal leaf, Castrol oil leaf, papaya leaf in order to characterize the structure/architecture of these leaves. The present study deals with the analysis of leaf shapes in terms of fractal geometry with medicinal leaves using the techniques of Image Processing. In this work we determined the fractal dimension of different leaves. The results are very informative

Magneto Hydrodynamic Flow of a Viscous Incompressible Fluid Between a Parallel Flat Wall and a Long Wavy Wall

Magneto-hydrodynamic flow of a viscous incompressible slightly conducting fluid between a parallel flat wall and a long wavy wall has been studied. The velocity distribution, the coefficient of skin friction and temperature distribution has been evaluated. The effects of magnetic, suction and frequency parameters are investigated on velocity, the coefficient of skin friction and temperature distribution

ADAPTIVE ROUTING BASED ON DELAY TRUSTED ROUTING IN ADHOC NETWORK

Existing network hardware is constantly being improved and new communication technology continues to be developed. Together with the trend that computing hardware becomes smaller and portable, this network technology progress has led to dynamic networks. Next generation wireless networks are characterized as heterogeneous networks, particularly in terms of its underlying technology. One of the challenges of these heterogeneous networks is to manage handoff. Mobile IP is chosen for managing the handoff to accommodate the all-IP vision of the future interconnected networks. However, the handoff management of the mobile IP is mainly for data services where delay is not of a major concern. Therefore, it would be considerable challenge to achieve low latency handoff for real-time services. In this paper, we propose a multicasting scheme for delay-sensitive applications

Mass Transfer Effects on Unsteady Free Convective Flow Past an Infinite, Vertical Porous Plate with Variable Suction

A two-dimensional unsteady flow of a viscous incompressible dissipative fluid past an infinite, vertical porous plate with variable suction, is studied. Approximate solutions to the coupled non linear equations governing the flow are derived and expressions for the fluctuating parts of the velocity, the transient velocity, temperature and concentration, the amplitude and the phase of the skin-friction, and the rate of heat transfer, are derived. The effects of w(Omega)(frequency), Gr (Grashof number), Gc (modified Grashof number), Sc (Schmidt number), P (Prandtl number) and A (variable suction parameter), on the above physical quantities are calculated numerically and presented in figures and table. Problems of this nature find place in ablative cooling, transpiration and film cooling of rocket and jet engines

IMPLEMENTATION OF VOICE CALL TRANSFER SERVICE BETWEEN SMART PHONE AND TABLET THROUGH WI-FI

Communication through voice call leads to significant growth in technology in distant areas where two or more people from opposite ends of world will connect. This research describes a case study of voice call transfer service. This research aims at designing a system that will allow Android users to communicate over Wi-Fi. This design is able to transfer voice of incoming telephone caller over Wi-Fi network at real time through UDP. It uses client/server architecture: Server for receiving telephone call and transferring voice (one user) and client for receiving incoming caller voice and enables communication with server. Architecture designed could be used on Android smart phones with telephony enabled and tablets with telephony not enabled. Outcome of this research will allow users to communicate on real time at no cost. Proposed design gives cost effective, reliable and real time voice communication over Wi-Fi. It provides good and comfort experience to users in emergency situation where user cannot effort cost for telephone call. Proposed design is useful for educational organizations, construction buildings, shopping malls and hospitals which point to new possibilities for voice communication