228 research outputs found
A Novel Rate-2 Space Time Block Code & Implementation of its Decoder
No full textMaster of Engineering-ThesisWireless communications have been developed widely and rapidly in the modern world especially during the last decade. Recent advance ment in wireless communication systems has entailed the develop-ment of various coding technique.Through these coding techniques, the reliability of wireless communication has also been increased. Space time block codes have achieved the high spectral efficiency, low complexity and good error performance in continued research in this field.But still the demand of higher rate of transmission is endless. In this thesis, we present a new high rate space time block code for two transmit antenna and one receive antenna. The presented Space Time Block Code transmits two symbols per time slot. Hence the code achieves double data rate of transmission. Using QPSK modulation technique, a data rate of 4 bits/Hz/sec has been achieved instead of 2 bits/Hz/sec. It has been shown that if perfect channel state information is available at the receiver, thehigher rate of transmission can be achieved. In this thesis, we have designed a new decoder of the proposed code and implemented it on FPGA board to show the practicability of the decoder VHDL is used for the development of decoder.Results are simulated on ModelSim simulator. Synthesis report shows that complexity of decoder is approximately same as that of conventional methods. Practicability of the proposed rate- 2 Space Time Block Code has been proved in this thesis.Electronics and Communication, Thapar University, Patial
Nature, Nurture, and Empowerment: An Ecofeminist Reading of Utkarsh Patel’s Mythological Fiction Shakuntala: The Woman Wronged
No full textThe present research revisits the mythological fiction of Shakuntala: The Woman Wronged (2015) through an ecofeminist lens. Author Utkarsh Patel approaches the legendary tale of submissive Shakuntala and recreates it by arming her with the attributes of resilience, assertiveness, and compassion. Her deep bond with nature equips her with the strength to fight against patriarchal strictures. Based on the study of ecofeminism, this paper draws parallels between the exploitation of women and nature at the hands of mercenary and oppressive forces. An analysis of this work suggests that nature itself provides strength and succour and is also a source of empowerment. The strength gained through communion with nature allows her to make her voice heard. The ecofeminist perspective reveals how Shakuntala’s connection with nature offers her a sanctuary where she can explore her identity and voice, unimpeded by the norms that seek to suppress her. Her love for and defence of the environment transcends mere ecological concern—it becomes a catalyst leading to her transformation. Additionally, Shakuntala’s deep connection with Aranyani, the Forest Goddess, aligns with the concept of nature as a mother figure. By drawing attention to the intertwined dynamics of nature, nurture, and empowerment, this research celebrates and propagates the harmony between nature, feminine forces, and their transformative power
Risk Assessment of Cardiovascular Diseases Utilizing Individual Lifestyle Factors with Machine Learning Techniques
No full textDetermining the Activation Energy of Glucose Syrup Using the Arrhenius Equation
No full textThis experiment finds the activation energy of corn syrup using the Arrhenius equation. This was done through a simple experiment of dropping a ball into corn syrup and measuring its terminal velocity. From this, the viscosity could be derived, through the use of rearrangement of Newton’s First Law. The temperature of the corn syrup was also varied through the use of a microwave by raising it to 50 degrees Celsius. It is known that the more viscous a liquid is, the greater the activation energy for the liquid, which is essentially the energy barrier that a molecule has to overcome to travel, and thus the slower the liquid travel. Through linearization of the equation, it can be seen that graphing the inverse of temperature against the natural log of the viscosity, the equation of the slope would be equivalent to the activation energy over the universal gas constant. After conducting the experiment, it was proven that corn syrup has a very high activation energy, and thus is a very viscous liquid
ADAPTIVE REINFORCEMENT LEARNING-BASED TRAFFIC STEERING IN OPEN RAN: TOWARDS INTELLIGENT RESOURCE MANAGEMENT.
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Student Showcase – Satyagraha: The Right to Protest, The Responsibility to Resist Violence
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Finding Activation Energy of Corn Syrup
No full textThis experiment finds the activation energy of corn syrup using the Arrhenius equation. This was done through a simple experiment of dropping a ball into corn syrup and measuring its terminal velocity. From this, the viscosity could be derived, through the use of rearrangement of Newton’s First Law. The temperature of the corn syrup was also varied through the use of a microwave by raising it to 50 degrees Celsius. It is known that the more viscous a liquid is, the greater the activation energy for the liquid, which is essentially the energy barrier that a molecule has to overcome to travel, and thus the slower the liquid travel. Through linearization of the equation, it can be seen that graphing the inverse of temperature against the natural log of the viscosity, the equation of the slope would be equivalent to the activation energy over the universal gas constant. After conducting the experiment, it was proven that corn syrup has a very high activation energy, and thus is a very viscous liquid
Unlocking Business Potential in FMCG with Predictive Analytics: A Machine Learning Approach
No full textThe Fast-Moving Consumer Goods (FMCG) segment is one of the most important segments in the world economy comprising goods that can be sold quickly at rather low margin – foods & beverages, non food personal healthcare products, home care etc. Traditional models of the FMCG segment have burdened organizations with the problems of low sales forecast, customer actions examination, and stock manage. Many of these models are based upon historical sales data and last tendencies plus simple forecasting methods which do not reflect current market or consumer demands, seasonality, and variability of many aspects of supply chain. These challenges are addressed in this study by using advanced machine learning (ML) models and algorithms for decision-making process in the FMCG operations. Using the tools of predictive sales, customer behavior analysis using K-Means clustering and optimisation of an inventory through reinforcement learning, the paper gives a more comprehensive approach. In this paper, the authors highlight an integrated system for supply chain management and sales forecasting with the assistance of ML methods. The study focuses on three primary domains: forecasting of sales, understanding of the customer behaviour and the management of supply chain efficiently. In the first domain, five models of ML Linear Regression, Random Forest, Decision Tree, SVR, KNN was used to forecast the retail sales to which the Random Forest was exclusively identified as the most suitable model within the three performance indicators of RMSE as well as R². The second domain used K-Means clustering to assess customers’ behavior; this broke down the customers into three groups based on their retail, transfer and warehouse sales. These segments offered valuable information when it comes to the management of stock and sales outlets. The third domain was concerned with stock-up or stock-down decisions based on seasonal sales forecasts of the organisation’s products. Moreover, for the formation of an inventory control system, Reinforcement Learning was used to find the optimal between stock surplus and stockout, holding cost, and profit
Design of High-Speed High-Resolution SAR ADC Exploiting Inherent Residue Computation
No full textSuccessive Approximation Register (SAR) ADCs are popular in RF receiver front ends especially in cell-phone applications due its low power. SAR ADCs also enjoy performance improvement on moving to lower process nodes. IEEE802.11ac standard defines the highest bandwidth as 80 MHz. To have suitable margins for digital processing, the ADCs in the receiver require sampling speed of 320 MS/s with a signal to noise ratio of 8 - 10 bits to satisfy the noise budget. Increasing resolution is a challenge because one bit extension requires 2X increase in CDAC (Capacitive Digital to Analog Converter). With an increase in circuit area, it also increases the settling times. At higher speeds it becomes extremely critical to meet the timing specification of the SAR feedback loop. This research project aims to extend resolution at high speeds without increasing the CDAC size. Thus there is no additional timing constraint over the original SAR.
The SAR ADC is implemented in TSMC 40nm process. Schematic simulations show that it achieves a sampling speed of 320 MS/s with an SNDR of 58.4 dB (9.4 bits) at Nyquist. The power consumption reported is 10.23mW .Other than the digital logic for resolution extension it also involves a semi-synchronous digital logic which relaxes the timing requirements
Grid interactive bidirectional solar PV array fed water pumping system
No full textThis paper proposes a grid interactive bidirectional solar water pumping system using a three phase induction motor drive (IMD). A single phase voltage source converter (VSC) is used to direct the flow of power from grid supply to the pump and back to the grid from SPV array. A boost converter is used for the maximum power point tracking (MPPT) of the SPV array. A smart power sharing control is proposed, with preference given to the power from SPV array over the grid power. Moreover, the grid input power quality is also improved. Various modes of operation of the pump are elaborated and the performance of the system at starting, in steady state and dynamic conditions are simulated. The simulated results show the novelty and the satisfactory performance of the system
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