542 research outputs found
Neelam Saxena Chandra: A Literary Luminary Bridging Languages and Genres
Get PDFNeelam Saxena Chandra, a prolific bilingual author, discusses her journey in poetry, literary influences, and creative process. She reflects on poetry as a medium for emotional expression and social change, sharing insights into her works, inspirations, and thoughts on gender sensitization and evolving poetic forms in contemporary literature
Trust Prediction: Use of Decision Tree in Training & Evaluation
No full textAbstract: The growth of Cloud Computing is the outcome of numerous benefits associated with this technology. Like: Reduce Energy consumption, waste & carbon emission and affluence & Comfort of its working apparatus. At the same point of time its security concern is making vibrations in the research Community and regulating organizations to find the means of making it a secure and reliable stream where consumers’ interests are ensured & protected. More uncertainty arises in this sector, when data theft cases are cracked up and consumers have compromised some confidential details due to intentional or unintentional action of Cloud providers. It leads the need of Trust evaluation of the provider. This trust evaluation should be in the quantitative terms and completed before selection & registration with the provider for cloud services. This paper is using predictive modeling technique to predict the trust level of the provider. Classification, a supervised Machine Learning technique that uses certification attainment status of the provider to predict its trust level.Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
© Copyright: All rights reserved
Marketing rural tourism: Experience and enterprise
No full textGunjan Saxena seeks to encourage a fuller understanding of rural tourism marketing by uncovering the lived experiences and enterprise of different actor groups as they respond to the impact of tourism on their communities and cultural identities. In so doing, the author makes a key contribution to the wider marketing discourse that circulates around place marketing and rural destinations
Functional relations involving generalized H-function
Get PDFA number of papers have appeared in literature in which certain functional relations associated with hypergeometric functions and Digamma function ψ(z) are derived. In order to unify and extend the existing results due to Kalla [7]. Kalla and Ross [9], Al-Saqabi and Kalla [1], Nishimoto and Saxena [12], Srivastava and Nishimoto [17] and Pandey and Srivastava [14] etc., the author establishes two functional relations between ψ(z) and generalized H -function due to Inayat-Hussain [6]. The results obtained are of general character and provide extension and unification of functional relations of various hypergeometric functions available in literature. Existence conditionsand computable representation of the H -function are also investigated.<br /
The evolving politics of labor standards in Bangladesh: taking stock and looking forward
No full textThis chapter provides a brief history of three or more decades of national and international efforts to improve labor standards for the workers in the garment industry. It concludes by looking forward to what could be done in the future. The author draws on her own research in this field to structure the wider literature on this topic. This chapter argues that any account of achievements and failures in relation to these efforts has to be embedded in the wider context in which the Bangladesh industry emerged and grew because this helps us to understand why its working conditions continue to fall short of international conventions and national regulations. While it faces the difficulties faced by any underdeveloped country with a limited history of industrialization and an industrial working class, Bangladesh has featured particularly prominently in international efforts to promote labour standards in global value chains in the garment sector. It can therefore provide an important case study of the challenges encountered by these efforts when the apparent protectionism of powerful global actors encounter the apparent intransigence of locally powerful actors
RoHeMaSys: Medical Revolution with Design and Development of Humanoid for Supporting Healthcare
No full textArchitectural & circuit level techniques to improve energy efficiency of high speed serial links
Get PDFHigh performance computing and communication are two key aspects of all information processing systems. With aggressive scaling of silicon technology enabling integration of a large number of transistors in a small area, managing power and thermal reliability has become very challenging. While lowering the power needed for performing computation has been the prime focus for decades, energy consumed for data transfer has recently become a major bottleneck especially in high performance applications. The focus of this thesis is on improving energy efficiency of communication links by exploring design techniques at both the architectural and circuit levels.
In the first part of this work, we propose a time-based equalization scheme to implement transmit de-emphasis in voltage-mode output drivers. Using two-level pulse-width modulation, it overcomes the tradeoff between impedance matching, output swing, and de-emphasis resolution in conventional voltage-mode drivers. A prototype PWM-based 5Gb/s voltage-mode transmitter was implemented in a 90nm CMOS process and characterized across different channels and output swings to demonstrate the effectiveness of proposed techniques. The horizontal/vertical eye openings (BER=) at the ends of 60inch and 96inch stripline channels are 78mV/0.6UI and 8mV/0.3UI, respectively. This transmitter achieves an energy efficiency of 3.1mW/Gb/s while compensating for 16-28dB channel loss, which compares favorably with the state-of-the-art.
In the second part, techniques to improve energy efficiency of a complete transceiver are presented. The transmitter employs a novel partially segmented voltage-mode output driver to lower power consumption in pre-drivers during 2-tap FIR equalization. The receiver implements a low power half-rate clock and data recovery with the proposed ring PLL based multi-phase sampling clock generation in CDR loop and charge-based sampling and deserialization. These techniques are verified using the measured results obtained from a 14Gb/s transceiver prototype. Transmitter achieves an energy efficiency of 0.89mW/Gb/s while securing a 0.36UI sampling time margin with at the end of the channel with 11dB loss at Nyquist frequency. The receiver recovers sampling clock with 1.8 long term absolute jitter while recovering 14Gb/s data at . The receiver achieves an energy efficiency of 1.69mW/Gb/s. Transmitter and receiver share an LC PLL, which achieves 0.605 integrated jitter at 7GHz output with an energy efficiency of 0.5mW/GHz. The transceiver as a whole achieves an energy efficiency of 2.8mW/Gb/s.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2017-12-01The student, Saurabh Saxena, accepted the attached license on 2015-11-16 at 16:11.The student, Saurabh Saxena, submitted this Dissertation for approval on 2015-11-16 at 16:37.This Dissertation was approved for publication on 2015-11-18 at 17:00.DSpace SAF Submission Ingestion Package generated from Vireo submission #8792 on 2016-03-02 at 14:13:10Made available in DSpace on 2016-03-02T21:06:32Z (GMT). No. of bitstreams: 2
SAXENA-DISSERTATION-2015.pdf: 5686569 bytes, checksum: 8aa8ea9b5016dcf7970fa62dc73973b8 (MD5)
LICENSE.txt: 4211 bytes, checksum: 69dd22c5bd2c8d283a935e663cca2b14 (MD5)
Previous issue date: 2015-11-18Embargo set by: Seth Robbins for item 91405
Lift date: 2018-03-02T21:07:27Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 91405 on 2018-03-03T10:15:31Z
Interpretable neural network with limited weights for constructing simple and explainable HI using SHM data
No full textRecently, companies all over the world have been focusing on the improvement of autonomous health management systems in order to enhance performance and reduce downtime costs. To achieve this, the remaining useful life predictions have been given remarkable attention. These predictions depend on the proper designing process and the quality of health indicators (HI) generated from structural health monitoring sensors based on prior established multiple prognostic evaluation criteria. Constructing such HIs from noisy sensory data demands powerful models that enable the automatic selection and fusion of features taken from those relevant measurements. Deep learning models are promising to autonomously extract features in scenarios with a huge volume of data without requiring considerable domain expertise. Nonetheless, the features established by artificial neural networks are complicated to comprehend and cannot be regarded as physical system characteristics. In this regard, the goal of this paper is to extend a new model; an interpretable artificial neural network that enables the automatic selection and fusion of features to construct the most appropriate HIs with remarkably fewer parameters. This model consists of additive and multiplicative layers that provide a feature fusion that better reflects the system’s physical properties. Additionally, the weights are discretized in two ways: a) using a ternary form with values {-1, 0, 1}, and b) relaxing the aforementioned ternary form by rounding the weights at the first decimal point in the range of [-1, 1]. Both discretization techniques have the ability to softly control the number of parameters that should be ignored. This trick guarantees interpretability for the neural network by extracting simple yet powerful equations representing the constructed HIs. Finally, the model’s performance is evaluated and compared with other approaches using a practical case study. The results show that the proposed approach's designed HIs are both interpretable and of high quality according to the criteria of the HI's evaluation.Structural Integrity & Composite
- …
