425 research outputs found
Structural, electronic transport and optical properties of Cr doped PbS thin film by chemical bath deposition
No full textA Comprehensive Review of Torque and Speed Control Strategies for Switched Reluctance Motor Drives
No full text[EN] Switched Reluctance Motors (SRMs), outfitted with rugged construction, good speed range, high torque density, and rare earth-free nature that outweigh induction motors (IM) and permanent magnet synchronous motor (PMSM), afford a broad range of applications in the domain of electric vehicles (EVs). Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs, which give them high efficiency in the range of 85-95%. Despite SRM's desirable features over traditional motor-speed drives, high torque ripples and radial distortions constrain their deployment in EVs. Precise rotor position is imperative for effective management of the speed and torque of SRMs. This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications. The various schemes were evaluated on their performance metrics-operational speed range, control complexity, practical realization, need for pre-stored parameters (lookup tables of current, inductance and torque profiles) and motor controller memory requirements. The findings provide valuable insights into balancing the gains and tradeoffs associated with EV applications. Furthermore, they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.This work was supported in part by the Universitat Politecnica de Valencia under grant PAID-10-21. This study was also supported through AMRITA Seed Grant (Proposal ID: ASG2022188)Sreeram, K.;Preetha, PK.;Rodríguez-García, Javier;Álvarez, Carlos (2025). A Comprehensive Review of Torque and Speed Control Strategies for Switched Reluctance Motor Drives. CES TRANSACTIONS ON ELECTRICAL MACHINES AND SYSTEMS. 9(1):46-75. https://doi.org/10.30941/CESTEMS.2025.00006S46759
Temporal Delta Layer: Training Towards Brain Inspired Temporal Sparsity for Energy Efficient Deep Neural Networks
No full textIn the recent past, real-time video processing using state-of-the-art deep neural networks (DNN) has achieved human-like accuracy but at the cost of high energy consumption, making them infeasible for edge device deployment. The energy consumed by running DNNs on hardware accelerators is dominated by the number of memory read/writes and multiplyaccumulate (MAC) operations required. As a potential solution, this work explores the role of activation sparsity in efficient DNN inference. As the predominant operation in DNNs is matrix-vector multiplication of weights with activations, skipping operations and memoryfetches where (at least) one of them is zero can make inference more energy efficient. Although spatial sparsification of activations is researched extensively, introducing and exploiting temporal sparsity is much less explored in DNN literature. This work presents a new DNN layer (called temporal delta layer) whose primary objective is to induce temporal activation sparsity during training. The temporal delta layer promotes activation sparsity by performing delta operation facilitated by activation quantization and l1 norm based penalty to the cost function. During inference, the resulting model acts as a conventional quantizedDNN with high temporal activation sparsity. The new layer was incorporated as a part of the standard ResNet50 architecture to be trained and tested on the popular human action recognition dataset (UCF101). The method caused 2x improvement in activation sparsity, with 5% accuracy loss.Electrical Engineerin
USING A K-NEAREST NEIGHBORS MACHINE LEARNING APPROACH TO DETECT CYBERATTACKS ON THE NAVY SMART GRID
No full textIn 2019, the Naval Facilities Engineering Command (NAVFAC) deployed the Navy smart grid across multiple bases in the United States. The smart grid can improve the reliability, availability, and efficiency of electricity supply. While this brings about immense benefit, placing the grid on a network connected to the internet increases the threat of cyberattacks aimed at intelligence collection, disruption, and destruction. In this thesis, we propose an Intrusion Detection System (IDS) for the NAVFAC smart grid. This IDS comprises a feature extractor, classifier, anomaly detector, and response manager. We use the K-Nearest Neighbors machine learning algorithm to show that various attacks (web attacks, FTP/SSH attacks, DOS, DDOS and port scanning) can be grouped into broader attack classes of Active, Denial, and Probe for appropriate response management. We also show that in order to reduce the load on the security operations center (SOC), the accuracy of the classifier can be maximized by optimizing the value of k, which is the number of data points nearest to the sample under consideration that decides the class assigned.Approved for public release. distribution is unlimitedOutstanding ThesisCommander, Republic of Singapore Navyhttp://archive.org/details/usingaknearestne109456605
Valluvar's Dependency Principle in Consciousness
No full textIn Arathuppaal, Valluvar creates a state of asceticism (by charity) and lays down the true principles. In the 36th chapter of Meiyunarthal' (Realization), he gives a very beautiful description of the realisation of the real object of God. This article examines only the single verse 359 in this authority. In this verse, the word 'Charbu' (dependency) occurs in two places. The word 'Charbu' that comes first denotes God. It also says to feel sfor him. The word 'Charbu' that comes second refers to the misfortunes that man earns. Valluvar says that if one wants to get rid of them, one should practise Ashtaanga Yoga (eight limbs of yoga). Valluvar says that if we practise in this way, all the vices that are waiting to torment us will be destroyed and the state of salvation will be attained. This article explains this message by quoting the sayings of sages, including Thirumoolar. This article emphasises that the purpose of human birth is to overcome birth. Through this, the virtue of wisdom to merge with God is realized. Recovering from the current selfish life, our soul becomes a loving soul and attains the maturity to respect the welfare of others. Love shown to other living beings becomes grace and honours human dignity
Kaviko's 'Ghazal' Songs - A Glimpse
No full textTwentieth century Tamil literature is considered to have reached the peak of social change. Such literary forms have in themselves an expression of sentiment similar to that of Sangam literature. Tamil Modern Poetry is based on the intellectual genre of Tamil that subtly conveys the call for social change. Traveling with the ideas of various creators, Tamil poetry is a field of study that is still appreciated today. Kavico Abdul Rahman is one of the few poets who can ever be thought of in the history of Tamil poetry. He has achieved many achievements through his socially conscious writing journey. His writings are profound, meticulously recording individual emotions. In his poetic works, poet Abdul Rahman has taken many new initiatives. One of them is the "ghazal" literary genre. It is a two-line song that is called "Kanni." These ghazals are mostly about love. Abdul Rahman wrote the ghazal in a new poetic style and sang it on all subjects. Out of the two volumes of poems, ‘A Letter from Minmini’, and ‘Secret Flower', written by him, only 'Rakasiyapoo' was taken as the subject of the study. Many poems, including love, God, philosophy, society, and fantasy, are included in the ghazal volume. They are resourceful in the aspect of cultivating minds. Therefore, this article is based on the above-mentioned subjects as sub-headings. 'Whenever my mind gets dirty, I bathe in poetry' is the ghazal of the poet. Each of his ghazals is a boon to the heart, forming a watery flower bed and giving pleasure
Effect of interphase permittivity on the electric field distribution of epoxy nanocomposites
No full textEvaluating Modified Soil Erodibility Factors with the Aid of Pedotransfer Functions and Dynamic Remote-Sensing Data for Soil Health Management
No full textSoil erosion is a critical factor impacting soil health and agricultural productivity, with soil erodibility often quantified using the K-factor in erosion models such as the universal soil loss equation (USLE). Traditional K-factor estimation lacks spatiotemporal precision, particularly under varying soil moisture and land cover conditions. This study introduces modified K-factor pedotransfer functions (Kmlr) integrating dynamic remotely sensed data on land use land cover to enhance K-factor accuracy for diverse soil health management applications. The Kmlr functions from multiple approaches, including dynamic crop and cover management factor (Cdynamic), high resolution satellite data, and downscaled remotely sensed data, were evaluated across spatial and temporal scales within the Fish River watershed in Alabama, a coastal watershed with significant soil–water interactions. The results highlighted that the Kmlr model provided more accurate sediment yield (SY) predictions, particularly in agricultural areas, where traditional models overestimated erosion by upto 59.23 ton/ha. SY analysis across the 36 hydrological response units (HRUs) in the watershed showed that the Kmlr model captured more accurate soil loss estimates, especially in regions with varying land use. The modified K-factor model (Kmlr-c) using Cdynamic and high-resolution soil surface moisture data outperformed the traditional USLE K-factors in predicting SY, with a strong correlation to observed SY data (R² = 0.980 versus R² = 0.911). The total sediment yield predicted by Kmlr-c (525.11 ton/ha) was notably lower than that of USLE-based estimates (828.62 ton/ha), highlighting the overestimation in conventional models. The identification of erosive hotspots revealed that 6003 ha of land was at high erosion risk (K-factor > 0.25), with an average soil loss of 24.2 ton/ha. The categorization of erosive hotspots highlighted critical areas at high risk for erosion, underscoring the need for targeted soil conservation practices. This research underscores the improvement of remotely sensed data-based models and perfects them for the application of soil erodibility assessments thus promoting the development of such models
Benthic ecology of selected prawn culture fields and ponds near Cochin
No full textIn the recent past, world-wide fishing effort has increased and the
resources must be approaching or must have already surpassed the maximum
sustainable yield. In this context, aquaculture assumes a significant
role as the next alternative to enhance food production. During the year
1993-94, export of marine products from India recorded an all time high
of 239918 hit valued at Ks. 2252.80 crores, of which 60,000 t was
contributed by prawns from lands under shrimp farming. The exploitation
of this economically significant group has reached an optimum level in
our waters. As a source of additional resource, aquaculture has been
resorted to which has a long recorded history in India and has been
traditionally practised in suitable low-lying areas
Investigations on fish and fisheries of Cochin backwaters in and around southwest monsoon period.
No full textThe fisheries sector has been accorded an important role in India's economic development plans. With the restrictions in the areas of exploitations of the marine fisheries by declaration of the Exclusive Economic Zone, and the need for meeting additional supplies of fish and earnings of foreign exchange, most of the countries have directed their attention and interests to brackishwater fish farming. India's potential brackishwater area for culture, based on various estimates is about 9 lakh ha of
which the present utilization is a meagre 2.91%
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