Abstract:
This paper presents an empirical, data-driven investigation of a novel StrongARM latch-based dynamic comparator designed and characterized in 20 nm CMOS technology. Dynamic comparators are the decision-making core of high-speed analog-to-digital converters (ADCs) and their delay, power, offset, and noise performance directly dictate converter accuracy and throughput. Building on the classical StrongARM regenerative topology, the proposed design introduces optimized transistor sizing, a modified tail-switching scheme, and a redistributed cross-coupled load to jointly reduce propagation delay, dynamic power, and kickback noise while limiting random offset voltage. Empirical characterization was carried out through simulation-based data collection across supply voltage sweeps, clock-frequency sweeps, 1000-run Monte Carlo mismatch analysis, and common-mode voltage sweeps, and the resulting datasets are summarized in five tabulated experiments. Quantitatively, the proposed 20 nm comparator achieves a 28.8% reduction in propagation delay, a 32.4% reduction in average power at 1 GHz, a 33.3% reduction in 3σ input-referred offset, and a 32.4% reduction in peak kickback noise relative to a 28 nm reference StrongARM design. These empirical results are discussed critically against prior published comparator architectures, confirming that node scaling combined with topology-level optimization yields compounding benefits beyond scaling alone. The findings validate the central claim of this study: architectural refinement of the StrongARM comparator at advanced 20 nm nodes provides a favorable, empirically verifiable trade-off among speed, power, and precision suitable for next-generation high-speed, low-power SAR and pipeline ADCs.
Area: Department of Electronics and Communication
Author: Anil Anant¹, Mr. Dhananjay Ingle²
DOI: MJAP/05/2057
Abstract:
Reinforced concrete (RC) structural elements are fundamental components in modern construction, bearing critical importance in determining the overall safety and durability of infrastructure. This empirical research paper presents a comprehensive investigation into the strength characteristics and behavioral patterns of reinforced concrete structural elements through both experimental testing and numerical simulation methodologies. The study encompasses a systematic evaluation of forty specimens under varying load conditions, incorporating different concrete grades (M20, M30, M40), reinforcement ratios, and geometric configurations. Advanced testing protocols were employed to monitor deflection, strain distribution, and failure mechanisms across all specimens. Parallel finite element analysis was conducted using industry-standard software to validate experimental observations and predict structural response under extreme loading scenarios. The research reveals significant correlations between concrete strength, reinforcement configuration, and overall element performance. Critical findings indicate that the interaction between concrete compressive strength and steel reinforcement provides a complex nonlinear relationship affecting ultimate load capacity. Numerical predictions demonstrated 94.3% accuracy when validated against experimental data, confirming the efficacy of the proposed modeling approach. The investigation identifies optimal reinforcement ratios and concrete compositions for enhanced structural efficiency. Results from this study contribute substantially to existing knowledge regarding RC structural behavior and provide practical guidelines for engineering design and optimization. The findings have direct applications in seismic-resistant design, sustainable construction, and bridge infrastructure development.
Area: Department of Structural Engineering
Author: Sachin Goswami1, Mr. Vivek Shukla2, Dr Jyoti Yadav3
DOI: MJAP/05/2056
Abstract:
Fifth-generation (5G) wireless communication networks represent a foundational architectural paradigm shift, engineered to deliver multi-gigabit per second peak data rates, sub-millisecond end-to-end latency, ultra-high reliability, and massive device connectivity across heterogeneous radio frequency spectra. This empirical research paper presents an exhaustive, quantitative performance analysis of standalone 5G New Radio (NR) deployments operating across mid-band Sub-6 GHz (3.5 GHz, Band n78) and millimeter-wave (28 GHz, Band n258) frequency spectra. Leveraging an enterprise-grade hardware testbed coupled with extensive metropolitan field drive-test campaigns, we systematically evaluate physical and transport layer key performance indicators, including downlink and uplink throughput, user-plane latency, jitter, block error rate (BLER), spectral efficiency, beamforming gains under massive Multiple-Input Multiple-Output (MIMO) array configurations, and radio frequency energy efficiency. Empirical findings reveal that mm Wave carriers achieve a peak downlink throughput of 4.18 Gbps over 400 MHz bandwidths under Line-of-Sight (LOS) conditions, but suffer steep propagation attenuation beyond 140 meters, exhibiting a 78.4% throughput reduction under Non-Line-of-Sight (NLOS) conditions. On the other hand, Sub-6 GHz carriers build better coverage: 620 Mbps at 450 meters The Ultra-Reliable Low-Latency Communication (URLLC) slice reached a mean one-way latency of 0.84 ms with 99.999% packet delivery reliability, meeting the strictest musts of industrial automation. Also, as massive MIMO antenna arrays were scaled from 8x8 to 128x128 elements, a SINR gain of 15.8 dB and spectral efficiency gains from approximately 5.8 bps/Hz to 38.1 bps/Hz were observed respectively. Finally, the integration of dynamic AI-enabled sleep modes achieved upto a 68.2% cut in base station energy consumption across low-traffic regimes, setting foundational empirical thresholds for future evolutions
Area: Department of Digital Communication
Author: Sachin Aggarwal¹, Dr. Bhawani Singh²
DOI: MJAP/05/2055
Abstract:
The P-Delta (P-Δ and P-δ) effect represents a critical second-order phenomenon influencing the stability, strength, and serviceability of steel frames subjected to combined gravity and lateral loads. While modern design codes mandate consideration of second-order effects, the differential impact of P-Delta on braced versus unbraced steel frames remains inadequately synthesized in existing literature. This review paper presents a comprehensive meta-analysis of past research spanning from 1990 to 2024 focusing on the comparative performance of braced and unbraced steel frames under lateral loading considering geometric nonlinearity[2]. A systematic search across Scopus, Web of Science, and ASCE Library identified 450 studies, from which 30 high-quality experimental, analytical, and numerical investigations were selected based on predefined inclusion criteria emphasizing frame typology, loading protocol, and consideration of P-Delta effects. Quantitative synthesis reveals that P-Delta effects amplify inter-story drift by 8-15% in concentrically braced frames (CBFs) and 18-42% in unbraced moment-resisting frames (MRFs) under design-basis earthquakes. The review critically evaluates evolution of analytical methods from conventional amplification factor approaches to direct analysis methods (DAM), and highlights inconsistencies in modeling assumptions, bracing configuration effects, and large-scale experimental validation. The findings underscore the necessity for enhanced stability design provisions, particularly for high-rise unbraced frames in seismic zones, and propose directions for integrated sustainability and robustness considerations[1].
Area: Department of Civil Engineering
Author: Ramsevak Vamne¹, Dr. Anudeep Nema²
DOI: MJAP/05/2054
Abstract:
Power electronic converters are the principal actuating and interfacing hardware of modern smart grids, coupling renewable generators, energy storage, electric vehicles, microgrids, and the bulk network through controlled dc-dc, dc-ac, and ac-dc stages. As converter-interfaced resources multiply, conventional fixed-gain and strictly model-based control methods struggle to preserve dynamic performance, efficiency, power quality, and grid-support functions under uncertainty, degradation, and rapidly changing operating conditions. This paper presents a systematic review and critical meta-analysis of past research on artificial-intelligence (AI)-based control and optimization of power electronic converters for smart-grid applications, covering 192 peer-reviewed studies published between 1990 and 2025. The corpus is organized into four methodological families: fuzzy logic control; neural-network and machine-learning methods; metaheuristic optimization; and (deep) reinforcement learning, with model predictive control treated as a hybrid bridge between model-based and learning-based design. Application domains spanning maximum power point tracking, grid-connected inverter control, microgrid and storage coordination, voltage regulation, and condition monitoring are consolidated, and reported performance gains are cross-compared. Beyond mapping the landscape, the review grades each study against five methodological quality criteria, ranging from hardware validation to statistical rigor, and quantifies how evidence quality varies across method families and application domains. Implications for researchers, developers, and standards bodies are drawn throughout. The critical meta-analysis exposes recurring weaknesses in past work: limited hardware validation, non-standardized benchmarks, weak reproducibility, insufficient statistical rigor, and inadequate safety guarantees. Prioritized research directions are identified to steer future efforts toward verifiable, certifiable, a
Area: Department of electrical and electronics engineering
Author: Hemraj Patel¹, Prabodh Khampariya²
DOI: MJAP/05/2053
Abstract:
Multilevel inverters (MLIs) are the key power-electronic interface for converting the direct-current (DC) power generated by variable renewable sources, in particular photovoltaic (PV) arrays and wind turbines, into grid-quality alternating-current (AC) power. This paper presents a comprehensive review and a quantitative meta-analysis of past work on the design and optimization of high-efficiency multilevel inverters for renewable energy applications. A systematic search of IEEE Xplore, Scopus, Web of Science, and ScienceDirect identified peer-reviewed studies published between 2000 and 2025, which were screened and coded for topology family, modulation strategy, optimization algorithm, validation method, and reported performance metrics; a total of 62 studies were included in the meta-analysis. Across all sampled designs, switching-angle schemes optimized with metaheuristic algorithms, including the genetic algorithm, particle swarm optimization, grey wolf optimizer, and their hybrids, consistently reduced total harmonic distortion (THD) by between 3.2 and 41.6 percent relative to conventional sinusoidal pulse-width-modulation baselines, while efficiency gains over unoptimized single-stage two-level converters ranged from 1.8 to 6.4 percentage points. Cascaded H-bridge topologies dominate low- and medium-power PV systems because of their modular structure, string-level maximum power point tracking, and low switching losses, whereas neutral-point-clamped and T-type configurations are preferred where a low component count and neutral-point balance are critical. The paper also synthesizes the evidence on voltage-stress reduction, soft-switching techniques, and digital-twin and hardware-in-the-loop validation practices, and it identifies the methodological gaps, notably the scarcity of published experimental validation and the absence of standardized efficiency metrics, that future research should address.
Area: Department of Electrical and Electronics Engineering
Author: Sumit Kumar Verma¹, Dr. Prabodh Khampariya²
DOI: MJAP/05/2052
Abstract:
The Sundarbans, the world's largest contiguous mangrove ecosystem shared between India and Bangladesh, has attracted sustained scholarly attention owing to its ecological, socio-economic, and climatic significance. Despite the growing volume of scientific output, a comprehensive quantitative mapping of this literature has remained limited, creating a gap between the pace of publication and the field's self-understanding of its own structure. This study addresses that gap by conducting a systematic bibliometric review of 1,102 peer-reviewed documents indexed in Scopus and Web of Science between 2005 and 2024, using performance analysis and science mapping techniques implemented through VOSviewer and Biblioshiny. The analysis quantifies annual publication growth, leading contributing countries and institutions, dominant subject categories, keyword co-occurrence networks, and citation patterns across the most influential journals. Results reveal an exponential rise in publication output after 2015, driven primarily by India and Bangladesh, with climate change, salinity intrusion, remote sensing, biodiversity conservation, and ecosystem services emerging as the dominant thematic clusters. The findings establish quantitative evidence for a shift in research emphasis from descriptive ecological surveys toward climate-vulnerability and geospatial modelling approaches over the past decade. By synthesizing three decades of scholarship into structured, tabular, and visual evidence, this paper builds a direct empirical link between historical research trajectories and future priorities, offering a data-grounded foundation for the conclusions and recommendations presented. The study contributes a replicable methodological framework for bibliometric assessment of ecologically critical but understudied regions and identifies concrete gaps for future interdisciplinary research on the Sundarbans.
Area: Department of Geography
Author: Dr. Anukul Ch. Mandal¹, Dr. Th. Devala Devi², Dr. Gouri Sankar Bhunia³
DOI: MJAP/05/2051
Abstract:
Miami-Dade County presents a critical case for understanding how organizations embed environmental management into operations within a coastal, climate-vulnerable, hyper-diverse metropolitan region. Rapid population growth, sea-level rise, saltwater intrusion into aquifers, and heat island intensification have elevated environmental governance from compliance exercise to existential infrastructure challenge. This empirical study examines SEM adoption across 320 organizations spanning manufacturing, hospitality, real estate development, municipal services, and port operations across Miami-Dade's three tiers: the central urban core (Miami proper), the intermediate suburban belt (Kendall, Westchester, Hialeah), and peripheral exurban communities (Florida City, Homestead, Princeton). Drawing on structured questionnaires, the analysis measures eight practice dimensions environmental policy, EMS certification, green procurement, waste and circular-economy initiatives, stormwater and water conservation, renewable energy, community/environmental-justice engagement, and staff training and regresses these against a sustainability performance index capturing resource efficiency, pollution reduction, regulatory compliance, climate adaptation capacity, and environmental justice outcomes. Results reveal uneven adoption (mean = 3.35), with significant performance gains for high adopters (r = 0.71; R² = 0.50), but stark disparities between affluent central Miami neighborhoods and underserved peripheral areas where industrial facilities, landfills, and port operations concentrate. The paper argues that SEM in Miami-Dade cannot succeed without explicit attention to environmental justice and climate resilience principles largely absent from the Western SEM literature. Policy recommendations center on building equitable, place-sensitive environmental capacity while integrating adaptation planning into municipal development frameworks.
Area: Department of Environmental Engineering
Author: Olaf Riedel
DOI: MJAP/05/2050
Abstract:
The increasing demand for renewable energy sources has intensified the focus on optimizing the performance of solar photovoltaic (PV) systems. A critical component for maximizing energy extraction is the Maximum Power Point Tracking (MPPT) system, which continuously adjusts the operating point of the PV array to harvest maximum power under prevailing conditions. This paper presents a comprehensive review of Adaptive Neuro-Fuzzy Inference System (ANFIS)-based MPPT strategies, a class of intelligent control algorithms that have demonstrated significant potential in enhancing PV efficiency. The review synthesizes findings from recent research, highlighting the evolution from conventional MPPT techniques like Perturb and Observe (P&O) and Incremental Conductance (IncCond) to more advanced AI-driven approaches. ANFIS, by integrating the learning capabilities of neural networks with the rule-based reasoning of fuzzy logic, offers superior adaptability to dynamic environmental conditions such as varying solar irradiance and temperature, and is particularly effective in mitigating issues like partial shading. Studies consistently report high tracking efficiencies, often exceeding 99%, for ANFIS-based MPPT controllers, with advantages including faster convergence times, reduced steady-state oscillations, and improved global maximum power point (GMPP) detection compared to traditional methods. This review critically analyzes various ANFIS implementations, discussing their architectures, training methodologies, and performance metrics. It also explores hybrid approaches combining ANFIS with metaheuristic algorithms and advanced control strategies, and identifies avenues for future research to further refine these advanced MPPT strategies for robust and efficient solar energy harvesting in real-world applications.
Area: Department of Electrical and Electronics Engineering
Author: Varsha Nagle¹, Prabhodh Khampariya²
DOI: MJAP/05/2007
Abstract:
Aging reinforced concrete (RC) multi-storey infrastructure across high-seismic zones in India exhibits severe vulnerability under revised seismic demand criteria established by IS 1893 (Part 1):2016. This empirical investigation evaluates the seismic adequacy of an existing G+10 residential RC frame building situated in Seismic Zone IV (peak ground acceleration PGA = 0.24g) on medium soil (Type II), originally constructed in accordance with legacy IS 1893:1984 provisions. In-situ destructive and non-destructive material evaluations, including concrete core extraction and ultrasonic pulse velocity testing, established a baseline concrete compressive strength of 20 MPa and rebar yield strength of 415 MPa. Three-dimensional finite element modeling and non-linear static pushover analysis conducted in accordance with ATC-40 and FEMA 356 protocols revealed that the existing bare frame experiences an excessive roof lateral displacement of 66.8 mm and a maximum inter-storey drift ratio of 0.54%, directly violating the codal limit of 0.40% and locating the building at the Collapse Prevention (CP) performance limit state. To remediate these structural deficiencies, three distinct seismic retrofit strategies were empirically appraised: Carbon Fiber Reinforced Polymer (CFRP) confinement, Reinforced Concrete (RC) column jacketing, and concentric Steel X-bracing. Structural response data demonstrate that concentric Steel X-bracing achieves superior performance, reducing peak lateral displacement to 31.2 mm (a 53.3% reduction) and maximum drift to 0.21%, while elevating the base shear capacity by 97.2% (from 1410 kN to 2780 kN) and shifting the global performance state to Immediate Occupancy (IO) with a modest structural mass increase of 3.2%, establishing it as the optimal techno-economic retrofit solution for Indian urban building stock.
Area: Department of Structural Engineering
Author: Abhiranjan Kumar¹, Mrs. Kamni Laheriya²
DOI: MJAP/05/2006
Abstract:
This review surveys and meta-analyses five decades of work at the confluence of three programmes: character sheaves on commutative group schemes and group ind-schemes, the local Langlands correspondence for an algebraic torus T over a non-archimedean local field F, and the inertial refinement classifying smooth characters by the restriction of their parameter to the inertia subgroup I_F. Writing LT for the loop ind-scheme colim_n T_n attached to T and CS(LT) for the Picard groupoid of multiplicative rank-one local systems on it, the central object of study is the comparison square asserting that the sheaf-function dictionary applied to the Contou-Carrère Fourier transform agrees with Langlands' isomorphism composed with dualisation. We formalise thirty contributions through a coding of formal invariants: object class, ambient triangulated category, dualising functor, hypotheses on residue characteristic and on the splitting field, and the type of inertial output. On that basis we reconstruct the logical dependency skeleton of the field, quantify its thematic and chronological structure, and audit which asserted compatibilities carry explicit proofs. Our principal mathematical synthesis is the statement that for a split torus in equal characteristic the depth filtration on CS(LT) matches the upper-numbering ramification filtration on H^1 (W_F,T-dual), so that the inertial correspondence is realised by a filtered equivalence of Picard groupoids rather than by an imported bijection. Four gaps are isolated: wild ramification in mixed characteristic, non-standardised normalisations, the absent geometry of norm maps for non-split tori, and the missing comparison functor to categorical local Langlands on the Fargues-Fontaine curve.
Area: Department of Mathematics
Author: Pankaj Kumar Tiwari¹, Dr. Praveen Kumar Mathur²
DOI: MJAP/05/2005