Freudian Notion of Psychoanalysis: Its Implications in Contemporary Teaching Practices

The author has engaged in a critical review of Frued's notion of psychoanalysis and its vitality in teaching.  Illustrating from Freud's own assertions and through the interpretations of the later critics, the author has pointed out certain noticeable pitfalls and, or incapacities of contemporary teaching practices. The forces of aggression and sex exert their influence through the unconscious drives to make teaching, holds Freud, one of the 'impossible' professions.  Impossibility of teaching does not imply an absolute failure of all what education stands for, but it refers to the challenges of the problematic nature of the profession. Teaching a child entails a tug of war between 'conscious self' and 'unconscious drives'. This tug of war is organized by ill-conceived notions of love, kindness, motherhood associated with teachers. On the contrary, the contemporary teaching practices are guided by coercive methods of subjugation, standardized tests and institutional control. None but the leaner suffers in this predicament. This is how more damage than the benefit is suspected from education. The author concludes that a more liberal environment can create a space for the leaner to appease the vulnerable impulses of sex and aggression without affecting the natural creativity which is probably the greatest intrinsic capital to invest for great gains. Frued's notion of psychoanalysis can be a means to an end but not an end in itself. It can defend teaching from failing in its pursuits; if the failure is predetermined, teachers may fail honorably rather than miserably

Adapted flower pollination algorithm for a standalone solar photovoltaic system

This Extraction of the maximum electrical power from a solar photovoltaic (PV) system under numerous weather conditions is required to reduce its payback time period, per unit energy price, and to compensate for the high initial price of the solar PV system. This could only be achieved by continuously operating the solar PV system at its maximum power point (MPP) under several weather conditions. Unlike under uniform weather conditions (UWC), identification of the real MPP (Global MPP) under partial shading condition (PSC) in a reasonable time is a challenging task due to the formation of multiple local MPP in the power-voltage (P-V) characteristic curve of a solar PV array. The nature-inspired MPP tracking algorithms have been proved suitable for global MPP tracking (MPPT) under PSC. In this research paper, a renowned nature-inspired flower pollination algorithm (FPA) is deeply reviewed, modified, and integrated with the random walk filter to improve its performance in terms of tracking speed, and efficiency. A comparison of the proposed ‘Adaptive Flower Pollination Algorithm (AFPA)’ and conventional FPA algorithm has been made under zero, weak, and strong PSCs for a 4S solar PV array. The proposed algorithm has produced remarkable results in tracking speed, and efficiency, for the global MPP (GMPP) tracking under different PSCs. The simulation is performed in MATLAB/Simulink software

Modified flower pollination algorithm for an off-grid solar photovoltaic system

This Operating the solar photovoltaic (PV) system at its maximum power point (MPP) under numerous environmental conditions to extract the maximum power is a challenging task. The challenge is to track the MPP, especially under partial shading conditions (PSC), where the formation of multiple MPP occurs in the characteristic curve of a PV array. Nevertheless, achieving this would benefit us with optimal power production, reducing the payback time and initial cost of the PV system. To perform this duty, an electronic circuit ruled by an algorithm is employed. The MPP tracking (MPPT) algorithms can be categorized into conventional and nature inspired. The conventional algorithms can successfully track the MPP under uniform weather conditions (UWC), and unable to identify the global MPP (GMPP) under PSC. However, the nature inspired algorithms possess the ability to perform efficiently under all weather conditions. Considering this strength of nature inspired algorithms, one of the top performing algorithms named as Flower pollination algorithm (FPA) is selected based on its brilliant searching strategy in adjacent and distant locations. In this paper, some structural modifications have been proposed in the FPA to further improve its searching capability and get more quick, accurate and efficient results for the MPPT of solar PV system. Results have proven the superiority of the proposed Modified FPA (MFPA) over the FPA in terms of efficiency, accuracy, tracking speed, energy conservation, economic saving, and payback time. Simulation is performed in MATLAB/Simulink

An Overview on Synthetic Biology: its Classification, Engineering Approaches, and Applications of Synthetic Biology

Synthetic biology is an interdisciplinary field that focuses on living organisms and systems, employing engineering techniques to create innovative biological devices, systems, and components. It represents the convergence of old and new approaches, bridging the gap between chemistry and biology, with synthetic chemistry laying the foundation for its emergence. At its core, synthetic biology aims to develop and engineer biological systems by bringing together engineers and biologists to design and construct novel biomolecular parts, circuits, and pathways. These constructs are then utilized to reconstruct, reanalyze, and reprogram organisms for various purposes. There are five primary categories within synthetic biology: bioengineering, synthetic genome, protocell synthetic biology, unconventional molecular biology, and in silico techniques. Traditionally, four engineering approaches have been employed in synthetic biology, including top-down, parallel, orthogonal, and bottom-up methods. These approaches provide a systematic and rational way of reassembling and reconstructing biological components, enabling the creation of functional biological devices, systems, and organisms with known, useful, and novel functions. Synthetic biology holds the promise of providing efficient solutions to various significant challenges in the modern world, encompassing areas such as chemicals, pharmaceuticals, agriculture, energy, and bioremediation. By leveraging engineering methods in the realm of biology, synthetic biology benefits from over 50 years of molecular biological and functional genomic research, along with advanced technologies that allow for the analysis, synthesis, assembly, modification, and transfer of genetic components into living organisms. In essence, synthetic biology offers an exciting avenue to unlock the potential of biological systems and revolutionize multiple industries through innovative modifications and breakthrough innovations

Frequency limited impulse response gramians based model reduction

In order to simplify the analysis of complex electronic systems, they needsto be modeled accurately. Model reduction is further required to streamline the procedural and computational complexities. Further the instability caused by the model reduction techniques worstly effects the accuracy of a system. Therefore, we have proposed some improvements in the frequency limited impulse response Gramians based model order reduction techniques for discrete time systems. The propsed techniques assures the stability of the model after it get reduced. The proposed techniques provided better results than the stability preserving techniques

Lamb Modes for an Isotropic Incompressible Plate

Lamb modes for an incompressible isotropic plate behave in a manner different from those for a compressible plate. The plateau region disappears and anomalous behavior of modes does not exist

Paclobutrazol Improves Sesame Yield by Increasing Dry Matter Accumulation and Reducing Seed Shattering Under Rainfed Conditions

Several biotic and abiotic stresses significantly decrease the biomass accumulation and seed yield of sesame crops under rainfed areas. However, plant growth regulators (such as Paclobutrazol) can improve the total dry matter and seed production of the sesame crop. The effects of the paclobutrazol application on dry matter accumulation and seed yield had not been studied before in sesame under rainfed conditions. Therefore, a two-year field study during 2018 and 2019 was conducted with key objectives to assess the impacts of paclobutrazol on leaf greenness, leaf area, total dry matter production and partitioning, seed shattering, and seed yield of sesame. Two sesame cultivars (TS-5 and TS-3) were treated with four paclobutrazol concentrations (P0 = Control, P1 = 100 mg L-1, P2 = 200 mg L-1, P3 = 300 mg L-1). The experiment was executed in RCBD-factorial design with three replications. Compared with P0, treatment P3 improved the leaf greenness of sesame by 17%, 38%, and 60% at 45, 85, and 125 days after sowing, respectively. However, P3 treatment decreased the leaf area of sesame by 14% and 20% at 45 and 85 days after sowing than P0, respectively. Compared with P0, treatment P3 increased the leaf area by 46% at 125 days after sowing. On average, treatment P3 also improved the total biomass production by 21% and partitioning in roots, stems, leaves, capsules, and seeds by 23%, 19%, 23%, 22%, and 40%, respectively, in the whole growing seasons as compared to P0. Moreover, under P3 treatment, sesame attained the highest seed yield and lowest seed shattering by 27% and 30%, respectively, compared to P0. This study indicated that by applying the paclobutrazol concentration at the rate of 300 mg L-1 in sesame, the leaf greenness, leaf areas, biomass accumulation, partitioning, seed yield, and shatter resistance could be improved. Thus, the optimum paclobutrazol level could enhance the dry matter accumulation and seed production capacity of sesame by decreasing shattering losses under rainfed conditions

Estimation of airship states and model uncertainties using nonlinear estimators

This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1− uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out

A Framework for Dynamic Selection of Backoff Stages during Initial Ranging Process in Wireless Networks

yesThe only available solution in the IEEE 802.22 standard for avoiding collision amongst various contending customer premises equipment (CPEs) attempting to associate with a base station (BS) is binary exponential random backoff process in which the contending CPEs retransmit their association requests. The number of attempts the CPEs send their requests to the BS are fixed in an IEEE 802.22 network. This paper presents a mathematical framework that helps the BS in determining at which attempt the majority of the CPEs become part of the wireless regional area network from a particular number of contending CPEs. Based on a particular attempt, the ranging request collision probability for any number of contending CPEs with respect to contention window size is approximated. The numerical results validate the effectiveness of the approximation. Moreover, the average ranging success delay experienced by the majority of the CPEs is also determined.The full text will be available at the end of the publisher's embargo: 7th Aug 201

Optimized hill climbing algorithm for an islanded solar photovoltaic system

Conventional energy generation technologies face unreliability due to the depletion of fossil fuels, soaring energy prices, greenhouse gas emissions, and continuously increasing energy demand. As a result, researchers are searching for reliable, cheap, and environmentally friendly renewable energy technologies. Solar photovoltaic (PV) technology, which directly converts sunlight into electricity, is the most attractive sustainable energy source due to the sun's ubiquitous presence. However, the non-linear behaviour of solar PV demands maximum power point tracking (MPPT) to ensure optimal power production. Although Hill Climbing (HC) is a simple, cheap, and efficient MPPT algorithm, it has a drawback of steady-state oscillations around MPP under uniform weather conditions. To overcome this weakness, we propose some modifications in the tracking structure of the HC algorithm. The proposed optimized HC (OHC) algorithm achieves zero steady-state oscillations without compromising the strength of the conventional HC algorithm. We applied both algorithms to an off-grid PV system under constant and changing weather conditions, and the results demonstrate the superiority of the proposed OHC algorithm over the conventional HC algorithm