bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy loss of monopolium in a medium
Authors: Fanchiotti Huner , Canal Carlos A. García , Vento Vicente
Published: September 2023

We study the energy loss of excited monopolium in an atomic medium. We perform a classical calculation in line with a similar calculation performed for charged particles which leads in the non-relativistic limit to the Bethe–Bloch formula except for the density dependence of the medium, which we do not consider in this paper. Our result shows that for maximally deformed Rydberg states, the ionization of monopolium in a light atomic medium is similar to that of light ions.
A review of mathematical and computational aspects of CSIDH algorithms
Authors: Maino Luciano , Mula Marzio , Pintore Federico
Published: September 2023

CSIDH is a post-quantum key-exchange scheme based on the action of ideal class groups on supersingular elliptic curves over prime fields. Its short keys and ciphertexts, together with its flexibility as a building block to construct complex cryptographic primitives, has motivated significant research on the efficiency of CSIDH and its resistance against side-channel attacks. In this work, some cutting-edge results from recent contributions are reviewed in a unified treatment, focusing on the mathematical ideas lying behind them rather than on cryptographic and low-level implementation techniques. In particular, we first describe ways to speed up the class-group-action evaluation, which range from the use of different models of elliptic curves to working with different ideal class groups. We then survey some constant-time variants of CSIDH, that make the time and memory consumption during the computation of a public/shared key independent of the secret key. Finally, we examine the computation of the ideal class action when the structure of the ideal class group is known, which is the case for a specific set of CSIDH parameters.
Inferring Real Mobility in Presence of Fake Check-ins Data
Authors: Gao Qiang , Fu Hongzhu , Zhang Kunpeng , Trajcevski Goce , Teng Xu , Zhou Fan
Published: September 2023

Understanding human mobility has become an important aspect of location-based services in tasks such as personalized recommendation and individual moving pattern recognition, enabled by the large volumes of data from geo-tagged social media (GTSM). Prior studies mainly focus on analyzing human historical footprints collected by GTSM and assuming the veracity of the data, which need not hold when some users are not willing to share their real footprints due to privacy concerns—thereby affecting reliability/authenticity. In this study, we address the problem of Inferring Real Mobility (IRMo) of users, from their unreliable historical traces. Tackling IRMo is a non-trivial task due to the: (1) sparsity of check-in data; (2) suspicious counterfeit check-in behaviors; and (3) unobserved dependencies in human trajectories. To address these issues, we develop a novel Graph-enhanced Attention model called
IRMoGA
, which attempts to capture underlying mobility patterns and check-in correlations by exploiting the unreliable spatio-temporal data. Specifically, we incorporate the attention mechanism (rather than solely relying on traditional recursive models) to understand the regularity of human mobility, while employing a graph neural network to understand the mutual interactions from human historical check-ins and leveraging prior knowledge to alleviate the inferring bias. Our experiments conducted on four real-world datasets demonstrate the superior performance of IRMoGA over several state-of-the-art baselines, e.g., up to 39.16% improvement regarding the Recall score on Foursquare.
Optimal Polynomial-Time Compression for Boolean Max CSP
Authors: Jansen Bart M. P. , Włodarczyk Michał
Published: September 2023

In the Boolean maximum constraint satisfaction problem—
Max CSPΓ
—one is given a collection of weighted applications of constraints from a finite constraint language Γ, over a common set of variables, and the goal is to assign Boolean values to the variables so that the total weight of satisfied constraints is maximized. There exists a concise dichotomy theorem providing a criterion on Γ for the problem to be polynomial-time solvable and stating that otherwise, it becomes NP-hard. We study the NP-hard cases through the lens of kernelization and provide a complete characterization of
Max CSPΓ
with respect to the optimal compression size. Namely, we prove that
Max CSPΓ
parameterized by the number of variables
n
is either polynomial-time solvable, or there exists an integer
d
≥ 2 depending on Γ, such that:

(1)

An instance of
Max CSPΓ
can be compressed into an equivalent instance with 𝒪(

n
d

log
n
) bits in polynomial time,

(2)

Max CSPΓ
does not admit such a compression to 𝒪(
n
d-ε
) bits unless NP ⊆ co-NP / poly.

Our reductions are based on interpreting constraints as multilinear polynomials combined with the framework of “constraint implementations”, formerly used in the context of APX-hardness. As another application of our reductions, we reveal tight connections between optimal running times for solving
Max CSPΓ
. More precisely, we show that obtaining a running time of the form 𝒪(2

(1-ε)
n

) for particular classes of
Max CSP
s is as hard as breaching this barrier for

Max
d
-SAT

for some
d
.
Explainable Deep Learning Methods in Medical Image Classification: A Survey
Authors: Patrício Cristiano , Neves João C. , Teixeira Luís F.
Published: September 2023

The remarkable success of deep learning has prompted interest in its application to medical imaging diagnosis. Even though state-of-the-art deep learning models have achieved human-level accuracy on the classification of different types of medical data, these models are hardly adopted in clinical workflows, mainly due to their lack of interpretability. The black-box nature of deep learning models has raised the need for devising strategies to explain the decision process of these models, leading to the creation of the topic of eXplainable Artificial Intelligence (XAI). In this context, we provide a thorough survey of XAI applied to medical imaging diagnosis, including visual, textual, example-based and concept-based explanation methods. Moreover, this work reviews the existing medical imaging datasets and the existing metrics for evaluating the quality of the explanations. In addition, we include a performance comparison among a set of report generation–based methods. Finally, the major challenges in applying XAI to medical imaging and the future research directions on the topic are discussed.
Incomplete Multiview Clustering via Semidiscrete Optimal Transport for Multimedia Data Mining in IoT
Authors: Gao Jing , Li Peng , Laghari Asif Ali , Srivastava Gautam , Gadekallu Thippa Reddy , Abbas Sidra , Zhang Jianing
Published: September 2023

With the wide deployment of the Internet of Things (IoT), large volumes of incomplete multiview data that violates data integrity is generated by various applications, which inevitably produces negative impacts on the quality of service of IoT systems. Incomplete multiview clustering (IMC), as an essential technique of data processing, has the potential for mining patterns of incomplete IoT data. However, previous methods utilize notion-strong distances that can only measure differences between distributions at the overlap of data manifolds in fusing complementary information of data for pattern mining. They may suffer from biased estimation and information loss in capturing intrinsic structures of incomplete multiview data. To address these challenges, a semidiscrete multiview optimal transport (SD-MOT) is defined for IMC, which utilizes distances with weak notions to capture intrinsic structures of incomplete multiview data. Specifically, IMC is recast as an equivalent optimal transport between continuous incomplete multiview data and discrete clustering centroids, to avoid the strict assumption on overlap between manifolds in pattern mining. Then, SD-MOT is instantiated as a deep incomplete contrastive clustering network to remedy biased estimation and information loss on intrinsic structures of incomplete multiview data. Afterwards, a variational solution to SD-MOT is derived to effectively train the network parameters for pattern mining. Finally, extensive experiments on four representative incomplete multiview datasets verify the superiority of SD-MOT in comparison with nine baseline methods.
Experimental Study and Numerical Simulation of the Effect of Rigid Pile Composite Foundations on Slab Culverts
Authors: Wang Xiqing , Feng Zhongju , Wang Siqi , Wang Wei
Published: September 2023

For culverts installed in soft soil, the rigid composite pile foundation is used for soil treatment, and the stresses around the culverts are complicated. Centrifuge experiments and numerical simulations are conducted to investigate the vertical earth pressures and soil settlement over a slab culvert under high backfill in soft soil, and the foundations are treated with rigid composite piles. The influences of lateral pile length and pile spacing on the earth pressures at the top of the culvert are analysed, and they have significant effects on the vertical earth pressure coefficients. It also indicates a strong correlation between the backfill height and the vertical earth pressure coefficients. For a high-backfill culvert, there is a uniform settlement surface where the settlement of the interior and exterior soil prisms is at the same level. According to the experiments, the height of the uniform settlement surface and the vertical earth pressures decrease with increasing the lateral pile length and pile spacing. Numerical simulations were conducted using finite element software Midas GTS to evaluate the performance of the experiments. Further, recommendations for selecting an appropriate pile composite foundation for slab culvert in soft soil are provided.
JNK- and Rel-Mediated Regulation of Inflammation and Neurotoxicity in Nauphoeta cinerea Exposed to Methylmercury and Monosodium Glutamate
Authors: Obafemi Blessing A. , Adedara Isaac A. , Segatto Ana L. A. , Souza Diogo O. , da Rocha João B. T. , Olagoke Olawande C.
Published: September 2023

Food contaminants are closely monitored to establish food safety profiles. Previously, we used the lobster cockroach to delineate the oxidative and antioxidant activities that characterize exposure to the organometallic cation (methylmercury; MeHg) sometimes found in fish and the common cooking seasoning (NaCl and MSG). Here, we further examined the mechanism of inflammatory response to MeHg, NaCl, and MSG, in an attempt to establish the crosstalk between redox and inflammatory signaling during heavy metal exposure in food. The insects were exposed to diets contaminated with MeHg, NaCl, and MSG for 21 days. Subsequently, mRNA from head homogenate was used to quantify the expression of a member of the Nox/Duox NADPH oxidases that produce reactive oxygen species (DUOX), as well as target genes of the JNK, TOLL, and UPD3/JAK/STAT pathways. MeHg exposure deregulated redox and inflammation-related genes, including upregulated DUOX in the MeHg group, upregulated Reaper, UPD3, and SOCS36E in the MeHg + NaCl group, and downregulated Reaper in the MeHg + MSG group. Both MeHg + NaCl and MeHg + MSG exposures upregulated PVF, EGR, and REL and downregulated FOXO levels. Our results suggest a role for the activation of the Nox/Duox NADPH oxidases, alongside JNK and Rel signaling during MeHg and MSG exposure, therefore offering insights for handling heavy metal poisoning and showcasing Nauphoeta cinerea as a viable model for understanding redox and inflammatory signaling.
Species-Specific Allometric Equations, Biomass Expansion Factor, and Wood Density of Native Tree Species in the Dry Afromontane Forest of Ethiopia
Authors: Egeta Dereje , Negash Mesele , Alebachew Mehari , Eshete Abeje , Mulugeta Sinke , Lemi Tamiru
Published: September 2023

A forest is a storehouse of carbon released from different sources when the activities of sustainable forest management, planting, and rehabilitation exist. However, few allometric equations are present to determine its contribution to carbon reduction. The target of the study was to develop species-specific allometric equations and establish a database for biomass expansion factor and wood density for five tree species grown in the dry Afromontane forest of Ethiopia. A direct or destructive sampling method was used on 62 trees from different diameter classes. The diameter at breast height and the total height of selected trees ranged from 7 to 48 cm and 6.7 to 23.4 m, respectively. Trees were felled and divided into various biomass sections. Stem and big branch discs were sampled to determine the wood density and volume of the trees. Sample wood and foliage were oven-dried for three days and two days at 105°C and 70°C, respectively, to get their dry weight. Total above-ground biomass was regressed using diameter at breast height, total height, wood density, and average crown diameter as independent variables. R software version 4.0.1 was used to fit the biomass equations. The best biomass models were determined to have lower AIC and RSE and highest adj. R2. The biomass expansion factor and wood density of five tree species ranged from 1.19 to 1.40 and 0.53 to 0.74 g/cm−3, respectively. Species-specific allometric equations were better than both mixed species and pan tropical models for the assessment of above-ground biomass in the Chilimo dry Afromontane forest of Ethiopia.
Effective metal shields of high voltage distribution cable lines
Authors: Popovic Ljubivoje M.
Published: September 2023

The presented methodology enables determining induced currents and voltages relevant to the correct estimation of security conditions required in operating and maintenance of the metal installations surrounding high-voltage distribution cable lines. It is based on the on-site measurements of currents appearing in two phase conductors of the considered cable line during a simulated ground fault in the supplied substation. Their values are utilized to compensate for the deficiency of all relevant but unknown data concerning the surrounding metal installations. It was done by introducing an equivalent cable shield substituting, from the standpoint of inductive influence, all surrounding metal installations. Here is shown that this equivalent shield can be determined in such a way that it becomes identical from the standpoint of its appearance to the actual cable line shield but with a changed value of its longitudinal resistance. When this value is determined for single-core cables belonging to a certain cable line it becomes possible to determine the actual reduction factor, inductive influence, and sequence impedance of the considered cable line by using a standard and well-known calculation procedure.
Evaluation of energy management system of a hybrid energy source in EV
Authors: Touileb Rachid , Abbou Ahmed
Published: September 2023

This paper presents a comparative study of different energy management strategies and technologies of fuel-cell hybrid electric vehicles integrating a proton exchange membrane fuel cell device in addition to a lithium-ion battery as a secondary energy source. Therefore, an experimental analysis is carried out to seek the successful hybrid powertrains considering the hydrogen utilization in fuel cells and state-of-charge regulation in Li-ion batteries. Different approaches were simulated using a developed vehicle simulator in MATLAB/Simulink. The simulations were performed using three standard driving cycles in which a second study based on energy management strategies tested was presented and analyzed. Simulation’s results show the superiority and economic success of the proposed technology and method, especially the FSBS and MEPT management strategies due to the successful use of the sources and the significant optimization in terms of hydrogen consumption while maintaining optimal Li-ion battery usage.
FOPID controlled PV based QBC fed gamma Z-source inverter applicable for pump operations in an induction motor drive
Authors: Selvaraj Krishnan , David Anbarasi Jebaselvi Gnanaiah , Sathi Rama Reddy , Kuppusamy Pradeepa
Published: September 2023

A closed loop current mode-fractional-order-PID (CM-FOPID) controlled and PV based quadratic-boost-converter (QBC) fed gamma Z-Source Inverter with Induction motor system (PV-QBC-GZSI-IMS) for pump operation is proposed here. This work recommends a combination of QBC with gamma Z-source-inverter between the DC link source and asynchronous motor system. This will reduce the voltage rating of PV panel and its initial cost. GZSI reduces the current spikes in stator current. The objective of this research work is to regulate the speed of PV-QBC-GZSI-IMS. This effort deals with the closed loop response of PV-QBC-GZSI-IMS accompanied by current-mode-proportional integral (CM-PI) and CM-FOPID controllers. The performance investigations are analyzed with the control of QBC fed Gamma Z-source inverter with motor load using CM-PI and CM-FOPID controllers and the detailed comparison has been presented. MATLAB/Simulink outputs obtained with their respective speed and torque characteristics in time domain have been depicted. The closed loop CM-FOPID control of PV-QBC-GZSI-IMS is superior to the closed loop CM-PI control of PV-QBC-GZSI-IMS. The proposed QBC-converter reduces the voltage rating of PV panel and GZSI reduces current spikes in motor. The novelty of the article is to enhance the dynamic response of PV-QBC-GZSI-IMS using FOPID. The steady state error in torque is reduced to 0.52 N-m using FOPID.
Evaluation of the possibility of chaos for doubly-fed induction generator in wind power generation system
Authors: Van Co Nhu , Quang Nguyen Phung , Hai Nguyen Thanh
Published: September 2023

The doubly-fed induction generator (DFIG) has the advantages of compactness and low cost, so it has been applied more and more in practice. However, the structure of the DFIG system is complex, multivariable, nonlinear, and difficult to control. Chaos is a phenomenon that only occurs with nonlinear dynamical systems, sensitive to initial conditions and aperiodic but it is governed by deterministic laws, unlike random perturbations. For most powertrain systems, chaos causes disadvantages, reduce performance, and even destruction of the system. By method of analysis based on theory and simulation, the paper will demonstrate the chaotic phenomenon for DFIG when the parameters of the system change into a certain value. From that set of parameters, the controller is designed to avoid or eliminate that chaotic behavior, so that the system works more reliably and with better quality.
Artificial intelligence-enhanced DTC command methods used for a four-wheel-drive system
Authors: Max Ndoumbé Matéké , Eric Njock Batake Emmanuel , Maurice Nyobe Yomé Jean , Jordan Mouné Cédric , Moise Manyol , Georges Olong , Biboum Alain
Published: September 2023

This paper presents an artificial intelligence direct torque control (DTC) method for an electric vehicle (EV) drive system. The architecture of the proposed electric vehicle is that of four wheels each with an induction motor (IM). A comparative study of the different torque and speed controllers proposed in this paper is made. An electronic differential is used to control the speed of each wheel as well as a variable master-slave control (VMSC) for the management of the magnetic quantities because the motors on the same side are fed by the same converter. This study allows highlights the performance of the propulsion system in terms of dynamics and safety of the vehicle and better stability. The different controllers are implemented by the MATLAB/Simulink software and the simulation results obtained show better flexibility in the control of the vehicle. It is worth noting that direct torque control with fuzzy logic (DTFC) performs better than DTC associated with neural networks in terms of a time reduction increase of 1.47%, an overshoot of less than 5.33, and a static steady-state error close to zero.
Low-cost platform for real time data acquisition and fractional control with application to a DC motor
Authors: Berkani Hemza Abdel Fettah , Keziz Bouziane , Lashab Mohamed , Djouambi Abdelbaki , Kerouche Abdelfetah
Published: September 2023

This paper presents a low-cost experimental platform for real time data acquisition, identification and fractional order control of some low dynamic systems using Arduino-Simulink interface. As a demonstrative example, a DC motor is considered and modeled as a first order plus time delay plant (FOPTD) using data acquisition-based Arduino setup. Then, simple analytical rules are used to design a robust fractional order controller (FOC) which required a high-performance computing. Several validation tests have been carried out using Arduino–Simulink interface. The comparison between the theoretical simulation and the experimental tests confirms that the proposed interface can be used to support research and teaching of feedback control systems using experimental tests and low-cost laboratory kit.
Biopotential multi-path current feedback instrumentation amplifier with automatic offset cancellation loop for resistive bridge microsensors
Authors: Laababid Younes , El Khadiri Karim , Tahiri Ahmed
Published: September 2023

This study introduces a refined current feedback instrumentation amplifier (CFIA) specifically designed for amplifying biopotential signals that originate from resistive-bridge sensors. The proposed architecture uniquely incorporates a multipath chopper-stabilized CFIA which has been developed to minimize the effects of bridge offsets, while maintaining low power usage, high input impedance, and reduced noise characteristics. The engineering blueprint employs a ripple reduction loop (RRL) to mitigate output ripple caused by chopper up-modulation. To speed up offset cancellation and to limit the offset caused by bridge mismatch, an automatic offset cancellation loop (AOCL) circuit is integrated within the analog front end (AFE). Crafted using a conventional 0.18 µm CMOS process, the CFIA in this design provides adjustable gain between 20.35 dB to 55.14 dB, with a power supply rejection ratio (PSRR) and a common mode rejection ratio (CMRR) of 103 dB and 114 dB, respectively. The system demonstrates an input-referred noise (IRN) value of 16 ηV/√Hz at 200 Hz frequency, equivalent to a noise efficiency factor (NEF) of 5.18. Operating from a supply voltage of 1.8V, the AFE shows a power consumption of 291 μW.
A novel method of overvoltage suppression due to de-energization of shunt reactor in high voltage system
Authors: Al-Tak Mazyed A. , Ain Mohd Fadzil Bin , Al-Yozbaky Omar Sh. , Jamil Mohamad Kamarol Mohd
Published: September 2023

Substations usually employ shunt reactors to reduce the reactive power of systems. Due to current chopping when the shunt reactor is shut off, a high frequency and amplitude overvoltage is generated. This study was aimed at eliminating switching-related overvoltages in shunt reactors so as to maintain the equipment, prevent insulation failure, and avoid reignition. Therefore, the circuit was modified according to the suggested mitigation strategy to verify that transient overvoltages are suppressed by the circuit breaker and shunt reactor. With a view to evaluate the existing chopping caused by the switching of reactor bank, the alternative transients program (ATP-Draw) model was used to simulate the transients resulting from switching a shunt reactor. This work has been put into practice for various current chopping values. The collected results of the simulation showed that the proposed model was significantly highlighted for the suppression of overvoltages, with the voltage across the circuit breaker being reduced from 679 KV to 478 KV at a current chopping value of 5 A and from 351 KV to 152 KV across the shunt reactor.
Intelligent controller based WECS fed unified power flow conditioner for PQ enhancement
Authors: Kumar Polishetty Vinay , Ganapathi Balamurugan , Kartigeyan Jayaraman
Published: September 2023

The dominance of non-linear loads, sustainable energy sources and power electronic devices in modern power system has in turn compromised the system stability by introducing numerous power quality (PQ) issues.  A wind energy conversion system (WECS) fed unified power flow conditioner (UPFC) architecture is suggested in this work since maintaining optimal PQ is important for both the supply authorities and customers. The proposed approach supports both clean energy generation and PQ enhancement. The UPFC aids with accomplishing control over reactive power flow, active power flow, phase angle, impedance and voltage. The reference current for the UPFC is generated using DQ theory. Moreover, a shunt and series compensators of an UPFC are controlled using cascaded fuzzy logic controller (CFLC). The stability of the DC voltage obtained from doubly fed induction generator (DFIG) based WECS is also controlled using a CFLC. The simulation model for the presented WECS fed UPFC is developed in MATLAB and its performance is evaluated.
Sliding modecontrolled PV-based bootstrap converter system with enhanced response and voltage stability
Authors: Jyothi Kesa , Varma Pinni Srinivasa , Kishore Dondapati Ravi , Jain Hari Shankar
Published: September 2023

In this paper, a straightforward method for locating the controller in a PV-based bootstrap converter system is presented. Recent developments in control strategies and power electronics have made it possible to create PV-based DC-to-AC converters for AC drives that are connected to 3-phase loads. High voltage gain is intended to be produced by the bootstrap converter (BSC). The BSC's purpose is to control load voltage. This study compares the time specification performance of the proportional resonant controller (PRC) and the sliding mode control (SMC) for photovoltaic systems with bootstrap three phase inverter (PV-BSTPI). For the delicate loads, steady voltage is typically more important. The BS-TPI system incorporates a closed loop control to fast achieve constant voltage. Choosing the best control approach is the aim. It is observed that the steady state error of SMC is 1.67 which is better when compared to PRC.
Experimental validation of quadratic-boost-zeta converter based on coat circuit
Authors: Ali Ahmed Mahmood , Hassan Turki Kahawish
Published: September 2023

This work proposed a high step-up DC-DC converter with a voltage gain of 12 at a duty cycle of 48.25% with a single active switch. The new design combines the quadratic-boost converter and an isolated zeta converter with a single-stage coat circuit by a transformer with a trans ratio of 2.3. This can result in low voltage stress on switch and diodes with low conduction losses without using an additional clamp circuit, which in turn causes an increase in total efficiency. It has continuous and low ripples in the input and output currents. The voltage conversion ratio and the component voltage stresses are calculated in continuous conduction mode (CCM). The prototype was constructed and tested practically while considering an input voltage of 30 V, an input power of 240 W, an output voltage of 360 V, and a switching frequency of 100 kHz to validate the theoretical evaluations. The maximum efficiency at maximum output power is 94.5%.
A robust microgrid using an inverter with CCS-MPC control and resilient operation
Authors: Das Epsita , Banerji Ambarnath , Biswas Sujit K.
Published: September 2023

Modern generation trend through renewable energy-based distributed energy resources has made microgrids an important part of the power system. Robust control of the inverter providing quality power has become an essential microgrid (MG) requirement. This paper proposes continuous control set model predictive control (CCS-MPC) on inverter for dynamic voltage regulation supplying reactive power to the load for a MG. The proposed method uses the terminal voltage magnitude, which reduces calculation time, sensor per phase, and the engagement burden of the controller. This paper applies a nonlinear VSI model and a series parallel structure nonlinear autoregressive exogenous (NARX) model of artificial neural network (ANN) to predict future output which CCS-MPC optimizes. The proposed VSI with CCS MPC is applied to a case study of a real system as a plug-and-play device. Simulation shows the satisfactory result of the proposed controller. The inverter control system has been made resilient to protect itself and automatically recover from faults on the DC and AC side, providing quality power to its local load when the fault has been removed.
Fault-tolerant single-input dual-output converter with preserved output under fault operation
Authors: Bharathi Botta Venkata Vara Lova Kala , Satish Raavi
Published: September 2023

DC-DC converters have played an important role in the auxiliary power supply to electric vehicles, DC micro-grids, and portable electronic applications. To reduce the number of components and to improve the power density, multiport DC-DC converters have been recently proposed. Many multi-output converters are designed based on specific operational constraints on duty ratio or inductor currents. Further, simultaneous control of outputs is critical and involves cross-regulation issues. This paper proposes a single-input dual-output (SIDO) DC-DC converter with fault-tolerant circuit configuration to circumvent these challenges. The designed converter is helpful for the simultaneous control of loads by cross-regulation issues and has simple control without any control constraints on duty ratio or inductor currents. The topology proposed in this paper, can most significantly tolerate the failure during open-circuit for single and multiple switches and gives the preserved output voltage under fault case. The effectiveness and feasibility of the proposed configuration is validated using MATLAB/Simulink.
The 1.5 bit-per-stage 10-bit pipelined CMOS A/D converter for CMOS image sensor
Authors: Menssouri Aicha , El Khadiri Karim , Tahiri Ahmed
Published: September 2023

This paper presents a 1.5-bit/stage pipeline analog-to-digital converters (ADC) with a 100 MHz operating frequency for CMOS image sensors built using TSMC 90nm CMOS technology. The design features a novel architecture including a comparator, CMOS transmission gates, a sub-ADC logic circuit, bootstrap switches, and a gain-boosted fully differential telescopic op-amp based switched-capacitor MDAC. The ADC operates on a 1.8 V power supply, with a typical power dissipation of 1.632 mW, and a full-scale input signal voltage of 0.8 V. At 100 MHz sampling frequency, it achieves a maximum ENOB of 12.42 bits, an SNR of 76.53 dB, and a FOM of 0.297 pJ/conversion step. This 1.5-bit/stage pipeline ADC is well-suited for CMOS image sensors.
Novel complementary Sziklai pair based high gain low noise small-signal amplifiers
Authors: Shukla SachchidaNand , Arshad Syed Shamroz , Srivastava Geetika
Published: September 2023

A new paired configuration of opposite polarity BJTs, the “complementary Sziklai pair” is introduced in the series of multi-BJT-based devices like Darlington and Sziklai pair, and its viability is tested in small-signal common emitter (CE) and common collector (CC) amplifier configurations. The Darlington and Sziklai both face the problem of poor frequency response at a higher frequency which is addressed by the proposed configuration. The proposed pair with CE amplifier holds class-A amplification property with a high voltage gain of 200.05, a high current gain of 11.62, wider bandwidth of 1.64 MHz, and a low THD of 1.29E-6%, hence supports the potential of wide applicability in analog communication. Similarly, the proposed pair with CC configuration produces approximately a unit current gain of 0.99 with wider bandwidth of 1.90 MHz and low THD of 1.76E-6%, therefore it can be used as a current buffer in a generalized current follower circuit. Conclusively, the device structure of this new BJT pair may be considered the third consecutive member of the series of Darlington pair and Sziklai pair. The layout of the proposed CE and CC amplifier occupy small areas of 158.30 μm2 (10.23×15.47 μm) and 141.16 μm2 (10.20×13.84 μm) respectively in 180 nm process technology.
A 1.8 V, 10 mA low dropout voltage regulator for IoT application in 90 nm CMOS technology
Authors: EL Mouzouade Said , EL Khadiri Karim , Tahiri Ahmed
Published: September 2023

A complementary metal-oxide-semiconductor CMOS low dropout voltage regulator (LDO) design flow using 90 nm CMOS technology is described and simulated in this paper. The circuit consists of an analogue LDO with using PMOS pass device, an error amplifier, a bandgap voltage, a biasing circuit, a feedback resistive network sized to have the desired closed loop gain. This LDO was designed to maintain stable voltage at 1.8 V and 10 mA of current output in low resistive load. The LDO regulator achieves 105 uA quiescent current, -47 PSRR@13 KHz noise frequency. The final design occupies approximately 0.05 mm2. The results were satisfying and make the designed circuit suitable for IoT application.
Parameter identification of the photovoltaic panel’s two-diode model
Authors: Madi Saida , Saoudi Kamel
Published: September 2023

This work deals with the two-diode model of a photovoltaic (PV) panel. It provides the per-unit energy and current representations in addition to identifying its unknown parameters. Mathematical equations have been proposed and built using the MATLAB/Simulink simulator to achieve this goal. Only one variable has been adjusted to get all the unknown parameters simultaneously at standard test conditions (STC). Three variables have to be adjusted under any other atmospheric conditions. Two different technologies have been used. The accuracy of the proposed mathematical model has been provided using the absolute relative error between the simulated value and the measured one. The biggest values of the absolute relative error are 0.000788%, 0.0006157%, and 0.000616% under STC, nominal cell temperature condition (NOCT), and random daily atmospheric conditions, respectively.
A statistically analysis to determine the use of renewable sources for campus lighting, case study of technical faculty of Kosova
Authors: Bylykbashi Blerina , Abdullahu Fitore , Hoxha Bukurije
Published: September 2023

Considering the ever-increasing demand for electricity and the current crisis in this sector, various ways of generating electricity have been studied. Most of them are based on hybrid technologies as a solution to replace the relevant resources during the absence. In Kosovo, as an economically poor country, such technologies are rarely used. Public lighting in some countries is still considered unaffordable due to high cost. This study further demonstrates an environmentally friendly option for power generation using hybrid PV and Wind systems. The current study presents the study that was carried out on the campus of the technical faculty in Pristina. The analysis has been done analytically, which has resulted in the need for 6 hybrid lighting systems to achieve a coverage of the lighting needs, which so far lacks lighting in this part of the campus. A total of 461,448 kWh can be generated during the year from the wind turbine system and 796.11 kWh from the solar photovoltaic system. Considering that we have an ever-decreasing cost of such devices and from the analysis done it results that these systems are cost effective and ideal solutions for such cases and similar needs which are vital needs today.
Modified instantaneous power theory control of dynamic voltage restorer powered by photovoltaic system
Authors: Asiri Yousef , Al-Gahtani Saad F. , Irshad Shaik Mohammad
Published: September 2023

Power quality issues have become widespread due to nonlinear electronic converters and loads. Nonlinear components in the power system hamper the power quality, network efficiency and voltage regulation. The power quality issues like sag, swell, and voltage unbalance can be reduced by employing a dynamic voltage restorer (DVR). DVR provides the compensating power from a DC source to minimize the effect of sag, swell, and voltage unbalance. This article presents a power system with DVR using a photovoltaic system (PV) as a DC source instead of a conventional battery source. This article proposes a modified instantaneous power (PQ) control technique to generate the reference signal of load voltage to assure the DVR's superior performance. This modified technique uses an anti-aliasing filter to generate a reference signal. This proposed technique is tested under extreme power quality issues of 80% sag, 20% sag, 120% swell, 170% swell, and voltage unbalance. The DVR is modeled and simulated using MATLAB/Simulink. A comparison is made between the traditional and modified PQ methods from the obtained results. The analyzed results under severe power quality issues suggest that the proposed P-Q control technique is a preferable option for the DVR with PV as a DC power supply.
Application of EV aggregators and SMES for frequency deviation control using fractional fuzzy controller
Authors: Tripathy Sabita , Debnath Manoj Kumar , Kar Sanjeeb Kumar
Published: September 2023

Secondary controllers are implemented in the alternator control loop to take care of the swinging of frequency initiated due to inequality of load and demand. A fractional fuzzy-PID controller (FFPID) is projected in this work for frequency deviation control in unified system including EV aggregators and superconducting magnetic energy storage (SMES). EVs and SMES are given primacy because of their ecofriendly nature. Proper adjustment of gains of FFPID is also required to extract the best performance of the secondary controllers. Here a recent tuning process named as artificial rabbits optimization (ARO) is applied for proper tuning of projected controller. The implemented dual area power system includes time varying delay-based EV aggregators, SMES, and thermal generating units. The ARO technique is applied in the model to tune the controller constraints with abrupt increment of demand in one of the control areas. A time-based function is treated as fitness function to evaluate the system performance. The dominance property of the projected FFPID controller over conventional PID and FPID controller in terms of different response specifications like maximum positive deviation (overshoot), settling time and minimum negative deviation (undershoot). The robust nature of the projected controller is also confirmed by multiple analysis like random load deviations and system constraint alteration.
A novel and effective method based deep learning model for detecting non-technical electricity losses
Authors: Baldawi Israa Mohammed Ridha , İnan Timur
Published: September 2023

This study focused on non-technical electricity loss detection. As mentioned, non-technical losses (NTLs) affect utilities and economies financially. Electricity theft, fraud, and metering issues can create NTLs. NTL generate most distribution losses in electrical power networks, costing utilities a lot. NTL detection approaches are data-focused, network-oriented, or hybrid. Data-oriented writing dominated this analysis. After data collection and cleaning and labeling the unlabeled dataset with a target, a methodology was supplied that used four machine learning techniques random forest, decision tree, KNN, and logistic regression and four neural network models-DNN, CNN, CNN-LSTM, and CNN-GRU. The CNN and DNN model have the best accuracy, stability, fast learning, and training time.
An intelligent PID controller tuning for speed control of BLDC motor using driving training-based optimization
Authors: Sarma Hrishikesh , Bardalai Aroop
Published: September 2023

Tuning of proportional-integral-derivative (PID) controller remains a matter of great concern for the control engineers as it plays a major role to obtain optimal performance of any system Due to their simplicity and excellent efficiency, metaheuristic algorithms have recently become extremely popular among researchers for handling a wide range of real-world optimization challenges. In order to optimize a PID controller for managing the speed of a BLDC motor, this work proposes a novel application of the driving training-based optimization (DTBO) algorithm, one of the latest and most recent human-based metaheuristic algorithms. The purpose of this present study is to optimize a PID controller for a BLDC motor speed control by DTBO method and evaluate its performance with a similar controller tuned by grey wolf optimization (GWO) method. Additionally, the suggested DTBO-PID controller's robustness analysis is being carried out with BLDC motor parameter modifications as well as a comparison to the GWO-PID controller. The comparison is carried out in MATLAB/Simulink, and the results are based on common step response metrics such rise time, settling time, and maximum overshoot. For easier comprehension, the results are presented in tabular and graphical form. The chosen BLDC motor drive system's selected DTBO-PID controller performs better and is more reliable than the GWO-PID controller, according to the final simulation findings.
Enhancing the performance of radial distribution systems via optimal integration of electric vehicles
Authors: Rabie Afaf , Ghanem Abdelhady , Kaddah Sahar S. , El-Saadawi Magdi M.
Published: September 2023

Electric vehicles (EVs) and their associated charging stations (CSs) are a promising avenue for greenhouse gas reduction and energy security. However, improper location and size of the EV charging station (CSs/EVs) negatively affect the power system. It results in some technical challenges such as increased real power-loss, decreased voltage stability and increased voltage deviation. This paper suggests optimum planning of CSs/EVs locations to conserve voltage, improve power-loss and reduce the effect of CSs/EVs in electrical distribution systems. The multi objective genetic algorithm method (MOGA) is utilized to solve the optimization problem and reduce the impact of the random location of CSs/EVs. The simulations are performed on IEEE 33-bus and IEEE 69-bus radial distribution systems (RDS). In addition, the optimal EV allocation is carried out with two fixed levels of loading from 100% to 150% of the candidate EV load. A comparison between the proposed MOGA technique and other optimization techniques is carried out. The results demonstrated the capability of the proposed technique for optimal placement of CSs/EVs in RDS. Moreover, it is providing an objective value to solve a complex multi-objective nonlinear optimization problem to reduce the total power-loss, improve the voltage profile and extend the voltage stability.
Nest construction and repairing habits of Baya Weaver Ploceus philippinus (Aves: Passeriformes: Ploceidae) in the agricultural landscape of Villupuram District, Tamil Nadu, India
Authors: M. Pandian
Published: September 2023

The intricate nesting habits of Baya Weaver Ploceus philippinus were studied on two Palmyrah Palm Borassus flabellifer trees in Chendur village, Villupuram district, Tamil Nadu between 20 March and 30 November 2020. Observations concentrated on sources of fibers, developmental stages of nests, re-construction & repairing of nests, deposition of clay in the nest walls, and various threats. A total of 98 nests of various developmental stages (wad stage—4, helmet stage—31, egg-chamber closed stage—5, and complete nests—58) were studied on these two nest colonies. The birds used leaf fibers of Indian date Palm Phoenix sylvestris and Sugarcane Saccharum officinarum as nest materials, and took 6–48 days for construction of a complete nest. 95% of helmet stage nests (n = 126) contained clay deposits. Analysis of plastered clay revealed it was alkaline with pH 9, and dry weight ranged from 5.1–5.8 g. Males re-constructed new nests from the remnant stalks attached to tips of palm fronds, and also made repairs on damaged nests. Anthropogenic factors, wind, rain, and avian predators, such as House Crow Corvus splendens, Long-billed Crow Corvus macrorhynchos, Rufous Treepie Dendocitta vagabunda, and Shikra Accipeter badius posed threats to Baya Weavers. A total of 42 nests, 11 broken eggs, and 14 dead chicks were found fallen under the two supporting trees. The detailed systematic survey covering entire district, rapid urbanization, and the anthropogenic pressures will help in nest drafting an action plan to conserve local populations of Baya Weaver.
Oatp (Organic Anion Transporting Polypeptide)-Mediated Transport: A Mechanism for Atorvastatin Neuroprotection in Stroke
Authors: Williams Erica I. , Betterton Robert D. , Stanton Joshua A. , Moreno-Rodriguez Valeria M. , Lochhead Jeffrey J. , Davis Thomas P. , Ronaldson Patrick T.
Published: September 2023

BACKGROUND:

Drug discovery for stroke is challenging as indicated by poor clinical translatability. In contrast, HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase inhibitors (ie, statins) improve poststroke neurological outcomes. This property requires transport across the blood-brain barrier via an endogenous uptake transporter (ie, Oatp1a4 [organic anion transporting polypeptide 1a4]). Our goal was to study Oatp1a4 as a drug delivery mechanism because the blood-brain barrier cannot be assumed to be completely open for all drugs in ischemic stroke.

METHODS:

Male Sprague-Dawley rats (200–250 g) were subjected to middle cerebral artery occlusion (90 minutes) followed by reperfusion for up to 7 days. Atorvastatin (20 mg/kg, IV) was administered 2 hours following intraluminal suture removal. Involvement of Oatp-mediated transport was determined using fexofenadine (3.2 mg/kg, IV), a competitive Oatp inhibitor. Oatp1a4 transport activity was measured by in situ brain perfusion. Infarction volumes/brain edema ratios and neuronal nuclei expression were determined using 2,3,5-triphenyltetrazolium chloride–stained brain tissue slices and confocal microscopy, respectively. Poststroke functional outcomes were assessed via neurological deficit scores and rotarod analysis.

RESULTS:

At 2-hour post–middle cerebral artery occlusion, [
3
H]atorvastatin uptake was increased in ischemic brain tissue. A single dose of atorvastatin significantly reduced post–middle cerebral artery occlusion infarction volume, decreased brain edema ratio, increased caudoputamen neuronal nuclei expression, and improved functional neurological outcomes. All middle cerebral artery occlusion positive effects of atorvastatin were attenuated by fexofenadine coadministration (ie, an Oatp transport inhibitor).

CONCLUSIONS:

Our data demonstrate that neuroprotective effects of atorvastatin may require central nervous system delivery by Oatp-mediated transport at the blood-brain barrier, a mechanism that persists despite increased cerebrovascular permeability in ischemic stroke. These novel and translational findings support utility of blood-brain barrier transporters in drug delivery for neuroprotective agents.
Voces Furiarum
Authors: Paul Joshua M.
Published: September 2023

I argue that Priapus offers a bilingual gloss on the name ‘Tisiphone’ in Horace, Satires 1.8. I trace the folk etymology of the Fury’s name and identify various passages in which Latin authors emphasize a perceived connection between Tisiphone and φωνή, voice. I then demonstrate how this bilingual pun casts Priapus as a narrator capable of learned, Alexandrian wordplay.
Throwing Jason off the Scent
Authors: Daly Alastair
Published: September 2023

This article argues that Apollonius was aware of the foul smell of the Lemnian women and its mythological variants. While Apollonius does not mention the δυσοσμία, he builds a complex allusion to it and its omission around the rare verb ἀμαλδύνω. Its deployment to cap Hypsipyle’s speech to Jason (A.R. 1.834) draws a parallel between her erasure of the Lemnian crime and the obliteration of the Achaean wall in the Iliad, but with a witty sting in its tail. The verb first occurs at Iliad 7.463 where Zeus grants Poseidon permission to annihilate the wall, followed by the arrival of Euneus (the son of Jason and Hypsipyle) bringing wine from Lemnos to the Achaean camp. Apollonius uses the verb once more to describe the sun wiping out the scent of prey (4.112) thus making a meta-reference to his own omission of the Lemnian odour in Book 1.