Hasil untuk "Electric apparatus and materials. Electric circuits. Electric networks"

Atsushi Ouchi, Saroj R. Tripathi

Recent advancements in terahertz wave applications for sensing, imaging, and high-speed communication have spurred a substantial demand for low-cost, easily accessible optical components capable of manipulating terahertz wave polarization. In this study, terahertz circular dichroism spectroscopic measurements of micrometer-sized metallic chiral helix arrays, fabricated using computer numerical control (CNC) machining, are presented. Experimental results demonstrate a giant circular dichroism of ±0.6 in an axial mode of operation for left- and right-handed arrays within a sub-terahertz frequency range. The helix array converts linearly polarized light into circularly polarized light from 120 GHz to 200 GHz, with a 3 dB axial ratio relative bandwidth approaching 50%. The polarization extinction ratio is in excess of 20 dB. These outstanding features, combined with their low cost, high accessibility, as well as their potential for mass production, pave the way for development of diverse range of optical components such as polarizers, filters, absorbers, and isolators operating in the terahertz frequency region.

Yingjie Zhou, Minjie Hou, Xiecheng Yang et al.

Lithium-ion batteries (LIBs) are indispensable for contemporary energy storage, powering portable electronics and enabling renewable energy integration. However, their limited energy density remains a critical barrier for demanding applications such as electric vehicles and aerospace devices. This review systematically examines recent advancements in multidimensional (0D-3D) nanomaterials for LIB electrodes, comparatively analyzing their dimension-dependent performance characteristics. Specifically, solid-phase, liquid-phase, and vapor-phase preparation methods are critically assessed, emphasizing their respective advantages and limitations regarding scalability. Dimension-specific advantages are highlighted: 0D nanomaterials (e.g., quantum dots) enhance interfacial compatibility and energy density; 1D nanostructures (e.g., nanowires) improve charge transport efficiency; 2D materials (e.g., graphene) maximize specific capacity; and 3D architectures promote electrode porosity and accommodate volume strain. Despite these advancements, persistent challenges include volume expansion, parasitic reactions, and high production costs. Future research must focus on elucidating interfacial mechanisms, enhancing system compatibility, and developing scalable synthesis methods. These efforts are critical for translating laboratory innovations into commercially viable next-generation LIBs.

Xiangyu Hao, Haozhe Wang, Tiaoyang Li et al.

ABSTRACT IGZO has been identified as a promising channel material for next‐generation memory integration. Although extensive studies have been carried out to optimize the electric transport properties, the trade‐off between mobility and threshold voltage remains to be challenging. Furthermore, the subthreshold swing often degrades at more positive threshold voltages. Atomic layer deposition (ALD) offers the unique capability to control the layer composition and element arrangement at the atomic level with additional tunability from supercycle growth conditions at different temperatures. This work employs a supercycle thermal ALD method for IGZO deposition and systematically investigates the influence of deposition temperatures and compositions on the electrical characteristics of IGZO FETs. The results reveal that increasing the deposition temperature enhances the surface reactions of metal precursors, reducing carbon residues substantially in the IGZO channel, with the M‐O peak proportion reaching 89.8% at 300°C and oxygen‐related impurities decreasing to 4.1%. Furthermore, as the In2O3 sub‐cycle varies from 5 to 1, the ratio of oxygen vacancies decreases from 21.0% to 8.6%, with a widely tunable threshold voltage from −2 to +2.3 V. It should be noted that the mobility with the most positive threshold voltage of 2.3 V still exceeds 15 cm2 V−1 s−1. Furthermore, the subthreshold slope of the optimized transistors keeps under 65 mV dec−1 for the entire range of threshold voltages and can reach the ideal value of 60 mV dec−1 for Vth near 0.5 V. This work provides valuable insights into co‐optimizing mobility and Vth while keeping low SS by tuning the ALD growth parameters for IGZO.

Zhenlin Huang, Xing Wen, Jinwei Zhu et al.

The technologies such as data, information and intelligence are gradually applied to the power industry, and the power industry is gradually realizing digital transformation to meet the requirements of more reliable, stable, intelligent and safe power supply. UHV converter station is the heart of power grid equipment, which mainly ensures the conversion between AC and DC to ensure the stable operation of the power system. Facing the situation that the fault location is difficult and the loss is too large, this paper introduces the Digital Twin Technology(DTT), which completes the real-time mapping of the data state between the physical body and the virtual body of the converter station line through the digital modeling of the physical intelligent equipment. The recognition rate of CNN-BiGRU model for line fault and type reaches 99.78 % and 98.56 %. The CNN-BiGRU model has the highest recognition rate and the best effect in terms of the line recognition rate and the fault type recognition rate. The maximum Recall and Precision values of CNN-BiGRU model are 99.67 % and 97.96 %. The closer the F1 is to 1, the better the performance of the model is, and the value of CNN-BiGRU reaches 0. 94, which shows that the model has good performance.

Lili Xu

In order to save the consumption of natural high quality aggregate and improve the utilization rate of nano-composite materials, the investigation on the compressive strength and water permeability of nano-composite modified reclaimed aggregate concrete materials was proposed. In this experiment, reclaimed nano-ceramic aggregate was used to replace natural aggregate, and the effects of reclaimed aggregate substitution rate, water-cement ratio and target porosity on the compressive strength and permeability coefficient of reclaimed ceramic aggregate pervious concrete were studied. The reclaimed ceramic aggregate was pretreated with modifier. The results show that with the increase of substitution rate, the compressive strength decreases and the permeability coefficient has little difference. With the increase of water-cement ratio, the compressive strength increases first and then decreases, and the water permeability coefficient has little difference, but the value is lower when the water-cement ratio is greater than 0.4. As the target pore increases, the compressive strength decreases and the permeability coefficient increases. The optimal test scheme is as follows: the replacement rate is 40 %, the water-cement ratio is 0.35, and the porosity is 15 %. In this case, the performance of the specimen is better. Conclusion: With the increase of replacement rate, the performance index of recycled aggregate decreases, the compressive strength of pervious concrete decreases continuously, and the permeability coefficient has little difference. With the continuous increase of water-cement ratio, the compressive strength increases first and then decreases, which can meet the construction requirements.

Océane Terral, Guillaume Audic, Arnaud Claudel et al.

Abstract Graphene field effect transistors (G‐FETs) have appeared as suitable candidates for sensing charges and have thus attracted large interest for ion and chemical detections. In particular, their high sensitivity, chemical robustness, transparency, and bendability offer a unique combination for interfacing living and soft matters. Here demonstrated their ability to sense targeted biomolecules is demonstrated, by combining them with ion channel‐coupled receptors (ICCRs). These receptors are naturally or artificially expressed within living cell membranes to generate ion fluxes in the presence of chemicals of interest. Here, those biosensors are successfully combined with a G‐FET array which converts the bio‐activation of the ICCRs into readable electronic signals. This hybrid bioelectronic device leverages the advantages of the biological receptor and the graphene field effect transistor enabling the selective detection of biomolecules, which is a current shortcoming of electronic sensors. Additionally, the G‐FET allows for discrimination of the polarity of the ion fluxes which otherwise remains hidden from conventional electrophysiological recordings. The multisite recording ability offered by the G‐FET array raises numerous possibilities for multiscale sensing and high throughput screening of cellular solutions or analytes, which is of both fundamental and applied interest in health and environment monitoring.

Linkui Niu, Peiran Xu, Tiantian Huang et al.

Abstract Tunable optical information storage is crucial in artificial retinal systems for mimicking neurobiological visual characteristics. The perception and storage of light signals rely heavily on the regulation of the conductivity states of memristor materials (e.g., transition metal oxides). Controlling light memristor behavior via defects and polymorphic phases remains underexplored and differs from traditional plasticity training via repeated testing. In this study, defect‐driven ultraviolet light perception and memristor storage with phase transitions in vanadium dioxide (VO2) thin films are presented. The effects of oxygen defects and the corresponding polymorphic phases on ultraviolet light memristors are investigated. The dependence of phonon vibrations and insulator–metal transition behavior on defect levels are revealed. Self‐doping and polymorphs enable VO2 to exhibit distinct ultraviolet memristor performance. It is anticipated that defect‐driven light memristors significantly contribute to the realization of artificial synaptic devices and the implementation of advanced electronic neuron systems.

Jie Meng, Qian Zhao, Weihua Lin et al.

Abstract Understanding high‐order biexciton dynamics is important for the use of semiconductor quantum dots (QDs) in optoelectronic devices. The core–shell structure can be used to modulate biexciton dynamics by varying the shell thickness and core–shell energy band alignment. In this study, the biexciton dynamics in an unconventional case in which each QD is encapsulated by a submonolayer shell are demonstrated. The result of a transient absorption spectroscopic study shows that InP/ZnS core/shell QDs with submonolayer shell coverage exhibit a prolonged Auger lifetime. However, the QD size dependence of the Auger recombination time features two constant distinct stages instead of the typical monotonic volume scaling law in conventional QDs. It is attributed to the tradeoff between the enlarged QD size and quantum‐well confinement for the Auger processes. However, the abrupt change between the two stages is due to the change in the shell coverage. This study provides a reference for the application of core–shell QDs in optoelectronic devices in which full coverage of the shell is not achieved.

Ashok Kumar Sahoo, Sampada Gulavani, Manika Manwal et al.

Risk administration has increased due to increased online orders to avoid sales invoices. Failure to pay a bill within 90 days of receipt constitutes overdue payment. The credit rating is used to determine the probability that consumers will fail. The CR has been thoroughly studied and several learning algorithms have been proposed. The main goal is to create a CR model for the role of Risk Solution Services (RSS), an industry standard for predicting the parameters of customer default in e-commerce risk assessment. The risk assessment included a general concept, exclusion criteria, and details of the ordering process. The most recent design should operate both independently and in conjunction with the NRC Primary Risk Audit as it is intended to replace the overall screening risk assessment. This article is about a CR implementation of Genetic Programming (GP) with Artificial Intelligence (AI). The dataset includes RSS-enabled purchase requisitions. The results show that the GP pre-risk control model goes beyond the generic CR model in terms of classification accuracy. A system with more discriminatory capacity is produced by combining GP models with the NRC's major risk assessment.

Lucky Dewa Satria, Dinar Nugroho Pratomo, Rona Nisa Safia Amriza

Perkembangan teknologi informasi sangat penting dalam mendapatkan informasi secara cepat, akurat, dan efisien. Di Komando Cadangan Strategis Angkatan Darat (Kostrad), media sosial berbasis pesan instan digunakan untuk mendukung komunikasi dan koordinasi antara personel di lapangan dalam operasi pertahanan dan keamanan. Namun, penggunaan media sosial tersebut memiliki kekurangan dalam hal koordinasi, seperti pelacakan personel dan sentralisasi laporan kegiatan. Hal ini dapat mengganggu proses koordinasi tim dan menyebabkan penyebaran informasi yang salah. Dari permasalahan tersebut, diperlukan pengembangan aplikasi yang dapat digunakan oleh Komandan Brigadir dan staf Komando Cadangan Strategis Angkatan Darat (Kostrad) guna memperoleh komunikasi yang cepat, akurat, dan efisien. Aplikasi ini bertujuan untuk meningkatkan efektivitas pelaporan kegiatan harian, serta memberikan informasi lokasi personel secara real-time dalam laporan tersebut. Sistem ini dibangun dengan menggunakan framework Vue, memanfaatkan fitur geolokasi, dan push-notification untuk menerima informasi lokasi personel secara real-time. Hasil penelitian yang telah dilakukan menghasilkan sebuah sistem informasi pelaporan kegiatan harian menggunakan Vue dengan fitur geolokasi real-time dan push notifications. Sistem ini memiliki manfaat dalam sentralisasi laporan kegiatan dan memberikan kemampuan untuk melihat lokasi personel secara real-time. Selain itu, sistem ini juga dapat memberikan pengumuman langsung kepada personel yang berada di lapangan, sehingga memperkuat komunikasi dan koordinasi antara personel di dalam operasi.

Zakia AICI , Hamid Bentarzi

Temperature is an important indicator of the electrical equipment conditions. An accurate fault diagnosis can be performed by using the temperature profile of the electrical equipment surface. Infrared thermograph has gained more attention and becomes an interesting method in electrical fault diagnosis due to its advantages. This paper presents a review of different methods of image segmentation (clustering algorithms) applied to infrared thermograph which has been used to get useful information from electrical equipment of power system for faults detection, classification and localization.  

Sakthivel M, SivaSubramanian S, Priyanka Brahmaiah V et al.

This research paper investigates the use of Deep learning and Auto-encoders (DAE) for the automated detection of cardiac arrest in human beings. We propose a new method for automated detection that utilizes auto encoders, a type of deep learning model, to detect abnormalities in the cardiovascular system. To achieve this, a dataset of cardiovascular heart disease was used to train and evaluate an auto encoder model. We confirm the efficacy of the proposed approach by evaluating its performance on a dataset of cardiac arrest patients. The results indicate that the proposed technique can accurately detect cardiac arrest in human beings yielding a high degree of accuracy rate of 93%. This study highlights the potential of using DAE for automated detection of cardiac arrest and provides a promising direction for further research in the field. Results from the model show that it is possible to accurately detect cardiac arrest in humans. The performance evaluation metrics are f-measure, accuracy, precision and recall. The proposed DAEalgorithm is compared with other existing approaches are ANN, BPNN, SVM, DT, XG Boost, RF, DNN and SAE.

Diptashree Das, Ziyue Xu, Mehdi Nasrollahpour et al.

A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulse-modulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals. The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms.

Archisman Ghosh, Debayan Das, Shreyas Sen

Mathematically secure cryptographic algorithms leak significant side-channel information through their power supplies when implemented on a physical platform. These side-channel leakages can be exploited by an attacker to extract the secret key of an embedded device. The existing state-of-the-art countermeasures mainly focus on power balancing, gate-level masking, or signal-to-noise (SNR) reduction using noise injection and signature attenuation, all of which suffer either from the limitations of high power/area overheads, throughput degradation or are not synthesizable. In this article, we propose a generic low-overhead digital-friendly power SCA countermeasure utilizing a physical Time-Varying Transfer Function (TVTF) by randomly shuffling distributed switched capacitors to significantly obfuscate the traces in the time domain. We evaluate our proposed technique utilizing a MATLAB-based system-level simulation. Finally, we implement a 65nm CMOS prototype IC and evaluate our technique against power side-channel attacks (SCA). System-level simulation results of the TVTF-AES show <inline-formula> <tex-math notation="LaTeX">$\sim 5000\times $ </tex-math></inline-formula> minimum traces to disclosure (MTD) improvement over the unprotected implementation with <inline-formula> <tex-math notation="LaTeX">$\sim 1.25\times $ </tex-math></inline-formula> power and <inline-formula> <tex-math notation="LaTeX">$\sim 1.2\times $ </tex-math></inline-formula> area overheads, and without any performance degradation. SCA evaluation with the prototype IC shows <inline-formula> <tex-math notation="LaTeX">$3.4M$ </tex-math></inline-formula> MTD which is <inline-formula> <tex-math notation="LaTeX">$500\times $ </tex-math></inline-formula> greater than the unprotected solution.

K. Velraja, V. Srinivasan

Machining is the process of cutting or removing materials from a work item with a cutting tool to get the desired form. CNC is widely used because of its compact size which enables more number of productions in all type of automotive industries. Many intricate parts required by various industries are created using computer numerical control (CNC) machining. While mass production is useful in some cases, which require selective parts in most industries. Businesses require CNC for their manufacturing process, which enables them for précised jobs with help of this CNC machine software. CNC lathes can make precise cuts quickly with a variety of tools. Hence, the major objective of this work is to extend the life and quality of the cutting tool by improving its hardness and wear resistance by using DC Magnetron Sputtering to coat a 1 μm thin film layer of Tungsten carbide on High speed steel insert. This insert is to be characterized for chemical composition, micro structured, grain distribution and hardness of its surface etc.

Yujia Huo, Sydney Sofronici, Michael J. D'Agati et al.

The recording and analysis of biomagnetic fields have widespread applications in medical research and diagnostics. Wearable magnetic field sensors offer a noncontact and portable method for sensing biopotentials. This article presents a readout circuit in 180-nm CMOS for strain-modulated multiferroic vector magnetic field sensors. By utilizing a demodulator-first architecture, the circuit bandwidth and dynamic range requirements are greatly reduced allowing for a low power consumption of 5.9 mW. The circuit bandwidth is from 76 mHz to 2.2 kHz, allowing for measurement across the range of interest for biomagnetic signals. Utilizing a modulation noise cancellation technique, the noise performance of the sensor system is significantly improved, and the sensor modulation amplitude can be increased, resulting in improved sensor sensitivity. Measurements for the sensor-readout system demonstrate a 144 pT/<inline-formula> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz magnetic noise floor at 1 kHz. The noise and power consumption are significantly lower than alternative magnetic sensor systems of similar volume.

Yousef Methkal Abd Algani, G Arul Freeda Vinodhini, K. Ruth Isabels et al.

Internet connections and cellular technologies are extensively used throughout the globe. Anomaly detection systems have considered an essential tool for detecting a broad range of hostile activity in the cyberspace domain. The researchers of this paper address the problems and existing knowledge of anomalous detecting for mobile networks as they prepare to embrace the “big data” age. As new computer cyber-security defects and vulnerabilities are reported every day, anomaly detection systems (ADSs) are getting increasingly crucial. The major objective is to develop methods for scanning networks activity and detecting unusual behaviours that could be the result of anomalous assaults.The Dirichlet mixture prototype dependent on anomaly detection methodology is a proposed methodology called DM-ADs; anomaly detecting engine that incorporates 3 components: collecting and logging, pre-processing, and a novel statistical decision processor. This paper offers a hybrid anomaly detection method that combines several characteristic selecting strategies with an appropriate mixture approach to recognize each assault form with great precision. The suggested method's effectiveness is assessed using two databases, the NSL-KDD. The effectiveness of the suggested ADS was proved by retaining excellent precision and minimal false-positive percentages in all sorts of attacks.

Allison Marsh

Dr. Maria Stuchly is an IEEE Life Fellow recognized for her contributions to the understanding of interactions of electromagnetic fields with living systems. Born and educated in Poland, she immigrated to Canada as a Postdoctoral Fellow in 1970. For 16 years she worked as a research scientist at the Bureau of Radiation and Medical Devices for Health &amp; Welfare Canada, developing protection standards for occupational, medial, and public exposure to radio frequency (RF) and microwave fields. She later became a professor and named research chair at the University of Victoria before retiring in 2004. This article is the second in a continuing series of biographical pieces on women who have made significant and continuous contributions to microwave science, technology, and applications over the course of their careers. The articles are based on oral histories with the subject, conducted in conjunction with the IEEE History Center and deposited online with the Engineering and Technology History Wiki.

Farah Abdel Khalek, Marc Hartley, Eric Benoit et al.

Continuous gait measurement can bring relevant indicators for healthcare professionals. Several techniques were developed for this cause. However, the beneficiaries, especially senior adults, find it hard to accept a monitoring device as it takes away their privacy. In this paper, we present a non-intrusive, low-cost and easy to implement model for gait measurement at home. It consists of implementing 4 passive infrared (PIR) sensors facing each other by pair. Our approach is based on a Deep Learning (DL) model that takes as input the signals generated by the PIR sensors, as they are representative of the distance and the speed of the moving object. A temporary Depth camera is used for training the model on the gait parameters. To evaluate our approach, we conducted multiple series of experiments on real sensor data. The results are promising and show that our approach is efficient for continuous gait measurement.

Shinichi Oshima, Yoshito Isei

A laser Doppler velocimeter (LDV) is a useful sensor for measuring the velocity and length of steel products. However, the distance to the measurement target is restricted to the intersection region of the two laser beams, making it difficult to measure steel products with large distance fluctuations and dimensional ranges. To remove this restriction, a new non-contact distance and velocity sensor FSFL-RVM (frequency shifted feedback laser range and velocity meter) employing FSFL, whose frequency changes proportionally to the time at ultra-high speed, was developed. Its measurement principle and accuracy were evaluated using a rotating disk, confirming its ability to measure velocities with the same accuracy as the LDV in a distance range 5 times the measurement distance range of the LDV and simultaneously measure distances with the accuracy within 0.1 mm.