vlsi research papers 2023

The IEEE Circuits and Systems Society is the leading organization that promotes the advancement of the theory, analysis, computer-aided design and practical implementation of circuits, and the application of circuit theoretic techniques to systems and signal processing. The Society brings engineers, researchers, scientists and others involved in circuits and systems applications access to the industry’s most essential technical information, networking opportunities, career development tools, and many other exclusive benefits. 

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The IEEE International Symposium on Circuits and Systems (ISCAS) is the flagship conference of the IEEE Circuits and Systems (CAS) Society and the world’s premiere forum for researchers in the active fields of theory, design and implementation of circuits and systems. This is accomplished through technical conference sessions, poster sessions, live demonstration sessions, and publication of conference papers. ISCAS 2024 is inspired by the theme "circuits and systems for sustainable development", which is perfectly aligned with the host city's goal.

2024 IEEE International Symposium on Circuits and Systems

2024 ieee 22nd interregional newcas conference, 2024 ieee international conference on multimedia and expo, 2023 international vlsi symposium on technology, systems and applications.

The 2023 International VLSI Symposium on Technology, Systems, and Applications will be held in the Ambassador Hotel Hsinchu, Taiwan  April 17-20, 2023 . Established in 1983, the Symposium has been the premier event on VLSI in Taiwan and a leading technology symposium in the world for nearly 40 years. To address the needs of the ever-changing semiconductor industry and the tight coupling between technology and design, VLSI-TSA and VLSI-DAT will be merged into one Symposium in 2023. Organized by  Industrial Technology Research Institute (ITRI) , the International VLSI Symposium on Technology, Systems, and Applications is proud to create an annual platform for technical exchanges by experts from all over the world on the advancements in semiconductor research, development, and manufacturing. 

Join us at the Symposium technical programs as well as experience historic Hsinchu city, in which the technical and cultural atmosphere have been harmoniously connected. 

Hsinchu City The well-known Taiwan Silicon Valley is based on clusters of world-class high Tech. IC manufacturing and design. It is a one-hour drive from Taipei, and 40 minutes from the airport. Industry attendees may take this opportunity to visit the Science Park business unit and academia attendees may visit major universities/institutes of Taiwan, either in Hsinchu or down to the south by the high-speed train within one hour. Join us at the 2023 VLSI-TSA technical programs as well as experience historic Hsinchu city, in which the technical and cultural atmosphere have been harmoniously connected.

Call for Papers Before submitting your abstract/paper, please review the information on IEEE Intellectual Property Rights .   For an accepted paper to be published in the proceedings, one of its co-author(s) MUST register and attend the symposium to present the paper. Note that each accepted paper shall be accompanied by a distinct registration; that is, two registrations are required for presenting two papers even if the presenter is the same.   Presentation of accepted papers at the symposium must be in English. The final manuscripts of all accepted papers will be published as submitted in the proceedings.   No-show papers will not be included in the symposium proceedings and will not be submitted to the IEEE Xplore database.   COVID-19 Watch The 2023 International VLSI Symposium on Technology, Systems and Applications is planned for an in-person/on-site event. In the meantime, we will keep Hybrid symposium (same as 2022) if COVID-19 still keeps a threat to the convention, i.e., arranging overseas presenters to provide a pre-recorded video for presentation on condition that they render into travel restrictions.

Important Dates

• Deadline for Paper Submission - 1 November 2022
• Deadline for Author Registration - 28 February 2023

Submit a Paper

                                         Submission to TSA                 Submission to DAT

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Research Areas

Circuits and vlsi design, associated publications, researchers.

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Many Congratulations to the GLSVLSI 2023 Best Papers and Best Poster/LBR Award Winners:

Best paper 1st place.

Bit-Stream Processing with No Bit-Stream: Efficient Software Simulation of Stochastic Vision Machines Sercan Aygun, M. Hassan Najafi, Mohsen Imani, and Ece Olcay Gunes

Best Paper 2nd Place

IMA-GNN: In-Memory Acceleration of Centralized and Decentralized Graph Neural Networks at the Edge Mehrdad Morsali, Mahmoud Nazzal, Abdallah Khreishah and Shaahin Angizi

Best Paper 3rd Place

SCRAMBLE-CFI: Mitigating Fault-Induced Control-Flow Attacks on OpenTitan Pascal Nasahl and Stefan Mangard

Best Poster/LBR Award 1st Place

Noise-Resilient and Reduced Depth Approximate Adders for NISQ Quantum Computing Bhaskar Gaur, Travis Humble and Himanshu Thapliyal

Best Poster/LBR Award 2nd Place

Statistical Weight Refresh System for CTT-Based Synaptic Arrays Samuel Dayo, Ataollah Saeed Monir, Mousa Karimi and Boris Vaisband

The 33 rd edition of GLSVLSI will be held as an in-person conference. Original, unpublished papers describing research in the general areas of VLSI and hardware design are solicited. Stay tuned for more information.

In addition to the traditional topic areas of GLSVLSI listed below, papers are also solicited for a new track on “ IoT and Smart Systems ” .

Important Dates

Keynote speakers, program tracks.

• VLSI Circuits and Design: ASIC and FPGA design, microprocessors/micro-architectures, embedded processors, high-speed/low-power circuits, analog/digital/mixed-signal systems, NoC, SoC, IoT, interconnects, memories, bio-inspired and neuromorphic circuits and systems, BioMEMs, lab-on-a-chip, biosensors, CAD tools for biology and biomedical systems, implantable and wearable devices, machine-learning for design and optimization of VLSI circuits and design.
• IoT and Smart Systems: Circuits, computing, processing, and design of IoT and smart systems such as smart cities, smart healthcare, smart transportation, smart grid etc.; cyber-physical systems, edge computing, machine learning for IoT, TinyML, cloud computing for IoT devices.
• Computer-Aided Design (CAD): Hardware/software co-design, high-level synthesis, logic synthesis, simulation and formal verification, layout, design for manufacturing, algorithms and complexity analysis, physical design (placement, route, CTS), static timing analysis, signal and power integrity, machine learning for CAD and EDA design.
• Testing, Reliability, Fault-Tolerance: Digital/analog/mixed-signal testing, reliability, robustness, static/dynamic defect- and fault-recoverability, variation-aware design, learning-assisted testing.
• Emerging Computing & Post-CMOS Technologies: Nanotechnology, quantum computing, approximate and stochastic computing, sensor and sensor networks, post CMOS VLSI.
• Hardware Security: Trusted IC, IP protection, hardware security primitives, reverse engineering, hardware Trojans, side-channel analysis, CPS/IoT security, machine learning for HW security.
• VLSI for Machine Learning and Artificial Intelligence: Hardware accelerators for machine learning, novel architectures for deep learning, brain-inspired computing, big data computing, reinforcement learning.
• Microelectronic Systems Education: Pedagogical innovations using a wide range of technologies such as ASIC, FPGA, multicore, GPU, TPU, educational techniques including novel curricula and laboratories, assessment methods, distance learning, textbooks, design projects, and industry/academic collaborative programs and teaching.

Author Guidelines

Paper Submission: Authors are invited to submit full-length (6 pages maximum), original, unpublished papers along with an abstract of at most 200 words. To enable blind review, the author list should be omitted from the main document. Previously published papers or papers currently under review for other conferences/journals should NOT be submitted and will not be considered. Electronic submission in PDF format to the http://www.glsvlsi.org website is required. Author and contact information (name, affiliation, mailing address, telephone, fax, e-mail) must be entered during the submission process.

Paper Format (camera-ready): Submissions should be in camera-ready two-column format, following the ACM proceedings specifications located at: ACM Template and the classification system detailed at: ACM 2012 Class

For Overleaf users, please find the following template: ACM Proceedings Template - Overleaf . For LaTeX users, please find the following ZIP file: acmart-primary.zip . For Word users, please find the following template: interim-layout.docx .

The submission site is already open . The email with a submission link and the copyright forms will be sent to the corresponding author as specified during submission. Each author gets a unique link and unique DOI. Please use the link in the email for Camera-Ready submission. If you have questions regarding the corresponding author, please contact Kyle Rupnow, Proceedings Chair . Camera-Ready submission instruction is available

Paper Publication and Presenter Registration: Papers will be accepted for regular or poster presentation at the symposium. Every accepted paper MUST have at least one author registered to the symposium by the time the camera-ready paper is submitted; at least one of the authors is also expected to attend the symposium and present the paper.

This site is maintained by: GLSVLSI 2023 Webmaster Tyler Cultice ( [email protected] ), University of Tennessee - Knoxville.

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Back propagation neural network based power estimation method for CMOS VLSI circuits

Low power vlsi design techniques: a review.

Since CMOS technology consumes less power it is a key technology for VLSI circuit design. With technologies reaching the scale of 10 nm, static and dynamic power dissipation in CMOS VLSI circuits are major issues. Dynamic power dissipation is increased due to requirement of high speed and static power dissipation is at much higher side now a days even compared to dynamic power dissipation due to very high gate leakage current and subthreshold leakage. Low power consumption is equally important as speed in many applications since it leads to a reduction in the package cost and extended battery life. This paper surveys contemporary optimization techniques that aims low power dissipation in VLSI circuits.

Design of low-power CMOS VLSI circuits using multi-objective optimization in genetic algorithms

This paper presents a design CAD tool for automated design of digital CMOS VLSI circuits. In order to fit the circuit performance into desired specifications, a multi-objective optimization approach based on genetic algorithms (GA) is proposed and the transistor sizes are calculated based on the analytical equations describing the behavior of the circuit. The optimization algorithm is developed in MATLAB and the performance of the designed circuit is verified using HSPICE simulations based on 0.18µm CMOS technology parameters. Different digital integrated circuits were successfully designed and verified using the proposed design tool. It is also shown in this paper that, the design results obtained from the proposed algorithm in MATLAB, have a very good agreement with the obtained circuit simulation results in HSPICE.

Technologies for creating radiation-resistant VLSI

The technology of radiation-resistant CMOS VLSI is based on industrial IC technology. The design uses feedback circuits and guard rings to compensate for single effects of cosmic particles (SEE). In most critical cases, these influences in digital circuits lead to single faults (SEU), which temporarily disrupt the state of memory cells, to latching (SEL), and in the long term to a catastrophic change of state. Various space programs confirm great prospects for their use in future space structures. The article discusses the effects of using radiation-resistant CMOS technology, technology based on a silicon-on-sapphire structure, CMOS technology on an insulating substrate taking into account typical characteristics, SIMOX-SOI technology, which consists in separation by implantation of oxygen ions. In new designs of circuits, more advanced algorithms should be implemented for the future.

Machine Learning Based Power Estimation for CMOS VLSI Circuits

Abstract The authors have requested that this preprint be withdrawn due to a need to make corrections.

Abstract Nowdays, machine learning (ML) algorithms are receiving massive attention in most of the engineering application since it has capability in complex systems modelling using historical data. Estimation of power for CMOS VLSI circuit using various circuit attributes is proposed using passive machine learning based technique. The proposed method uses supervised learning method which provides a fast and accurate estimation of power without affecting the accuracy of the system. Power estimation using random forest algorithm is relatively new. Accurate estimation of power of CMOS VLSI circuits is estimated by using random forest model which is optimized and tuned by using multi-objective NSGA-II algorithm. It is inferred from the experimental results testing error varies from 1.4 percent to 6.8 percent and in terms of and Mean Square Error is 1.46e-06 in random forest method when compared to BPNN. Statistical estimation like coefficient of determination (𝑅) and Root Mean Square Error (RMSE) are done and it is proven that random Forest is best choice for power estimation of CMOS VLSI circuits with high coefficient of determination of 0.99938. and low RMSE of 0.000116.

Leakage Power Reduction in CMOS VLSI Circuits using Advance Leakage Reduction Method

Recently, consumption of power is key problem of logic circuits based on Very Large Scale Integration. More potentiality consumption isn’t considered an appropriate for storage cell life for the use in cell operations and changes parameters such as optimality, efficiency etc, more consumption of power also provides for minimization of cell storage cycle. In present scenario static consumption of power is major troubles in logic circuits based on CMOS. Layout of drainage less circuit is typically complex. Several derived methods for minimization of consumption of potentiality for logic circuits based on CMOS. For this research paper, a technique called Advance Leakage reduction (AL reduction) is proposed to reduce the leakage power in CMOS logic circuits. To draw our structure circuit related to CMOS like Inverter, inverted AND, and NOR etc. we have seen the power and delay for circuits. This paper incorporates, analyzing of several minimization techniques as compared with proposed work to illustrate minimization in ratio of energy and time usage and time duration for propagation. LECTOR, Source biasing, Stack ONOFIC method is observed and analyzed with the proposed method to evaluate the leakage power consumption and propagation delay for logic circuits based on CMOS. Entire work has done in LT Spice Software with 180nm library of CMOS.

Revisiting the Utility of Transmission Gate and Passtransistor Logic Styles in CMOS VLSI Design

Peculiarities of appearance and registration of the latchup in cmos vlsi under uniform pulsed laser irradiation, export citation format, share document.

Emerging VLSI Trends in 2023

• by Maven Silicon
• July 19, 2023
• 3 minutes read

Looking for the latest VLSI trends and VLSI jobs in 2023? Maven Silicon, a leading VLSI training institute, is here to guide you. VLSI is revolutionizing industries with its ability to integrate millions of transistors onto a single chip. In this blog post, we’ll explore the emerging VLSI trends in 2023 that are shaping the future and highlight the exciting job openings in this field. Discover the benefits of pursuing a career in VLSI and how Maven Silicon can help you kick-start your journey.

VLSI Application & Trends in 2023

The applications of VLSI span across various industries, including telecommunications, automotive, healthcare, and artificial intelligence. As we move into 2023, several VLSI trends are making waves:

AI-driven VLSI

Artificial Intelligence (AI) has merged with VLSI, opening up endless possibilities. AI-driven VLSI solutions have gained significant traction in industries like autonomous vehicles, robotics, smart homes, and beyond. The integration of AI algorithms directly into VLSI chips allows for the real-time processing of massive amounts of data, leading to intelligent decision-making and unprecedented levels of efficiency. This trend empowers autonomous vehicles to analyze complex surroundings, robots to navigate dynamically changing environments, and smart homes to adapt to residents’ preferences seamlessly. The synergy between AI and VLSI has propelled us toward a new era of intelligent and responsive technologies.

IoT and VLSI

The Internet of Things (IoT) revolution is in full swing, and VLSI plays a pivotal role in shaping this interconnected ecosystem. Emerging trends in VLSI focus on designing chips optimized for IoT-enabled devices, ensuring efficient data communication, low power consumption, and enhanced security. These specialized VLSI chips enable IoT devices to communicate seamlessly over the internet, exchanging data with other devices and cloud services. Moreover, with advancements in low-power design techniques, IoT devices can operate for extended periods on battery power, making them more practical and environmentally friendly. VLSI’s contribution to IoT is driving the proliferation of smart homes, smart cities, and industrial automation, transforming the way we interact with our surroundings.

Edge Computing and VLSI

Edge computing has emerged as a game-changer in handling real-time data processing and analysis. VLSI’s role in this trend is crucial, as it enables the development of high-performance, energy-efficient chips tailored for edge devices. By processing data locally at the edge, these VLSI chips significantly reduce latency and response times, making them ideal for applications that demand immediate results. Edge devices, such as sensors and cameras, benefit from low-power VLSI solutions that allow for prolonged operation without compromising performance. The combination of edge computing and VLSI has unlocked a new realm of possibilities, from responsive AI applications to smart infrastructure like traffic management and environmental monitoring.

Benefits of VLSI

Exciting and challenging work.

The field of VLSI indeed provides a dynamic and intellectually stimulating work environment for engineers and professionals. As a VLSI engineer, you get the opportunity to be at the forefront of designing complex integrated circuits that power a wide range of electronic devices, from smartphones and computers to IoT devices and automotive electronics.

Also read: Why VLSI is Used?

Lucrative Job Opportunities

The demand for VLSI professionals is on the rise, making it a highly sought-after field with numerous job opportunities across various industries. As technology continues to advance and electronic devices become an integral part of our lives, the need for skilled VLSI engineers has grown significantly.

Positions such as VLSI Design Engineer, Verification Engineer, and Physical Design Engineer are in high demand. VLSI Design Engineers are responsible for designing and architecting integrated circuits, while Verification Engineers focus on validating and testing chip designs. Physical Design Engineers, on the other hand, play a crucial role in implementing the circuit layout to optimize performance and power consumption.

Also read: Skills required to become a VLSI engineer?

Job Openings

If you’re eager to embark on a VLSI career, numerous job openings await you. Maven Silicon is renowned for its VLSI training with 100% placement assistance. Explore exciting roles like VLSI Design Engineer, Verification Engineer, Physical Design Engineer, FPGA Engineer, and Analog/Mixed-Signal Design Engineer.

Also read: Salary of VLSI Engineers in India

As we step into 2023, the world of VLSI presents abundant opportunities. Stay updated with the latest VLSI trends, leverage the benefits of this field, and secure a rewarding career in VLSI. Maven Silicon can equip you with the necessary skills to excel in the ever-evolving VLSI landscape. Start your journey towards a successful VLSI career today with our job-oriented courses .

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Why should i do vlsi training.

All the Integrated Chips we use in mobiles, TVs, computers, satellites, and automobiles, etc. are designed with VLSI technology. Hence, there is a huge scope and growth in the VLSI Industry and it is full of job opportunities. Since there is a huge gap between what the college education offers and the industry expectation, it is recommended to go for the VLSI training which bridges that gap and gives you a great hands-on experience.

What is chip designing?

Steps involved in Chip design Chip’s architecture: Create circuit designs, Run simulations, Supervise layout, Tape out the chip to the foundry and Evaluate the prototype once the chip comes back from the laboratory. Chip designers work to make faster, cheaper and more innovative chips that can automate parts or the entire function of electronic devices. A chip design engineer’s job involves architecture, logic design, circuit design and physical design of the chip, testing, and verification of the final product.

Is VLSI a good career?

VLSI is a very good domain to build a career with a huge number of opportunities. There is a demand for chips in every sector, be it automobiles, consumer electronics or high-end servers. You should have good command on Verilog, SystemVerilog, and UVM to start your career as VLSI Design or VLSI Verification Engineer

What is the eligibility for VLSI Chip Designing Courses?

The undergraduates, graduates, or postgraduates from below streams can take up VLSI Chip Design Course and make a career in VLSI Industry. BE/BTech in EEE/ECE/TE or ME/MTech/MS in Electronics/MSc Electronics

To join the industry as a VLSI verification engineer, you must have hands-on experience of below topics: SystemVerilog, Universal Verification Methodologies UVM, Assertion based Verification SVA

Maven Silicon provides the best quality VLSI training through a variety of design and verification courses to suit your need and demand. We offer online VLSI courses, Job-oriented fulltime and Blended VLSI courses, Internship programs, part time courses and corporate training.Explore our offerings at https://www.maven-silicon.com/

Every course has a different admission procedure: 1. For Advanced VLSI Design and Verification course at Maven Silicon, you can apply while you are in the final semester, graduation or post-graduation. 2. For the Internship program, you can apply in your pre-final/final year. Advise you to book your seats in advance, pertaining to limited admissions and increased demand. 3. You can subscribe to our online courses directly from our elearn portal https://elearn.maven-silicon.com/ You can apply for our Online, Job-oriented, Part-time and Corporate courses on https://www.maven-silicon.com/application

We do have an entrance exam for our job-oriented courses VLSI RN and VLSI VM. After you meet the eligibility criteria you have to undergo an Online Entrance Test which would check you on the concepts of Basic Electronics and Digital Electronics. Post scoring 60% in this test, you are processed for the technical interview with our technical experts. Based on your performance during the interview, you will be selected for the Advanced VLSI Design and Verification course. For our online VLSI courses, we do not have any entrance exams. You can directly subscribe the courses from our elearn portal https://elearn.maven-silicon.com/

Yes, we do provide the scholarship on our job-oriented courses VLSI RN and VLSI VM based on your performance in the technical interview. To excel in the Online entrance test and the technical interview, we suggest you take our Online Digital electronics course at https://elearn.maven-silicon.com/digital-electronics This online Digital electronics course will help you to learn and refresh the complete fundamentals of digital electronics, highly needed for any VLSI course. Contact us for more details.

We provide 100% placement assistance with our job-oriented course until you get placed. You can refer the link for the placement updates and know more about our hiring partners: https://www.maven-silicon.com/placement

VLSI Frontend course imparts training in the Design and Verification of a chip which mostly includes RTL(Register Transfer Level) coding using either VHDL/Verilog/SystemVerilog and the verification of the DUT(can be an IP or SOC) by building verification Environment or Testbench using SystemVerilog/UVM/.You also learn to meet the timing constraints of the chip using STA(Static Timing Analysis) and Synthesizing the design using synthesizable constructs. The maximum number of VLSI job opportunities are available in the Verification segment. Backend courses mostly deal with the physical design part of the chip which includes Floorplan, Map, Place and route and DFT and ATPG scan insertion and checks for the flip flops. It also includes the physical verification part of the chip, memory characterization, analog layout, and design.

Yes. VLSI is a high growth domain with huge job opportunities. Electronics is the basic knowledge required to get into the VLSI industry. Engineers with Electronics background can enter into VLSI Industry easily. The VLSI Course is helpful for ECE/EEE students to learn and build up the skill set as per the Industry requirement to enter the Chip/IC Design and Verification Domain.

Inexpensive courses with the utmost quality are our unique selling points. You can explore our courses at https://elearn.maven-silicon.com/

We help you with support material to enhance your basic knowledge of Digital electronics and perform your best. Our online Digital electronics course will help you to learn and refresh the complete fundamentals of digital electronics, which are highly needed for any VLSI course. Contact us for more details.

We do have online VLSI courses for engineers like you. You can start learning with our hands-on online VLSI courses which comes with labs, project, reference material. We also connect with live Q&A, doubt clarification sessions and Whatsapp support group. Click here to explore and subscribe https://elearn.maven-silicon.com/ . If you are looking for online VLSI course with Placement support, then you refer our Blended VLSI learning program at https://www.maven-silicon.com/blended-vlsi-design-asic-verification

We always encourage you to join the course along with friends because it motivates you to learn and finish the course at a fast pace. Contact us to know about group discount options.

Yes. It is good to start early. You can explore and subscribe to our online VLSI design methodologies course or our Internship Program. It is a front-end VLSI course that imparts the VLSI Design Flow, Digital Design and RTL programming using Verilog HDL. After completing the online VLSI DM course/Internship Program, you can easily crack college campus interviews or you can also take up our Advanced ASIC Verification course with 100% placement assistance and can avail up to 100% scholarship based on your grades in our Online VLSI Design Course and the scores of technical interview with our experts.

Yes, we have part-time/Weekend VLSI courses for working professionals. They are specially designed to help you strike a balance between your job and learning. Explore VLSI DM and VM part-time course under Part-time VLSI course in Program offerings at our website https://www.maven-silicon.com/systemverilog-uvm-functional-verification-course

Our Job oriented VLSI courses are highly effective and rigorous programs and follow a continuous evaluation scheme. Candidates are evaluated in the courses through lab reports, project reports, practice tests, assignments, technical presentations, and mock interviews. We also have an evaluation program in our Online VLSI courses through quizzes, tests, and assignments.

You do not need to pay extra for the requisite learning material. We do provide free library access and free online VLSI Courses to our trainees enrolled for job oriented courses for reference and support.

Once you complete your online VLSI course you can upgrade to job oriented VLSI Courses with a very good scholarship. We provide 100% placement assistance for the job oriented VLSI Courses. Advanced VLSI Design and Verification [VLSI – RN ] and Advanced ASIC Verification [ VLSI-VM ] are the job oriented VLSI Courses.

Maven Silicon offers customized in-house and onsite corporate VLSI training courses. This program is specially designed for engineers keeping in view the ever-changing demands of the industry. The participants are equipped with the latest tools, techniques, and skills needed to excel as Verification Engineers. Some of our Corporate training VLSI Courses are SystemVerilog HVL, Verilog HDL, Universal Verification Methodology and Assertion based Verification. Click here for more details: https://www.maven-silicon.com/corporate-training

Yes. Our courses will be very useful. We have had many students taking up our course before going to foreign universities for their Master’s program in VLSI. The practical approach of the courses could help them get campus job opportunities and assistantships..

You can opt for online or offline course but you must choose the right mode considering the time you can spend and the flexibility you need. The online course also provides you Live Q&A, doubt clarification, handy technical support and reference material. So, it is a great offering with best of both worlds. You can learn on the go along with your college studies/ regular office hours and upskill yourself. With Maven Silicon’s Online Verification course, you can master VLSI even if you stay in a remote corner of the world.

Steps involved in Chip design Chip’s architecture: Create circuit designs, Run simulations, Supervise layout, Tape out the chip to the foundry and Evaluate the prototype once the chip comes back from the laboratory. Chip designers work to make faster, cheaper and more innovative chips that can automate parts or the entire function of electronic devices. A chip design engineer’s job involves architecture, logic design, circuit design and physical design of the chip, testing, and verification of the final product.

We do have online VLSI courses for engineers like you. You can start learning with our hands-on online VLSI courses which comes with labs, project, reference material. We also connect with live Q&A, doubt clarification sessions and Whatsapp support group. Click here to explore and subscribe https://elearn.maven-silicon.com/ . If you are looking for online VLSI course with Placement support, then you refer our Blended VLSI learning program at https://www.maven-silicon.com/blended-vlsi-design-asic-verification

Once you complete your online VLSI course you can upgrade to job oriented VLSI Courses with a very good scholarship. We provide 100% placement assistance for the job oriented VLSI Courses. Advanced VLSI Design and Verification [VLSI – RN ] and Advanced ASIC Verification [ VLSI-VM ] are the job oriented VLSI Courses.

You can opt for online or offline course but you must choose the right mode considering the time you can spend and the flexibility you need. The online course also provides you Live Q&A, doubt clarification, handy technical support and reference material. So, it is a great offering with best of both worlds. You can learn on the go along with your college studies/ regular office hours and upskill yourself. With Maven Silicon’s Online Verification course, you can master VLSI even if you stay in a remote corner of the world.

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MINI REVIEW article

This article is part of the research topic.

Bridging Chemistry with Biology through Speciation Chemistry in Important Processes Involving Essential and Non-essential Metal Ions: Developed from the ICBIC 2023

Special issue: "Bridging Chemistry with Biology through Speciation Chemistry in Important Processes Involving Essential and Non-essential Metal Ions": Developed from ICBIC 2023 Provisionally Accepted

• 1 University of São Paulo, Brazil
• 2 Rio de Janeiro State University, Brazil

The final, formatted version of the article will be published soon.

In the development of new medicinal or pharmaceutical agents, the presence of isomers is a huge challenge, since the main goal is to obtain the most active compound in high purity and yield. Tautomerism is a phenomenon quite common in biomolecules, that also appears in many drugs, and strategies to control the corresponding desired species and related equilibria conditions leading to an efficient chemical speciation are frequently required. In the literature, there are many reports about the presence of tautomers, despite some papers which do not emphasize properly their occurrence or its importance for the differences verified in biological activity. Herein, a discussion about tautomers, observed both in metalated and non-metalated compounds, and their importance in the biological properties of promising drugs is revisited. Mainly, keto-enol equilibria among imines and hydrazones oxindole derivatives are showcased, based on significant examples, as well as strategies to improve their speciation or to better elucidate their modes of action.

Keywords: chemical speciation, tautomerism, Keto-enol equilibria, Medicinal agents, promising scaffolds

Received: 13 Mar 2024; Accepted: 29 Apr 2024.

Copyright: © 2024 Ferreira, Oliveira and Wegermann. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Ana Maria D. Ferreira, University of São Paulo, São Paulo, Brazil

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

• Age & Generations
• Demographic Research
• Generation X
• Generation Z
• Generations
• Greatest Generation
• Methodological Research
• Millennials
• Silent Generation

Kim Parker is director of social trends research at Pew Research Center

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Westat-Led Article Awarded 2023 JRM Best Paper

April 30, 2024

The Journal of Registry Management (JRM) Best Paper of the Year for 2023 has been awarded to a Westat-led journal article. “ Rationale and Methodologic Approach for Assessing Ovarian Cancer Treatment and Gynecologic Oncologist Involvement in the Midwest Region of the United States ” was written as a collaborative effort with CDC authors, led by Westat’s Diane Ng, MPH, and included Westat authors Wilhelmina Ross, PA, MPH, ODS, and Maricarmen Traverso-Ortiz, MPH, ODS.

The JRM , affiliated with the National Cancer Registrars Association (NCRA), awards the Best Paper based on its contribution to medical registry work, as well as for encompassing theory, practice, and management of registries, professional development, and/or the collection, quality review, reporting, and use of registry data.

The article discusses a CDC study focused on ovarian cancer treatment and outcomes in the Midwest, where access to specialized gynecologic oncologists is limited and the region is geographically diverse with respect to urbanicity. The article describes how central cancer registries were used to gather additional data, particularly concerning the involvement of gynecologic oncologists in the patient’s care and specific treatment details.

“The article outlines lessons learned that can help inform future studies interested in a similar methodologic approach to obtain additional data beyond what is collected by cancer registries, including detailed treatment associated with cancer cases,” notes Ng. “This additional data can help enable researchers to identify disparities in care, which can lead to interventions to improve outcomes in cancer patients.”

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