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**Personal Background**: I got a PhD degree from Electrical Engineering at Peking University, currently a postdoc in the U.S., and preparing to pursue a faculty position. I have published 4 first-author conference/journal papers (with IF>8, CCF-A), 2 are under review, and 2 are in the implementation stage. I have led multiple successful tape-outs, with 28nm technology and designs involving millions of transistors. I have modest expectations – I’m not a big shot, just looking to make progress.
**Target Collaborators**: Peers, undergraduates, master’s students, or PhD students. Undergraduates are particularly welcome.
**Research Situation**: I have many mature ideas and solutions that lack the manpower for implementation. These are not just purely algorithmic, far-fetched ideas but are combined with hardware and can demonstrate real results, with a high probability of success. Specifically, the work involves optimizing existing implementations, requiring either training network algorithms or writing hardware modules, with a high likelihood of resulting in strong publications. Alternatively, I already have hardware and need to explore its application scenarios.
**What I Offer**: Co-authorship (with order based on contribution), along with soft support such as research guidance, AI algorithms, hardware implementation, chip tape-out mentoring, recommendations for further education, etc.
**What You Should Offer**: Most importantly, sufficient time to carry out the work (estimated at three months, with an average of 3 hours per day). Secondly, you should have a basic programming foundation or Verilog hardware background, or enjoy conducting research. Ideally, you should not be affiliated with a specific advisor.
Serious inquiries only, thanks.
If convenient, please send your resume for review. Personal information can be omitted.
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Dear Sir,
I studied your research background and requirements. I have experience of writing research publications and I have published a journal paper with detailed design and development based on verilog programming and FPGA. I also design and develop electrical power and electronic circuits and systems. So, we can collaborate in research.
Regards
Naseer Ahmed
Senior Engineer Electrical.
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What are the best practices for optimizing the performance of hardware components?
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First things, clean hardware regularly (such as dust). Keep drivers updated, ensure proper cooling, upgrade RAM/SSD, cautiously overclock, , use a reliable power supply, optimize storage, adjust BIOS settings, disable unnecessary background services, and monitor system performance with tools.
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Are the most powerful hardware options for deep learning always the best choice?
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Machine Learning (ML) tasks are diverse, and so is the hardware on which they can be computed. To better understand how to speed up the calculations, it is important to know what kind of calculations are performed. Calculations used by ML algorithms are largely vector and matrix calculations. For this reason, a suitable computational accelerator for ML applications must be able to perform these calculations.
Regards,
Shafagat
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What is the long-term effect of the today’s hardware architecture choices (Von Neumann or parallel architectures of GPUs etc.) on the trajectory of AI system development?. What do Marr’s three levels say about that? How do NVIDIA's parallel hardware impact the way we perceive intelligence?
Let us consider the possibility that the behavioural similarity of different intelligences could be coupled with their endogenous structural similarities. While it’s plausible for other forms of intelligences to exhibit some similarity to the human traits, the likelihood of such emergence might be comparatively lower once designed independent of human brain. In other words, it seems reasonable to hypothesize that similar structural properties might lead to similar functional and operational characteristics under several known conditions.
I would suppose ground breaking genuine research work might be needed to precisely define such conditions and demonstrate a potentially inherent coupling between the hardware (the architecture) and the software (algorithm and/or learnable applications) in any intelligent system.
How about the effects of the hardware on which the intelligence is implemented on the development of our brain tissue? neural connectivity? biochemistry of information transfer? All such considerations must be given priority in the design of next generation AI if we really want to maintain a healthy mental state at the societal level and uphold human values against corruption.
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1. Enhanced Processing Power
  • Parallel Processing: Modern computational architectures, particularly those utilizing Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), enable parallel processing capabilities. This allows AI models to perform numerous computations simultaneously, significantly speeding up the training of deep learning models compared to traditional Central Processing Units (CPUs).
  • Resource Scalability: Cloud computing architectures enable the scaling of resources on-demand, allowing developers to leverage vast computational power for training large models without needing significant physical hardware investments.
2. Increased Memory and Storage
  • Handling Large Datasets: Advanced memory architectures with greater capacities allow for the storage and quick retrieval of large datasets, which are essential for training complex AI models. This is particularly important in fields like natural language processing (NLP) and computer vision, where datasets can be enormous.
  • Efficient Reinforcement Learning: Architectures that support greater memory bandwidth and faster access speeds facilitate reinforcement learning tasks that require rapid iteration and evaluation of numerous simulations.
3. Specialized Hardware Accelerators
  • TPUs and FPGAs: Tensor Processing Units (TPUs) and Field-Programmable Gate Arrays (FPGAs) are designed specifically to optimize the computations required for machine learning tasks. Developers can achieve faster training times and improved inference performance by utilizing these specialized devices.
  • Architecture Innovation: The design of specialized architectures that cater to various AI workloads enhances the performance of specific model types (e.g., convolutional neural networks for image processing).
4. Energy Efficiency
  • Low-Power Designs: New computational architectures emphasize energy efficiency, which is essential for deploying AI models in edge devices and IoT applications. This reduces operational costs and enhances the sustainability of AI solutions, enabling the deployment of AI models in resource-constrained environments.
  • Adaptive Computing: Some architectures can dynamically adjust power consumption based on workload, allowing for efficient performance while managing energy expenditures.
5. Improved Algorithm and Model Optimization
  • Development of New Algorithms: The advancements in computational architecture often drive algorithm innovations, enabling the exploration of more complex models (e.g., transformer architectures in NLP) that were previously impractical to train.
  • Hardware-Aware Training: Modern architectures allow for hardware-aware training methods that optimize model performance based on the specific capabilities of the deployed hardware, enhancing both training and inference speeds.
6. Distributed Computing
  • Collaborative Training: Modern computational architectures facilitate distributed training across multiple machines or clusters. This allows for faster processing, especially for large-scale datasets, and enables collaborative model training that harnesses the computational power from various nodes.
  • Federated Learning: Innovations in distributed systems support federated learning, allowing models to be trained across decentralized devices without data centralization, thereby improving privacy and security.
7. Real-Time Processing
  • Low-Latency Inference: Improvements in computational architecture support real-time processing capabilities necessary for applications like autonomous vehicles, smart surveillance, and interactive AI systems, where immediate model responses are critical.
  • Stream Processing: Modern architectures are designed to handle streaming data efficiently, which is vital for applications where data is continuously generated and must be processed in real time.
8. Easier Deployment and Integration
  • Frameworks and Tools: Modern architectures often come with robust frameworks and libraries (like TensorFlow, PyTorch, and ONNX) that simplify the development of AI models and enable easy deployment across different hardware environments.
  • DevOps Practices: Integrating AI with cloud-native architectures supports DevOps practices, allowing for smoother CI/CD pipelines, version control, and model management.
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I am currently studing Electrical & Electronics Engineering. For my individual research my institution asked to do only software or simulation based research. Please suggest an IOT or electronics side topic without hardware implementation.
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Let me see if I can paraphrase your question. You are being asked to analyze 'something' using only software or a software-based simulator. The 'something' needs to be either an IOT device or system, or a piece of stand alone hardware, but in either case no hardware implementation is to be attempted. For example, in the case of a piece of stand alone hardware, you would only have a schematic circuit diagram but no actual hardware, and you would simulate this hardware with, say, SPICE. Do I understand your question, correctly?
Regards,
Tom Cuff
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I need to implement it
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Hey there Nowsheen Khan!
Implementing a wind energy system in your hardware prototype sounds like an exciting project! To get started, you'll want to consider a few key factors.
Firstly, determining the scale of your wind energy system will help guide your design choices. Are you Nowsheen Khan aiming for a small-scale demonstration or something larger? This will impact the components you'll need and the complexity of your setup.
Next, consider the location and environmental conditions where your prototype will be tested. Understanding the average wind speeds and patterns will help optimize the efficiency of your system.
Regarding the use of a wind emulator, it depends on your specific requirements. While emulators can be useful for testing and validation, they may not always be necessary, especially if you Nowsheen Khan have access to real-world wind conditions for testing.
If you Nowsheen Khan do decide to use a wind emulator, ensure it accurately replicates the conditions your system will encounter. This will help validate your prototype's performance under various scenarios.
Remember, thorough planning and testing will be key to the success of your wind energy system implementation. Feel free to ask if you Nowsheen Khan need further guidance along the way!
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Hi everyone, my computer don't recognize the nanodrop and shows an error Code 10. Could be a driver error or a damage in hardware? Thanks for your help! :)
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To accurately determine the reason for the yellow light and ensure the proper functioning of your NanoDrop 8000, I recommend consulting the instrument's user manual or contacting the manufacturer's technical support for assistance. They can provide specific guidance based on the instrument's design and any error codes or messages displayed.
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Does anyone recommend an inexpensive and reliable software for animal behavior video recording?
I'm looking for a digital video recording software that can receive external hardware signal like 5V TTL pulse to trigger START/STOP of the camera. Therefore, the video can synchronize with other data acquisition software. Thank You!
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I believe these are both free. I have used JWatcher in the past and thought it was great, but that was over a decade ago and someone recently recommended Boris to me.
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I could not find a proper model to replicate or to make changes in.
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Sure, I can help you with the Simulink model for Hardware in Loop (HIL) for BLDC and induction motor test benches. Here are some general guidelines and considerations:
Simulink Model for BLDC Motor HIL:
  1. Plant Model: Create a detailed plant model of the BLDC motor, including electrical and mechanical parameters. This model should accurately represent the motor's dynamics and behavior under various operating conditions.
  2. Real-Time Interface: Implement a real-time interface to connect the Simulink model to the HIL system. This interface should allow for seamless data exchange between the simulation and the hardware.
  3. Controller Model: Develop a controller model that utilizes sensor feedback to regulate the speed and torque of the BLDC motor. The controller should be designed to achieve desired performance metrics such as speed accuracy, torque ripple, and efficiency.
  4. Data Acquisition and Monitoring: Implement data acquisition and monitoring blocks to capture relevant signals such as motor currents, voltages, speed, and torque. These signals can be visualized and analyzed to evaluate the performance of the motor and controller.
Simulink Model for Induction Motor HIL:
  1. Plant Model: Create a detailed plant model of the induction motor, including electrical, mechanical, and magnetic parameters. This model should accurately represent the motor's dynamics and behavior under various operating conditions.
  2. Real-Time Interface: Implement a real-time interface to connect the Simulink model to the HIL system. This interface should allow for seamless data exchange between the simulation and the hardware.
  3. Controller Model: Develop a controller model that utilizes sensor feedback to regulate the speed and torque of the induction motor. The controller should be designed to achieve desired performance metrics such as speed accuracy, torque ripple, and efficiency.
  4. Data Acquisition and Monitoring: Implement data acquisition and monitoring blocks to capture relevant signals such as motor currents, voltages, speed, and torque. These signals can be visualized and analyzed to evaluate the performance of the motor and controller.
Additionally, consider the following specific aspects of BLDC and induction motor HIL testing:
BLDC Motor HIL:
  1. PWM Generation: Implement a PWM generation block to generate the appropriate switching signals for the BLDC motor's inverter.
  2. Sensor Emulation: If using real-time hardware-in-the-loop (RT-HIL) testing, ensure that the HIL system can emulate sensor signals accurately.
  3. Fault Simulation: Implement fault simulation blocks to test the controller's response to various faults such as sensor failures or motor overloads.
Induction Motor HIL:
  1. Field-Oriented Control (FOC): Implement a FOC algorithm to achieve precise control of the induction motor's speed and torque.
  2. Parameter Identification: Develop algorithms to identify the induction motor's parameters online, ensuring accurate model representation.
  3. Load Simulation: Implement load simulation blocks to test the motor's performance under different load conditions.
Remember that safety is paramount when working with hardware-in-the-loop systems. Always follow proper safety procedures and ensure that the test environment is secure and controlled.
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The required hardware, software skills, and knowledge to build a computation platform for drug discovery from scratch.
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Hardware Requirements:
  1. High-Performance Computing (HPC) Cluster: Invest in dedicated HPC resources for computational tasks.
  2. Powerful Workstations: Equip research workstations with high-performance CPUs and GPUs.
  3. Storage Infrastructure: Set up scalable and high-capacity storage for handling large datasets.
  4. Data Backup and Redundancy: Implement data backup and redundancy solutions for data protection.
Software and Skills:
  1. Molecular Modeling Software: Use software like Schrödinger Suite, AutoDock, GROMACS, and CHARMM.
  2. Chemoinformatics Tools: Employ tools for compound library management and virtual screening.
  3. Bioinformatics Software: Analyze genomics data and identify drug targets using bioinformatics tools.
  4. Machine Learning and Data Science: Utilize Python, R, TensorFlow, and PyTorch for predictive modeling.
  5. Database Management: Manage databases for chemical and biological data.
  6. Data Visualization: Visualize research findings with tools like Matplotlib and Tableau.
  7. Version Control: Use Git for code versioning and repository management.
  8. Linux/Unix Skills: Navigate Linux/Unix for data management and simulations.
  9. Scripting and Programming: Automate tasks with Python and other scripting languages.
  10. Parallel Computing: Harness the power of multi-core processors and HPC clusters.
Knowledge and Expertise:
  1. Pharmaceutical and Biochemical Knowledge: Understand pharmacology and medicinal chemistry for drug target identification.
  2. Bioinformatics and Chemoinformatics: Analyze data and perform structure-activity relationship (SAR) studies.
  3. Molecular Biology: Grasp DNA, RNA, and protein structure and function.
  4. Machine Learning and Data Science: Apply ML and data science for predictive modeling.
  5. Regulatory and Ethical Considerations: Stay compliant with regulatory guidelines and ethical standards.
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Hello Everyone,
We have LTE tool box option in MATLAB and we can generate the LTE signal for visualization. Is this possible to have an LTE signal in .C or .HDL form? What are the possibilities to get LTE signal in these form, because to develop a hardware and if LTE used as a reference signal then what are the solutions?
Thanks in advance and I welcome to all researchers, Faculties and Industrialist for your participation.
Best Wishes,
Dr. Akhilesh Verma
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Thanks Shukur!
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Maximum time when I going to finetune a big modal like GPT-neo GPT-J. after download I I have faced RAM issue or GPU or version issue. if need more resource what will be the best pc configuration because I am going to build a new pc for this issue. at present I have 16GB RAM , 4GB graphic and Core-i5 HQ series processor.
Thanks in advance.
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Here are some strategies to address PC resource limitations:
  1. Upgrade Hardware: Consider upgrading the PC's hardware components, such as adding more RAM, upgrading the CPU or GPU, or installing a faster storage drive (e.g., SSD). Upgrading hardware can significantly improve performance and responsiveness.
  2. Close Unnecessary Programs: Ensure that unnecessary programs and background processes are closed to free up system resources. Use Task Manager (Windows) or Activity Monitor (Mac) to identify resource-hungry applications and terminate them.
  3. Optimize Startup Programs: Disable unnecessary startup programs to reduce the load on system resources during boot-up. This can be done through the Task Manager (Windows) or System Preferences (Mac).
  4. Regularly Update Software: Keep the operating system and software applications up to date to benefit from performance improvements and bug fixes.
  5. Use Lightweight Software: Consider using lightweight and optimized software alternatives that consume fewer resources compared to resource-intensive applications.
  6. Disk Cleanup: Regularly perform disk cleanup to remove temporary files, cache, and unnecessary system files that may consume disk space and slow down the PC.
  7. Limit Background Processes: Be mindful of resource-intensive background processes like automatic updates, syncing services, and real-time scans. Adjust the settings to reduce their impact on system performance.
  8. Use Cloud Storage: Offload data and files to cloud storage services to free up local disk space and reduce the strain on the system.
  9. Virtual Memory Management: Adjust virtual memory settings to ensure efficient usage of RAM and avoid excessive swapping to disk.
  10. Malware Protection: Use reliable antivirus and anti-malware software to prevent resource-draining malware from affecting system performance.
  11. Browser Optimization: Optimize web browsers by limiting extensions, clearing cache regularly, and avoiding too many open tabs.
  12. Defragmentation (for HDDs): If using a traditional hard disk drive (HDD), perform occasional disk defragmentation to improve file access speed.
  13. Use Resource Monitoring Tools: Utilize resource monitoring tools to identify resource bottlenecks and monitor system performance over time.
  14. Consider Task Prioritization: Prioritize tasks based on resource requirements. For example, avoid running resource-intensive applications simultaneously.
  15. Consider Cloud Computing: For tasks that require significant resources, consider using cloud computing services to offload the processing burden from the local PC.
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We have an Akta Purifier at the lab and It was working Ok til last month when without warning the comunication between the software and the Akta doesn't seem to work properly.
I can send orders from the software and the akta response, but the software doesn't register anything in the logbook. It also does not register the UV or de Conductivity data, and the Run, Pause, End buttoms are disabled.
The software does not send any error at all. but if I disconnect the AKTA, the software warns that it loose the connection.
So, software sends orders, the equipment react properly
the software does not register anything (no logbook/no Error/no UV/ no Cond)
The software, received signals form the Akta, when it is disconnected.
can anyone give me an idea of what the problem could be the problem?
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Hello friends, we tried everything, we called for the technical service from the Cytiva representative here in my country. There was no way to fix it, the box was not communicating with computer. We bought the CU-950 again
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I recently reactivated our AKTA Pure (after we moved it to a new bench), but the AKTA is suddenly not recognizing the F9-C fraction collector. (It was working well before.) I can hear the fraction collector arm trying to move, but it does not. The AKTA shows the error message "(Error) Hardware Manager: Fraction Collector Arm (F9-A) : (30) The fractionation arm failed to find the home position."
I checked the tubing from the fraction collector to the AKTA and the cable from the fraction collector to the AKTA, and they are connected. I checked the system properties, and the enabled components of the system look correct. I manually purged all the valves with ethanol. I restarted the AKTA and the computer several times, but I get the same message. Has anyone experienced this, and how did you fix it? Thanks.
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1. Turn off both the AKTA Pure and the F9-C fraction collector.
2. Locate the communication cable that came with the F9-C fraction collector. The cable will have a DB-9 connector on one end and an RJ-45 connector on the other end.
3. Connect the DB-9 connector of the communication cable to the RS-232 port on the back of the F9-C fraction collector.
4. Connect the RJ-45 connector of the communication cable to the RS-232 port on the back of the AKTA Pure system.
5. Turn on the F9-C fraction collector, and then turn on the AKTA Pure system.
6. Once both systems are powered on, navigate to the "System Configuration" menu on the AKTA Pure system.
7. Select "Hardware Configuration" and then choose "F9-C Fraction Collector" from the drop-down menu.
8. Enter the appropriate communication settings for the F9-C fraction collector, such as the baud rate, data bits, stop bits, and parity. These settings can usually be found in the F9-C fraction collector user manual.
9. Save the changes, and then exit the menu.
10. You should now be able to control the F9-C fraction collector from the AKTA Pure system. To test the connection, try running a sample purification and verify that the fractions are being collected correctly by the F9-C fraction collector.
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mainly for result validation by using matlab based simulation
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There are a number of hardware platforms that can be used for executing EV-related simulations. Here are a few options:
1. Typhoon HIL: Typhoon HIL offers a range of real-time hardware-in-the-loop simulation platforms that can be used for EV-related simulations. Their platforms are designed to provide high-fidelity, real-time simulation of power electronics and control systems.
2. National Instruments: National Instruments offers a range of hardware platforms, including the CompactRIO and the PXI, that can be used for real-time simulation and control of EV-related systems. Their platforms can be programmed using LabVIEW or other programming languages.
3. MathWorks: MathWorks offers a range of hardware platforms that can be used for real-time simulation and testing of control systems, including EV-related systems. These platforms include the xPC Target and the Simulink Real-Time.
4. Vector: Vector offers a range of hardware platforms for real-time simulation and testing of automotive and transportation systems, including EV-related systems. Their platforms include the CANoe and CANalyzer software tools.
5. ETAS: ETAS offers a range of hardware platforms for real-time simulation and testing of automotive and transportation systems, including EV-related systems. Their platforms include the LABCAR and the INCA software tools.
It's important to note that the choice of hardware platform will depend on the specific requirements of your EV-related simulation. Consider factors such as the complexity of the system, the level of fidelity required, and the available budget when selecting a hardware platform.
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Recently domain-specific hardware accelerators are getting more popular. While designing them what should be the approach? If anyone can guide me here. As I am a bit confused about the implementation part.
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Thanks a lot. answers and feedback gave me confidence that I am working in the correct direction.
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What is the difference between a conventional rectifier and an ultrafast rectifier?
What is the hardware difference ?
What different control technique is implemented to make the rectifier ultrafast?
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See the properties of Diode SCHOTTKY.
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Simulating AM processes are time-consuming action compared with doing casting process, since the AM processes fabricate CAD models upon a layer-by-layer method. Let's consider condition that the model dimensions are roughly large. Thus, the computing time will take a long time to be done. Apart from the time issues, this action definitely has a bad effect on the hardware of the system!
Are there any practical alternatives to solve this problem? In my opinion, the solution may include changing such material properties as density and conductivity in a way differing from those which have been selected for computing casting process, or just simplifying the model and reducing the domain sizes!
Any comments will be appreciated.
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Modeling software such as CAD, CAE, and CAM is widely used in simulation and other animation processes. Higher specifications for the processor, RAM, and graphic processor are needed for this software. There are other programs like Flow-3D Cast and Novacast Software that are built for particular procedures.
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I am doing research in IOT/WSN and developing my own protocols in NetSim. For testing with real hardware, I want to connect Raspberry Pi to NetSim. Would you know how this can be done?
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How can we incorporate MAC/PHY impairments in NetSim when connecting a Raspberry PI (controller) and sensor to NetSim?
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Hi all the ResearchGate community!
I am going to do some spectrophotometric measures, for what I am going to use a spectrophotmeter which is controlled by means of a software installed in a computer (to which the spectrophotometer is connected).
Even though the spectrophotometer is properly connected to the computer via the corresponding wire, I am not able to control the spectrophotometer with the computer.
I have made sure to install the program correctly, and I have also installed the drivers which allow the software to control the spectrophotometer.
The spectrophotometer cannot be used without the software. Could someone give me some light about this?
Thanks in advance!
Pablo
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I need more information on the way the device is connected. Is the Analog to Digital conversion being done in the Device (Spec.) and only results communicated to the computer, or is the communication being done over one of the "standard" interfaces like HDMI or any PD (thru PD++)or just Ethernet, but with the conversions being done within the computer. There are 2 basic questions: 1) where are the control function decisions being made 2)how are the communications being managed. The difference is how much the vendor is using commercial off the shelf (COTS) components with industry standard interface definitions, and how much is a custom proprietary implementation?
You would need to know these details of the interface to diagnose the issues you described.
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we want to develop 5G research lab so please suggest software/hardware
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My recommendations are:
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Can we look at relationship between brain and consciousness similar to relationship between hardware and software?
There conciseness sound more like GUI part of computer software?!
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Your question reminded me of a comparison between different components of the mind, regarded as hardware and software. Hambrick and Engle (2002) mention that working memory capacity and other aspects of the cognitive system are the mind's hardware due to their relatively stable nature. On the other hand, domain knowledge would be a more flexible aspect. Hence, it would be considered the software.
Cheers,
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I am a CSE student in last year of undergraduate program . I need a specific thesis proposal .
my interest is in AI . I am really struggling to find a real life problem . I've got 6month to complete my graduation . I would like to avoid hardware implementation . Please suggest some specific topic or idea that might help me to start thesis early .
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Aparna Sathya Murthy mam i would like to work in image processing . if you please give some suggetion
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I'm struggling with understanding and troubleshooting qPCR issues with cycles 1-3.
The rate of change for the cycles 1-3 is so high, it is tricking the software into thinking that is where the fastest rate of change is and throwing an error. See attached pictures of the PCR curve (Top) and rate of change graph (bottom).
My questions are as follows:
What are the factors and phenomenon that control PCR fluorescence in ~cycles 1-3? How do I eliminate the sudden increase at the start? Is there a hardware problem?
Note: Multiplex QPCR reaction using Taqman probes. Established and FDA approved assay.
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Looks like the baseline wasn't set correctly. Check the settings to make sure that someone didn't change the default settings.
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Dear respected
I would like to implement Automatic Switch between two PV panel Depending on output voltage (Exactly I mean depending on the shading ) to change connection form series to parallel or from parallel to series .... I implement it hardware by using two relay but in Simulink I can not do it
so how I can implement below image as MATLAB Simulink ?
kindly any one can help ?
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And very is "below image"?
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Why vedic mathematics based algorithms for division, multiplication etc. are not seen in reputed journals of Algorithms, Hardware architectures.
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For this we need to do Vedic maths smoothly and properly. we need proper comparative study.
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Dear colleagues,
from a practical point of view, how do I accurately measure sediment pH of more or less compacted, anoxic lake sediments in the field? Imagine there is a freshly recovered and opened core in front of you.
The problems that I imagine I have to deal with are:
1. that I may only have a very small amount of material available, say maximum 2 g or ml, maybe even less
2. that water content of the sediment will vary (maybe this is important when preparing a suspension?)
3. that handling steps should be minimezed due to anoxic sediment becoming oxidised quickly
4. that due to the small amount of of sediment available, the amount of suspension is also limited, so I might have to use 2 ml Eppendorf tubes, if I am lucky I can use 15 ml falcons, to obtain enough suspension for the pH-Meter to be submerged into and measure. Standard lab pH-Meters only barely fit 15 ml falcon tubes but not 2 ml Eppendorf tubes. Any advice about the hardware?
Using needle-like microsensors to measure directly in the sediment core is unfortunately not feasilbe.
Thank you for your comments!
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I would also go for a Microsensor. Unisense has sensors in a hypodermic needle which are rather robust do that you can push them into the sediment. Taking a small subsample always bears the risk of getting it oxidized and thus too low pH readings
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gmx mdrun -v -deffnm em
Back Off! I just backed up em.log to ./em.log.
Running on 1 node with total 8 cores, 16 logical cores
Hardware detected:
CPU info:
Vendor: GenuineIntel
Brand: Intel(R) Xeon(R) CPU E5620 @ 2.40GHz
SIMD instructions most likely to fit this hardware: SSE4.1
SIMD instructions selected at GROMACS compile time: SSE4.1
Reading file em.tpr, VERSION 5.1.5 (single precision)
Using 16 MPI threads
Using 1 OpenMP thread per tMPI thread
Back Off! I just backed up em.trr to ./em.trr.
Back Off! I just backed up em.edr to ./em.edr.
Steepest Descents:
Tolerance (Fmax) = 1.00000e+03
Number of steps = 100000
Step= 0, Dmax= 1.0e-02 nm, Epot= 9.29257e+19 Fmax= inf, atom= 8167
Step= 14, Dmax= 1.2e-06 nm, Epot= 9.29257e+19 Fmax= inf, atom= 8167
Energy minimization has stopped, but the forces have not converged to the
requested precision Fmax < 1000 (which may not be possible for your system).
It stopped because the algorithm tried to make a new step whose size was too
small, or there was no change in the energy since last step. Either way, we
regard the minimization as converged to within the available machine
precision, given your starting configuration and EM parameters.
Double precision normally gives you higher accuracy, but this is often not
needed for preparing to run molecular dynamics.
You might need to increase your constraint accuracy, or turn
off constraints altogether (set constraints = none in mdp file)
writing lowest energy coordinates.
Back Off! I just backed up em.gro to ./#em.gro.3#
Steepest Descents converged to machine precision in 15 steps,
but did not reach the requested Fmax < 1000.
Potential Energy = 9.2925744e+19
Maximum force = inf on atom 8167
Norm of force = inf
NOTE: 8 % of the run time was spent in domain decomposition,
13 % of the run time was spent in pair search,
you might want to increase nstlist (this has no effect on accuracy)
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It looks like a problem in the geometry of your system. If you don't notice anything unusual on visual inspection, you can try to rebuild your system or perform a double-precision minimization.
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I am looking for PhD level project related to optimizing blockchain using hardware acceleration. For example, implementing PoW in hardware may reduce resource consumption in IoT application, however, as PoS is becoming popular PoW may not be feasible in the future. Are there any other areas such as this in BC that can benefit from hardware acceleration?
Thank you for your time.
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If you are interested in developing hardware that will help to increase the huge number of transactions at low cost, such as; Application Specific Integrated Circuit, Smart Network Interface Card and FPGA.
These research papers include some information that you are looking for
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How to drive a 36v motor within Arduino hardware?
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We are using Agilent 7700X ICP-MS to test Iodine in milk products. Blank reading is usually at 4008-8000cps but recent readings are now at about 20000cps. Standards and samples have shown an increase in cps readings as well. We have replaced sample and standard tubings and cleaned the torch and cones. We have also purged the sample introduction system with Argon for around 8hrs at 0.2L/min. No other deviations were observed during hardware settings optimization and tuning but the problem still persists.
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Hi Abigail
After you did and if you fallow the above suggestion, if you still have the same issue, I am guessing the auto sampling probe contaminated your standards/blanks due too some kind of failure - obvious, If you have an auto-sampling...
Good luck
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HI!
I was wondering if it is possible and to a certain extent viable program a normal webcamera to be used as an eyetracker? This can be a great tool for those who may not have funds to procure a professional eyetracking hardware.
Also, are there any opensource softwares available that can do the abovementioned task?
Regards
Thanks
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Yes, it seems like that. Try here:
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How can I go for low-cost implementation of QPSK/BPSK transceiver, with one transmitting and another receiving antenna? For the reconfigurability, I need to implement it using SDR and USRP.
Which hardware devices or boards shall be required? Any suggestions?
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I am interested to buy hardware for validating my simulation results. Which hardware equipment do you recommend to me in the following two?, and why?
Typhoon HIL 402 or dSpace MicroLAb Box.
Or
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I need some help with the simulation of the device on Matlab simulink .
Thank you
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Question please..
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I have been researching the topic of image encryption and implementing it in software, using Wolfram Mathematica and Mathworks Matlab. So far, this has been successful and I am able to publish my results, for example:
How would you suggest I go down the path of learning about and implementing the same ideas using hardware?
What are good options to start with? A Raspberry Pi, Arduino, more advanced ICs?
Would you suggest any specific textbooks to go through in this learning journey?
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hi,
kindly refer this link:
Best wishes..
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I hv to send signals to Honeywell notifier system / Fire Alarm system using potential free relay from a python program running on a server machine. What hardware (potential free relay board) and libraries do I need to implement this?
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Hardware-in-the-loop (HIL) simulation
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Computer Aided tools like LTSpice, PSpice, OrCAD etc., are available , but check this link which can help you in which they provided a Matlab Package for FPGA (Hardware ) implementation
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Research Elements articles are brief, peer-reviewed articles that complement full research papers and describe output that has come about as a result of following the research cycle – this includes things like data, methods and protocols, software, code, hardware and more.
What do you think about it's acceptance and future scope?
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Elementary articles do have relevance if published in refereed and indexed journals.
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I am running various Abaqus simulations with a model size of about 1.5 million degrees of freedom in total. To speed up the calculations I am trying to decide what number of CPUs would be optimal and what are influencing factors (like model size, steps, time steps, outputs, hardware etc.). I'm interested in the question at what number the writing and merging of partial results and data between the different cores outweighs the benefit of using multiple CPUs.
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Abaqus Standard tends to have benefit of number of cores start to level off significantly after 16 cores. More is always better though for larger problems. Using the MP_HOST_SPLIT parameter and setting it to an integer that can be evenly divided into the number of cores or sockets will help immensely, more so than even GPU computing. GPU computing can help in larger problems, but you need number of GPUs installed in a machine equal to MP_HOST_SPLIT parameter. If MP_HOST_SPLIT = 1 you'll get poor performance, and a single GPU can help a lot then. But with MP_HOST_SPLIT set to the proper number (say 2 or 4 for 16 cores) you'll get a good speed up, better than an single GPU and MP_HOST_SPLIT=1. All the hype on GPU computing is totally overblown, believe me I know. I have 3 GPUs installed and I still don't get much improvement, if at all. Spent many an hour with the Abaqus people on this. You do well with MP_HOST_SPLIT = 1 and GPU, but just set MP_HOST_SPLIT equal to the proper number and you'll do better with no GPU. Did I mention they don't support or document this much? Silly. For Abaqus Explicit, that is a different animal, and more cores is always much better for larger problems.
Good luck,
Steve
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I have drawn a sample using Proportionate stratified random sampling technique.
The variables include name, designation, group, division, pay-scale
I would like to know what metrics I could use to check if the sample represents the population. Any resources will be useful. Thankyou!
Since the variables are categorical I am not sure what I can use here
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The following link is also very useful: http://pages.stat.wisc.edu/~st571-1/03-samples-2.pdf
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Dear All,
Is anyone aware of any benchmarks that pit pmemd.cuda (the GPU accelerated AMBER simulation software) against GROMACS' simulation software in a "apples to apples" comparison?
Same protein, water model, salt concentration, temperature, time step, and most importantly, same Hardware configuration.
How to the suites compare in that regard? Are they both 100% efficient and hardware bound? Or does one or the over have an edge in their efficiency and use of hardware to perform the SAME simulation.
Thanks in advance
ps. I've failed to find any 'head-to-head' benchmarks of my own.
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If you are not afraid of speed (!), using Amber of charmm FF, you can use ACEMD (performance are described here: https://software.acellera.com/docs/latest/acemd/performance.html)
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I wanted to know how states in US manage their traffic signal hardware - there maintaninance schedule, standards?
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Hello, Ujwal. I hope everything is going well for you. I'd like to share a DOT-related link with you. You can find several helpful pdf files at this link. I hope I was able to assist you.
Regards,
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I suppose peak cancellation CFR(PC-CFR) is now a feasible method concerning to hardware implementation. But when evaluating TM2.0A example of matlab 2020b 5g toolbox in which there is a fast freqency content switching of waveform in each slot(shown in figure), I suppose it's hard to know the frequency content of the signal in advance or recompute the new cancellation pulse coefficients in real time since each set of cancellation pulse coefficients is specified for certain carrier configuration of waveform. Is there any good solution to solve the problem? Or is there any other CFR algorithm which is feasible in this application secene with not much difficulty in hardware implementation?
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probably it will increase delay
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I want to simulate biped robot before going to hardware. I'll send the simulated kinematics from visual studio to that platform. It'll be great if that plat form can give some feedback after applying the kinematics like real life (using position sensors) to visual studio again so that my code can calibrate itself.
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Program execution time depends on the number of instructions as well as on computing power of the machine. Does anyone have some recommendation where to find an analytical model for estimating program execution time according to program instructions and CPU, RAM, and DISK characteristics?
For example, if we know the number of instructions, CPI (cycles per instruction), as well as hardware specifications of CPU, RAM, DISK, how to calculate (estimate) program execution time?
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Prof. Alem Čolaković: I think that our colleague Prof. Ashraf Suyyagh has given a good answer to your valuable question.
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I would be interested to know more about the software itself, hardware requirements, features and pricing.
I think new information would be helpful.
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Thank you both Lael and Tea for your answers to my question!
--------------------------
I have talked recently with a colleague about free Open Source electronic lab notebook for chemists. She gave me the following hints:
Maybe this helps anyone who looks for electronic lab notebook software.
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Could you help me to find articles on topical on hardware and software implementations of collision warning block(unit) for cars?
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You can use ultrasound transducers to measure the distance between the adjacent cars. You send a pulse and receive it after back bouncing from the adjacent car. The time delay between the two pulses is equal double the distance between the two cars. If the distance is smaller than a critical distance then alarm will be launched.
For more details about the building of the system please follow the paper in the link:
You may find similar papers by searching the web.
Best wishes
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Answers to the question will greatly contribute to the acquisition of hardware and software for academic and research purposes.
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As already suggested I would use R that does not only offer several mapping options but a large suite of statistical packages. Keep in mind that if coding and programming is not exactly your thing and you need something more user-friendly, you could use the free Quantum GIS software which can be interfaced to a series of other applications, including R scripts, GRASS and many more to run propertary algorithms throug a GUI user-friendly interface
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I intend to work on topic modeling in embedding spaces based on the following paper (Dieng, Blei, et al. 2020) https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00325/96463.
and Dynamic Embedding Topic Modeling (Dieng, Ruiz, Blei, et al. 2018)
My question is whether anyone has worked on the python code and had any hardware issues during implementation. I've been working on it for two days, and the algorithm is not yet finished.
I really appreciate any help.
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This may not be a hardware issue. Please check you cost function or model and its codes carefully. Also check the sizes of your matrices and the singularities, sparseness of your matrices. I hope by rechecking your theory & codes, you will solve your problem easily.
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Xilinx System Generator hardware co-simulation compilation is complete without any problem but the block used for simulation did not appear? Does anyone know where or how to find the generated block for co-simulation?
Thank you
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Can any body tell me the procedure of making hardware of any microstrip line to rectangular waveguide transitions or suggest me the name of person who can make this hardware. its very urgent...
thanks...
+917983388622
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maybe we can discuss this privately :my e-mail
in any case there are several standard methods of doing this..(like Malcolm indicated already) and it all depends on your particular parameters
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We have a Raman spectrometer (HORIBA/ Jobin-Yvon, LabRAM) purchased around 2005 and uses LabSpec 4.14.01. I was wondering if anyone uses the same system. I have some technical questions about the calibration of the hardware and software.
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Have you contacted Horiba? In Piscataway, New Jersey? That is where all the Raman experts are located and I am sure that they will answer your questions. The phone numbers are on the website as well as the email addresses.
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I tried to design this circuit into proteus i m getting my output in software but i m not getting my output on hardware.
i write the code for on time 5s and off time 1s
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Blockchain is revolutionizing all information and communications technologies. However, many of its functionalities depend on repetitive and computational intensive operations. Is there a way to implement a blockchain in hardware? What would be the benefits? What possible technologies could be employed?
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The answer depends on the purpose Blockchain (BC) applying for. For crypto there are some wallets now available in the market, i.e., https://www.ledger.com/. However if BC is used for IoT purpose, then there are some emerging applications can be seen here..https://builtin.com/blockchain/blockchain-iot-examples. Appreciated the quesion.
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Dear all,
I am currently studying MPC in a temperature controller. I've got the concepts of MPC such as model, control horizon, prediction horizon, constraint, ..etc. With these fundamental understanding, I can easily do simulations test on Matlab Simulink toolbox.
However, I need to implement this MPC algorithm on C# WinForm Application, since I created UI on C# with temperature controllers basing on Modbus ASCII protocol. The hardware configuration is as the figure.
I've found someone who has done with CASADI toolbox on Python, but it seems quite hard to follow.
I am looking for suggestions on which library on Python to implement it. Besides, are there any problems with the hardware configuration?
Thank you!
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Have you tried Apmonitor examples? http://apmonitor.com/wiki/index.php/Main/Control
I have their unit but been busy and haven gotten through to the MPC example, but they provide excellent documentation for Matlab and Python examples. Here is also a video https://www.youtube.com/watch?v=nqv6jFeVUYA&list=PLLBUgWXdTBDhrs5FuoJXni-cIeNYEyxw1&index=23&ab_channel=APMonitor.com
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Hello,
I'm trying to run my Abaqus simulation using gpus. I have a PC with AMD Ryzen™ 5 2400G & Radeon™ RX Vega 11 Graphics.
Calling the gpu from CAE and the Command window doesn't work. I have found a possible solution using CUDA, which I have not tried yet since it refers to NVIDIA hardware. Other posts suggest using OpenCL but I can not find how to download it.
Any ideas would be helpful!
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You should use OPEN GL for the AMD graphics card. I'm not sure AMD supports Abaqus parallel computing.
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The paper describes the possibilities of training drivers and students to effective driving modes of the train. Could you suggest the similar Software and Hardware Simulators for combine harvester Drivers Training?
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Agree with Qamar Ul Islam.
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How to implement software and hardware of fractional order controllers on robots?
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Farzad Tat Shahdost I did an implementation on robots a while ago. Please see
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how can we understand the meaning of "r317 , r3_17 or r31_7" at decompressor stage using Hardware Data Compression (HDC) where r is a run of length on number 7?
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what’s about of example r317 or r3_17 or r31_7
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I need to know the computing requirements to do SAR time series analysis and how many SAR rasters (images) should be analyzed?
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Well, it's depended how you are doing SAR Data processing.
if you are using Sofware like SNAP, you need a powerful processing computer.
As of now Google Earth Engine is suitable alternative if you have programming command.
Number of images required is totally depends on what you are doping through SAR data
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Speech Based Silence ejection algorithm is tested for results in MATLAB. To implement it as a Hardware, what type of recent Micro - controller can be used ?
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Ask the following questions - how much memory does your code need, how much data memory is needed, what is the required CPU speed, do you need any special interfaces?
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Hello! I am needing some help with HPLC - I had to pick it back up after years of not doing it.
Re-learning has been going well, but I have never had to collect compound fractions and this is what I need help with.
I am performing extracts on microalgae to detect and isolate specific compounds in the UV range. My extract is generated using 100% HPLC -grade Methanol, and my eluents are 100% methanol and DDI water (all compounds have been filtered by 0.22un membrane and degassed via vacuum pump) for my flow gradient. I generated great chromatographs, spectra, etc
BUT, how do I collect specific fractions for analysis? I have multiple peaks at various times that I need to collect. I know that I can manually time it and manually collect the sample, but I need better resolution than a manual collection. I've been looking for manuals and protocols online, but the information for my systems seems to be sporadically available.
Any chemists/biologists/physicists or experienced HPLC users have some tips or resources?
System Information:
Waters 2695 Separations Module w/Column-Heating Cabinet (set to 40*C) - Hardware
Waters 2996 Photodiode Array Detector - Hardware
Waters Fraction Collector II - Hardware
C18 Column - Hardware
Empower 2on a Windows XP OS - Software
There is also a Waters 2424 ELS Detector (Hardware) , but I don't think I need this.
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One thing you will need to do is verify that the HPLC and fraction collector are "aligned". Some HPLC systems specify tubing lengths from the detector(s) and fraction collector, suggesting their software compensates for the delay time. This link (https://www.waters.com/webassets/cms/support/docs/71500012102re.pdf ) page 86, makes reference to a delaying time (I realize this is for a different fraction collector than yours, but the concept still holds).
I think you can choose the peaks for collection from a prior run.
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I'm trying to run excitation-emission matrices on some water samples, but I'm running into some software issues that the manuals aren't helpful for. In order to use R studio to extract my data, I need to save my output as a .eem file, but I don't see how to do that.
When I try to save my matrix, the only option I get is an .spc, which it doesn't even let me do that - I get an error saying I need to change my matrix into a worksheet. I can't even figure out how to do that.
Is it saving these eems automatically somewhere I can't find? All I've been able to do is save an ASCII version of my data, which isn't a format the eemR package lets me import.
Hardware: Horiba Fluoromax 4
Software: Horiba FluorEscence, R studio eemR, Matlab drEEM
Thanks!
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Hi Eric,
I no longer work at Horiba and am not familiar with the latest software. I was going to forward this to my former colleague, but it's probably best/faster if you just call their help desk. Someone can answer this for you in a couple minutes.
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I have built a piece of hardware that produce random samples from a Gaussian distribution. Now that I have the hardware I want to empirically evaluate how random the samples are.
I am aware that the NIST and Diehard randomness tests exist but as far as I am aware they are for uniformly distributed random numbers and therefore not directly applicable to Gaussian distributed random numbers. Is there a standard empirical test for the randomness of Gaussian distributed random numbers?
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Since the mapping enforces a one-to-one correspondence between the original set with a gaussian distribution and the new one with a uniform distribution, any correlation in the former must be traceable in the latter as well.
As for how to qualitatively measure it, let's say you generate N numbers with a gaussian distribution, x_G, you then map these numbers into their corresponding set with a uniform probability distribution, x_u, using the cumulative distribution function:
x_u=0.5(1+erf(x_G/sqrt(2))
Mind that here I assume your Gaussian probability distribution has sigma=1 and is clustered around x=x0=0. If this is not the case, you should use the general expression:
x_u=0.5(1+erf( (x_G-x0) / (sigma*sqrt(2)) )
Once you've got the uniformly distributed set x_u, you can then check its randomness using any standard toolkit like NIST test suite.
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EyeTribe eye trackers are now obsolete, following the shutdown of the company. Yet we think that there may be labs that are still using these devices.
Recently, in our lab at METU Cognitive Science we tried to make their EyeTribe eye tracking devices work in a Windows 10 Release 1803. However, the trackers were initialized as generic USB devices and were not recognized by neither the EyeTribe eye tracking server nor the EyeTribe eye tracking UI. A roll back to Windows 1607 patch solved the problem. With the exact same driver set and hardware in place, the only observed difference between the two systems were the OS level security patches against Spectre & Meltdown security vulnerabilities. The Intel microcode level patches applied via BIOS updates were still in place, yet the devices operated correctly after OS rollback.
Relevant system settings with EyeTribe eye tracker problem present:
- Intel 7th gen Core i5 7500
- Dell OptiPlex 3050, BIOS ver. 1.10.2
- Windows 10 ver. 1803
System settings with no issues:
- All other settings were kept the same
- Windows 10 ver. 1607
Thanks Efecan Yılmaz for testing and implementation.
--
Cengiz Acarturk, PhD
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We did not patch it, indeed. We still use that previous version of Windows 10 (1607) when needed.
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Hi,
I need to get a quote for oral endoscopy equipment, all the components (hardware and software) going with it. I've been trying to get a quote from different companies, but am not getting any answers or reactions. Would anyone happen to have a recent quote from a reliable company, or recommendations for a company that's likely to communicate with me?
Many thanks!
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Dear Míša: I would recommend PAM Argentina. They have excellent stroboscopy equipments with beautiful images quality, besides their proper international assistance.
Here you have a whatsapp seller contact: +5491144062244
best regards
Dr Rey Caro Gonzalo
ENT Service
Cordoba, Argentina
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I would like to know whether VASP and/or Wien2K are affected in terms of performance by the type the hardware (Hard disk SSD or HDD). If yes, what do you suggest for a better (VASP and Wien2K) environement?
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VASP is better than Wien2K. You can use VASP.
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Let 𝑘, 𝑚, 𝑎𝑛𝑑 𝑛 are positive integers and 𝑚 ≤ 𝑛 I need to calculate the following function as accurately as possible when my hardware has ability to calculate only integer values.
f(𝑚,𝑛,𝑘)=𝑘x2^(𝑚/𝑛)
For example 𝑘=2 , 𝑚=𝑛 then my system can calculate f(𝑚,𝑛,𝑘)=𝑘x2 (Upper bound)
if 𝑚 < 𝑛 then my system gives f(𝑚,𝑛,𝑘)=𝑘 (Lower bound )
Anyone can suggest me how to calculate the intermediate steps by using basic arithmetic operations for example +,-,/,x ?
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Dear Waqas,
Please see the attachment.
I hope this solution is useful.
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What are the differences between 1D, 2D and 3D hydrological model in terms of advantage, disadvantage, function, compatibility and hardware requirement?
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Hi Firdaus
This article is helpful to answer your question.
Kind Regards!
Arfan Arshad
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I need to implement matrix inversion in hardware. The size of the matrix can be anywhere from 50 *50 to 8*8. Are ready-made standard codes available or inbuilt modules available with FPGA boards, please let me know? How feasible it is. If not FPGA can anyone suggest, another type of hardware to do so.
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It is absolutely feasible. I presume you want to solve a set of linear equations, so I would go for an LU factorization scheme. These rely on row/column operations that can be readily implemented in FPGAs. I suggest familiarizing yourself with matrix factorization algorithms and then thinking about how to transfer the factorization scheme into an FPGA. Since this sounds like a class project, I can't give you the solution! ;-)
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Hi,
We are having issues using Desmond on our workstation. Simulations run fine on one of our gpus ("Gpu0") but crash consistently on the other gpu ("gpu1" - which is also set up as the display gpu). Not sure if hardware issue or software/set up problem. I have attached screenshots of errors. Both gpus are visible to schrodinger. Similar issue on both schrodinger 2020-3 and 2019-1.
Ubuntu 20.04.1 LTS
2x GeForce RTC 2080
-nvcc returns:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
Any suggestions to work out if this is a hardware or set-up problem?
Thanks,
JK
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Just proves Schrodinger's law.....
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Dear colleagues,
does anybody know of a analytical service company providing measurements of NQR (most preferably 14N) spectra.
What are the vendors providing the hardware needed if we want to purchase our own instrument.
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Dear Raivo, I was also thinking of Janez Seliger...I think he has retired but he is here on RG - I'll get in contact with him directly!
Thanks anyways..
Alfred
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For limited hardware resources, which ones are best? Is it the CNN architectures based on depthwise convolution or any other concept?
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It depends on your problem as well as the resource constrained device you're using. From your question, what I get is that you're more interested to know about some alternative better solutions for convolutions, that can be Atrous convolutions which may take much time during training, but inferencing will be comparatively efficient. Further, you can also go for pruning strategies and please have a look at the concept explained in recent ESPNet convolutions.