GrapheneX
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Our GraphenX products are comprised of single layers of graphene oxide. It is a product of oxidation of graphite through a modified Hummers’ method. In contrast to commercially available graphene oxide sheets which possess lateral size generally less than 5μm, GraphenX are monolayers of oxidized graphene with outstandingly high lateral size (up to 0.1mm), rendering these products as an excellent candidate for diverse applications such as electronics, composite materials, energy and etc. GraphenX is a polar and functionalized material bearing several types of oxygen groups and is available in polar solvents (Water, NMP, DMF and Ethanol).
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kashifwattu798@gmail.com
ENJOY ...!!!
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Comparative analysis between traditional aquaponics and reconstructed aquapon...
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Slides for the 4th Presentation on LLM Fine-Tuning with QLoRA Presented by Anant, featuring DataStax Astra
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
CalArts毕业证学历书【微信95270640】CalArts毕业证’圣力嘉学院毕业证《Q微信95270640》办理CalArts毕业证√文凭学历制作{CalArts文凭}购买学历学位证书本科硕士,CalArts毕业证学历学位证【实体公司】办毕业证、成绩单、学历认证、学位证、文凭认证、办留信网认证、（网上可查，实体公司，专业可靠）
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Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Data Driven Maintenance | UReason Webinar
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Advanced control scheme of doubly fed induction generator for wind turbine us...
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
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3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Design and optimization of ion propulsion drone
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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This Presentation will give you a brief idea about what Computational Engineering at IIT Hyderabad has to offer.
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GrapheneX
- 1. Attribute: Our GraphenX products are comprised of single layers of graphene oxide. It is a product of oxidation of graphite through a modified Hummers’ method. In contrast to commercially available graphene oxide sheets which possess lateral size generally less than 5μm, GraphenX are monolayers of oxidized graphene with outstandingly high lateral size (up to 0.1mm), rendering these products as an excellent candidate for diverse applications such as electronics, composite materials, energy and etc. GraphenX is a polar and functionalized material bearing several types of oxygen groups and is available in polar solvents (Water, NMP, DMF and Ethanol). GO Single Layer Graphene Oxide Dispersing Media Conc. Volume (ml) 50 100 250 1000 Water 1 g/lit NMP, DMF,DMSO, DMAc 2 g/lit Ethanol,Methanol, Isopropanol 2 g/lit Ethylene glycol 2 g/lit Property Later size (μm) 5 - 100 Thickness (nm) 0.7 - 1.4 Nitrogen content (XPS) <0.1% Carbon to oxygen atomic ratio (XPS) 1.3 Formula (XPS) C2.0O1.54 Functional groups (XPS, FTIR) OH, COOH, C-O-C Graphene content Up to 20 mg.ml-1 Appearance Yellow brown with anisotropic texture No 30, Maleklu st, Farjam st., Resalat ave, Tehran, Iran +(98)2177456705 info@graphene.ir www.graphene.ir Delivering emerging materials with high quality
- 2. XRD spectrum of pure and composite GO XPS spectrum of GO showing pres- ence of carbon and oxygen in the chemical structure of graphene oxide FTIR spectrum of GO showing pres- ence of oxygen groups (carboxyl, epoxy, and hydroxyl) in the chemical structure of graphene oxide XRD-GO in organic solvents
- 3. a) SEM , b)TEM , c) HRTEM d,e) Optical Microscopy SEM of graphene sheets arrangement in polymeric matrix UV-vis
- 4. Delivering emerging materials with high quality Top: AFM images Bottom: Aspect ratio distribution Lateral size distribution with mean = 37 um