Higher College of Technology

About: Higher College of Technology is a based out in . It is known for research contribution in the topics: Higher education & Tourism. The organization has 369 authors who have published 379 publications receiving 729 citations.

Ultra-Low Power 8-Transistor Modified Gate Diffusion Input Carbon Nano-Tube Field Effect Transistor Full Adder

Abstract: An ultra-low power 8-Transistor Modified Gate Diffusion Input (MGDI) Carbon Nano Tube Field Effect Transistor (CNTFET) Full Adder (FA) has been presented in this paper. The proposed 8-T MGDI CNTFET...

IoT based Smart Sensing and Alarming System with Autonomous Guiding Robots for Efficient Fire Emergency Evacuation

Abstract: The Internet of Things based Smart Sensing and Alarm System with Autonomous Guiding Robots for Efficient Fire Emergency Evacuation System was designed and developed to provide immediate monitoring and alerts, allowing for efficient emergency evacuation with robotic assistance. The project includes two types of robots: a robot guide and a robot transporter. The NodeMCU-controlled Vex Navigating Robot directs people to the closest and most appropriate safety exits, while the Remote-Controlled Arduino-based Robot Transporter shuttles restrained or elderly people. The system employs an Internet of Things-based microcontroller to read and process data from sensors that detect temperature, humidity, and the number of people present in each room. This data is sent to the Cloud server and shown in the Blynk Mobile App. When a fire occurs, an alert signal using GSM and GPS technologies is sent to the fire station, the building health and safety team, and the autonomous guiding robot that replaces the Fire Warden, informing them of the incident's location and possible casualties. In this system, the robot system plays an important role in the evacuation process, assisting in the avoidance of delays and the saving of lives. The Autonomous navigating Robot was tested in a Floor plan layout with 9 rooms. The sensing unit was fixed in all rooms and the Robot in front of BS109 is tested with 3 different sources of fire, one in BS108, BS103 and BS 110. The robot successfully chose the appropriate exit path of path2 when the source of fire is in BS103 and BS110 and path1 when source of Fire is BS108. Testing of the algorithm is done with robot in front of Bs104, BS109, BS110 with 3 different source of fire. Transporting Robot is tested with remote controlled unit and is found to successfully transport people up to the weight of 80kgs with less than 2% deviation from its destined angle of travel.

Nanotechnology for Green Applications: How Far on the Anvil of Machine Learning!

Abstract: Almost 40 years since Eric Drexler’s 1991 MIT dissertation, “Molecular Machinery and Manufacturing with Applications to Computation” (Drexler, Nanosystems: molecular machinery, manufacturing, and computation, Wiley, 1992), a lot of exciting has happened in nanotechnology. By far, this nascent field of technology in combination with biotechnology has contributed heavily in medicine and biomaterials R&D sector, but nanomaterials for “green applications” are still quite away from realization. There are several issues underlying this delay, and these can be classified into two broad categories: (i) issues intrinsic to nanomaterials: associated with sustainable tailor-made production, optimization, scale-up, and stability and (ii) environmental issues of nanomaterials associated with their interaction and safe disposal. To have further clarity on first category above, the major intrinsic issues of nanomaterials are grouped into six attributes of studies. These are composition, synthesis, internal and external properties, stability, toxicity, and lifecycle assessment. Although these appear independent attributes but actually they interact with each other and a term “Ensemble Heterogeneity” (he) is defined here to understand their interdependence. Machine learning (ML) can provide deeper insights into both visible and hidden levels of these interdependencies. In the present chapter, firstly, these six attributes are reviewed and an understanding is developed that these attributes must be studied for hidden parameters and patterns using ML for producing optimized design solutions for nanomaterials. Secondly, an overview of different types of ML approaches is given that can contribute to the development of optimized design of nanomaterials. Finally, life cycle assessment (LCA) of nanomaterials is discussed. LCA is a tool to assess the environmental impact and sustainability of any technology to be “green.”

Synthesis of transparent bio-electrodes for biophysiological measurements based on modified graphene oxide.

Abstract: The main objective of this work was to fabricate smart nanocomposite transparent conductive biophysiological electrodes based on modified graphene oxide (GO). The GO is abundant, flexible conductors that can be formulated as a transparent sheet and thereby alleviate the drawbacks of using indium tin oxide in transparent electrodes, like its scarcity, brittleness, and cost. GO was synthesized by a modified version of Hummers' method under highly acidic conditions with sulfuric acid and showed good distribution at a high temperature of 90 °C. Polyvinyl alcohol (PVA) was used as a polymer host in the composite. Glycerol (Gl) was used to increase the flexibility and conductivity through an esterification reaction. Characteristic techniques were used to detect the morphology and structure of GO fillers and their polymer composites, such as transmission electron microscopy, x-ray diffraction, scanning electron microscopy and Fourier transform infrared spectroscopy. The GO/Gl/PVA transparent nanocomposite was tested for the synthesis of electrocardiogram (ECG) and electrodermal (EDA) electrodes. The Biopac device was used to evaluate the behavior of the GO/Gl/PVA plastic transparent electrode in comparison to the GO/Gl/PVA black electrode and a commercial one. The results indicated improved efficiency of the GO/Gl/PVA ECG transparent electrode. The GO/Gl/PVA EDA electrode produced signals with higher conductivity and lower noise than the commercial electrode.