ORCID Profile
0000-0003-1360-7357
Current Organisation
University College Dublin School of Electrical and Electronic Engineering
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Publisher: MDPI AG
Date: 20-11-2022
DOI: 10.3390/MI13112031
Abstract: Considering the prerequisite need for a protected e-commerce platform, absence of haptic interaction in head-mounted displays (HMD), and exploitation of faster communication technology, this research work aims to present an amended version of the tele-weight device that utilizes the 6G visible light communication (VLC) technology, is faster in performance, and deals with a heavier article. The enhanced version of the device is to be called the ‘VLC tele-weight device’ and the aim for the VLC tele-weight device is to get it affixed over the headset which will allow the user to have the weight-based sensation of the product ordered on the virtual store. The proposed device sending end and receiving end part performs communication over the VLC link. Furthermore, Arduino Nano is used as the microcontroller (MCU) in the project. Sending end circuitry measures the weight using the load cell and HX711 lifier combination and transmits it via the connected LED. The pre-equalizer circuit is connected between the LED and sending end part to improve the bandwidth. On the receiver side, the post-equalizer circuit improves the shape of the received pulse. The received weight value is then displayed using the motor-gear combination. The sending end device is to be sited at the virtual store, while the receiving end is planned to be positioned over the VR headset. The performance of the device was measured by performing repeated trials and the percentage error was found to be between 0.5–3%. Merging the field of embedded systems, internet of things (IoT), VLC, signal processing, virtual reality (VR), e-commerce, and haptic sensing, the idea proposed in this research work can help introduce the haptic interaction, and sensational realization-based innovation in immersive visualization (IV) and graphical user interface (GUI) domain.
Publisher: Emerald
Date: 27-11-2017
DOI: 10.1108/JSTPM-05-2017-0015
Abstract: The purpose of this research work is to design and apply LabVIEW in the area of traffic maintenance and flow, by introducing improvements in the smart city. The objective is to introduce the automated human–machine interface (HMI) – a computer-based graphical user interface (GUI) – for measuring the traffic flow and detecting faults in poles. This research paper is based on the use of LabVIEW for designing the HMI for a traffic system in a smart city. This includes considerable measures that are: smart flow of traffic, violation detection on the signal, fault measurement in the traffic pole, locking down of cars for emergency and measuring parameters inside the cars. In this paper, the GUIs and the required circuitry for making improvements in the infrastructure of traffic systems have been designed and proposed, with their respective required hardware. Several measured conditions have been discussed in detail. PJRC Teensy 3.1 has been used because it contains enough general-purpose input–output (GPIO) pins required for monitoring parameters that are used for maintaining the necessary flow of traffic and monitor the proposed study case. A combination of sensors such as infrared, accelerometer, magnetic compass, temperature sensor, current sensors, ultrasonic sensor, fingerprint readers, etc. are used to create a monitoring environment for the application. Using Teensy and LabVIEW, the system costs less and is effective in terms of performance. The microprocessor board shields for placing actuators and sensors and for attaching the input/output (I/O) to the LED indicators and display have been designed. A circuitry for scaling voltage, i.e. making sensor readings to read limits, has been designed. A combination of certain sensors, at different signals, will lead to a secure and more durable control of traffic. The proposed applications with its hardware and software cost less, are effective and can be easily used for making the city’s traffic services smart. For alarm levels, the desired alarm level can be set from the front panel for certain conditions from the monitoring station. For this, virtual channels can be created for allowing the operator to set any random value for limits. If the sensor value crosses the alarm value, then the corresponding alarm displays an alert. The system works by using efficient decision-making techniques and stores the data along with the corresponding time of operation, for future decisions. This study is an advanced research of its category because it combines the field of electrical engineering, computer science and traffic systems by using LabVIEW.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: MDPI AG
Date: 29-06-2021
DOI: 10.3390/SU13137253
Abstract: In view of the problem of e-commerce scams and the absence of haptic interaction, this research aims to introduce and create a tele-weight device for e-commerce shopping in smart cities. The objective is to use the proposed prototype to provide a brief overview of the possible technological advancements. When the tele-weight device is affixed over the head-mounted display, it allows the user to feel the item’s weight while shopping in the virtual store. Addressing the problem of having no physical interaction between the user (player) and a series game scene in virtual reality (VR) headsets, this research approach focuses on creating a prototype device that has two parts, a sending part and a receiving part. The sending part measures the weight of the object and transmits it over the cellular network to the receiver side. The virtual store user at the receiving side can thus realize the weight of the ordered object. The findings from this work include a visual display of the item’s weight to the virtual store e-commerce user. By introducing sustainability, this haptic technology-assisted technique can help the customer realize the weight of an object and thus have a better immersive experience. In the device, the load cell measures the weight of the object and lifies it using the HX711 lifier. However, some delay in the demonstration of the weight was observed during experimentation, and this indirectly altered the performance of the system. One set of the device is sited at the virtual store user premises while the sending end of the device is positioned at the warehouse. The sending end hardware includes an Arduino Uno device, an HX711 lifier chip to lify the weight from the load cell, and a cellular module (Sim900A chip-based) to transmit the weight in the form of an encoded message. The receiving end hardware includes a cellular module and an actuator involving a motor gear arrangement to demonstrate the weight of the object. Combining the fields of e-commerce, embedded systems, VR, and haptic sensing, this research can help create a more secure marketplace to attain a higher level of customer satisfaction.
Publisher: Elsevier BV
Date: 11-2022
Publisher: Akademiai Kiado Zrt.
Date: 13-10-2021
Abstract: Adenosine triphosphate (ATP) is an energy compound present in living organisms and is required by living cells for performing operations such as replication, molecules transportation, chemical synthesis, etc. ATP connects with living cells through specialized sites called ATP-sites. ATP-sites are present in various proteins of a living cell. The life span of a cell can be controlled by controlling ATP compounds and without the provision of energy to ATP compounds, cells cannot survive. Countless diseases treatment (such as cancer, diabetes) can be possible once protein active sites are predicted. Considering the need for an algorithm that predicts ATP-sites with higher accuracy and effectiveness, this research work predicts protein ATP sites in a very novel way. Till now Position-specific scoring matrix (PSSM) along with many physicochemical properties have been used as features with deep neural networks in order to create a model that predicts the ATP-sites. To overcome this problem of complex computation, this exertion proposes k-mer feature vectors with simple machine learning (ML) models to attain the same or even better performance with less computation required. Using 2-mer as feature vectors, this research work trained and tested five different models including KNN, Conv1D, XGBoost, SVM and Random Forest. SVM gave the best performance on k-mer features. The accuracy of the created model is 96%, MCC 90% and ROC-AUC is 99%, which are the same or even better in some aspects than the state-of-the-art results. The state-of-the-art results have an accuracy of 97%, MCC 78% and ROC-AUC is 92%. One of the benefits of the created model is that it is much simpler and more accurate.
Location: Australia
Location: Ireland
No related grants have been discovered for Aqeel Farooq.