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577 results on '"Imran, Muhammad Ali"'

7. Shortening harvest interval, reaping benefits? A study on harvest practices in oil palm smallholder farming systems in Indonesia

Author

de Vos, Rosanne E., Nurfalah, Lisa, Tenorio, Fatima A., Lim, Ya Li, Monzon, Juan P., Donough, Christopher R., Sugianto, Hendra, Dwiyahreni, Asri A., Winarni, Nurul L., Mulani, Nadia, Ramadhan, Gilang, Imran, Muhammad Ali, Tito, Antonius P., Sulistiawan, Pandu, Khoirul, Muhammad, Farrasati, Rana, Pradiko, Iput, Grassini, Patricio, and Slingerland, Maja

Published
2023
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44. Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance

Author

Kaur, Jaspreet, Bhatti, Satyam, Popoola, Olaoluwa R, Imran, Muhammad Ali, Ghannam, Rami, Abbasi, Qammer H, and Abbas, Hasan T

Subjects
FOS: Computer and information sciences, Information Theory (cs.IT), Computer Science - Information Theory, FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control
Abstract

The pervasive nature of wireless telecommunication has made it the foundation for mainstream technologies like automation, smart vehicles, virtual reality, and unmanned aerial vehicles. As these technologies experience widespread adoption in our daily lives, ensuring the reliable performance of cellular networks in mobile scenarios has become a paramount challenge. Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages and implications. Notably, the study presents an impressive 53% improvement in signal-to-noise ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and Zero forcing (ZF) techniques, alongside deep neural networks (DNN) employing Bayesian Optimization (BO), represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino, in enabling location-aware beamforming.

Published
2023

46. A Privacy and Energy-Aware Federated Framework for Human Activity Recognition.

Author

Khan, Ahsan Raza, Manzoor, Habib Ullah, Ayaz, Fahad, Imran, Muhammad Ali, and Zoha, Ahmed

Subjects
HUMAN activity recognition, ARTIFICIAL neural networks, FEDERATED learning, DEEP learning, ENERGY consumption, PRIVACY
Abstract

Human activity recognition (HAR) using wearable sensors enables continuous monitoring for healthcare applications. However, the conventional centralised training of deep learning models on sensor data poses challenges related to privacy, communication costs, and on-device efficiency. This paper proposes a federated learning framework integrating spiking neural networks (SNNs) with long short-term memory (LSTM) networks for energy-efficient and privacy-preserving HAR. The hybrid spiking-LSTM (S-LSTM) model synergistically combines the event-driven efficiency of SNNs and the sequence modelling capability of LSTMs. The model is trained using surrogate gradient learning and backpropagation through time, enabling fully supervised end-to-end learning. Extensive evaluations of two public datasets demonstrate that the proposed approach outperforms LSTM, CNN, and S-CNN models in accuracy and energy efficiency. For instance, the proposed S-LSTM achieved an accuracy of 97.36% and 89.69% for indoor and outdoor scenarios, respectively. Furthermore, the results also showed a significant improvement in energy efficiency of 32.30%, compared to simple LSTM. Additionally, we highlight the significance of personalisation in HAR, where fine-tuning with local data enhances model accuracy by up to 9% for individual users. [ABSTRACT FROM AUTHOR]

Published
2023
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47. A Contrastive Study of Politeness Strategies Between Arumpone and Batara Wajo Based on Dialogue Discourse in the Lontara Latoa and Sukku'na Wajo Manuscripts.

Author

Kamsinah, Darwis, Muhammad, Fatimah, Ainun, Nurahmad, Muhammad, and Imran, Muhammad Ali

Subjects
COURTESY, LINGUISTIC politeness, MANUSCRIPTS, DISCOURSE
Abstract

This paper aims to demonstrate the differences in the values of linguistic politeness strategies in the Bugis language inherited by King Bone, Arumpone (abbreviated as AP), and King Wajo, Batara Wajo (abbreviated as BW), respectively through the Latoa Lontara manuscript (Bone) and the Sukku'na Wajo Lontara manuscript. This is very interesting because theoretically (Brown & Levinson, 1978), the dialogue in the two Lontara manuscripts was asymmetrical or hierarchical (the dialogue between the king and the subordinates), so superiors may use the cukuk speech to subordinates. However, this study found that BW used the cukuk speech, while AP did not. The difference in the choice of politeness strategy was that AP chose the type of distance politeness or self-politeness, while BW chose camaraderie politeness. As for subordinates, they should use congaa speech to their superiors in asymmetrical speech situations. However, the facts show that the subordinates of both kings never use the congaa speech to their respective superiors. In this case, Kajaolallido (abbreviated as KL), the AP's subordinate used the sanraa speech as used by AP to him, and even used the cukuk speech to AP when was asked to give moral advice. Meanwhile, BW's subordinates always used the cukuk language to BW. The most important finding here is that the power of the moral advice variable becam [ABSTRACT FROM AUTHOR]

Published
2023
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48. Towards a Sustainable Internet-of-Underwater-Things based on AUVs, SWIPT, and Reinforcement Learning

Author

Omeke, Kenechi G., Mollel, Michael, Shah, Syed T., Zhang, Lei, Abbasi, Qammer H., and Imran, Muhammad Ali

Subjects
Signal Processing (eess.SP), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing
Abstract

Life on earth depends on healthy oceans, which supply a large percentage of the planet's oxygen, food, and energy. However, the oceans are under threat from climate change, which is devastating the marine ecosystem and the economic and social systems that depend on it. The Internet-of-underwater-things (IoUTs), a global interconnection of underwater objects, enables round-the-clock monitoring of the oceans. It provides high-resolution data for training machine learning (ML) algorithms for rapidly evaluating potential climate change solutions and speeding up decision-making. The sensors in conventional IoUTs are battery-powered, which limits their lifetime, and constitutes environmental hazards when they die. In this paper, we propose a sustainable scheme to improve the throughput and lifetime of underwater networks, enabling them to potentially operate indefinitely. The scheme is based on simultaneous wireless information and power transfer (SWIPT) from an autonomous underwater vehicle (AUV) used for data collection. We model the problem of jointly maximising throughput and harvested power as a Markov Decision Process (MDP), and develop a model-free reinforcement learning (RL) algorithm as a solution. The model's reward function incentivises the AUV to find optimal trajectories that maximise throughput and power transfer to the underwater nodes while minimising energy consumption. To the best of our knowledge, this is the first attempt at using RL to ensure sustainable underwater networks via SWIPT. The scheme is implemented in an open 3D RL environment specifically developed in MATLAB for this study. The performance results show up 207% improvement in energy efficiency compared to those of a random trajectory scheme used as a baseline model.

Published
2023

49. In‐Home Monitoring Using Wireless on the Walls for Future HealthCare: Real‐World Demonstration.

Author

Kazim, Jalil ur Rehman, Tahir, Ahsen, Rains, James, Cui, Tie Jun, Jabbar, Abdul, Jamshed, Muhammad Ali, Ur-Rehman, Masood, Alomainy, Akram, Imran, Muhammad Ali, and Abbasi, Qammer H.

Abstract

Since the last decade radio frequency (RF) sensing has emerged as an alternative in‐home monitoring and tracking technology because of its inherent device‐free and privacy‐preserved features over camera and wearable technologies. In this work, contrary to conventional radar‐based sensing and WiFi‐based setups which require line‐of‐sight (LoS) to process and collect the RF signals for monitoring, it is shown for the first time in literature the potential of using RF sensing for vitals, that is, heartbeat detection in the non‐line‐of‐sight (NLoS) using an in‐house‐developed reconfigurable intelligent surface (RIS), that is, wireless on the walls. The developed RIS is the world's first prototype which consists of "4096 elements". The unit cell elements are individually controlled via PIN diodes, 1‐bit, operating at 3.75 GHz specified for the fifth‐generation (5G) network. Near‐field beam steering is demonstrated, with a switching speed of 15 ms. For the first time in the literature its is demonstrated that RIS can assist in the detection of microactivities including the human heartbeat in NLoS indoor complex environment, a limitation with the existing RF sensing technologies to date. In addition, it is experimentally verified that the RIS can potentially reduce the e‐field magnitude at the user's by regulating the gain at the user terminal. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Syntactic Characteristic Analysis of Colloquial Makassar Indonesian Based on the Use of Personal Pronoun Affixes: From Interference to Borrowing.

Author

Kamsinah, Darwis, Muhammad, Fatimah, Ainun, Nurahmad, Muhammad, and Imran, Muhammad Ali

Subjects
INDONESIAN language, LANGUAGE policy, VARIATION in language, CITY dwellers, NATIVE language
Abstract

This paper will prove the existence of colloquial Makassar Indonesian (CMI) by showing its syntactic characteristics based on the use of personal pronoun affixes. This is very interesting and important because in general colloquial Indonesian languages are spoken in other cities in Indonesia, for example Jakarta, Manado, Ambon, etc. is a subsystem of the Indonesian language (hereinafter abbreviated as IND), but CMI is really a subsystem or subvariant of the Makassar language (MAK), the mother tongue of the Makassarese people. Therefore, it is not easy for Makassar newcomers to master this CMI. To master it, they must first learn the basic rules of MAK syntax. The fundamental thing in this case is the change in language typology, namely CMI has been proven to have adopted the V-S-O (Verb-Subject-Object) typology of MAK. Meanwhile, IND has the S-V-O (Subject-Predicate-Object) typology. This happened because there was language contact between MAK and Malay (now IND), a language which became the forerunner to the birth of IND as the national language and the state language of the Republic of Indonesia. In this case, at first Makassar city residents tried to use Malay, but with MAK syntactic interference. Gradually this form of interference became the entry point for the borrowing of the MAK syntactic subsystem in the IND speeches of Makassar city residents. IND utterances with the characteristics of MAK syntax then become the characteristics of CMI, which has now reached the level of integration and convergence. [ABSTRACT FROM AUTHOR]

Published
2023
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