Digital Commons Network^™

U2.38.272_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.382_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.360_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.369-370_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

Low-Resource Clickbait Spoiling For Indonesian Via Question Answering, Ni Putu Intan Maharani, Ayu Purwarianti, Alham Fikri Aji

Natural Language Processing Faculty Publications

Clickbait spoiling aims to generate a short text to satisfy the curiosity induced by a clickbait post. As it is a newly introduced task, the dataset is only available in English so far. Our contributions include the construction of manually labeled clickbait spoiling corpus in Indonesian and an evaluation on using cross-lingual zero-shot question answering-based models to tackle clikcbait spoiling for low-resource language like In-donesian. We utilize selection of multilingual language models. The experimental results suggest that XLM-RoBERTa (large) model outperforms other models for phrase and passage spoilers, meanwhile, mDeBERTa (base) model outperforms other models for multipart spoilers.

Qasina: Religious Domain Question Answering Using Sirah Nabawiyah, Muhammad Razif Rizqullah, Ayu Purwarianti, Alham Fikri Aji

Natural Language Processing Faculty Publications

Nowadays, Question Answering (QA) tasks receive significant research focus, particularly with the development of Large Language Model (LLM) such as Chat GPT [1]. LLM can be applied to various domains, but it contradicts the principles of information transmission when applied to the Islamic domain. In Islam we strictly regulates the sources of information and who can give interpretations or tafseer for that sources [2]. The approach used by LLM to generate answers based on its own interpretation is similar to the concept of tafseer, LLM is neither an Islamic expert nor a human which is not permitted in Islam. Indonesia …

Self-Supervised Learning With Diffusion-Based Multichannel Speech Enhancement For Speaker Verification Under Noisy Conditions, Sandipana Dowerah, Ajinkya Kulkarni, Romain Serizel, Denis Jouvet

Natural Language Processing Faculty Publications

The paper introduces Diff-Filter, a multichannel speech enhancement approach based on the diffusion probabilistic model, for improving speaker verification performance under noisy and reverberant conditions. It also presents a new two-step training procedure that takes the benefit of self-supervised learning. In the first stage, the Diff-Filter is trained by conducting time-domain speech filtering using a scoring-based diffusion model. In the second stage, the Diff-Filter is jointly optimized with a pre-trained ECAPA-TDNN speaker verification model under a self-supervised learning framework. We present a novel loss based on equal error rate. This loss is used to conduct self-supervised learning on a dataset …

Advanced Nlp Techniques For Summarizing Multilingual Financial Narratives From Global Annual Reports, Dilshod Azizov, Jiyong Li, Hilal Alquabeh, Shangsong Liang

Machine Learning Faculty Publications

The increasing volume of financial documents requires efficient summarization methods. This study investigates the use of natural language processing (NLP) to summarize financial narratives from annual reports in English, Spanish, and Greek. We employ T5 for English and mT5 for Greek and Spanish, generating structured summaries of firms' yearly financial trends. Despite the challenges posed by diverse and unstructured reports, our approach effectively identifies key narrative elements, excluding financial tables and numerical data. In competition, our system significantly exceeded the baseline model, with placements varying by language and a weighted score distribution of 50% for English, 25% for Greek and …

Enhancing Edge Multipath Data Security Offloading Efficiency Via Sequential Reinforcement Learning, Wenxuan Qiao, Yuyang Zhang, Ping Dong, Xiaojiang Du, Chengxiao Yu, Hongke Zhang, Mohsen Guizani

Machine Learning Faculty Publications

The multipath transmission structure decouples network services from a single transmission carrier, which has great potential for shaping a more secure and efficient 6G network. Existing multipath transmission schemes face challenges such as network heterogeneity, perception lag, and additional scheduling delay, which limits their ability to improve bandwidth aggregation capacity and information security. To address these issues, we propose the Sequential Reinforcement Evolution (SRE) scheme, which utilizes deep reinforcement learning to predict the value of future scheduling actions based on past network states. The SRE scheme regards improving bandwidth aggregation capacity and anti-eavesdropping ability as optimization goals, and designs a …

Feature Shrinkage Pyramid For Camouflaged Object Detection With Transformers, Zhou Huang, Hang Dai, Tian Zhu Xiang, Shuo Wang, Huai Xin Chen, Jie Qin, Huan Xiong

Machine Learning Faculty Publications

Vision transformers have recently shown strong global context modeling capabilities in camouflaged object detection. However, they suffer from two major limitations: less effective locality modeling and insufficient feature aggregation in decoders, which are not conducive to camou-flaged object detection that explores subtle cues from indistinguishable backgrounds. To address these issues, in this paper, we propose a novel transformer-based Feature Shrinkage Pyramid Network (FSPNet), which aims to hierarchically decode locality-enhanced neighboring transformer features through progressive shrinking for camou-flaged object detection. Specifically, we propose a non-local token enhancement module (NL-TEM) that employs the non-local mechanism to interact neighboring tokens and explore graph-based …

Mitigating Security Risks In 6g Networks-Based Optimization Of Deep Learning, Ammar Kamal Abasi, Moayad Aloqaily, Mohsen Guizani, Merouane Debbah

Machine Learning Faculty Publications

The rapid development of 6G millimeter-wave (mmWave) networks has introduced new challenges for network security. Adversarial attacks on beamforming algorithms in these networks can lead to severe communication performance degradation. This paper proposes an optimization framework for Deep Learning (DL) hyperparameters that enhances adversarial security in 6G mmWave networks through beam prediction. We develop a robust DL model that can adapt to various adversarial attacks and maintain high prediction accuracy. The proposed framework optimizes hyperparameters using hybrid Particle Swarm Optimization (PSO) with Multi-Verse Optimizer (MVO) for improved security. The framework is evaluated through extensive simulations, demonstrating its effectiveness in improving …

A Dual-Objective Bandit-Based Opportunistic Band Selection Strategy For Hybrid-Band V2x Metaverse Content Update, Sherief Hashima, Zubair Md Fadlullah, Mostafa M. Fouda, Kohei Hatano, Eiji Takimoto, Mohsen Guizani

Machine Learning Faculty Publications

As vehicular communication networks embrace metaverse beyond 5G/6G systems, the rich content update via the least interfered subchannel of the optimal frequency band in a hybrid band vehicle to everything (V2X) setting emerges as a challenging optimization problem. We model this problem as a tradeoff between multi-band VR/AR devices attempting to perform metaverse scenes and environmental updates to metaverse roadside units (MRSUs) while minimizing energy consumption. Due to the computational hardness of this optimization, we formulate an opportunistic band selection problem using a multi-armed bandit (MAB) that provides a good quality solution in real-time without computationally burdening the already stretched …

A Fine-Grained Cross-Chain Spectrum Sharing Mechanism Based On Oracle, Mengjie Cao, Qian Wang, Xiaojiang Du, Juan Fang, Bei Gong, Mohsen Guizani

Machine Learning Faculty Publications

The dramatically increased wireless communication needs make non-renewable spectrum resources extremely scarce and costly. Consortium blockchain realizes trusted spectrum sharing among untrusted spectrum owners. Yet, most existing studies ignore spectrum sharing among blockchains, which greatly reduce spectrum utilization. In the paper, we focus on cross-chain spectrum sharing. We propose a Fine-grained Cross-chain Spectrum Sharing mechanism based on Oracle (FCSSO) to realize trusted and efficient cross-chain spectrum transactions. To guarantee benefits of spectrum owners, we design a fine-grained time partition method to decide spectrum renting time in transactions. The method reduces the waste of owners' available spectrum time caused by spectrum …

Credibility Management Of Cloud-Based Digital Forensic Data: A Decentralized Verification Mechanism, Ruiqing Chu, Xuanyu Liu, Xiao Fu, Bin Luo, Mohsen Guizani

Machine Learning Faculty Publications

With the continuous development of digital forensics technology, its application is becoming more and more widespread in various fields, and the use of digital forensics storage services is also increasing. However, the issue of the credibility of digital forensics data has always been a focus of attention. In this paper, we conduct in-depth research on the credibility of digital forensics data. By analyzing existing technologies and methods, we propose a credibility verification mechanism for digital forensics data based on decentralized and distributed public ledgers, aiming to improve the credibility and security of digital forensics data.

Drone/Bird Classification Based On Features Of Tracks Trajectories, Maksat Kengeskanov, Amal El Fallah Seghrouchni, Raed Abu Zitar, Frederic Barbaresco

Machine Learning Faculty Publications

This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable recognition task. Standard Machine Learning methods such as SVM and Random Forest are used for learning this classification. Features based on the kinematics, Gabor filter, and Gray Level Co-occurrence Matrix are utilized. Several comparisons and experiments based on benchmark data sets are shown.

Fag-Scheduler: Privacy-Preserving Federated Reinforcement Learning With Gru For Production Scheduling On Automotive Manufacturing, Jinhua Chen, Keping Yu, Joel J.P.C. Rodrigues, Mohsen Guizani, Takuro Sato

Machine Learning Faculty Publications

The automotive manufacturing industry faces challenges in production planning, but current heuristic algorithms and solvers have limitations in scalability and local optima. Moreover, data security concerns are often overlooked. To address these issues, this paper introduces the FAG-Scheduler, a federated reinforcement learning approach integrating asynchronous advantage actor-critic, gated recurrent unit algorithms, and federated learning. By sharing model parameters instead of raw data, data security is ensured among participants. The FAG-Scheduler achieves optimal solutions in under 5 seconds and demonstrates high adaptability to other manufacturing contexts. It presents potential applications with significant improvements over conventional methods.

Ferkd: Surgical Label Adaptation For Efficient Distillation, Zhiqiang Shen

Machine Learning Faculty Publications

We present FerKD, a novel efficient knowledge distillation framework that incorporates partial soft-hard label adaptation coupled with a region-calibration mechanism. Our approach stems from the observation and intuition that standard data augmentations, such as RandomResizedCrop, tend to transform inputs into diverse conditions: easy positives, hard positives, or hard negatives. In traditional distillation frameworks, these transformed samples are utilized equally through their predictive probabilities derived from pretrained teacher models. However, merely relying on prediction values from a pretrained teacher, a common practice in prior studies, neglects the reliability of these soft label predictions. To address this, we propose a new scheme …

Joint Association And Computing Resource Optimization For Distributed Wireless Metaverse, Latif U. Khan, Mohsen Guizani, Bassem Ouni, Mohamed Adel Serhani

Machine Learning Faculty Publications

Metaverse enables wireless systems with many features, such as self-sustainability and proactive online learning. However, deploying metaverse for wireless systems will face many challenges. These challenges are the deployment of meta spaces over the network edge, association of end-devices with meta spaces, and computing resource optimization. Therefore, in this work, we consider the joint association of end-devices with meta spaces and computing resources optimization for running meta spaces over the network edge devices. The formulated optimization problem is a mixed integer non-linear programming problem. We separate the problem into two sub-problems: the computing resource optimization problem and the association sub-problem. …

Message From The Executive General Chair, Moayad Aloqaily

Machine Learning Faculty Publications

No abstract provided.

Message From The Imeta 2023 General And Technical Program Chairs, Ilir Capuni, Feras Awaysheh, Gautam Srivastava, Jun Wu, Moayad Aloqaily

Machine Learning Faculty Publications

No abstract provided.

Solt: A Software-Defined Load Balancing Algorithm For Time Sensitive Networks, Venkatraman Balasubramanian, Sundar Vedantham, Niall Mcdonnell, Ambalavanar Arulambalam, Martin Reisslein, Moayad Aloqaily

Machine Learning Faculty Publications

Motivated by the need to provide a precisely determined delay between source and sink nodes in time-sensitive networks, we propose an architecture that provisions near-zero queuing delay in new Quality-of-Service frameworks, e.g., those of 5G solutions. To this end, various studies have shown how load balancing can reduce delay. Most of these studies consider N parallel processing queues with exponential service rates and Poisson arrivals with mean rate λ. These queues are handled by a single controller that assigns a new task to the shortest queue. The so-called power-of-d-servers or power-of-d-choices approach was proven to provide necessary delay improvements. In …

Utalk: Bridging The Gap Between Humans And Ai, Muhammad Ali, Omar Alsuwaidi, Salman Khan

Machine Learning Faculty Publications

In the digital age of ever-increasing data sources, accessibility, and collection, the demand for generalizable machine learning models that are effective at capitalizing on given limited training datasets is unprecedented due to the labor-intensiveness and expensiveness of data collection. The deployed model must efficiently exploit patterns and regularities in the data to achieve desirable predictive performance on new, unseen datasets. Naturally, due to the various sources of data pools within different domains from which data can be collected, such as in Machine Learning, Natural Language Processing, and Computer Vision, selection bias will evidently creep into the gathered data, resulting in …

U2.38.15_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.111_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.175_Ta3 06.17.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.37.820_Ta3 06.24.21 Ps.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U1.38.77_Ta3 06.15.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U1.38.24_Ta3 06.15.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.37.653_Ta3 06.24.21 Ps.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …

U2.38.106_Ta3 06.18.21 Femora.Ta3, Alyssa Bolster, Hannah Jeanlouis

Bolster et al. 2024 AJBA

Objectives We estimate adult age distributions from Unar 1 and Unar 2, two late Umm an-Nar (2400-2100 BCE) tombs in the modern-day Emirate of Ras al-Khaimah, United Arab Emirates. These collective tombseach contained hundreds of skeletons in commingled, fragmented, and variably cremated states. Previous studies placed the vast majority of this mortuary community in a generalized “adult” category, as have most analyses of similar tombs from this period. We sought to test how adult age estimation methods compare in identifying young, middle, and old age individuals in commingled assemblages.

Materials and Methods We employed Transition Analysis 3 (TA3) and traditional …