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Depression Detection Using a Hybrid CNN-BiGRU-BiLSTM Model With BERT Embedding and Data Augmentation

Depression Detection Using a Hybrid CNN-BiGRU-BiLSTM Model W...

引用

IEEE SSD international Multi-conference on Systems, Signals and Devices

作者： Saadat M. Alhashmi Saleema Hashim Ahmed Mohamed Khedr College of Computing and Informatics University of Sharjah UAE

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Depression is a mood disorder that causes a persistent feeling of sadness and loss of interest. Also called major depressive disorder or clinical depression, it affects how you feel, think, and behave and can lead to a variety of emotional and physical problems. Automatic detection, as in a clinical interview can be derived from various modalities which includes video, audio, and text. Among them, detection from text data has emerged as a crucial task in mental health monitoring. In this study, we propose a hybrid deep learning model combining Convolutional Neural Networks (CNN), Bidirectional Gated Recurrent Units (BiGRU), and Bidirectional Long Short-Term Memory (BiLSTM) layers to enhance depression detection accuracy. Using BERT embedding for robust feature extraction, the proposed model processes social media or clinical text data to identify signs of depression. Additionally, we incorporate a novel data augmentation technique using synonym replacement to address data imbalance and improve generalization. Evaluations are conducted using key performance metrics, including accuracy, precision, recall, and F1 score. With an accuracy of 86.2 %, the results demonstrate that the combined CNN-BiGRU-BiLSTM architecture, alongside BERT embedding and augmented data, significantly improves classification performance compared to traditional models. This approach shows promise in contributing to more effective automatic depression detection systems.

关键词： Deep learning Accuracy Social networking (online) Bidirectional long short term memory Bidirectional control Depression Data augmentation Encoding Data models Convolutional neural networks

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22nd international conference on Scientific computing and Bioinformatics, CSC 2024, and 25th international conference on Computational Biology, BIOCOMP 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

22nd International Conference on Scientific Computing and Bi...

引用

22nd international conference on Scientific computing and Bioinformatics, CSC 2024, and 25th international conference on Computational Biology, BIOCOMP 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

ISBN: (纸本)9783031859014

The proceedings contain 31 papers. The special focus in this conference is on Scientific computing and Bioinformatics,. The topics include: Austere Runway Simulated Identification;using Rhai to Create and Benchmark Bevy Entities;pyO3: Building Python Extension Modules in Native Rust with Performance and Safety in Mind;Leveraging Python Interpreters for Concurrency in SeQUeNCe;benchmark Performance of a Rust-Based Python Extension;quantum Error Correction in Repetition Codes;investigating Selective Reliability with the Laminar networking Package;an Entanglement Swapping Throughput Analysis for Quantum Networks Using Linear Quantum Optics;notes on Symmetric Generalized Tent Map: Route to Chaos;scalable Service Model and Scheduler for Delay-Sensitive Services;regret-Minimization Heuristics for Identifying Monotone Boolean Functions;multi-class Classification of Satellite Orbits for Database Quality Control;real-Time Motion Planning for Autonomous Vehicles in Dynamic Environments;A Novel Deep Learning Method for Solving PDE’s Applied to a Shallow Water Problem;exploring the Impact of Social Media on Mental Health and Well-Being: A Multi-dimensional Analysis;the Strategic Optimization of a Tabletop Role-Playing Game;Problem-Solving Using Logic and Reasoning, Mathematics, Algorithms, Python, and Generative AI: Part Two;acquisition and Analysis of Mobile Data Using Digital Forensics Tools and Techniques;structural Health Monitoring for Risk Assessment and Reliability of a Structure After Extreme Loads;scientific Constructing Adequate Statistical Decision Rules Under Parametric Uncertainty of Applied Mathematical Models via the Smart Use of Pivotal Quantities and Ancillary Statistics;a Smart Air Quality Analysis and Pollutant Diffusion Detection and Prediction System Based on Tree Canopy Shape Research Using Machine Learning and Artificial Intelligence;a High Order Scheme for Modelling Viscous Incompressible Fluid Flow in a Channel with a Step;Feasibility Study of Neutron M

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distributed Denial of Service Attack Detection by Machine Learning Techniques

Distributed Denial of Service Attack Detection by Machine Le...

引用

Learning and Technology conference (L&T)

作者： Varkha K. Jewani Prafulla E. Ajmire Mohd. Atique Bhisham Sharma Imed Ben Dhaou Suhashini Awadhesh Chaurasia Sant Gadge Baba Amravati University Amravati India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science Hekma School of Engineering Computing and Design Dar Al-Hekma University Jeddah Saudi Arabia Department of Computer Science RTM Nagpur University Nagpur

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

The exponential expansion of computer networks and the internet makes it clear that there is a chance of being attacked and harmed. In the meantime, one of the most crucial defensive measures against the more complex and frequent network attacks is the intrusion detection and prevention systems (IDSs and IPSs). Due to insufficient datasets, anomaly-based research in intrusion detection systems is plagued by imprecise deployment, analysis, and evaluation. The researchers analyzed a variety of datasets, including DARPA98, KDD99, ISC2012, and ADFA13, to assess how well their suggested intrusion detection and intrusion prevention techniques performed. There are several issues: lack of adequate attack coverage, unrepresentative payloads, and anonymised packet information, insufficient traffic volume and diversity, or a deficiency in feature set and metadata. This study is focused on CICIDS-2017 which is the recently updated IDS dataset that meets real-world requirements and is accessible publicly. In addition to benign network flows and distributed denial of service (DDoS) attacks, it contains seven common attack network flows as well. To provide the optimal combination of features for the identification of the attack category, it also assesses the efficacy of several machine learning (ML) algorithms and network traffic feature sets. Even though various ML techniques like Linear Regression, Random Forests, and Decision Tree can be used, and performed very well, Hybrid Algorithm is designed to get better analysis on dataset.

关键词： Accuracy Machine learning algorithms Prevention and mitigation Linear regression Intrusion detection Training data Predictive models Decision trees Computer crime Random forests

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Llama-Recipe - Fine-Tuned Meta's Llama LLM, PBOM and NFT Enabled 5G Network-Slice Orchestration and End-to-End Supply-Chain Verification Platform 22

Llama-Recipe - Fine-Tuned Meta's Llama LLM, PBOM and NFT Ena...

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Bandara, Eranga Bouk, Safdar H. Shetty, Sachin Roy, Sandip Mukkamala, Ravi Rahman, Abdul Foytik, Peter Liang, Xueping Keong, Ng Wee De Zoysa, Kasun Old Dominion University Norfolk VA United States Deloitte & Touche Llp United States Florida International University United States Nanyang Technological University Singapore University of Colombo School of Computing Sri Lanka

ISBN: (纸本)9798331508050

Modern 5G networks offer a network-sliced infrastructure where each network slice contains a dedicated 5G core software service layer. The 5G core software services in each slice shares common core network resources to meet specific customer needs. A primary challenge in 5G network slicing involves resource sharing and efficient network slice orchestration. Container-based methodologies, including tools like Docker and Kubernetes, have become popular for orchestrating 5G network slice services and managing configurations in microservices-based cloud-native service deployment. However, despite their utility, these tools present significant challenges. Their complexity often necessitates dedicated DevOps teams for effective management, while configuration management can prove arduous, and end-to-end supply chain oversight is lacking. To address these challenges, this paper introduces 'Llama-Recipe,' a cloud-native 5G-core service deployment and orchestration platform integrating Generative AI, SBOM, PBOM and NFT. 5G-core service configurations across different network slices are represented as 'HOCON (Human-Optimized Config Object Notation)' config objects adhering to the GitOps paradigm. Leveraging custom-trained Meta's Llama2 LLM, Llama-Recipe generates the Kubernetes manifests for network-sliced 5G-core services based on the defined HOCON configurations. The generated Kubernetes manifests of the 5G-core services are deployed in designated Kubernetes clusters utilizing GitOps tools (e.g., ArgoCD), ensuring seamless and automated deployment processes. Additionally, Llama-Recipe introduced a novel mechanism to handle end-to-end supply chain verification of 5G-core software services using Software-Bill of Materials (SBOM) and Pipeline-Bill of Materials (PBOM). SBOMs track all the dependencies and PBOMs facilitate the comprehensive tracking of end-to-end supply chain data for 5G-core software services, enhancing transparency and security. These PBOMs are also generated

关键词： 5G 6G DevSec-Ops Generative-AI Llama2 LLM NFT PBOM

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Llama-Recipe — Fine-Tuned Meta's Llama LLM, PBOM and NFT Enabled 5G Network-Slice Orchestration and End-to-End Supply-Chain Verification Platform

Llama-Recipe — Fine-Tuned Meta's Llama LLM, PBOM and NFT En...

引用

Consumer Communications and networking conference, CCNC IEEE

作者： Eranga Bandara Safdar H. Bouk Sachin Shetty Sandip Roy Ravi Mukkamala Abdul Rahman Peter Foytik Xueping Liang Ng Wee Keong Kasun De Zoysa Old Dominion University Norfolk VA USA Deloitte & Touche LLP Florida International University USA Nanyang Technological University Singapore University of Colombo School of Computing Sri Lanka

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

Modern 5G networks offer a network-sliced infrastructure where each network slice contains a dedicated 5G core software service layer. The 5G core software services in each slice shares common core network resources to meet specific customer needs. A primary challenge in 5G network slicing involves resource sharing and efficient network slice orchestration. Container-based methodologies, including tools like Docker and Kubernetes, have become popular for orchestrating 5G network slice services and managing configurations in microservices-based cloud-native service deployment. However, despite their utility, these tools present significant challenges. Their complexity often necessitates dedicated DevOps teams for effective management, while configuration management can prove arduous, and end-to-end supply chain oversight is lacking. To address these challenges, this paper introduces “Llama-Recipe,” a cloud-native 5G-core service deployment and orchestration platform integrating Generative AI, SBOM, PBOM and NFT. 5G-core service configurations across different network slices are represented as “HOCON (Human-Optimized Config Object Notation)” config objects adhering to the GitOps paradigm. Leveraging custom-trained Meta's Llama2 LLM, Llama-Recipe generates the Kubernetes manifests for network-sliced 5G-core services based on the defined HOCON configurations. The generated Kubernetes manifests of the 5G-core services are deployed in designated Kubernetes clusters utilizing GitOps tools (e.g., ArgoCD), ensuring seamless and automated deployment processes. Additionally, Llama-Recipe introduced a novel mechanism to handle end-to-end supply chain verification of 5G-core software services using Software-Bill of Materials (SBOM) and Pipeline-Bill of Materials (PBOM). SBOMs track all the dependencies and PBOMs facilitate the comprehensive tracking of end-to-end supply chain data for 5G-core software services, enhancing transparency and security. These PBOMs are also generated

关键词： Training 5G mobile communication Network slicing Supply chains Transforms Software Nonfungible tokens Security Resource management Radio access networks

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Invariant consistency: A mechanism for inter-process ordering in distributed shared memory systems

Invariant consistency: A mechanism for inter-process orderin...

引用

22nd international conference on distributed computing Systems

作者： Singh, G Kansas State Univ Manhattan KS 66506 USA

ISBN: (纸本)0769515851

The notion of invariant consistency was proposed that allowed the programmers to specify inter-process ordering requirements. Data consistency protocols provided a consistent view of the shared memory in the presence of multiple copies, implemented in message passing systems. The combination of invariant consistency and sequential consistency, known as InvSC consistency was studied, and a systematic way to modify the Lazy Cache algorithm for implementing InvSC consistency was proposed.

关键词： Multiprocessing systems

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Parallel computing of CG using an Open Source Windows Grid

Parallel Computing of CG using an Open Source Windows Grid

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22nd international Workshops on Advanced Information networking and Applications

作者： Tanaka, Kenichi Uehara, Minoru Mori, Hideki Toyo Univ Dept Informat & Comp Sci Saitama 3508585 Japan

ISBN: (纸本)9781424442331

Recent times have seen a strong increase in the size, scope and number of information processing tasks computers are commonly used to perform. Grids are one form of distributed computing that, generally, aim for HTC (High Throughput computing). Grids can also be constructed to perform HPC (High Performance computing) at a relatively low cost when compared to clusters. There currently exists open source middleware for building grids. But when such grids consist of Windows machines it is difficult to use members of the grid efficiently. This research concerns the construction of a cheap grid of Windows machines. In this paper we describe a Windows grid that uses multiple core processors which are becoming increasingly popular.

关键词： Middleware

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Scheduling in Grid Databases

Scheduling in Grid Databases

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22nd international Workshops on Advanced Information networking and Applications

作者： de Carvalho Costa, Rogerio Luis Furtado, Pedro Univ Coimbra Dept Informat Engn P-3030290 Coimbra Portugal

ISBN: (纸本)9781424442331

Many global organizations are generating large volumes of highly distributed data that must be shared for querying by the organization's participants, which can be put together by a grid infrastructure. Scheduling query execution in these environment is an important issue. Centralized and Hierarchical scheduling architectures are between the most commonly used scheduling architectures in distributed databases and grid computing, respectively Each architectural model has its own advantages and disadvantages. In this paper we evaluate the usage of both models in querying highly distributed data. We consider several scheduling policies and experimentally compare scheduling models and policies in terms of throughput and SLO-fulfillment. The obtained results indicate that layered on-demand scheduling may lead to good results in both throughput and SLO-oriented environments.

关键词： Grid computing

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Script: Simulations from Grid to Ubiquitous computing

Script: Simulations from Grid to Ubiquitous Computing

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22nd international Workshops on Advanced Information networking and Applications

作者： Lee, Yih-Jiun Lien, Kai-Wen Department of Information Management ChienKuo Technology University Taiwan

ISBN: (纸本)9781424442331

Ubiquitous computing has gained ground over the last five years. It focuses on devices being able to connect to the net at any time from any place. It includes the modern term distributed computing, which means accessing resources from any place. Several behaviours in modern distributed computing can be observed. For instance, a process in one place can send an object to other places;a process can request an object from a remote provider;a process can be moved from one place to another and then continue its execution;a message might travel through many intermediaries before its destination. Too many participants in one action might cause computational complications. It is better if the system structure can be at proved before the action really takes place. Therefore, Script is a modelling language designed for "simulating" and "verifying" distributed computing, grid computing and ubiquitous computing. Although Script is currently a modelling language, it will be provided with a transformation tool to move a Script-based model into a real environment. This tool is under development.

关键词： Ubiquitous computing

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Dynamic behaviour of the distributed tree quorum algorithm

Dynamic behaviour of the distributed tree quorum algorithm

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22nd international conference on distributed computing Systems

作者： Kafri, N Janecek, J Czech Tech Univ Dept Comp Sci & Engn CZ-12135 Prague 2 Czech Republic

ISBN: (纸本)0769515851

Mechanisms that ensure mutual access, replication and resilience to failures in large distributed systems can be based on quorum consensus. Effectiveness and scalability of the method selected are crucial. The aim of this paper is to present a message/time cost analysis of a distributed algorithm based on the tree quorum, which needs no global information, and has message complexity independent of the load. Results obtained for the different identifications of the requests (a requester's identification, timestamp, and group priority) illustrate the flexibility of the method. The algorithm supports priority, the feature important for current middleware technologies.

关键词： distributed quorum consensus tree quorum scalability message complexity synchronization delay

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