Abdelaziz Bouras

Abdelaziz Bouras

Qatar University

H-index: 30

Asia-Qatar

Abdelaziz Bouras Information

University

Qatar University

Position

___

Citations(all)

5464

Citations(since 2020)

2980

Cited By

3690

hIndex(all)

30

hIndex(since 2020)

26

i10Index(all)

85

i10Index(since 2020)

53

Email

University Profile Page

Qatar University

Abdelaziz Bouras Skills & Research Interests

Information Systems

PLM

Product lifecycle management

Ontology Based Engineering

Blockchains for Supply Chains

Top articles of Abdelaziz Bouras

BIM EDUCATION FOR QATAR’S CONSTRUCTION INDUSTRY: A LIFECYCLE VISION

New technologies and tools used in BIM (Building Information Modeling) process enable information exchange among different involved stakeholders in a project, from the initial conception to the final demolition. Qatar’s future construction projects will shift to mid-sized scale, as the country has already completed and tendered a large infrastructure around the football World-Cup 2022 mega-event. SMEs (Small and Medium Enterprises) should learn from the example of large-scale organizations and adopt BIM solutions and lifecycle concepts. This demands higher BIM skills and capabilities. Therefore, BIM concepts and collaborative workflows need to be included in tertiary educational programs to support current and prepare future industry practitioners. Many academic institutions around the world have either created new courses or added BIM into existing courses and programs. BIM education curricula need to …

Authors

A Hammi,D Ouahrani,A Bouras,K Naji

Published Date

2024

Stacking-based multi-objective ensemble framework for prediction of hypertension

Hypertension is a common health problem that is costly to treat, difficult to control, and frequently results in serious and fatal disorders like cardiovascular disease (CVD) and stroke. The main objective of this work was to design and verify a stacking ensemble framework-based model for predicting hypertension risk prospectively. Firstly, we proposed a Multi-objective Iterative Model Selection (MoItMS) strategy to maximize the accuracy of meta-learners and the diversity of the ensemble model at the same time. An effective method for classifying people for managing population health and assisting in the assessment and identification of hypertension is then provided using a stacking-based multi-objective ensemble framework that can be applied to enormous volumes of clinical data. The National Health and Nutrition Examination Survey (NHANES) collected data from 2007 to 2018. Of the 11,341 patients studied, 67 …

Authors

Lijuan Ren,Haiqing Zhang,Aicha Sekhari Seklouli,Tao Wang,Abdelaziz Bouras

Journal

Expert Systems with Applications

Published Date

2023/4/1

Product Lifecycle Management. PLM in Transition Times: The Place of Humans and Transformative Technologies: 19th IFIP WG 5.1 International Conference, PLM 2022, Grenoble …

Humanity is facing crises in many areas (health, environment, wars, social risks, etc.) which are reaching the end of the convergence cycle towards the globalisation model. These crises require us to think of the world in a transitional mode. Industrial systems for the production of goods and services are not spared this need for transition. The PLM conference series is completely dedicated to support production systems to meet emerging challenges. The concept of Industry 4.0 was introduced in Western countries to bridge the digital divide but has already been overtaken by the idea of a people-centred industry, which some call Industry 5.0. In this context, it seemed reasonable in 2022 to approach product and service lifecycle management from the perspective of PLM in transition times, and particularly the place of humans and transformative technologies. After the first wave of the COVID-19 crisis restricting our social life and freedom of movement, while information technology kept communication alive during the pandemic, PLM 2022 returned to the tradition of face-to-face conferences. This is not a step backwards. The place of people and social relations in the face of technology remains an imperative. For PLM, a conference is still a networking activity which leads to synergies between industrialists and academics, and while videoconferencing can maintain existing relationships it does not yet allow for the creation of new permanent contacts.

Authors

Frédéric Noël,Felix Nyffenegger,Louis Rivest,Abdelaziz Bouras

Published Date

2023/1/31

A Prediction Framework for Lifestyle-Related Disease Prediction Using Healthcare Data

With the improvement of living standards and changes in work habits caused by industrialization, the prevalence of diseases related to lifestyle is rising. In this context, the prevention of lifestyle-related diseases (LRDs) is extremely important. The majority of existing research exclusively concentrates on the prognosis of a particular LRD sickness, making it impossible for them to intelligently identify the important characteristics of the disease. Therefore, this study aims to propose a lifestyle-related disease prediction framework including three key components, called missing value module, feature selection module, and disease prediction module. The performance of the proposed framework is evaluated by using real medical data gathered during a hospital in Nanjing, China. The experiment shows that the proposed framework can automatically generate prediction ensemble models for specific LRDs diseases, and …

Authors

Lijuan Ren,Haiqing Zhang,Aicha Sekhari Seklouli,Tao Wang,Abdelaziz Bouras

Published Date

2023/9/15

Toward an NLP Approach for Transforming Paper Contracts into Smart Contracts

Identifying and extracting information from contracts is an important task of contract analysis, which is mostly performed manually by lawyers and legal specialists. This manual analysis is a time-consuming, error-prone task. We can overcome this by automating the task of legal entity extraction using the Natural Language Processing (NLP) techniques. For extracting information from the natural language text, we can use popular NLP methods Named Entity Recognition (NER) and relation extraction (RE). Most NER and RE methods rely on machine learning and deep learning to identify relevant entities in natural language text. The main concern in adapting the AI methods for contract element extraction is the scarcity of annotated datasets in the legal field. Aiming at tackling this challenge, we decided to prepare the contract datasets for NER and RE tasks by manually annotating publicly available English contracts …

Authors

Bajeela Aejas,Abdelhak Belhi,Abdelaziz Bouras

Published Date

2023/1/25

A review on missing values for main challenges and methods

Several recent reviews summarize common missing value analysis methods. However, none of them provide a systematic and in-depth summary of the analytical challenges and solutions for dealing with missing values. For the purpose of guiding the handling of missing values, this review aims to consolidate current developments in novel missing-value research methodologies. In particular, we comprehensively investigated cutting-edge missing value solutions and methodically studied the main challenges associated with missing values analysis (missing mechanisms, missing patterns, and missing rates). Furthermore, we reviewed 63 publications that compare different strategies for deleting and imputing missing values. Then we investigated data characteristics, highlighted three main problems when analyzing missing values, and analyzed the performance of missing value solutions in these studied papers …

Authors

Lijuan Ren,Tao Wang,Aicha Sekhari Seklouli,Haiqing Zhang,Abdelaziz Bouras

Published Date

2023/8/11

An integrated framework for the interaction and 3D visualization of cultural heritage

In this study, the aim is to design and develop a 3D acquisition, visualization, and interaction framework to preserve cultural heritage and provide new ways to enable museum visitors and cultural audiences to virtually interact with cultural objects. Indeed, cultural assets are nowadays at higher risk and most cultural institutions prohibit visitors from physically manipulating their collections. The main motivation behind our framework is to enable end-user interaction with high valuable cultural objects while addressing cost-effectiveness concerns as well as minimizing the time required to digitize and generate 3D models of cultural heritage objects. The design idea of our framework is to allow interaction with the protected assets’ 3D representation using a real-world 3D screen equipped with a depth sensor namely the leap motion controller. Our framework is an end-to-end solution that optimizes all the stages of the 3D …

Authors

Abdelhak Belhi,Hosameldin Osman Ahmed,Taha Alfaqheri,Abdelaziz Bouras,Abdul H Sadka,Sebti Foufou

Journal

Multimedia Tools and Applications

Published Date

2023/1/11

A machine learning framework for enhancing digital experiences in cultural heritage

PurposeDigital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which decreases their attractiveness and induces loss of value. This paper introduces a new framework that aims at tackling the cultural data enrichment challenge using machine learning.Design/methodology/approachThis framework focuses on the automatic annotation and metadata completion through new deep learning classification and annotation methods. It also addresses issues related to physically damaged heritage objects through a new image reconstruction approach based on supervised and unsupervised learning.FindingsThe authors evaluate approaches on a data set of cultural objects collected from various cultural institutions around the world. For annotation and classification part of …

Authors

Abdelhak Belhi,Abdelaziz Bouras,Abdulaziz Khalid Al-Ali,Sebti Foufou

Journal

Journal of Enterprise Information Management

Published Date

2023/4/24

Blockchain-based Access Control for Secure Smart Industry Management Systems

Smart manufacturing systems involve a large number of interconnected devices resulting in massive data generation. Cloud computing technology has recently gained increasing attention in smart manufacturing systems for facilitating cost-effective service provisioning and massive data management. In a cloud-based manufacturing system, ensuring authorized access to the data is crucial. A cloud platform is operated under a single authority. Hence, a cloud platform is prone to a single point of failure and vulnerable to adversaries. An internal or external adversary can easily modify users’ access to allow unauthorized users to access the data. This paper proposes a role-based access control to prevent modification attacks by leveraging blockchain and smart contracts in a cloud-based smart manufacturing system. The role-based access control is developed to determine users’ roles and rights in smart contracts …

Authors

Aditya Pribadi Kalapaaking,Ibrahim Khalil,Mohammad Saidur Rahman,Abdelaziz Bouras

Published Date

2022/12/7

Blockchain Driven Supply Chains and Enterprise Information Systems

Systems, aims at establishing a common ground to provide solutions and best practices around blockchain for supply chain management and enterprise information systems. This book considers the implementation of blockchain platforms in both existing traditional supply chain systems and future enterprise information solutions.

Authors

Abdelaziz Bouras

Published Date

2023

Blockchain technology regulation: time for standardized frameworks

In an age of rich data and information streams, the governments’ role with regard to new technology in terms of regulation is continuously changing. Novel areas for this era of big data must be considered when introducing new policies and issuing regulations. These areas cover privacy, security, retention, processing, ownership, and the integrity of information. In this paper, we have focused on the blockchain technology and its features such as distributed ledger and smart contracts in a regulation point of view. We have defined the current regulation landscape and initiatives across the globe and then highlighted some applications of the blockchain technology through regulation perspective in different sectors. We have emphasized some challenges faced by the blockchain technology and came up with some recommendations to tackle those challenges.

Authors

Assam Hammi,Anjaneyulu Jinugu,Malike Bouaoud,Ahmed Hefnawy,Abdelaziz Bouras

Published Date

2022/9/7

Hypertension Prediction Using Optimal Random Forest and Real Medical Data

Long-lasting and difficult-to-treat, hypertension frequently leads to serious and life-threatening diseases. As a result, early risk assessment and prevention of hypertension are crucial. The majority of research currently available ignore the preprocessing analysis of real medical data, particularly the analysis of missing values, in favor of using clean data to increase the performance of hypertension prediction. Thus, in this study, real but incomplete data were subjected to preprocessing analysis including missing value analysis and feature divergence analysis, and then a Bayesian optimization technique was employed to find the optimal random forest model. Experimental results showed that proper missing value strategy (i.e., MissForest) can slightly enhance the data quality and produce slightly better predictive performance (from 0.001% to 0.069%) even the missing rate is less than 1%. Additionally, compared to …

Authors

Lijuan Ren,Aicha Sekhari Seklouli,Tao Wang,Haiqing Zhang,Abdelaziz Bouras

Published Date

2022/12/2

Anomaly detection: A survey

Anomaly detection (AD) is considered one of the important research areas that have a diverse range of application domains. Some of the anomaly detection techniques presented in the literature were specifically implemented for certain domains, whereas others were more generic. In this paper, we aim at providing a structured yet extensive overview of current research directions on anomaly detection, including the definition of anomalies and their types, current anomaly detection modes, the output of anomaly detection techniques, and an overview of those techniques presented in the literature, in order to provide a guide when selecting the appropriate approach for certain application domains.

Authors

Tahani Hussein Abu Musa,Abdelaziz Bouras

Published Date

2022

Product Lifecycle Management. Green and Blue Technologies to Support Smart and Sustainable Organizations: 18th IFIP WG 5.1 International Conference, PLM 2021, Curitiba, Brazil …

The two-volume set IFIP AICT 639 and 640 constitutes the refereed post-conference proceedings of the 18th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2021, held in Curitiba, Brazil, during July 11-14, 2021. The conference was held virtually due to the COVID-19 crisis. The 107 revised full papers presented in these proceedings were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: Volume I: Sustainability, sustainable development and circular economy; sustainability and information technologies and services; green and blue technologies; AI and blockchain integration with enterprise applications; PLM maturity, PLM implementation and adoption within industry 4.0; and industry 4.0 and emerging technologies: Volume II: Design, education and management; lean, design and innovation technologies; information technology models and design; and models, manufacturing and information technologies and services.

Authors

Osiris Canciglieri Junior,Frédéric Noël,Louis Rivest,Abdelaziz Bouras

Published Date

2022/2/8

TMSLedger: A Transactions Management System Through Integrated Odoo Hyperledger Smart Contracts

Ever since their big impact in the financial sector, blockchains have never ceased to make disruptions in collaborative applications. Blockchains are considered nowadays the go-to solution for developing critical data exchange platforms. Unfortunately, their interaction with existing and already established platforms is still limited due to many reasons such as legacy platforms complexity and resistance to change. Through this chapter, we aim at addressing this gap by proposing an end-to-end solution for managing business workflows using blockchain smart contracts. We propose a proof of concept of a manufacturing supply chain scenario integration between Odoo (supply chain processes) and Hyperledger Fabric (blockchain development platform). We demonstrate how Odoo workflows can be optimized, secured, and made trustworthy using smart contracts and highlight the impact of this solution on current and …

Authors

Abdelhak Belhi,Houssem Gasmi,Assam Hammi,Abdelaziz Bouras,Belaid Aouni,Ibrahim Khalil

Published Date

2022/9/7

Blockchain-of-blockchains: An interoperable blockchain platform for ensuring IoT data integrity in smart city

We propose a hierarchical blockchain-based platform for ensuring the integrity of smart city Internet-of-Things (IoT) data and blockchain interoperability in this paper. The well-defined structural hierarchy of managing organizations in a smart city face several data management issues. The integration of emerging technologies, such as (IoT), has introduced more complexity to data maintenance in the smart city. At present, cloud-based information systems have become the norm for managing IoT data. Due to the centralized administrative control, the cloud-based information management is untrusted. Hence, it fails to guarantee the integrity of IoT data and traceability of operations to achieve transparency within the smart city organizations. Adoption of blockchain-based information systems can be viable solution to address these challenges. However, it introduces a new challenge of interoperability of transactions …

Authors

Mohammad Saidur Rahman,MAP Chamikara,Ibrahim Khalil,Abdelaziz Bouras

Journal

Journal of Industrial Information Integration

Published Date

2022/11/1

3D Quantum Cuts for automatic segmentation of porous media in tomography images

Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves around primitive techniques based on global or local adaptive thresholding that have known common drawbacks in image segmentation. Moreover, the absence of a unified benchmark prohibits quantitative evaluation, which further undermines the impact of existing methodologies. In this study, we tackle the issue on both fronts. First, by drawing parallels with natural image segmentation, we propose a novel, and automatic segmentation technique, 3D Quantum Cuts (QCuts-3D) grounded on a state-of-the-art spectral clustering technique. Secondly, we curate and present a publicly available dataset of 68 multiphase volumetric images of porous media with diverse solid geometries, along with …

Authors

Junaid Malik,Serkan Kiranyaz,Riyadh I Al-Raoush,Olivier Monga,Patricia Garnier,Sebti Foufou,Abdelaziz Bouras,Alexandros Iosifidis,Moncef Gabbouj,Philippe C Baveye

Journal

Computers & Geosciences

Published Date

2022/2/1

Blockchain-based lifecycle approach towards a secure building information modelling (BIM) workflow

Data safety concerns are critical during the whole lifecycle of any built asset from the design stage until destruction. Information security in Building Information Modeling (BIM) enabled projects represents a key factor for the whole process success. Unsuitable distribution of sensitive information may cause financial loss, lack of trust and even physical security threats. This paper would propose a novel solution to secure BIM workflow through a Blockchain technology-based lifecycle approach. The aim in this solution is to integrate a blockchain-based lifecycle management platform with BIM software. The interactions and system transactions between the two entities will be managed by distributed ledger technology and smart contracts. This will ensure workflow's security by strengthening the transparency, traceability and securing information exchange.

Authors

Assam Hammi,Abdelhak Belhi,Houssem Gasmi,Abdelaziz Bouras

Published Date

2022/8/18

Integration potentiality of Blockchain technology within BIM enabled projects

Information safety in BIM enabled projects represents a key factor for the whole process success. Data security concerns are critical during the entire lifecycle of any built asset from design until demolition. Unsuitable distribution of sensitive information may cause financial loss, lack of trust and even physical security threats. This paper highlights through a literature review the integration’s potentiality of Blockchain technology within BIM enabled projects that would tackle those security issues and would provide more trust and reliability. This paper also highlights some of the advantages offered by the contribution of distributed ledger technology and smart contracts to the digitalization and digital transformation of the AEC-FM sector in terms of procurement, payment and supply chain management.

Authors

Assam Hammi,Abdelhak Belhi,Houssem Gasmi,Abdelaziz Bouras

Journal

Value Management Journal

Published Date

2022/9/23

Chatbot application to support smart agriculture in Thailand

A chatbot is a software developed to help reply to text or voice conversations automatically and quickly in real time. In the agriculture sector, the existing smart agriculture systems just use data from sensing and internet of things (IoT) technologies that exclude crop cultivation knowledge to support decision-making by farmers. To enhance this, the chatbot application can be an assistant to farmers to provide crop cultivation knowledge. Consequently, we propose the LINE chatbot application as an information and knowledge representation providing crop cultivation recommendations to farmers. It works with smart agriculture and recommendation systems. Our proposed LINE chatbot application consists of five main functions (start/stop menu, main page, drip irri gation page, mist irrigation page, and monitor page). Farmers will receive information for data monitoring to support their decision-making. Moreover, they can …

Authors

Paweena Suebsombut,Pradorn Sureephong,Aicha Sekhari,Suepphong Chernbumroong,Abdelaziz Bouras

Published Date

2022/1/26

Smart Contracts Auto-generation for Supply Chain Contexts

The introduction of blockchain technology into Supply Chain management has opened the possibility of faster and more secure transactions of commodities and services. As for every blockchain, Smart Contracts are the tool for controlling the transactions in blockchain-based supply chains. In this paper, we introduce a method for automating the implementation of natural language contracts into Smart Contracts in the Supply Chain context. The basic idea here is to extract information from a natural language contract using two Natural Language Processing (NLP) techniques, the Named Entity Recognition (NER) and Relation Extraction (RE), and then use this extracted information to automatically create a corresponding Smart Contract. This is an ongoing project, and we implemented the first phase of NLP, i.e., NER. The main issue we are facing here is the limited availability of annotated contract datasets. To tackle …

Authors

Bajeela Aejas,Abdelhak Belhi,Abdelaziz Bouras

Published Date

2022/7/10

Development of a Research Tracking System for Higher Education Institution Research Grants

This paper presents an overview of the processes and tools governing the research administration in Higher Education Institutions (HEIs) in general and Qatar University (QU) in particular. It also encompasses the best practices being employed or to be adopted for smooth sailing of research projects all the way from their inception to closeout. It can serve as a referring point for management to get an eagle view of the present research policies and accordingly take decisions to boost the quality of research outcomes by implementing automated systems such as tracking and monitoring of research activities to tackle the grants in a more effective and productive manner. Moreover, the requirement of a research tracking system (RTS) has been emphasized by proposing a stepwise implementation to manage grants more efficiently both from an administration and management point of views.In order to detail the implementation of RTS, a brief review of contemporary available grant management systems, applicable to research, has been conducted. The salient features of these systems are studied to develop an in-house solution for the university in the form of web applications using open-source tools. A tailored tracking and monitoring of research activities, from post-award until the closeout of the grants, is a valuable addition that contributes to building best practices for higher education and research institutions.

Authors

Abdelaziz Bouras,Mariam Al-Maadeed,Hira Naseem,Shahbaz Hussain,Abdelali Agouni,Mohammed Al-Salem

Journal

Proceedings of EUNIS

Published Date

2022/9/20

An Ontology Model for Medical Tourism Supply Chain Knowledge Representation

This study developed an application ontology related to the medical tourism supply chain domain (MTSC). The motivation for developing an ontology is that current MTSC studies use a descriptive approach to provide knowledge, which is difficult to comprehend and apply. The formalization of MTSC knowledge can provide medical tourism stakeholders with a shared understanding of the medical tourism business. As a result, the MTSC domain requires efficient semantic knowledge representation. Ontology is a popular approach for integrating knowledge and comprehension because it presents schema and knowledge base in an accurate and relevant feature. This paper employed the ontology engineering methodology, which included specification, conceptualization, and implementation steps. The conceptual model and facets of the MTSC are proposed. The MTSC objective and scope are tested with semantic competency questions against SPARQL Query formulations. The ontology metrics evaluation was used to verify the ontology quality including the external validation done by the domain experts. The results showed that the MTSC ontology has an appropriate schema design, terminologies, and query results. 2022. All Rights Reserved.

Authors

Worawit Janchai,Abdelaziz Bouras,Veeraporn Siddoo

Published Date

2022

Missing Values for Classification of Machine Learning in Medical data

Missing values are an unavoidable problem for classification tasks of machine learning in medical data. With the rapid development of the medical system, large scale medical data is increasing. Missing values increase the difficulty of mining hidden but useful information in these medical datasets. Deletion and imputation methods are the most popular methods for dealing with missing values. Existing studies ignored to compare and discuss the deletion and imputation methods of missing values under the row missing rate and the total missing rate. Meanwhile, they rarely used experiment data sets that are mixed-type and large scale. In this work, medical data sets of various sizes and mixed-type are used. At the same time, performance differences of deletion and imputation methods are compared under the MCAR (Missing Completely At Random) mechanism in the baseline task using LR (Linear Regression) and …

Authors

Lijuan Ren,Tao Wang,Aicha Sekhari Seklouli,Haiqing Zhang,Abdelaziz Bouras

Published Date

2022/5/27

An adaptive Laplacian weight random forest imputation for imbalance and mixed-type data

As the application of information technology in the medical field is resulting in a large amount of medical data. As early withdrawal and refusal of participants, there are a lot of missing values in medical data. Although various processing methods for missing values have been proposed, few methods for those medical data with characteristics of imbalance and mixed-type data. In this work, we proposed an adaptive Laplacian weight random forest, called ALWRF. In ALWRF, feature weights were adjusted dynamically when model constructing, which increases selection probabilities of features with low Laplacian score and high importance. Meanwhile, a random operator is introduced to increase the diversity of trees. Furthermore, we proposed an imputation method based on SMOTE-NC oversampling technology and the ALWRF method for imbalanced and mixed-type data, called SncALWRFI. Meanwhile, Bayesian …

Authors

Lijuan Ren,Aicha Sekhari Seklouli,Haiqing Zhang,Tao Wang,Abdelaziz Bouras

Journal

Information Systems

Published Date

2022/9/13

A review of contract entity extraction

A contract is a binding document between two or more parties for executing any kind of activities that are defined clearly in its clauses. The parties who are assigned specific roles and rights must review and act accordingly until the contract expires. Automation of contract management is an emerging topic in various fields such as supply chain and legal domains. Recognition of various entities related to the document and their extraction are the main tasks to be performed for automating the contract management process. Named Entity Recognition is a well-known task in NLP that deals with the recognition of named entities such as person and date from a text. But traditional NER models perform poorly for domain-specific entity recognition and extraction such as legal and contract documents. For domain-specific entity recognition, we need to train the model with a dataset from the specific domain. In this …

Authors

Bajeela Aejas,Abdelaziz Bouras,Abdelhak Belhi,Houssem Gasmi

Published Date

2022

Designing an Efficient Consensus Protocol for Supply Chain

Blockchain is being a game-changer for digital supply chain systems to enable traceability and immutability. The consensus mechanism is the key technology that powers the immutability of data stored in the blockchain. As blockchain and its consensus mechanisms are primarily designed for cryptocurrency, the existing consensus mechanisms are not efficient and directly applicable to supply chain systems. Therefore, it is extremely important to design a consortium consensus mechanism that is suitable for supply chain systems. In general, a supply chain system is a consortium of multiple stakeholders offering different services. Also, the supply chain is a complex process and requires fast consensus for avoiding any delay in the operations. This chapter presents a new consensus mechanism for blockchain-based supply chain management systems to provide the solutions to data security and establish trust among …

Authors

Mohammad Saidur Rahman,Ibrahim Khalil,Abdelaziz Bouras

Published Date

2022/2/23

Named Entity Recognition for Cultural Heritage Preservation

To preserve historical documents, many cultural institutions started digitizing the historical manuscripts and cultural assets metadata. This digitization not only preserves data but also helps in processing these texts to provide easy access to the world of cultural heritage. Named entity recognition (NER) plays an important role in processing the textual data and dealing with the named entities in the text. NER is a subfield of natural language processing that deals with the identification of named entities in the document and is the basic task of many NLP applications such as information extraction (IE) and question answering (QA). Different methods for NER have been proposed such as rule-based approaches initially. Now, along with rule-based methods, machine learning approaches as well as deep learning methods are also adopted in the field of NER researches. In this paper, we present a survey on NER …

Authors

Bajeela Aejas,Abdelaziz Bouras,Abdelhak Belhi,Houssem Gasmi

Published Date

2021

A Framework for Modelling Blockchain based Supply Chain Management System to ensure soundness of Smart Contract Workflow.

We propose a smart contract workflow verification framework for blockchain-based supply chain management systems. The proposed framework introduces a Petri-Net-based formalism to model smart contract workflow in a supply-chain context. Smart contracts are deployed in the blockchain nodes and executed automatically if a predefined condition is met. As deployment and execution of smart contracts require payment, it is necessary to ensure smart contract logic before the deployment to avoid unnecessary execution costs. Multiple business rules should be followed in a predefined order and criteria to complete a complex supply chain process. Therefore, a set of smart contracts representing digital business rules should also be executed in a predefined order and criteria. To verify the soundness of smart contract-based blockchain systems, the modeling of smart contract execution is required. The proposed Petri-Net model for smart contracts ensures smart contract workflow correctness before execution in a blockchain-based system. We conduct multiple experiments to evaluate the performance of our proposed framework.

Authors

Mohammad Saidur Rahman,Ibrahim Khalil,Abdelaziz Bouras

Published Date

2021/1/5

A broker-based manufacturing supply chain integration with blockchain: Managing odoo workflows using hyperledger fabric smart contracts

Nowadays, Blockchains are considered the go-to solution when it comes to secure and trust-ensuring platforms for critical data exchange. However, integrating this technology with existing systems is quite a challenging task as there is an unclear path to achieve the integration. Usually, the main motivation behind integrating blockchain with information systems is the fact that it ensures trustworthiness, security, and traceability by design. In this paper, we investigate the integration of this technology from an information system perspective in the context of manufacturing supply chains. We propose a proof-of-concept of a manufacturing supply chain scenario integration between Odoo (Supply Chain processes) and Hyperledger Fabric (blockchain development platform). We demonstrate how Odoo workflows can be optimized, secured, and made trustworthy using smart contracts and highlight the impact of this solution …

Authors

Abdelhak Belhi,Houssem Gasmi,Assam Hammi,Abdelaziz Bouras,Belaid Aouni,Ibrahim Khalil

Published Date

2021/7/11

Study and Evaluation of Pre-trained CNN Networks for Cultural Heritage Image Classification

The classification of digital images is an essential task during the restoration and preservation of cultural heritage (CH). In computer vision, cultural heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and evaluate the use of pre-trained deep convolutional neural networks such as VGG16, VGG-19, ResNet50, and Inception-V3 for cultural heritage images classification using transfer learning techniques. The main idea is to start with CNN models previously trained for definite tasks with specific datasets and classes, instead of designing a full stand-alone CNN-based model. Two image datasets are used to validate the performance of these models in CH images classification. The …

Authors

Abdelhak Belhi,Hosameldin Osman Ahmed,Taha Alfaqheri,Abdelaziz Bouras,Abdul Hamid Sadka,Sebti Foufou

Journal

Data Analytics for Cultural Heritage: Current Trends and Concepts

Published Date

2021

Rule based recommendation system to support crop lifecycle management

Crop lifecycle management is important for crop care and maintenance throughout its life. The existing recommendation and expert systems do not provide advice for the entire crop lifecycle. However, each stage of the crop's lifecycle necessitates a different set of recommendations. As a result, this paper proposed a recommendation system based on sensor data and rule-based extraction from expert people to provide crop management advice throughout its lifecycle. The proposed system's rules are built around IF-THEN situations. The proposed system will analyze the data by searching for relationships between input data and rule-based using a PHP script to define the best recommendation for farmers. This proposed system was put into action in a greenhouse dome in Chiang Mai, Thailand. Farmers were overwhelmingly pleased with it, giving it a 96% satisfaction rating.

Authors

Paweena Suebsombut,Aicha Seklouli-Sekhari,Pradorn Sureephong,Abdelaziz Bouras

Journal

The Journal of Modern Project Management

Published Date

2021

Smart contracts implementation based on bidirectional encoder representations from transformers

The distribution and immutability properties of blockchains made it possible to use them in various fields, such as Supply Chain, finance and health. The automation of the creation and execution of transactions in a blockchain in a decentralized and transparent manner is realized through Smart Contracts programming codes. This paper presents the implementation of Smart Contracts in specific manufacturing Supply Chains and discusses their life cycle and impact on the Supply Chain management. The presented application deals with the possibility of transforming natural language contracts of a given Supply Chain to automated Smart Contracts that makes the Supply Chain management faster and safer. A first solution is proposed based on Bidirectional Encoder Representations from Transformers (BERT) model and limited to the implementation of Smart Contracts of the Supply Chain legal contracts. Also …

Authors

Bajeela Aejas,Abdelaziz Bouras,Abdelhak Belhi,Houssem Gasmi

Published Date

2021/7/11

Field data forecasting using LSTM and Bi-LSTM approaches

Water, an essential resource for crop production, is becoming increasingly scarce, while cropland continues to expand due to the world’s population growth. Proper irrigation scheduling has been shown to help farmers improve crop yield and quality, resulting in more sustainable water consumption. Soil Moisture (SM), which indicates the amount of water in the soil, is one of the most important crop irrigation parameters. In terms of water usage optimization and crop yield, estimating future soil moisture (forecasting) is an essentially valuable task for crop irrigation. As a result, farmers can base crop irrigation decisions on this parameter. Sensors can be used to estimate this value in real time, which may assist farmers in deciding whether or not to irrigate. The soil moisture value provided by the sensors, on the other hand, is instantaneous and cannot be used to directly compute irrigation parameters such as the best timing or the required water quantity to irrigate. The soil moisture value can, in fact, vary greatly depending on factors such as humidity, weather, and time. Using machine learning methods, these parameters can be used to predict soil moisture levels in the near future. This paper proposes a new Long-Short Term Memory (LSTM)-based model to forecast soil moisture values in the future based on parameters collected from various sensors as a potential solution. To train and validate this model, a real-world dataset containing a set of parameters related to weather forecasting, soil moisture, and other related parameters was collected using smart sensors installed in a greenhouse in Chiang Mai province, Thailand. Preliminary results show …

Authors

Paweena Suebsombut,Aicha Sekhari,Pradorn Sureephong,Abdelhak Belhi,Abdelaziz Bouras

Journal

Applied Sciences

Published Date

2021/12/13

3D Visual Interaction for Cultural Heritage Sector

During the past three decades, digital cultural heritage deployment in the communication domain has changed significantly. One of the main interests of heritage curation institutions and research is to implement user-friendly 3D visual interaction system to museums visitors. In this chapter, we firstly reviewed human-computer interaction techniques used in the cultural heritage sector, followed by details of hand gesture recognition applications implemented in the cultural heritage context. In attempting to improve user experiences for 3D visual interaction in a cultural heritage, we designed efficient processing pipeline to address the system usability and cost-effectiveness concerns. The presented work of visual interaction system is evaluated in terms of user’s experience. The evaluation results showed the effectiveness of the proposed framework in offering a high-quality visual experience with a …

Authors

T Alfaqheri,HO Ahmed,A Belhi,AH Sadka,A Bouras

Published Date

2021

Integration of business applications with the blockchain: Odoo and hyperledger fabric open source proof of concept

Since its revolution in the financial sector, the blockchain technology disrupted the majority of collaboration-based applications including supply chain management. The supply chain is one of the most important sectors benefiting from all the advantages of blockchain. Through this paper, we are mainly focusing on the practical aspects of integrating blockchain technology with traditional and existing business applications. Indeed, most businesses and corporations will find it hard to shift from traditional architectures to a decentralized one with fears related to upgrading risks, unknown tools, and resistance to change. Thus, we mainly propose several scenarios for blockchain integration focusing on the most used Enterprise Resource Planning (ERP) platforms. Besides, we present our proof of concept integration that uses the HyperLedger Fabric blockchain platform and the Odoo ERP framework. The selection of …

Authors

Abdelhak Belhi,Houssem Gasmi,Abdelaziz Bouras,Belaid Aouni,Ibrahim Khalil

Journal

IFAC-PapersOnLine

Published Date

2021/1/1

Anomaly detection in Blockchain-enabled supply chain: an ontological approach

In our work, we propose an anomaly detection framework, for detecting anomalous transactions in business processes from transaction event logs. Such a framework will help enhance the accuracy of anomaly detection in the global Supply Chain, improve the multi-level business processes workflow in the Supply Chain domain, and will optimize the processes in the Supply Chain in terms of security and automation. In the proposed work, Ontology is utilized to provide anomaly classification in business transactions, based on crafted SWRL rules for that purpose. Our work has been evaluated based on logs generated from simulating a generic business process model related to a procurement scenario, and the findings show that our framework was able to detect and classify anomalous transactions form those logs.

Authors

Tahani Abu Musa,Abdelaziz Bouras

Published Date

2021/7/11

Conceptualization of Artificial Intelligence in Airway Management

Background Failed intubation is the single most important cause of patient morbidity and mortality during anesthesia for surgery. The incidence of difficult intubation could be as high as 12% while failed intubation is around 0.5%. Disaster and mass casualty management may increase this risk multi-fold due to the paucity of airway-trained medical personnel. Automation of the entire procedure could potentially save lives particularly in situations where mass casualties could happen without the immediate availability of skilled airway specialists. Thanks to the combination of existing technology involving 3-D image capture, artificial intelligence (AI), machine learning (ML) for image analysis, and robotics, airway management could be revolutionized. Work is already underway in this domain, but many challenges still need to be overcome to make the technology more practical and user-friendly. Methods Experts in the …

Authors

Ramkumar Dhananchey,Guillaume Henri Jean Alinier,Abdelaziz Bouras,Alamgir Hossain,Marcus Lance,Vijay Jeganath

Journal

Journal of Emergency Medicine, Trauma & Acute Care

Published Date

2021/12/9

A Cost-Effective 3D Acquisition and Visualization Framework for Cultural Heritage

Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand law. New digital visualization technologies are found to give more excitements, especially to the younger generation as it is proven by multiple studies. Nowadays, museums around the world are currently trying to promote their collections through new multimedia and digital technologies such as 3D modeling, virtual reality (VR), augmented reality (AR), and serious games. However, the difficulty and the resources required to implement such technologies present a real challenge. Through this paper, we propose a 3D acquisition and visualization framework aiming mostly at increasing the value of cultural collections. This framework preserves cost-effectiveness and time constraints while still introducing …

Authors

Hosameldin Osman Ahmed,Abdelhak Belhi,Taha Alfaqheri,Abdelaziz Bouras,Abdul H Sadka,Sebti Foufou

Published Date

2021

Effective Smart Contracts for Supply Chain Contracts

Blockchain is in its way of revolutionizing different sectors with its decentralized peer-to-peer networking. Smart contracts are the piece of software that have written rules to be executed automatically to update the state of the block chain in a systematic way. One of the main use of Smart contract is in Supply Chain management. Supply Chain management deals with lot of legal contracts at a time. Contracts are agreements between two or more parties that define the duties and obligations for execution of any kind of activities. In this research, we are trying to automate the supply chain related contracts by identifying the important entities such as contract type, start date, end date etc., by using Natural Language Processing methods, then convert the contract to smart contract. This provides an efficient template for creation of smart contracts from natural language contracts and thereby offer best smart contract template for a given type of contract in Supply Chain.

Authors

Bajeela Aejas,Abdelaziz Bouras

Published Date

2021

Enterprise Information Systems enhancement: A HyperLedger Fabric based application

Nowadays data analytics and Artificial Intelligence (AI) tools are used at all levels of the extended enterprise, from the shop floor level to run and improve operations, to the strategic process level to make high levels decisions. Failing to provide a unique and fit for all solution, the system providers focus on joining the dots along the digital threads with data continuity in mind. Unfortunately, the existing separate solutions contribute to data overlaps and involve data safety issues. Re-defining the place of the Enterprise Information System components such as Product Lifecycle Management (PLM) and Supply Chain Management (SCM) solutions in a wider digitalization landscape, from product creation to smart factory/Industry 4.0 is the scope of many current works. This includes enhancement in terms of traceability and timely information sharing, addressed through blockchain as digital platforms with features like …

Authors

Abdelaziz Bouras,Houssem Gasmi,Abdelhak Belhi,Assam Hammi,Belaid Aouni

Published Date

2021/6/28

A blockchain-enabled privacy-preserving verifiable query framework for securing cloud-assisted industrial internet of things systems

Advanced Industrial Internet-of-Things (IIoT), such as smart grids, 5G-enabled unmanned aerial vehicles (UAV), and supply chain 4.o, can be used to facilitate smart management. Nevertheless, IIoT systems generate huge amounts of data that need to be outsourced to the cloud for storing and providing real-time search facilities to end-users. Outsourcing IIoT data to a third-party cloud service provider (CSP) introduces several data privacy and integrity issues related to verifying the reliability of users’ queries and aggregated outcomes. In this article, we propose a blockchain-based framework for provisioning a privacy-preserving and verifiable query facility to end-users in IIoT systems. The framework uses blockchain to store IoT data as on-chain data and the cloud to store extensive data (e.g., image) as off-chain data and provisioning search services to users by executing a query in both on-chain and off-chain data …

Authors

Mohammad Saidur Rahman,Ibrahim Khalil,Nour Moustafa,Aditya Pribadi Kalapaaking,Abdelaziz Bouras

Journal

IEEE Transactions on Industrial Informatics

Published Date

2021/8/18

Service based framework of research projects in higher education institutions

This work presents and disseminates the services and infrastructure required to manage research projects quantity and quality in higher education institutions. To achieve this objective, smart management of research offices, their processes and collaborative projects are of paramount importance in order to understand the underlying activities for effective decision making. This approach has been developed in depth considering the lifecycle of grants in a research office. The processes of a research office, its automation, importance of collaborative projects with academia and industry around the globe and their impact on research output have been developed first and then applied on a public higher education institution. The developed framework with its implementation example can be adopted by various research based organizations to efficiently manage and strengthen their research outlook.

Authors

Mariam Al Ali Al-Maadeed,Shahbaz Hussain,Mohammed Al-Salem,Abdelaziz Bouras

Journal

The Journal of Modern Project Management

Published Date

2021

Hybrid missing value imputation algorithms using fuzzy c-means and vaguely quantified rough set

In real cases, missing values tend to contain meaningful information that should be acquired or should be analyzed before the incomplete dataset is used for machine learning tasks. In this work, two algorithms named jointly fuzzy C-Means and vaguely quantified nearest neighbor (VQNN) imputation (JFCM-VQNNI) and jointly fuzzy C-Means and fitted VQNN imputation (JFCM-FVQNNI) have been proposed by considering clustering conception and sufficient extraction of uncertain information. In the proposed JFCM-VQNNI and JFCM-FVQNNI algorithm, the missing value is regarded as a decision feature, and then, the prediction is generated for the objects that contain at least one missing value. Specially, as for JFCM-VQNNI algorithm, indistinguishable matrixes, tolerance relations, and fuzzy membership relations are adopted to identify the potential closest filled values based on corresponding similar objects and …

Authors

Daiwei Li,Haiqing Zhang,Tianrui Li,Abdelaziz Bouras,Xi Yu,Tao Wang

Journal

IEEE Transactions on Fuzzy Systems

Published Date

2021/2/11

Blockchain-based manufacturing supply chain management using hyperledger fabric

Production of goods has reached record numbers in the last decades as it became more efficient and effective than ever before due to the automation and digitalization of the production process. This gave customers more choice and the delivery process became faster and more satisfying. However, supply chain management remains a bottleneck due to the limitations of the supply chain management systems which suffer from poor traceability, product tampering, lack of timely information sharing, and delays. These issues can be addressed by the blockchain as a digital platform with features like immutability, transparency, and decentralization of information. In this paper, we propose a case study for improving the manufacturing supply chain management through a blockchain-based solution. The proposed system would provide a more transparent supply chain with improved product traceability because of the …

Authors

Houssem Gasmi,Abdelhak Belhi,Assam Hammi,Abdelaziz Bouras,Belaid Aouni,Ibrahim Khalil

Published Date

2021/7/11

Product Lifecycle Management Enabling Smart X: 17th IFIP WG 5.1 International Conference, PLM 2020, Rapperswil, Switzerland, July 5–8, 2020, Revised Selected Papers

This book constitutes the refereed post-conference proceedings of the 17th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2020, held in Rapperswil, Switzerland, in July 2020. The conference was held virtually due to the COVID-19 crisis. The 60 revised full papers presented together with 2 technical industrial papers were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: smart factory; digital twins; Internet of Things (IoT, IIoT); analytics in the order fulfillment process; ontologies for interoperability; tools to support early design phases; new product development; business models; circular economy; maturity implementation and adoption; model based systems engineering; artificial intelligence in CAx, MBE, and PLM; building information modelling; and industrial technical contributions.

Authors

Felix Nyffenegger,José Ríos,Louis Rivest,Abdelaziz Bouras

Published Date

2020/11/19

Blockchains: a conceptual assessment from a product lifecycle implementation perspective

PLM systems are heavily distributed collaborative platforms resulting in multiple challenges related to the integrity and reliability of the exchanged information. Such issues are usually difficult to address using traditional software solutions. However, since the introduction of blockchains, such challenges are currently being effectively addressed. On the one hand, traditional PLM systems design philosophy was mainly about centralized proprietary systems that have difficulty to cope with new distributed and open environments imposed by the extensive use of IoT platforms and other Industry 4.0 tools. On the other hand, blockchains address data integrity issues by design, and mitigate some of the trust concerns found in collaborative platforms. Through this paper, we study and evaluate the integration of blockchain technology with PLM systems highlighting the different advantages, challenges, and issues that …

Authors

Abdelhak Belhi,Abdelaziz Bouras,Masood Khan Patel,Belaid Aouni

Published Date

2020

OntoM: An ontological approach for automatic classification

The concept of Ontologies has been used in a wide range of application domains, due to the fact that ontologies provide a useful mean for establishing a formal, shared and collective understanding of the concepts and their underlying relations at a certain domain of interest, which allows for interoperability and information exchange in a formal an understandable way for both humans and machines. In Cultural Heritage (CH) domain, ontologies serve as a fundamental building block for the traceability of the cultural heritage objects, especially with the increasing demand of providing digital formats for cultural objects and make them available for public. In this paper we implement OntoM; an Ontology model that incorporates the relevant concepts of the Cultural Heritage (CH) domain in Qatar. Then, we will use such an ontology to perform inferences about cultural object classifications via two approaches: string …

Authors

Tahani H Abu Musa,Abdelaziz Bouras,Abdelhak Belhi,Houssem Gasmi

Published Date

2020/2/2

Deep learning based identification of DDoS attacks in industrial application

Denial of Service (DoS) attacks are very common type of computer attack in the world of internet today. Automatically detecting such type of DDoS attack packets & dropping them before passing through is the best prevention method. Conventional solution only monitors and provide the feedforward solution instead of the feedback machine-based learning. A Design of Deep neural network has been suggested in this paper. In this approach, high level features are extracted for representation and inference of the dataset. Experiment has been conducted based on the ISCX dataset for year 2017, 2018 and CICDDoS2019 and program has been developed in Matlab R17b using Wireshark.

Authors

Akhilesh Bhati,Abdelaziz Bouras,Uvais Ahmed Qidwai,Abdelhak Belhi

Published Date

2020/7/27

AI-powered Motion Interaction for 3D Cultural Heritage

Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand law. New digital visualization technologies are found to give more excitements, especially to the younger generation as it is proven by multiple studies. Nowadays, museums around the world are currently trying to promote their collections through new multimedia and digital technologies such as 3D modeling, Virtual Reality (VR), Augmented Reality (AR), serious games, etc. However, the difficulty and the resources required to implement such technologies present a real challenge. Through this poster, we propose a 3D acquisition and visualization framework aiming mostly at increasing the value of cultural collections. This framework preserves cost-effectiveness and time constraints while still introducing new ways of visualization and interaction with high-quality 3D models of cultural objects. Our framework leverages a new acquisition setup to simplify the visual capturing process by using consumer-level hardware. The acquired images are enhanced using frame interpolation and super-resolution. A photogrammetry tool is then used to generate the asset 3D model. This model is displayed in a screen attached to the leap motion controller which allows hand interaction without having to deal with sophisticated controllers or headgear allowing almost natural interaction.

Authors

Abdelhak Belhi,Abdelaziz Bouras

Published Date

2020

Cyber physical systems and smart homes in healthcare: Current state and challenges

Cyber Physical Systems is an emerging paradigm which has gained particular attention in research and development. CPS has transformed the way we interact with the physical world by introducing smart communication between the physical world and its cyber components. As the requirements of today are increasing, a diverse range of applications has made its way in the healthcare domain. This paper provides a survey of noteworthy applications in the healthcare area, particularly smart homes, including state-of-the-art applications for medication intake systems and medical status monitoring. The success of every system is hindered by challenges that need to be addressed. Some of these challenges for CPS include security, patient information privacy, heterogeneous data management, real time patient monitoring, interoperability between different systems, system usability and energy consumption.

Authors

Sara Amin,Tooba Salahuddin,Abdelaziz Bouras

Published Date

2020/2/2

The implementation of a crop diseases APP based on deep transfer learning

Classifying the severity of crop diseases is the staple-basic element of the plant pathology for making disease prevent and control strategies. The diagnosis of disease needs timeliness and accuracy. Thanks to the development and popularity of smart phones and mobile networks, this makes possibly to develop mobile applications that can be widely accepted by users in the agricultural community. This paper provides a system that can detect the severity of crop diseases automatically and intelligently through taking photos. The development of this mobile app is based on deep transfer learning that we proposed an improved method with nearly 92% accuracy based on ResNet 50. The significantly high success rate makes the model a very useful advisory or warning tool. This project provides a new idea and solution for the detection of crop diseases in agriculture.

Authors

Mengji Yang,Daiwei Li,Minquan Chen,Abdelaziz Bouras,Yiqian Tang,Xi Yu

Published Date

2020/5/28

Machine learning and digital heritage: the CEPROQHA project perspective

Through this paper, we aim at investigating the impact of artificial intelligence technologies on cultural heritage promotion and long-term preservation in terms of digitization effectiveness, attractiveness of the assets, and value empowering. Digital tools have been validated to yield sustainable and yet effective preservation for multiple types of content. For cultural data, however, there are multiple challenges in order to achieve sustainable preservation using these digital tools due to the specificities and the high-quality requirements imposed by cultural institutions. With the rise of machine learning and data science technologies, many researchers and heritage organizations are nowadays searching for techniques and methods to value and increase the reliability of cultural heritage digitization through machine learning. The present study investigates some of these initiatives highlighting their added value and …

Authors

Abdelhak Belhi,Houssem Gasmi,Abdelaziz Bouras,Taha Alfaqheri,Akuha Solomon Aondoakaa,Abdul H Sadka,Sebti Foufou

Published Date

2020

An improvement of support vector machine imputation algorithm based on multiple iteration and grid search strategies

Data missing is a vitally important issue that influences the classification results in medical field. This paper proposes an improved support vector machine (SVM) imputation algorithm by using strategies of pre-imputation, multiple iteration and grid search (IG-SVMI). Based on the experimental performance, nine UCI datasets and two real datasets are used to compare the proposed algorithm with four existing imputation algorithms (RFI, KNNI, CCMVI and orthogonal coding SVMI). The datasets are considered into two types of originally containing missing value and randomly auto-generating missing of complete dataset. Classification accuracy and NRMSE are used as parameters to judge the efficient of the proposed IG-SVMI algorithm. The experiments have shown that the proposed IG-SVMI algorithm can achieve better results than the benchmark approaches.

Authors

Jie Wang,Daiwei Li,Haiqing Zhang,Xi Yu,Aicha Sekhari,Yacine Ouzrout,Abdelaziz Bouras

Published Date

2020/2/2

Covid-19: Challenges & Perspectives

A Virtual Conference to shed light on the QU's prominent trends and research efforts addressing Corona virus.

Authors

Talal Al-Emadi,Abdelaziz Bouras,Patrick Tang,Fatiha Benslimane,Abdoulaye Diop,Hanan Abdul Rahim,Tamer Khattab,Said Elbanna,Aboubakr Ali

Published Date

2020/4/19

Design Principles for Migrating from Traditional Systems to Blockchain Systems

Blockchain is a distributed database technology that builds on a tamper-proof list of time-stamped transaction records. The data structure of blockchain is a chained list of blocks [1]. Each block contains a hash of the previous block’s representation, thus creating the chain. As a result, historical transactions in the blockchain cannot be deleted or altered without invalidating the chain of hashes. With a combination of computational constraints and incentive schemes (eg Proof-of-Work (PoW) in Bitcoin [2]) for block creation, the tampering and revision of the information in the blockchain can be prevented.Blockchain also provides a general-purpose programmable interface. Programs can be deployed and run on a blockchain; such programs are called smart contracts [3]. The result of a smart-contract invocation is stored in public data storage. Smart contracts can express triggers, conditions, and business logic to enable …

Authors

Mohammad Saidur Rahman,Ibrahim Khalil,Abdelaziz Bouras,Mohammed Atiquzzaman

Published Date

2020/1

Product Lifecycle Management in the Digital Twin Era: 16th IFIP WG 5.1 International Conference, PLM 2019, Moscow, Russia, July 8–12, 2019, Revised Selected Papers

This book constitutes the refereed post-conference proceedings of the 16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019, held in Moscow, Russia, in July 2019. The 38 revised full papers presented were carefully reviewed and selected from 63 submissions. The papers are organized in the following topical sections: 3D modelling and data structures; PLM maturity and industry 4.0; ontologies and semantics; PLM and conceptual design; knowledge and change management; IoT and PLM; integrating manufacturing realities; and integration of in-service and operation.

Authors

Clement Fortin,Louis Rivest,Alain Bernard,Abdelaziz Bouras

Published Date

2020/2/28

Investigating low-delay deep learning-based cultural image reconstruction

Numerous cultural assets host a great historical and moral value, but due to their degradation, this value is heavily affected as their attractiveness is lost. One of the solutions that most heritage organizations and museums currently choose is to leverage the knowledge of art and history experts in addition to curators to recover and restore the damaged assets. This process is labor-intensive, expensive and more often results in just an assumption over the damaged or missing region. In this work, we tackle the issue of completing missing regions in artwork through advanced deep learning and image reconstruction (inpainting) techniques. Following our analysis of different image completion and reconstruction approaches, we noticed that these methods suffer from various limitations such as lengthy processing times and hard generalization when trained with multiple visual contexts. Most of the existing learning …

Authors

Abdelhak Belhi,Abdulaziz Khalid Al-Ali,Abdelaziz Bouras,Sebti Foufou,Xi Yu,Haiqing Zhang

Journal

Journal of Real-Time Image Processing

Published Date

2020/12

Formalizing dynamic behaviors of smart contract workflow in smart healthcare supply chain

We present a formal model for smart contract workflow using Colored Petri-Net in the context of a blockchain-based healthcare supply chain in this paper. Ensuring traceability of products is a crucial issue in a smart healthcare supply chain. Blockchain and smart contracts are two enabling technologies that ensure the traceability of products and prevent data tampering in the smart healthcare supply chain. In a blockchain-based supply chain, a workflow of smart contracts needs to created and executed based on the input data. The selection of smart contracts in the workflow is data-driven and dynamic. Hence, it is necessary to verify the correctness of the dynamic execution of smart contracts. In this paper, we develop a Colored Petri-Net based formalism to verify the correctness of dynamic behaviors of the smart contract workflow. We conduct experiments to evaluate the performance of our proposed model.

Authors

Mohammad Saidur Rahman,Ibrahim Khalil,Abdelaziz Bouras

Published Date

2020

CNN Features vs Classical Features for Largescale Cultural Image Retrieval

Modern applications for cultural content enrichment and management require low delay image retrieval methods in large databases. Classical image retrieval methods are suitable for certain applications but are also known to lack the ability of generalization and their use for low delay applications for retrieval tasks is not investigated for the context of cultural heritage. As a potential improvement, we propose a new approach for large scale image retrieval that uses a pre-trained CNN as a global features extractor and a clustering model trained on these features to regroup similarly looking images. For retrieval, this model quickly identifies the closest cluster and then, the matching is only carried out for the images of the selected cluster. As a result, our approach does not require indexation and the preliminary results show that it is suitable for real-time and low delay applications as in the matching step, no heavy …

Authors

Abdelhak Belhi,Abdelaziz Bouras

Published Date

2020/2/2

See List of Professors in Abdelaziz Bouras University(Qatar University)

Abdelaziz Bouras FAQs

What is Abdelaziz Bouras's h-index at Qatar University?

The h-index of Abdelaziz Bouras has been 26 since 2020 and 30 in total.

What are Abdelaziz Bouras's top articles?

The articles with the titles of

BIM EDUCATION FOR QATAR’S CONSTRUCTION INDUSTRY: A LIFECYCLE VISION

Stacking-based multi-objective ensemble framework for prediction of hypertension

Product Lifecycle Management. PLM in Transition Times: The Place of Humans and Transformative Technologies: 19th IFIP WG 5.1 International Conference, PLM 2022, Grenoble …

A Prediction Framework for Lifestyle-Related Disease Prediction Using Healthcare Data

Toward an NLP Approach for Transforming Paper Contracts into Smart Contracts

A review on missing values for main challenges and methods

An integrated framework for the interaction and 3D visualization of cultural heritage

A machine learning framework for enhancing digital experiences in cultural heritage

...

are the top articles of Abdelaziz Bouras at Qatar University.

What are Abdelaziz Bouras's research interests?

The research interests of Abdelaziz Bouras are: Information Systems, PLM, Product lifecycle management, Ontology Based Engineering, Blockchains for Supply Chains

What is Abdelaziz Bouras's total number of citations?

Abdelaziz Bouras has 5,464 citations in total.

What are the co-authors of Abdelaziz Bouras?

The co-authors of Abdelaziz Bouras are Professor Zahir Tari, Dimitris Kiritsis, Sergio Terzi, Eswaran Subrahmanian, Sebti Foufou, PhD, Nickolas S. Sapidis.

    Co-Authors

    H-index: 46
    Professor Zahir Tari

    Professor Zahir Tari

    RMIT University

    H-index: 46
    Dimitris Kiritsis

    Dimitris Kiritsis

    École Polytechnique Fédérale de Lausanne

    H-index: 40
    Sergio Terzi

    Sergio Terzi

    Politecnico di Milano

    H-index: 38
    Eswaran Subrahmanian

    Eswaran Subrahmanian

    Carnegie Mellon University

    H-index: 29
    Sebti Foufou, PhD

    Sebti Foufou, PhD

    Université de Bourgogne

    H-index: 23
    Nickolas S. Sapidis

    Nickolas S. Sapidis

    University of Western Macedonia

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