Article
Computer Science, Information Systems
Michal Krol, Alberto Sonnino, Mustafa Al-Bassam, Argyrios G. Tasiopoulos, Etienne Riviere, Ioannis Psaras
Summary: As cryptographic tokens and altcoins are increasingly being used as utility tokens, the concept of useful work consensus protocols becomes more crucial. Proof-of-Prestige (PoP) is a reward system that can reliably incentivize decentralized workers while keeping the system free for end-users. It is resistant to Sybil and collusion attacks, and can be applied to a wide range of unverifiable tasks.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Hamid Azimy, Ali A. Ghorbani, Ebrahim Bagheri
Summary: This paper analyzes the profitability of selfish mining over time and proposes an alternative difficulty adjustment algorithm that discourages selfish mining while allowing the Bitcoin network to remain scalable.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Milan Todorovic, Luka Matijevic, Dusan Ramljak, Tatjana Davidovic, Dragan Urosevic, Tatjana Jaksic Kruger, Dorde Jovanovic
Summary: This paper proposes a combinatorial optimization consensus protocol (COCP) based on the proof-of-useful-work (PoUW) concept for addressing security, privacy, consistency, and energy consumption issues in blockchain maintenance. The COCP utilizes heuristic methods to tackle complex combinatorial optimization problems and efficiently utilizes computing resources. It offers potential practical impacts and power consumption savings.
Article
Computer Science, Interdisciplinary Applications
Jing Fan, Hui Shi
Summary: The article describes the daily work issues of nursing assistants in hospitals, transforming it into a supply chain scheduling problem with the objective of minimizing the total flowtime of patients. The study shows that the problem is NP-hard in the strong sense, and presents an approximation algorithm with a performance ratio of 2.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2021)
Article
Computer Science, Theory & Methods
Ivan Malakhov, Andrea Marin, Sabina Rossi
Summary: In blockchain networks driven by Proof of Work, clients pay fees to control the transaction confirmation speed. Determining the optimal fee to satisfy delay requirements is still a challenge, and current methods rely on historical data. This study proposes a queueing model based on transient analysis to address this problem. By applying the model to the Bitcoin blockchain and analyzing transaction characteristics, insights on the relationship between fees and confirmation time are obtained.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Alireza Goli
Summary: Blockchain technology is a new financial concept that speeds up supply chains and improves the accuracy and speed of financial transactions in international trades. A comprehensive framework has been proposed to design a blockchain-enabled closed-loop supply chain, taking into account the role of the product portfolio. The results show that by optimizing the proposed mathematical model, the financial indexes of the supply chain, especially the change in equity, can be significantly improved. Compared to the integrated portfolio-supply chain model, this framework has a lower error rate and reduced lost revenue.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Food Science & Technology
Hao Song, Wenfei Ge, Pan Gao, Wei Xu
Summary: In this research, a jujube supply-chain management framework based on blockchain is proposed to address the issues of opaque information flow, unreliable traceability, and lack of bargaining power in traditional jujube supply-chain management. By optimizing the blockchain network topology architecture and data storage cost, this research not only solves the traceability of jujube, but also fills the gap in previous research on the traceability framework. Furthermore, transactions are innovatively divided into common transactions and private transactions, enhancing the bargaining power of jujube farmers. The effectiveness and feasibility of the framework are verified through benchmark tests.
Article
Business
Kangning Zheng, Leven J. Zheng, Jeffrey Gauthier, Linyu Zhou, Yinge Xu, Abhishek Behl, Justin Zuopeng Zhang
Summary: Credit data barriers exist in the supply chain financial credit system, and emerging blockchain technology can help improve credit-reporting ability. This study proposes a blockchain-based model that addresses the problem of large-scale credit investigation data and privacy protection through a consensus mechanism. The model helps optimize the supply chain financial credit system.
JOURNAL OF INNOVATION & KNOWLEDGE
(2022)
Article
Management
Jaeyoung Oh, Yunsik Choi, Joonhwan In
Summary: This paper aims to develop a conceptual framework that clarifies the multifaceted features and roles of blockchain technology in designing blockchain-enabled supply chains. The proposed framework offers guidance on how to incorporate blockchain technology into supply chain design.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Indra Eluubek Kyzy, Huaming Song, Ahmadreza Vajdi, Yongli Wang, Junlong Zhou
Summary: The trading aspect of agricultural supply chain system is complex, and blockchain technology has proven effective in maximizing profits and establishing consortiums. However, successful consortiums also need to address trustability, scalability, and share amount assignment, which have motivated the need for a new design of blockchain technology. Experimental results and analysis show the effectiveness and accuracy of the proposed design.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Keke Gai, Yue Zhang, Meikang Qiu, Bhavani Thuraisingham
Summary: This study proposes a blockchain-based digital twin solution for reengineering the supply chain management system, enhancing its digitization and intelligence. Through a strong-weak consensus mode and intelligent switch-based algorithms, energy and time savings are achieved. Experimental results show that our algorithm has lower time and energy consumption in consensus compared to other baseline algorithms.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Management
Rodney J. Garratt, Maarten R. C. van Oordt
Summary: This study assesses how the cost structure of cryptocurrency mining affects miners' response to exchange rate fluctuations and the immutability of cryptocurrency ledgers. The findings suggest that mining power in currencies relying on specialized hardware, like Bitcoin, is less responsive to adverse exchange rate shocks compared to other currencies, which helps protect against double-spending attacks. However, if mining equipment can be transferred to another cryptocurrency, the results may change. For smaller currencies with low exchange rate correlation, transferability weakens the protection provided by fixed costs. These results challenge doomsday predictions for Bitcoin and other cryptocurrencies with declining block rewards.
MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Information Systems
Yash Madhwal, Yury Yanovich, S. Balachander, K. Harshini Poojaa, R. Saranya, B. Subashini
Summary: This article presents a Proof of Concept that integrates IoT devices with blockchain technology to address challenges in traditional supply chain systems. By enabling IoT devices to autonomously sign transactions to the blockchain, the need for external wallets is eliminated, providing scalability, efficiency, and real-time responsiveness benefits.
Article
Computer Science, Interdisciplinary Applications
Valeri Natanelov, Shoufeng Cao, Marcus Foth, Uwe Dulleck
Summary: This paper explores and demonstrates the potential of blockchain and smart contracts for supply chain finance in the context of cross-border beef supply chains from Australia to China. The study uses the Agents Events Data (AED) process mapping method to improve supply chain processes and traditional SCF models. The findings highlight how blockchain technology and smart contracts can mitigate financial risks and transform credit financing. Additionally, the paper proposes the group buying business model as a promising approach for whole-of-supply-chain finance and showcases the utility of the AED process mapping method for future research.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Business
Sharfuddin Ahmed Khan, Muhammad Shujaat Mubarik, Simonov Kusi-Sarpong, Himanshu Gupta, Syed Imran Zaman, Mobashar Mubarik
Summary: The emergence of blockchain technologies is transforming the management of traditional supply chains by enhancing traceability, accountability, and sustainability. However, the direct impact of blockchain technologies on supply chain sustainability is not significant, with the improvement in sustainability being largely attributed to supply chain integration and mapping facilitated by blockchain.
BUSINESS STRATEGY AND THE ENVIRONMENT
(2022)
Article
Management
Amro M. El-Adle, Ahmed Ghoniem, Mohamed Haouari
Summary: This study investigates a single-vehicle parcel delivery problem where customers can be served by either the vehicle or a portable companion drone. The problem is modeled as a Traveling Salesman Problem with Drone and formulated as a 0-1 mixed-integer program to minimize the joint tour duration, with enhancements made to improve tractability.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Economics
Hesamoddin Tahami, Ghaith Rabadi, Mohamed Haouari
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2020)
Article
Computer Science, Interdisciplinary Applications
Monzure-Khoda Kazi, Fadwa Eljack, Mahmoud M. El-Halwagi, Mohamed Haouri
Summary: This study develops a strategic framework for the design of a hydrogen supply chain network (HSCN) using mixed integer linear programming, focusing on industrial decarbonization and multi-sectors integration through a green hydrogen economy. The model demonstrated applicability in a base case Eco-industrial city and can conduct detailed techno-economic-environmental analysis for various scenarios based on net present value.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Mohamed Haouari, Mariem Mhiri
Summary: This paper presents an approach for predicting the number of deaths from COVID-19 by modeling the number of infected cases and inferring the number of deaths as well as active cases. The proposed method is empirically assessed on official data from Qatar, showing good accuracy in predicting the number of deaths.
SCIENTIFIC REPORTS
(2021)
Review
Computer Science, Interdisciplinary Applications
Mazen El-Masri, Eiman Mutwali Abdelmageed Hussain
Summary: The study examines the evolving role of blockchain as a platform for securing IoT ecosystems, emphasizing its applicability and effectiveness in addressing IoT security threats. A two-dimensional framework is used to categorize the threats and countermeasures, highlighting the significance of blockchain features in enhancing IoT security.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Mohamed Ben Ahmed, Maryia Hryhoryeva, Lars Magnus Hvattum, Mohamed Haouari
Summary: This study addresses an integrated airline scheduling problem by combining fleet assignment, aircraft routing, and crew pairing. The proposed approach emphasizes robustness by restricting tight connections and increasing the number of connections where crews follow the aircraft, showing an average deviation of at most 0.6% from a conservative bound in real instances.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Energy & Fuels
Dana M. Alghool, Tarek Y. ElMekkawy, Mohamed Haouari, Adel Elomri
Summary: This study investigates the optimal design of solar electric cooling systems and compares their cost-effectiveness with conventional and solar thermal cooling systems. The findings show that solar electric cooling systems cover 42% of chiller electricity demand and achieve approximately 5.5% and 55% cost savings compared with conventional and solar thermal systems, respectively. Sensitivity analysis indicates that the efficiency of photovoltaic panels has the greatest impact on the annual cost of solar electric cooling systems, making them the most economical option.
ENERGY SCIENCE & ENGINEERING
(2022)
Article
Management
Amro M. El-Adle, Ahmed Ghoniem, Mohamed Haouari
Summary: We investigate a last-mile delivery problem where a firm determines customers to be prioritized for drone delivery while the rest are delivered by vehicle. We develop a mixed-integer program to obtain optimal solutions for instances with up to 40 customers over a 6-day horizon. Additionally, we propose a heuristic method based on the mixed-integer program to effectively prioritize customers for drone delivery.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Management
Mariem Mhiri, Karim Al-Yafi, Benjamin Legros, Oualid Jouini, Mohamed Haouari
Summary: This paper addresses two interrelated issues in the hinterland portion of the maritime container supply chain: reducing empty container movement and empty truck trips. The authors propose implementing empty container flow optimization through a blockchain utilizing the proof-of-useful-work concept. Anonymous miners compete to solve the NP-hard container truck routing problem and optimally match consignees and shippers, turning the blockchain into an optimization engine for the container supply chain.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Multidisciplinary Sciences
Nayla Ahmad Al-Thani, Tareq Al-Ansari, Mohamed Haouari
Summary: This research evaluates the sustainability of eight different PET waste bottle treatment methods using a holistic multi-criteria decision-making approach. The study finds that closed-loop recycling is the optimal method for PET waste bottle treatment.
Article
Computer Science, Interdisciplinary Applications
Jean-Francois Cote, Mohamed Haouari, Manuel Iori
Summary: In this paper, we address the two-dimensional bin packing problem, a challenging task in optimization, with a combinatorial Benders decomposition. By enriching the basic scheme with various techniques and algorithms, we were able to significantly improve upon previous algorithms in the literature and solve a number of challenging instances for the first time.
INFORMS JOURNAL ON COMPUTING
(2021)
Article
Ethics
Karma Sherif, Omolola Jewesimi, Mazen El-Masri
Summary: This study analyzed interview data from two organizations in the USA and Qatar within the oil and gas sector, finding that national and corporate cultures influence employees' acceptance of monitoring. In Qatar, EPM is better accepted as a way to enforce standardization and adapt to corporate culture, while in the USA, organizational mechanisms shift perceptions of EPM toward obtaining feedback.
JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY
(2021)
Article
Communication
Mazen El-Masri, Allan Ramsay, Hanady Mansour Ahmed, Tariq Ahmad
Summary: The study analyzes the emotional responses of Qatar residents during a blockade enforced by neighboring countries, finding that they used positive emotions like love and optimism to cope with adversities and accompanying emotions of fear and anger. Furthermore, their adaptive resilient capacities gradually strengthened during the nine months of blockade, supporting the renowned theory of positive emotions using an advanced methodology and a large-scale dataset.
INFORMATION COMMUNICATION & SOCIETY
(2021)
Article
Computer Science, Information Systems
Sang-Bing Tsai, Xusen Cheng, Yanwu Yang, Jason Xiong, Alex Zarifis
Summary: This article structurally concludes the methods proposed and evidenced to develop digital entrepreneurship from a socio-technical perspective. The technology itself and the process of utilization should be carefully considered. From a social perspective, fulfilling the needs of customers in social interaction and nurturing characteristics and social skills for the digital work environment are crucial.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xiaochang Fang, Hongchen Wu, Jing Jing, Yihong Meng, Bing Yu, Hongzhu Yu, Huaxiang Zhang
Summary: This study proposes a novel fake news detection framework, utilizing news semantic environment perception (NSEP) to identify fake news content. The framework consists of steps such as dividing the semantic environment into macro and micro levels, applying graph convolutional networks, and utilizing multihead attention. Empirical experiments show that the NSEP framework achieves high accuracy in detecting Chinese fake news, outperforming other baseline methods and highlighting the importance of both micro and macro semantic environments in early detection of fake news.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xudong Sun, Alladoumbaye Ngueilbaye, Kaijing Luo, Yongda Cai, Dingming Wu, Joshua Zhexue Huang
Summary: This paper proposes a scalable distributed frequent itemset mining (ScaDistFIM) algorithm to address the data scalability and flexibility issues in basket analysis in the big data era. Experiment results demonstrate that the ScaDistFIM algorithm is more efficient compared to the Spark FP-Growth algorithm.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Boxu Guan, Xinhua Zhu, Shangbo Yuan
Summary: This paper aims to improve the interpretability of machine reading comprehension models by utilizing the pre-trained T5 model for evidence inference. They propose an interpretable reading comprehension model based on T5, which is trained on a more accurate evidence corpus and can infer precise interpretations for answers. Experimental results show that their model outperforms the baseline BERT model on the SQuAD1.1 task.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Yanhao Wang, Baohua Zhang, Weikang Liu, Jiahao Cai, Huaping Zhang
Summary: In this study, we propose a data augmentation-based semantic text matching model called STMAP. By using Gaussian noise and noise mask signal for data augmentation, as well as employing an adaptive optimization network for training target optimization, our model achieves good performance in few-shot learning and semantic deviation problems.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Jiahao Yang, Shuo Feng, Wenkai Zhang, Ming Zhang, Jun Zhou, Pengyuan Zhang
Summary: To pursue profit from stock markets, researchers utilize deep learning methods to forecast asset price movements. However, there are two issues in current research, the discrepancy between forecasting results and profits, and heavy reliance on prior knowledge. To address these issues, researchers propose a novel optimization objective and modeling method, and conduct experiments to validate their approach.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Heng Zhang, Chengzhi Zhang, Yuzhuo Wang
Summary: This study provides an accurate analysis of technology development in the field of Natural Language Processing (NLP) from an entity-centric perspective. The findings indicate an increase in the average number of entities per paper, with pre-trained language models becoming mainstream and the impact of Wikipedia dataset and BLEU metric continuing to rise. There has been a surge in popularity for new high-impact technologies in recent years, with researchers accepting them at an unprecedented speed.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Davide Buscaldi, Danilo Dessi, Enrico Motta, Marco Murgia, Francesco Osborne, Diego Reforgiato Recupero
Summary: In scientific papers, citing other articles is a common practice to support claims and provide evidence. This paper proposes two automatic methods using Transformer models to address citation placement, and achieves significant improvements in experiments.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Baozhuang Niu, Lingfeng Wang, Xinhu Yu, Beibei Feng
Summary: This paper examines whether the incumbent brand should adopt digital technology to forecast demand and adjust order decisions in the face of soaring demand for medical supply caused by frequent outbreaks of regional COVID-19 epidemic. The study finds that digital transformation can lead to a triple-win situation among the incumbent brand, social welfare, and consumer surplus, as well as bring benefits to the manufacturer. Furthermore, the research provides insights for firms' digital entrepreneurship decisions through theoretical optimization and data processing/policy simulation.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xueyang Qin, Lishang Li, Fei Hao, Meiling Ge, Guangyao Pang
Summary: Image-text retrieval is important in connecting vision and language. This paper proposes a method that utilizes prior knowledge to enhance feature representations and optimize network training for better retrieval results.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Review
Computer Science, Information Systems
Gang Ren, Lei Diao, Fanjia Guo, Taeho Hong
Summary: This paper proposes a novel approach for predicting the helpfulness of reviews by utilizing both textual and image features. The proposed method considers the correlation between features through self-attention and co-attention mechanisms, and fuses multi-modal features for prediction. Experimental results demonstrate the superior performance of the proposed method compared to benchmark methods.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Zhongquan Jian, Jiajian Li, Qingqiang Wu, Junfeng Yao
Summary: Aspect-Level Sentiment Classification (ALSC) is a crucial challenge in Natural Language Processing (NLP). Most existing methods fail to consider the correlations between different instances, leading to a lack of global viewpoint. To address this issue, we propose a Retrieval Contrastive Learning (RCL) framework that extracts intrinsic knowledge across instances for improved instance representation. Experimental results demonstrate that training ALSC models with RCL leads to substantial performance improvements.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Ying Hu, Yanping Chen, Ruizhang Huang, Yongbin Qin, Qinghua Zheng
Summary: Biomedical relation extraction aims to extract the interactive relations between biomedical entities in a sentence. This study proposes a hierarchical convolutional model to address the semantic overlapping and data imbalance problems. The model encodes both local contextual features and global semantic dependencies, enhancing the discriminability of the neural network for biomedical relation extraction.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Zhou Yang, Yucai Pang, Xuehong Li, Qian Li, Shihong Wei, Rong Wang, Yunpeng Xiao
Summary: This study proposes a rumor detection model based on topic audiolization, which transforms the topic space into audio-like signals. Experimental results show that the model achieves significant performance improvements in rumor identification.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Alistair Moffat
Summary: This paper proposes the buying power metric for assessing the quality of product rankings on e-commerce sites. It discusses the relationship between the buying power metric and user reactions, and introduces an alternative product ranking effectiveness metric.
INFORMATION PROCESSING & MANAGEMENT
(2024)
