Article
Computer Science, Information Systems
Izzat Alsmadi, Zyad Dwekat, Ricardo Cantu, Bilal Al-Ahmad
Summary: The development of the Internet of Things has allowed better connectivity with devices and environments, but also poses security risks. The network security concerns for Industrial Control Systems have been highlighted, with specific ports identified as more vulnerable to attacks.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Sofia Mulero-Palencia, Victor Monzon Baeza
Summary: This study identifies and evaluates vulnerabilities specific to smart buildings using the Shodan tool and introduces an innovative assessment approach. The research highlights primary security risks in smart building systems and proposes targeted measures to mitigate potential impacts. Additionally, an evaluation methodology is proposed to measure the effects of vulnerabilities on system integrity, availability, and scope. The framework presented in this study strengthens the security of smart buildings by addressing insecure configurations, deployment inadequacies, and suboptimal cybersecurity practices.
Article
Communication
Steven Gonzalez Monserrate
Summary: Based on ethnographic research in data centers, this article introduces the concept of thermotemporalities to illustrate how time, temperature, and expertise converge in novel formations. By examining the practices and pronouncements of data center operators, the study reveals that uptime (cold) and downtime (hot) are performative genres rather than discrete referents.
NEW MEDIA & SOCIETY
(2023)
Article
Computer Science, Theory & Methods
Kjell Jorgen Hole
Summary: The article discusses the importance of designing and operating socio-technical systems with antifragility in mind to prevent downtime. It emphasizes the principles of separate processes, asynchronous communication, and injecting artificial failures into the production system to detect vulnerabilities and adapt to changes in the system and its environment. By following these design and operational principles, incidents can be minimized and uptime can be maintained at a high level.
Article
Construction & Building Technology
Mirsalar Kamari, Youngjib Ham
Summary: The study demonstrates the potential for robust volumetric measurements on point cloud models using deep learning to automatically detect and segment target objects, mapping semantic values for 3D segmentation. Case studies on real-world material piles show promise in enhancing vision-based measurements and supporting decision-making for material management in jobsites.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Computer Science, Information Systems
Jorge Reyes, Walter Fuertes, Paco Arevalo, Mayra Macas
Summary: This research aims to design and implement a prioritization model for detecting vulnerabilities based on their network environment variables and characteristics, utilizing a mathematical model algorithm to calculate the risk factor for improved prioritization efficiency.
Article
Business
Sateesh Shet, Tanuj Poddar, Fosso Wamba Samuel, Yogesh K. Dwivedi
Summary: This study examines the application and challenges of HR Analytics in organizations, presents a framework of factors impacting the adoption of HRA, and identifies key aspects and sub-dimensions crucial for successful implementation of HRA.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Energy & Fuels
A. A. Alakeely, R. N. Horne
Summary: Comparing the Gilbert correlation with Deep Learning algorithms for liquid flow prediction, it was found that DL methods can alleviate some issues and provide a novel approach for forecasting well liquid and multiphase restricted flow rates.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Review
Mathematics
Shiyu Liu, Ou Liu, Junyang Chen
Summary: This paper reviews the latest techniques and applications of business analytics based on existing literature, and presents the current challenges faced by business analytics and open research directions that need further consideration.
Article
Operations Research & Management Science
Dursun Delen, Hamed M. Zolbanin, Durand Crosby, David Wright
Summary: Despite the promises of analytics, the complexity and multidisciplinarity of the field can sometimes hinder its efficacy, especially when dealing with human behavior and social interactions. Drug courts offer an alternative to traditional criminal courts by focusing on therapeutic justice to rehabilitate offenders and improve social outcomes. Developing a comprehensive analytics model to accurately predict the success of participants in drug court programs can help authorities make more effective and efficient decisions to manage resources and improve outcomes.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Multidisciplinary Sciences
Tuomas Takko, Kunal Bhattacharya, Martti Lehto, Pertti Jalasvirta, Aapo Cederberg, Kimmo Kaski
Summary: This article presents and implements a novel knowledge graph and knowledge mining framework for extracting relevant information from incidents in the cyber domain. The framework generates graphs of organizations, countries, industries, products, and attackers using machine learning and estimates the incidence of cyberattacks within a given configuration using the extracted knowledge graph. The methods are tested using publicly available collections of real cyber-incident reports, showing accurate knowledge extraction and correlation with actual attack records.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Sambit Praharaj, Maren Scheffel, Marcel Schmitz, Marcus Specht, Hendrik Drachsler
Summary: Collaboration is essential in the 21st Century, and face-to-face collaboration analytics have seen advancements with sensor technology. Previous studies focused on how group members interact rather than what they discuss, but this research aims to automatically analyze the richness and connections within conversations.
Article
Chemistry, Multidisciplinary
Naif Radi Aljohani
Summary: This paper aims to explore the difference between manually assigned research labels and automatically extracted keywords for identifying specialist Learning Analytics researchers. Through text mining analysis of 4732 publications and 1236 authors, it was found that 446 authors were specialists, 643 were occasional researchers, and 90 were interested researchers in the field. The most interesting finding was the identification of 10 early career researchers independent of their Google Scholar citation count using the proposed methodology.
APPLIED SCIENCES-BASEL
(2023)
Review
Clinical Neurology
Tomaz Vrtovec, Bulat Ibragimov
Summary: The study summarizes and critically evaluates the existing studies of spinopelvic measurements of sagittal balance that are based on deep learning (DL). The results show that the application of complex DL architectures improves the measurement accuracy of spinopelvic parameters, with excellent performance against manual measurements. However, future methods should focus on multi-institution and multi-observer analyses, as well as uncertainty estimation and error handling implementations.
EUROPEAN SPINE JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Lin Zhu, Yinfeng Zhao, Yi Cui, Shutang You, Wenpeng Yu, Shengyuan Liu, He Yin, Chang Chen, Yuru Wu, Wei Qiu, Mirka Mandich, Hongyu Li, Adedasola Ademola, Chengwen Zhang, Chujie Zeng, Xinlan Jia, Weikang Wang, Haoyu Yuan, Huaiguang Jiang, Jin Tan, Yilu Liu
Summary: This study provides an overview of the latest progress of FNET/GridEye, including upgrades to sensors, communication, and data servers, as well as the introduction of AI-based advanced applications.
Article
Computer Science, Software Engineering
Wallace Anacleto Pinheiro, Geraldo Xexeo, Jano Moreira de Souza, Ana Barbara Sapienza Pinheiro
INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING
(2020)
Article
Computer Science, Information Systems
Huaming Wu, Ziru Zhang, Chang Guan, Katinka Wolter, Minxian Xu
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Information Systems
Huaming Wu, Katinka Wolter, Pengfei Jiao, Yingjun Deng, Yubin Zhao, Minxian Xu
Summary: This article explores how to achieve secure task offloading collaboration between edge computing and cloud computing using blockchain. By combining MEC and MCC, a blockchain-enabled IoT-Edge-Cloud computing architecture is proposed, providing faster computing services and stronger computational power while minimizing energy consumption and task response time.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Theory & Methods
Xuyang Ma, Du Xu, Katinka Wolter
Summary: This paper proposes a distributed Feedback-based Combinatorial Multi-unit Double Auction mechanism backed by blockchain to establish a cloud resource market that not only produces high social welfare but also motivates participants to provide high-quality service.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Francois Boechat, Gabriel Ribas, Lucas Senos, Miguel Bicudo, Mateus Schulz Nogueira, Leandro Pfleger de Aguiar, Daniel Sadoc Menasche
Summary: The Common Vulnerability Scoring System score is the standard for evaluating the risk of software vulnerabilities and includes three temporal components: exploitability, remediation level, and report confidence. The discussion focuses on inferring report confidence from the first two components and highlights practical and conceptual issues in the usage of temporal risk scores.
IEEE SECURITY & PRIVACY
(2021)
Article
Computer Science, Theory & Methods
Tianhui Meng, Yubin Zhao, Katinka Wolter, Cheng-Zhong Xu
Summary: This article introduces a queueing network-based method for analyzing consistency properties of consortium blockchain protocols and applies it to the Hyperledger Fabric system. Using this method, the security properties of the ordering mechanism and the impact of delaying endorsement messages in consortium blockchain protocols are analyzed, along with deriving an upper bound of the damage an attacker could cause. Additionally, analytical derivations are employed to investigate both security and performance features, showing close agreement with measurements on a wide-area network testbed running the Hyperledger Fabric blockchain.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Guang Peng, Huaming Wu, Han Wu, Katinka Wolter
Summary: This article proposes three constrained multiobjective evolutionary algorithms (CMOEAs) for solving IoT-enabled computation offloading problems in collaborative edge and cloud computing networks. These algorithms consider time and energy consumption, and aim to improve efficiency and optimization through a combination of search algorithms and constraint handling mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Theory & Methods
Xing Chen, Jianshan Zhang, Bing Lin, Zheyi Chen, Katinka Wolter, Geyong Min
Summary: This study proposes a new energy-efficient offloading strategy for DNN-based smart IoT systems with deadline constraints in the cloud-edge environments. By designing a system energy consumption model and using a self-adaptive particle swarm optimization algorithm and genetic algorithm operators, the offloading decisions for DNN layers are efficiently made, leading to reduced energy consumption.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Min Xue, Huaming Wu, Guang Peng, Katinka Wolter
Summary: This research focuses on optimizing the offloading of large-scale DNN models in a local-edge-cloud collaborative environment with limited resources, proposing a new algorithm that efficiently achieves DNN offloading strategies while reducing latency, energy consumption, and cost.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Biology
F. Noel, G. Xexeo, E. Mangeli, A. Mothe, P. Marques, J. Kritz, F. Blanchard, H. Vermelho, B. de Paiva
Summary: The article introduces a science game called "SCREENER," designed to educate players on the drug discovery and development process, suitable for students of pharmacology, medicinal chemistry, pharmacy, and medicine postgraduate programs. The game simulates the process from validating a target to registering a new drug with regulatory agencies, allowing for individual or monitored group play and incorporating decision making and challenge elements.
BRAZILIAN JOURNAL OF MEDICAL AND BIOLOGICAL RESEARCH
(2021)
Article
Public, Environmental & Occupational Health
Yuri Lima, Wallace Pinheiro, Carlos Eduardo Barbosa, Matheus Magalhaes, Miriam Chaves, Jano Moreira de Souza, Sergio Rodrigues, Geraldo Xexeo
Summary: The study proposes an Aedes aegypti inspection index through a multi-criteria analysis to assist public health practitioners in Brazil in preventing the appearance of new breeding sites. The priority for inspections should consider the number of sick people, medical evaluations, inspections, mosquito breeding sites, and days of absence from work.
JMIR PUBLIC HEALTH AND SURVEILLANCE
(2021)