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Topic Review
Synthetic Datasets
With the consistent growth in the importance of machine learning and big data analysis, feature selection stands to be one of the most relevant techniques in the field. Extending into many disciplines, the use of feature selection in medical applications, cybersecurity, DNA micro-array data, and many more areas is witnessed. Machine learning models can significantly benefit from the accurate selection of feature subsets to increase the speed of learning and also to generalize the results. Feature selection can considerably simplify a dataset, such that the training models using the dataset can be “faster” and can reduce overfitting. Synthetic datasets were presented as a valuable benchmarking technique for the evaluation of feature selection algorithms.
  • 342
  • 20 Mar 2024
Topic Review
Financial Technologies
Financial technology (fintech) is an emerging field where novel technologies are used to improve the business operations or services offered by financial institutions and enterprises. Artificial intelligence (AI), blockchain, and cloud services have caused process disruption, while big data enables greater customer acquisition and retention. Together, these technologies have enhanced the use of interactive fintech agents in finance.  
  • 323
  • 14 Nov 2023
Topic Review
Rack Locations in the Mobile-Rack Picking System
The flexible movement of racks in the mobile-rack picking system (MRPS) significantly improves the picking efficiency of e-commerce orders with the characteristics of “one order multi–items” and creates a challenging problem of how to place racks in the warehouse. This is because the placement of each rack in the MRPS directly influences the distance that racks need to be moved during order picking, which in turn affects the order picking efficiency.
  • 318
  • 23 Feb 2024
Topic Review
Blockchain-Based Traffic Bottleneck Management System
To alleviate traffic congestion, it is necessary to effectively manage traffic bottlenecks. In existing research, travel demand prediction for traffic bottlenecks is based on travel behavior assump￾tions, and prediction accuracy is low in practice. Thus, the effect of traffic bottleneck management strategies cannot be guaranteed. Management strategies are often mandatory, leading to problems such as unfairness and low social acceptance. To address such issues, this paper proposes managing traffic bottlenecks based on shared travel plans. To solve the information security and privacy prob￾lems caused by travel plan sharing and achieve information transparency, travel plans are shared and regulated by blockchain technology. To optimize the operation level of traffic bottlenecks, travel plan regulation models under scenarios where all/some travelers share travel plans are proposed and formulated as linear programming models, and these models are integrated into the blockchain with smart contract technology. Furthermore, travel plan regulation models are tested and verified using traffic flow data from the Su-Tong Yangtze River Highway Bridge, China. The results indicate that the proposed travel plan regulation models are effective for alleviating traffic congestion. The vehicle transfer rate and total delay rate increase as the degree of total demand increases; the vehicle transfer rate increases as the length of the time interval decreases; and the vehicle transfer rate and total delay rate increase as the number of vehicles not sharing their travel plans increases. By using the model and method proposed in this paper, the sustainability of urban economy, society, and environment can be promoted.
  • 293
  • 27 Mar 2024
Topic Review
Platform Supply Chain Coordination Considering Fresh-Keeping Service
With changes in demand and the emergence of new distribution channels, consumer-centric buyer’s markets for many products have been formed. The platform supply chain has been continuously optimized and upgraded. Supply chain leaders have moved downstream to the end of the supply chain. The operational value has been further enhanced. The corresponding systematic construction of the platform supply chain has become an important driving force for future development. 
  • 267
  • 09 Oct 2023
Topic Review
Sign2Pose: A Pose-Based Approach for Gloss Prediction
Word-level sign language recognition (WSLR) is the backbone for continuous sign language recognition (CSLR) that infers glosses from sign videos. Finding the relevant gloss from the sign sequence and detecting explicit boundaries of the glosses from sign videos is a persistent challenge. A Sign2Pose Gloss prediction transformer that can significantly identify the intermediate gloss for the given input video sequence.
  • 258
  • 10 Jan 2024
Topic Review
Digital Imaging and Communications in Medicine
Medical imaging plays a crucial role in modern healthcare, providing essential information for accurate diagnosis and treatment planning. The Digital Imaging and Communications in Medicine (DICOM) standard has revolutionized the storage, transmission, and sharing of medical images and related data. This research presents an implementation of DICOM communication and the development of a practical demonstration for simulation purposes. The simulation can be used for conducting cybersecurity tests in the context of DICOM communication.
  • 257
  • 25 Sep 2023
Topic Review
Budget Allocation with Combinatorial Constraints
Budget allocation problems, commonly referred to as capital budgeting problems, often involve many constraints. Consequently, efficiently and effectively solving these problems becomes increasingly challenging. Advancements in linear programming-based row generation and optimization-based sorting methods offer promising solutions to address these challenges.
  • 248
  • 21 Dec 2023
Topic Review
U-Shaped Conveyor Assembly Line Balancing Problem
Conveyors are used when material is to be moved frequently between specific points. Line balancing involves allocating an equal amount of work to each workstation along the line. The fundamental line balancing problem is to assign a set of tasks to an ordered set of workstations, so that the precedence relationships are satisfied and some measure of performance is optimized.
  • 234
  • 17 Jan 2024
Topic Review
Emission Reduction Decisions in Blockchain-Enabled Low-Carbon Supply Chains
With the rapid development of the global economy, carbon emissions are increasing year by year. The continuous promotion of low-carbon policies has led to a gradual increase in consumers’ carbon perception sensitivity and environmental awareness. With the increasing maturity of blockchain technology, its distributed database technology realizes the transparency and traceability of the carbon emission reduction process, which effectively enhances consumers’ trust in low-carbon products.
  • 228
  • 18 Mar 2024
Topic Review
Embedded Eye Image Defocus Estimation for Iris Biometrics
One of the main challenges faced by iris recognition systems is to be able to work with people in motion, where the sensor is at an increasing distance (more than 1 m) from the person. The ultimate goal is to make the system less and less intrusive and require less cooperation from the person. When this scenario is implemented using a single static sensor, it will be necessary for the sensor to have a wide field of view and for the system to process a large number of frames per second (fps). In such a scenario, many of the captured eye images will not have adequate quality (contrast or resolution). 
  • 191
  • 11 Sep 2023
Topic Review Peer Reviewed
Count Random Variables
The observation of randomness patterns serves as guidance for the craft of probabilistic modelling. The most used count models—Binomial, Poisson, Negative Binomial—are the discrete Morris’ natural exponential families whose variance is at most quadratic on the mean, and the solutions of Katz–Panjer recurrence relation, aside from being members of the generalised power series and hypergeometric distribution families, and this accounts for their many advantageous characteristics. Some other basic count models are also described, as well as models with less obvious but useful randomness patterns in connection with maximum entropy characterisations, such as Zipf and Good models. Simple tools, such as truncation, thinning, or parameter randomisation, are straightforward ways of constructing other count models.
  • 186
  • 25 Sep 2024
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