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Journal of digital information management
Digital Information Research Foundation
Journal of digital information management

Digital Information Research Foundation

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0972-7272

Journal of digital information management/Journal Journal of digital information management
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    Multi-Venue Basketball Match Scheduling Based on Simulated Annealing Algorithm

    Haiping Chen
    1-10页
    查看更多>>摘要:This work studies the multi-venue basketball event scheduling plan based on a simulated annealing algorithm, aiming to improve the stability and fairness of event scheduling. By reviewing the application advantages and disadvantages of traditional intelligent algorithms in basketball event scheduling, this paper introduces the principle of simulated annealing algorithm and its application in basketball event scheduling. A basketball tournament scheduling plan based on a simulated annealing algorithm was designed and implemented for multiple competition venues, and its effectiveness was verified through experiments. The experimental results show that compared with traditional intelligent algorithms, the plan exhibits better performance in terms of stability and fairness.

    An Android Malware Detection Method Based on MLSTM

    Yi LiuMd Gapar Md JoharJacquline Tham
    11-25页
    查看更多>>摘要:With the popularity of smartphones and mobile applications, the threat of Android malware is increasingly serious. The analysis and behaviour modelling of Android malware features is studied to realize the efficient and accurate detection of Android malware, and an Android malware detection method combining mean aggregator and long-term and short-term memory is proposed. The results show that the improved system detection time is relatively stable regardless of the number of samples. The average detection time of the improved and unimproved systems is 0.274 s and 0.336 s, respectively, and the improved detection efficiency of the improved system is more prominent. The highest improvement rate of the enhanced system reached 18.2%. Compared with other models, the average absolute error and root mean square error were the smallest, with 3.84 and 6.26, respectively, indicating that the detection performance of the improved model is the best. With permission features and third-party library features, the accuracy of the enhanced model was 98.89% and 92.65%, and the recall rate was 99.24% and 99.09%, respectively. The improved model detection performance is good, and the robustness and stability are enhanced. Applied to actual Android devices, it can improve the security and privacy protection level of user data. This method ensures enhanced efficiency and stability and provides a certain reference direction for Android malware detection.

    Performance Evaluation of Software in Large Data Environments Utilizing Time-Managed Computation Tree Logic

    Yuan SunMd Gapar Md JoharJacquline Tham
    26-46页
    查看更多>>摘要:The research aims to solve the problems of unstable performance parameters and insufficient coverage in software testing and proposes a big data platform software performance testing system based on the clock-controlled computation tree logic method. The particle swarm algorithm finds the optimal solution through the movement and cooperation of particles in the search space. The genetic algorithm evolves the population through selection, crossover, and mutation operations, ultimately finding the optimal solution. Secondly, long short-term memory networks and linear autoregressive models also have advantages in software testing, which can improve the effectiveness and efficiency of software testing through reasonable selection and combined use. The research uses the algorithmic logic of the particle swarm and genetic algorithms to confirm the software testing system's moment parameters and other information. At the same time, an algorithmic model researches the joint coverage and the use of the system's value, and finally, the big data platform is used to analyze the research system. The innovative combination of the CCTL method and optimization algorithm in the research has improved the accuracy and stability of software testing. The research results show that using the system to test software can achieve a coverage rate of 100% for its component use cases, while the functional coverage rates of the genetic algorithm and particle swarm algorithm reach 90.36% and 91.32%, respectively. The accuracy of software testing for researching usage methods is 5% and 6% higher than testing methods. When the moment range of the particle parameter position information of the model is [150 ms, 250 ms], the maximum value of the target parameter velocity is 80 m/s, and the minimum value is o m/s. The maximum value of the target azimuth velocity is 20 rad/s, and the minimum is o rad/s. The system can determine the various parameters of the software, and at the same time, if the software test results on the test results are typical, fault analysis can be completed typically; the performance of the use of algorithms is also better than other algorithms, and the study of the use of algorithms with a higher degree of stability. It can be seen that the system and methods used in this research are better than traditional methods, and the test results in software testing have improved, providing a research direction for software testing after the research.

    Regional Carbon Emission Prediction and Low-carbon Path Analysis Based on BP Neural Network Model

    Xuanke ZhangLijun WuJun YangRunbin Xue...
    47-66页
    查看更多>>摘要:To attain carbon emission control and sustainable economic development, tailored low-carbon policies must be adapted to distinct regional contexts. Given disparities in key industries, economic growth, and resource availability, variations in carbon emissions across China's eastern, central, and western regions necessitate divergent low-carbon strategies. To comprehensively grasp regional carbon emissions and provide precise recommendations, a Lasso regression method identified five influential factors from seven, including population, per capita GDP, total energy consumption, energy mix, industrial makeup, urbanization rate, and forest coverage. Analyzing the link between carbon emissions and total output, a predictive model employed a GA-optimized BP neural network to forecast emissions. Findings indicate higher carbon emissions in the developed eastern region due to rapid economic growth, industrial production, and energy use. While the east region maintains emission leadership, emission growth rates converge, reflecting nationwide progress in reduction efforts. Future strategies should focus on regional development, exploring low-carbon paths through energy restructuring, urban optimization, and synergy of energy strengths, thereby achieving shared low-carbon objectives.

    Beyond the Search Engine: Design of the Online Search Experience

    Hathairat Ketmaneechairat
    67-68页
    查看更多>>摘要:Most digital platforms and tools feature a search capability, represented by a simplified magnifying glass icon so familiar that many users overlook its meaning; they understand its purpose. The search functions across various interfaces are uniform and expected. A blank text field for entering a query produces suggestions for different queries, ultimately leading to a page filled with structured search results. The author viewed that over the following 15 years, online search has changed in some astounding and disappointing) ways.

    Fifth International Conference on Digital Data Processing (DDP 2025)

    69-70页
    查看更多>>摘要:As technology advances in different sub-domains of computing, data-driven models are becoming increasingly important. The data-dependent world now faces many challenges in terms of data accuracy and data privacy. High-impact advancements include machine learning, artificial intelligence, deep learning and many more. Data is growing exponentially in terms of diversity and complexity. One organization or industry processes over a few million transactions per hour and stores hundreds of billions of data. We live in a world with a great need for more efficient data analysis and processing. Data analytics can reveal hidden patterns, complex relationships, internal information relations, and even segmentation. Data applications have opened up new possibilities in every aspect of our lives. Studying data and its structure, dynamics, and modern data technologies is ongoing. There is a great deal of literature and research on data management, but it does not address the data processing needs. Many studies focus on developing models and systems for analyzing large datasets.