Intelligent Information Management

Journal Information
ISSN / EISSN : 21605912 / 21605920
Current Publisher: Scientific Research Publishing, Inc. (10.4236)
Total articles ≅ 334
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Dongfeng Li, Xiao Huang, Li Dongfeng, Huang Xiao
Intelligent Information Management, Volume 12, pp 36-42; doi:10.4236/iim.2020.121003

Abstract:
Since a complete DNA chain contains a large data (usually billions of nucleotides), it’s challenging to figure out the function of each sequence segment. Several powerful predictive models for the function of DNA sequence, including, CNN (convolutional neural network), RNN (recurrent neural network), and LSTM [1] (long short-term memory) have been proposed. However, all of them have some flaws. For example, the RNN can hardly have long-term memory. Here, we build on one of these models, DanQ, which uses CNN and LSTM together. We extend DanQ by developing an improved DanQ model and applying it to predict the function of DNA sequence more efficiently. In the most primitive DanQ model, the regulatory grammar is learned by the regulatory motifs captured by the convolution layer and the long-term dependencies between the motifs captured by the recurrent layer, so as to increase the prediction accuracy. Through the testing of some models, DanQ has greatly improved in some indicators. For the regulatory markers, DanQ achieves improvements above 50% of the area under the curve, via the measurement of the precision-recall curve.
Benjamin Requardt, Sebastian Wende-Von Berg, Martin Braun
Intelligent Information Management, Volume 12, pp 43-62; doi:10.4236/iim.2020.121004

Abstract:
Due to the increasing share of renewable energy, new requirements are placed on control room software. Such software is often exclusive to the supplier, but other suppliers could offer new and better methods. For security reasons, external applications often have no direct data access to control room software. Such software can provide information about the power grid via a periodic file transfer in CIM (Common Information Model) format. These files are often very large, containing complete records, delivering information not always relevant to the external applications. Extracting the relevant information required by external applications can be time-consuming, thus presenting a problem for time-critical applications. This paper presents a method allowing different applications to efficiently access the relevant data from the massive data stream contained in the CIM files. This method has been tested with a distribution system operator and clearly increases performance, allowing different applications to access the relevant data.
Yingwei Zhou
Intelligent Information Management, Volume 12, pp 75-87; doi:10.4236/iim.2020.123006

Abstract:
The traditional Apriori applied in books management system causes slow system operation due to frequent scanning of database and excessive quantity of candidate item-sets, so an information recommendation book management system based on improved Apriori data mining algorithm is designed, in which the C/S (client/server) architecture and B/S (browser/server) architecture are integrated, so as to open the book information to library staff and borrowers. The related information data of the borrowers and books can be extracted from books lending database by the data preprocessing sub-module in the system function module. After the data is cleaned, converted and integrated, the association rule mining sub-module is used to mine the strong association rules with support degree greater than minimum support degree threshold and confidence coefficient greater than minimum confidence coefficient threshold according to the processed data and by means of the improved Apriori data mining algorithm to generate association rule database. The association matching is performed by the personalized recommendation sub-module according to the borrower and his selected books in the association rule database. The book information associated with the books read by borrower is recommended to him to realize personalized recommendation of the book information. The experimental results show that the system can effectively recommend book related information, and its CPU occupation rate is only 6.47% under the condition that 50 clients are running it at the same time. Anyway, it has good performance.
Saad Aldoihi, Omar Hammami, Aldoihi Saad, Hammami Omar
Intelligent Information Management, Volume 12, pp 27-35; doi:10.4236/iim.2020.121002

Abstract:
Usability is a vital characteristic in operating medical machines, especially radiological machines, such as computed tomography (CT) scans and X-rays. The more the body is exposed to it, the greater the negative effect has. If usability is crucial to a specific industry, it is more crucial in the medical health industry due to its tremendous effect on safety and the patient’s health. This study examines the usability of CT scans based on 14 attributes from hospitals across Saudi Arabia. The study revealed that usability consistency, visibility, minimalism, memory, and flexibility have the most usability catastrophic complaints, where the overall catastrophic rate exceeds 20%. Creating a shortcut for frequently used operations is critically important, because it has a fundamental effect in minimizing physical and mental exertion.
Kanayo Kizito Uka, Stanley Ikechukwu Oguoma, Udochukwu Princewill Chuma-Uba
Intelligent Information Management, Volume 12, pp 88-104; doi:10.4236/iim.2020.123007

Abstract:
The aim of this paper is to analyze the sharing and management of files in a tertiary institution using blockchain architecture. It is expected to enable an online system that could provide a decentralized architecture for multiple transfers and sharing of files amongst participants, to design a system that can provide data integrity and security of files using IBM Blockchain technology, to provide a system that can allow multiple user and multiple transactions at once. The research was motivated because of the security challenges associated with existing system which include: delay in transfer and sharing of files, much authority and task given to a single user in a centralized system, high risk of attack and loss of files, reduced speed of file transfer and file access/retrieval, limited number of users per time. Methodology adopted was Object Oriented Analysis Design Methodology (OOADM) in conjunction with Unified Modeling Language (UML) and IBM Blockchain Technology while the programming language used was HTML, CSS, Java and Node Js. The result after design was a decentralized cloud based file sharing and management system that enables multi-shared, replicated and permissioned transactions amongst participants in a network.
Venkata A. Paruchuri, Bobby C. Granville
Intelligent Information Management, Volume 12, pp 63-74; doi:10.4236/iim.2020.122005

Abstract:
Physicians gather a vast amount of information about patients’ medical procedures, treatments, insurance coverage, and other clinical data. Such information is crucial in formulating diagnosis or treatment plans for patients with similar traits. A Case-Based Reasoning (CBR) system has been developed to address the effective organization and retrieval of vital patient information to aid physicians in making decisions. Integers are used to uniquely represent various medical procedures, treatments, etc. In this research, a new algorithm is presented to retrieve suitable cases to recommend to physicians. The system is tested in a simulated environment and the results prove that the system can adapt to changes such as new medical procedures or treatments that take place in the medical field.
Xuehua Sun, Jianjun Wang, Guozhang Xu, Hongwei Gao, Liping Ma
Intelligent Information Management, Volume 12, pp 105-120; doi:10.4236/iim.2020.123008

Abstract:
Information dissemination has become part of people’s daily communication and there is great interest for both academic and industrial communities. Most previous studies have focused on the strategy and mechanisms. The methods controlling the process of information diffusion have rarely been studied. Thus, previous studies have failed to effectively mine the value of product information diffusion on social networks. In this study, based on the information diffusion product in consumer self-organized social networks, the control of the product information diffusion process was explored. The node identification principle of the QR code sender designed in this study and the linked list that associated information with specific nodes allowed the acquisition of effective traces in long-chain transmission from the information source to the value nodes, and solved user information disclosure during the transmission process. This method was applied to the tracing system of defective vehicles, achieving accurate recall of defective vehicles.
Binbin Sang, Xiaoyan Zhang, Sang Binbin, Zhang Xiaoyan
Intelligent Information Management, Volume 12, pp 1-26; doi:10.4236/iim.2020.121001

Abstract:
For the moment, the representative and hot research is decision-theoretic rough set (DTRS) which provides a new viewpoint to deal with decision-making problems under risk and uncertainty, and has been applied in many fields. Based on rough set theory, Yao proposed the three-way decision theory which is a prolongation of the classical two-way decision approach. This paper investigates the probabilistic DTRS in the framework of intuitionistic fuzzy information system (IFIS). Firstly, based on IFIS, this paper constructs fuzzy approximate spaces and intuitionistic fuzzy (IF) approximate spaces by defining fuzzy equivalence relation and IF equivalence relation, respectively. And the fuzzy probabilistic spaces and IF probabilistic spaces are based on fuzzy approximate spaces and IF approximate spaces, respectively. Thus, the fuzzy probabilistic approximate spaces and the IF probabilistic approximate spaces are constructed, respectively. Then, based on the three-way decision theory, this paper structures DTRS approach model on fuzzy probabilistic approximate spaces and IF probabilistic approximate spaces, respectively. So, the fuzzy decision-theoretic rough set (FDTRS) model and the intuitionistic fuzzy decision-theoretic rough set (IFDTRS) model are constructed on fuzzy probabilistic approximate spaces and IF probabilistic approximate spaces, respectively. Finally, based on the above DTRS model, some illustrative examples about the risk investment of projects are introduced to make decision analysis. Furthermore, the effectiveness of this method is verified.
Serge Rebouillat, Benoit Steffenino, Mirosława Lapray, Antoine Rebouillat
Intelligent Information Management, Volume 12, pp 131-182; doi:10.4236/iim.2020.124010

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Vrian Jay Ylaya
Intelligent Information Management, Volume 12, pp 121-130; doi:10.4236/iim.2020.124009

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