• 제목/요약/키워드: Binary Systems

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CCAJS: A Novel Connect Coverage Algorithm Based on Joint Sensing Model for Wireless Sensor Networks

  • Sun, Zeyu;Yun, Yali;Song, Houbing;Wang, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권10호
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    • pp.5014-5034
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    • 2016
  • This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

Salient Region Extraction based on Global Contrast Enhancement and Saliency Cut for Image Information Recognition of the Visually Impaired

  • Yoon, Hongchan;Kim, Baek-Hyun;Mukhriddin, Mukhiddinov;Cho, Jinsoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권5호
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    • pp.2287-2312
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    • 2018
  • Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

N-ary Information Markets: Money, Attention, and Personal Data as Means of Payment

  • Stock, Wolfgang G.
    • Journal of Information Science Theory and Practice
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    • 제8권3호
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    • pp.6-14
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    • 2020
  • On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

Development of Processing System of the Direct-broadcast Data from the Atmospheric Infrared Sounder (AIRS) on Aqua Satellite

  • Lee Jeongsoon;Kim Moongyu;Lee Chol;Yang Minsil;Park Jeonghyun;Park Jongseo
    • 대한원격탐사학회지
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    • 제21권5호
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    • pp.371-382
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    • 2005
  • We present a processing system for the Atmospheric Infrared Sounder (AIRS) sounding suite onboard Aqua satellite. With its unprecedented 2378 channels in IR bands, AIRS aims at achieving the sounding accuracy of radiosonde (1 K in 1-km layer for temperature and $10\%$ in 2-km layer for humidity). The core of the processor is the International MODIS/AIRS Processing Package (IMAPP) that performs the geometric and radiometric correction for generation of Level 1 brightness temperature and Level 2 geophysical parameters retrieval. The processor can produce automatically from received raw data to Level 2 geophysical parameters. As we process the direct-broadcast data almost for the first time among the AIRS direct-broadcast community, a special attention is paid to understand and verify the Level 2 products. This processor includes sub-systems, that is, the near real time validation system which made the comparison results with in-situ measurement data, and standard digital information system which carry out the data format conversion into GRIdded Binary II (GRIB II) standard format to promote active data communication between meteorological societies. This processing system is planned to encourage the application of geophysical parameters observed by AIRS to research the aqua cycle in the Korean peninsula.

Abiotic effects on calling phenology of three frog species in Korea

  • Yoo, Eun-Hwa;Jang, Yi-Kweon
    • Animal cells and systems
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    • 제16권3호
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    • pp.260-267
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    • 2012
  • Calling behavior is often used to infer breeding patterns in anurans. We studied the seasonal and diel calling activities of anuran species in a wetland in central Korea to determine the calling season and to evaluate the effects of abiotic factors on male calling. Acoustic monitoring was used in which frog calls were recorded for a full day, once a week, throughout an entire year. Using acoustic monitoring, we identified three frog species in the study site. Males of Rana dybowskii called in late winter and early spring; we thus classified this species as a winter/spring caller. The results of binary logistic regression showed that temperature, relative humidity, and 1-day lag rainfall were significant factors for male calling in R. dybowskii. Temperature and relative humidity were important factors for the calling activity of R. nigromaculata, whereas 24-h rainfall and 1-day lag rainfall were not significant. Thus, we determined R. nigromaculata to be a summer caller independent of weather. In Hyla japonica, relative humidity, 24-h rainfall, and 1- day lag rainfall were significant for male calling, suggesting that this species is a summer caller dependent on local rain.

Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method

  • Bian, Yan;Gong, Yusheng;Ma, Guopeng;Duan, Ting
    • Journal of Information Processing Systems
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    • 제17권5호
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    • pp.947-959
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    • 2021
  • Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GA-OTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.

Copyright Protection of E-books by Data Hiding Based on Integer Factorization

  • Wu, Da-Chun;Hsieh, Ping-Yu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권9호
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    • pp.3421-3443
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    • 2021
  • A data hiding method based on integer factorization via e-books in the EPUB format with XHTML and CSS files for copyright protection is proposed. Firstly, a fixed number m of leading bits in a message are transformed into an integer which is then factorized to yield k results. One of the k factorizations is chosen according to the decimal value of a number n of the subsequent message bits with n being decided as the binary logarithm of k. Next, the chosen factorization, denoted as a × b, is utilized to create a combined use of the

    and elements in the XHTML files to embed the m + n message bits by including into the two elements a class selector named according to the value of a as well as a text segment with b characters. The class selector is created by the use of a CSS pseudo-element. The resulting web pages are of no visual difference from the original, achieving a steganographic effect. The security of the embedded message is also considered by randomizing the message bits before they are embedded. Good experimental results and comparisons with exiting methods show the feasibility of the proposed method for copyright protection of e-books.

A Cross-Platform Malware Variant Classification based on Image Representation

  • Naeem, Hamad;Guo, Bing;Ullah, Farhan;Naeem, Muhammad Rashid
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3756-3777
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    • 2019
  • Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.

Deep Learning in Drebin: Android malware Image Texture Median Filter Analysis and Detection

  • Luo, Shi-qi;Ni, Bo;Jiang, Ping;Tian, Sheng-wei;Yu, Long;Wang, Rui-jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3654-3670
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    • 2019
  • This paper proposes an Image Texture Median Filter (ITMF) to analyze and detect Android malware on Drebin datasets. We design a model of "ITMF" combined with Image Processing of Median Filter (MF) to reflect the similarity of the malware binary file block. At the same time, using the MAEVS (Malware Activity Embedding in Vector Space) to reflect the potential dynamic activity of malware. In order to ensure the improvement of the classification accuracy, the above-mentioned features(ITMF feature and MAEVS feature)are studied to train Restricted Boltzmann Machine (RBM) and Back Propagation (BP). The experimental results show that the model has an average accuracy rate of 95.43% with few false alarms. to Android malicious code, which is significantly higher than 95.2% of without ITMF, 93.8% of shallow machine learning model SVM, 94.8% of KNN, 94.6% of ANN.

Investigating the Regression Analysis Results for Classification in Test Case Prioritization: A Replicated Study

  • Hasnain, Muhammad;Ghani, Imran;Pasha, Muhammad Fermi;Malik, Ishrat Hayat;Malik, Shahzad
    • International Journal of Internet, Broadcasting and Communication
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    • 제11권2호
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    • pp.1-10
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    • 2019
  • Research classification of software modules was done to validate the approaches proposed for addressing limitations in existing classification approaches. The objective of this study was to replicate the experiments of a recently published research study and re-evaluate its results. The reason to repeat the experiment(s) and re-evaluate the results was to verify the approach to identify the faulty and non-faulty modules applied in the original study for the prioritization of test cases. As a methodology, we conducted this study to re-evaluate the results of the study. The results showed that binary logistic regression analysis remains helpful for researchers for predictions, as it provides an overall prediction of accuracy in percentage. Our study shows a prediction accuracy of 92.9% for the PureMVC Java open source program, while the original study showed an 82% prediction accuracy for the same Java program classes. It is believed by the authors that future research can refine the criteria used to classify classes of web systems written in various programming languages based on the results of this study.