• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.382-403
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• 2020

Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.172-174
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• 2007

An electronic watt-hour meter with high-precision measurement technology can provide many valuable metering data of a real-time system measurements, such as per-phase voltage, ampere, active power, reactive power, apparent power, power factor, and system frequency. Also many of accumulated metering data such as active energy, reactive energy, apparent energy, and load profile can be gettable from an electronic watt-hour meter[1]. This paper presents an approach of the small-sized AMR (Automatic Meter Reading) that provides customers with a very valuable electrical service. This AMR service transmits lots of a valuable metering data by using ZigBee communication module, so that users resided in their premises can use the information to audit a power quality and improve their electrical conditions by using the PQ monitoring device equipped with ZigBee receiver. This PQ monitoring device shows metering data on LCD and transmits to the PC through an internal network. Also, the device can keep the valuable meter data into a built-in non-volatile memory. The final goal of this paper is to better understand the power quality of electrical systems and offer the power qualify information for the convenience of all power consumers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.38-57
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• 2016

Service discovery is one of the major challenges in cloud computing environment with a large number of service providers and heterogeneous services. Non-uniform naming conventions, varied types and features of services make cloud service discovery a grueling problem. With the proliferation of cloud services, it has been laborious to find services, especially from Internet-based service repositories. To address this issue, services are crawled and clustered according to their similarity. The clustered services are maintained as a catalogue in which the data published on the cloud provider's website are stored in a standard format. As there is no standard specification and a description language for cloud services, new efficient and intelligent mechanisms to discover cloud services are strongly required and desired. This paper also proposes a key-value representation to describe cloud services in a formal way and to facilitate matching between offered services and demand. Since naïve users prefer to have a query in natural language, semantic approaches are used to close the gap between the ambiguous user requirements and the service specifications. Experimental evaluation measured in terms of precision and recall of retrieved services shows that the proposed approach outperforms existing methods.

• Smart Structures and Systems
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• v.19 no.3
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• pp.243-257
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• 2017

In this paper, free vibration of functionally graded (FG) size-dependent nanobeams is studied within the framework of nonlocal Timoshenko beam model. It is assumed that material properties of the FG nanobeam, vary continuously through the thickness according to a power-law form. The small scale effect is taken into consideration based on nonlocal elasticity theory of Eringen. The non-classical governing differential equations of motion are derived through Hamilton's principle and they are solved utilizing both Navier-based analytical method and an efficient and semi-analytical technique called differential transformation method (DTM). Various types of boundary conditions such as simply-supported, clamped-clamped, clamped-simply and clamped-free are assumed for edge supports. The good agreement between the presented DTM and analytical results of this article and those available in the literature validated the presented approach. It is demonstrated that the DTM has high precision and computational efficiency in the vibration analysis of FG nanobeams. The obtained results show the significance of the material graduation, nonlocal effect, slenderness ratio and boundary conditions on the vibration characteristics of FG nanobeams.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2381-2399
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• 2019

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.418-424
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• 2023

Natural killer (NK) cells play a crucial role in combating infections and tumors. However, their therapeutic application in solid tumors is hindered by challenges, such as limited lifespan, tumor penetration, and delivery precision. Our research introduces a novel ultrasonic actuation technique to navigate NK cells more effectively in the vascular system, particularly at vessel bifurcations where targeted delivery is most problematic. We use a hemispherical ultrasonic transducer array that generates phase-modulated traveling waves, focusing on an ultrasound beam to steer NK cells using blood-flow dynamics and a focused acoustic field. This method enables the precise obstruction of non-target vessels and efficiently directs NK cells toward the tumor site. The simulation results offer insights into the behavior of NK cells under various conditions of cell size, radiation pressure, and fluid velocity, which inform the optimization of their trajectories and increase targeting efficiency. The experimental results demonstrate the feasibility of this ultrasonic approach for enhancing NK cell targeting, suggesting a potential leap forward in solid tumor immunotherapy. This study represents a significant step in NK cell therapeutic strategies, offering a viable solution to the existing limitations and promising enhancement of the efficacy of cancer treatments.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.11-13
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• 2013

Background: Esophagus cancer, the third most common gastrointestinal cancer overall, demonstrates high incidence in parts of Iran. The counties of Iran vary in size, shape and population size. The aim of this study was to account for spatial support with Area-to-Area (ATA) Poisson Kriging to increase precision of parameter estimates and yield correct variance and create maps of disease rates. Materials and Methods: This study involved application/ecology methodology, illustrated using esophagus cancer data recorded by the Ministry of Health and Medical Education (in the Non-infectious Diseases Management Center) of Iran. The analysis focused on the 336 counties over the years 2003-2007. ATA was used for estimating the parameters of the map with SpaceStat and ArcGIS9.3 software for analysing the data and drawing maps. Results: Northern counties of Iran have high risk estimation. The ATA Poisson Kriging approach yielded variance increase in large sparsely populated counties. So, central counties had the most prediction variance. Conclusions: The ATAPoisson kriging approach is recommended for estimating parameters of disease mapping since this method accounts for spatial support and patterns in irregular spatial areas. The results demonstrate that the counties in provinces Ardebil, Mazandaran and Kordestan have higher risk than other counties.

• Journal of Korea Technology Innovation Society
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• v.16 no.2
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• pp.391-407
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• 2013

The paper tests the embodiment hypothesis by measuring the technological obsolescence of a specific year (1990)'s technology and investigating the relationship between labor productivity and technological obsolescence. This approach is based on Salter (1969) that emphasizes the economic aspect of technology. We use the rate of economic surplus as the proxy of technological obsolescence for 10 main industries, including food processing, textiles, chemicals, non-steel metals, steels, metal products, machinery, electronics, precision machinery, and transportation equipments. The result shows that the embodiment hypothesis is not accepted for the overall manufacturing sector. However, we found the vintage effect - a positive relationship between technological obsolescence and labor productivity over time - in textiles, chemicals, non-steel metals, metal products, electronics, and transportation equipments. Therefore, the government should support R&D investment as well as capital equipments investment for the industries with large vintage effect.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.56.2-56.2
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• 2016

We present a multi-aperture photometry pipeline for DEEP-South (Deep Ecliptic Patrol of the Southern Sky) time-series data, written in C. The pipeline is designed to do robust high-precision photometry and calibration of non-crowded fields with a varying point-spread function, allowing for the wholesale search and characterization of both temporal and spatial variabilities. Our time-series photometry method consists of three parts: (i) extracting all point sources with several pixel/blind parameters, (ii) determining the optimized aperture for each source where we consider whether the measured flux within the aperture is contaminated by unwanted artifacts, and (iii) correcting position-dependent variations in the PSF shape across the mosaic CCD. In order to provide faster access to the resultant catalogs, we also utilize an efficient indexing technique using compressed bitmap indices (FastBit). Lastly, we focus on the development and application of catalog-based searches that aid the identification of high-probable single events from the indexed database. This catalog-based approach is still useful to identify new point-sources or moving objects in non-crowded fields. The performance of the pipeline is being tested on various sets of time-series data available in several archives: DEEP-South asteroid survey and HAT-South/MMT exoplanet survey data sets.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.