Earticle

A watermark is a signal added to the original signal in order to preserve the copyright of the owner of the digital content. The basic challenge for designing a watermarking system is a dilemma between transparency and robustness. If we want a higher rate of transparency, there has to be a compromise in terms of its robustness and vice versa. Also, until now, watermarking is generalized, resulting in the need for a specialized algorithm to work for a specialized image processing application domain. Our proposed technique takes into consideration the image characteristics for watermark insertion and it optimizes transparency and robustness. It achieved a 99.98% retrieval efficiency for an image blurring attack and counterfeits other attacks. Our proposed technique counterfeits almost all of the image processing attacks.

The objective of this study is the development of discrete optimum design algorithms which is based on the genetic algorithms. The developed algorithms was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses structures and the constraints are stresses and displacements. This study solves the problem by introducing the genetic algorithms. The genetic algorithms consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed discrete optimum design algorithms was verified by applying the algorithms to optimum design examples.

The high peak-to-average power ratio (PAPR) is one of the major drawbacks of the orthogonal frequency division multiplexing (OFDM) systems that make non-linear distortion in practical implementation of high power amplifier (HPA). In this study, the performance of discrete Hartley matrix transform (DHMT) in precoding based OFDM system is analyzed to minimize the high PAPR. We demonstrate that the DHMT precoding method eliminates the multicarrier assumption in a special circumstance. The remarkable results are achieved and compared with conventional OFDM, Walsh?Hadamard matrix transform (WHMT), discrete cosine matrix transform (DCMT) and Vandermonde-like matrix transform (VLMT) in precoding based OFDM signals.

The present study investigates the difficulty of solving the mathematical problem, namely the DLP (Discrete Logarithm Problem) for ephemeral keys. The DLP is the basis for many public key cryptosystems. The ephemeral keys are used in such systems to ensure security. The DLP defined on a prime field $Z^*_p of random prime is considered in the present study. The most effective method to solve the DLP is the ICM (Index Calculus Method). In the present study, an efficient way of computing the DLP for ephemeral keys by using a new variant of the ICM when the factors of p-1 are known and small is proposed. The ICM has two steps, a pre-computation and an individual logarithm computation. The pre-computation step is to compute the logarithms of a subset of a group and the individual logarithm step is to find the DLP using the precomputed logarithms. Since the ephemeral keys are dynamic and change for every session, once the logarithms of a subset of a group are known, the DLP for the ephemeral key can be obtained using the individual logarithm step. Therefore, an efficient way of solving the individual logarithm step based on the newly proposed precomputation method is presented and the performance is analyzed using a comprehensive set of experiments. The ephemeral keys are also solved by using other methods, which are efficient on random primes, such as the Pohlig-Hellman method, the Van Oorschot method and the traditional individual logarithm step. The results are compared with the newly proposed individual logarithm step of the ICM. Also, the DLP of ephemeral keys used in a popular password key exchange protocol known as Chang and Chang are computed and reported to launch key recovery attack.

This paper presents an optimal implementation of a Daubechies-based pipelined discrete wavelet packet transform (DWPT) processor using finite impulse response (FIR) filter banks. The feed-forward pipelined (FFP) architecture is exploited for implementation of the DWPT on the field-programmable gate array (FPGA). The proposed DWPT is based on an efficient transpose form structure, thereby reducing its computational complexity by half of the system. Moreover, the efficiency of the design is further improved by using a canonical-signed digit-based binary expression (CSDBE) and advanced functional sharing (AFS) methods. In this work, the AFS technique is proposed to optimize the convolution of FIR filter banks for DWPT decomposition, which reduces the hardware resource utilization by not requiring any embedded digital signal processing (DSP) blocks. The proposed AFS and CSDBE-based DWPT system is embedded on the Virtex-7 FPGA board for testing. The proposed design is implemented as an intellectual property (IP) logic core that can easily be integrated into DSP systems for sub-band analysis. The achieved results conclude that the proposed method is very efficient in improving hardware resource utilization while maintaining accuracy of the result of DWPT.

This study proposes analytical methods to establish the eigenfunction of continuous system due to substructuring and decoupling of discrete subsystems. The dynamic characteristics of updated continuous system are evaluated by the constraint effect of consistent deformation at the interfaces between two systems. Beginning with the dynamic equation for constrained discrete system, this work estimates the modal eigenmode function for the continuous system due to the addition or deletion of discrete systems. Numerical applications illustrate the validity and applicability of the proposed method.

The exhaustive list of sparsification methods for a digital image suffers from achieving an adequate number of zero and near-zero coefficients. The method proposed in this paper, which is known as the Discrete Rajan Transform Sparsification, overcomes this inadequacy. An attempt has been made to compare the simulation results for benchmark images by various popular, existing techniques and analyzing from different aspects. With the help of Discrete Rajan Transform algorithm, both lossless and lossy sparse representations are obtained. We divided an image into $8{\times}8-sized$ blocks and applied the Discrete Rajan Transform algorithm to it to get a more sparsified spectrum. The image was reconstructed from the transformed output of the Discrete Rajan Transform algorithm with an acceptable peak signal-to-noise ratio. The performance of the Discrete Rajan Transform in providing sparsity was compared with the results provided by the Discrete Fourier Transform, Discrete Cosine Transform, and the Discrete Wavelet Transform by means of the Degree of Sparsity. The simulation results proved that the Discrete Rajan Transform provides better sparsification when compared to other methods.

Delivery of high quality video over a wide area network with large number of users poses great challenges for the video communication system. To ensure video quality, multiple descriptions have recently attracted various attention as a way of encoding and visual information delivery over wireless network. We propose a new efficient multiple description coding (MDC) technique. Quincunx lattice sub-sampling is used for generating multiple descriptions of an image. In this paper, we propose the application of a directional discrete cosine transform (DCT) to a sub-sampled quincunx lattice to create an MDC representation. On the decoder side, the image is decoded from the received side information. If all the descriptions arrive successfully, the image is reconstructed by combining the descriptions. However, if only one side description is received, decoding is executed using an interpolation process. The experimental results show that such the directional DCT can achieve a better coding gain as well as energy packing efficiency than the conventional DCT with re-alignment.

In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.

This paper aims to present a supervised classification algorithm based on data fusion for the segmentation of the textured images. The feature extraction method we used is based on discrete wavelet transform (DWT). In the segmentation stage, the estimated feature vector of each pixel is sent to the support vector machine (SVM) classifier for initial labeling. To obtain a more accurate segmentation result, two strategies based on information fusion were used. We first integrated decision-level fusion strategies by combining decisions made by the SVM classifier within a sliding window. In the second strategy, the fuzzy set theory and rules based on probability theory were used to combine the scores obtained by SVM over a sliding window. Finally, the performance of the proposed segmentation algorithm was demonstrated on a variety of synthetic and real images and showed that the proposed data fusion method improved the classification accuracy compared to applying a SVM classifier. The results revealed that the overall accuracies of SVM classification of textured images is 88%, while our fusion methodology obtained an accuracy of up to 96%, depending on the size of the data base.

In this study, a clustering algorithm that uses DCT transformed data is presented. The algorithm is a grid density-based clustering algorithm that can identify clusters of arbitrary shape. Streaming data are transformed and reconstructed as needed for clustering. Experimental results show that DCT is able to approximate a data distribution efficiently using only a small number of coefficients and preserve the clusters well. The grid based clustering algorithm works well with DCT transformed data, demonstrating the viability of DCT for data stream clustering applications.

In this paper, we propose an effective noise reduction method for photon counting imaging using a discrete wavelet transform. Conventional 2D photon counting imaging was used to visualize the object under dark conditions using statistical methods, such as the Poisson random process. The photons in the scene were estimated using a statistical method. However, photons which disturb the visualization and decrease the image quality may occur in the background where there is no object. Although median filters are used to reduce the noise, the noise in the scene remains. To remove the noise effectively, our proposed method uses the discrete wavelet transform, which removes the noise in the scene using a specific thresholding method that utilizes photon counting imaging characteristics. We conducted an optical experiment to demonstrate the denoising performance of the proposed method.

Popliteal entrapment syndrome caused by isolated popliteus muscle enlargement is very rare, although its occurrence has been reported after discrete trauma. However, popliteal artery stenosis with combined peroneal and proximal tibial neuropathy caused by popliteus muscle enlargement without preceding trauma has not been reported. A 57-year-old man presented with a tingling sensation and pain in his left calf. He had no previous history of an injury. The symptoms were similar to those of lumbosacral radiculopathy. Calf pain became worse despite treatment, and the inability to flex his toes progressed. Computed tomography angiography and magnetic resonance imaging of the lower extremity showed popliteal artery stenosis caused by popliteus muscle enlargement and surrounding edema. An electrodiagnostic study confirmed combined peroneal and proximal tibial neuropathy at the popliteal fossa. Urgent surgical decompression was performed because of the progressive neurologic deficit and increasing neuropathic pain. The calf pain disappeared immediately after surgery, and he was discharged after the neurologic functions improved.

Abstract A series of permeability tests was performed on the mixtures with specific mixing rates of sand and bentonite using modified rigid-wall permeameter. Sand-bentonite mixtures were permeated by organics, ethanol and TCE. Permeability of bentonite with several mixing rates had a tendency to decrease up to initial one pore volume and permeability was thereafter converged to a constant value. When sand-bentonite mixtures was permeated by water, permeability was decreased at the beginning but it was thereafter converged to a constant. Among several mixing rates, permeability was greatly decreased at 15% of mixing rate. When sand-bentonite mixtures with 15% mixing rate was permeated by ethanol, permeability was about 10 times larger value than permeability of water. Peameability was shown greater values when permeated by TCE (TrichloroEthylene) followed by ethanol. Suitable mixing rate of sand-bentonite for a liner of waste landfills was detected.

We propose a new contact detection algorithm for fine pitch wire bonding. Fast and stable contact detection of the z-axis in wire bonding is extremely important to maintain the quality of fine pitch gold wire bonding processes, which use a small pad less than $70{\mu}m$ in diameter. A small perturbation in the contact detection time causes a large difference in the size of the formed squashed ball. The new detection method is based on a statistical approach and designed for a discrete Kalman filter. It is faster and has smaller detection time variations than conventional detection methods. Experimental results are presented to demonstrate the advantages of the proposed algorithm.

The capability to examine an X-ray image is so far a challenging task. In this work, we suggest a practical and novel algorithm based on image fusion to inspect the issues such as background noise, blurriness, or sharpness, which curbs the quality of dual-energy X-ray images. The current technology exercised for the examination of bags and baggage is "X-ray"; however, the results of the incumbent technology used show blurred and low contrast level images. This paper aims to improve the quality of X-ray images for a clearer vision of illegitimate or volatile substances. A dataset of 40 images was taken for the experiment, but for clarity, the results of only 13 images have been shown. The results were evaluated using MSE and PSNR metrics, where the average PSNR value of the proposed system compared to single X-ray images was increased by 19.3%, and the MSE value decreased by 17.3%. The results show that the proposed framework will help discern threats and the entire scanning process.

목적: 본 연구는 밀레니얼 세대에 의해 주관적으로 생성된 구매 후 만족/보통/불만족에 대한 속성 리뷰의 구전 정보를 크롤링하여 텍스트 마이닝 기법인 워드클라우드 분석과 의미연결망 분석으로 각 영역간의 유사점과 차이점을 분석하고 확인적 요인분석을 실 시하고자 한다. 방법: 본 연구를 위해 R버전 4.1.2 프로그램을 빅데이터 수집 및 분석 도구로 사용하였으며, 수집된 데이터에 대한 전처리 및 불용어 처리 과정을 거쳐서 연구 목적에 맞는 텍스트 마이닝 분석을 수행하였다. 그리고 이 결과를 이용한 확인적 요인분 석은 LISREL 8.80 프로그램을 이용하여 수행하였다. 결과: 워드클라우드 분석 결과 '만족' 평가영역에서 피부가 1위, '보통' 평가영 역에서 제품이 1위, 평가영역에서 1위가 되는 것으로 나타났다. '불만족' 평가영역에서는 피부가 1위를 차지하였다. 그리고 확인적 요인분석에서는 만족/보통/불만족 3개의 잠재변수의 상관관계가 차별화가 되는 것으로 나타났다. 결론: 소셜미디어에 존재하는 밀 레니얼 소비자의 개별정서 반응을 만족/보통/불만족 영역으로 분류하여 도출된 워드클라우드 분석과 의미연결망 분석으로 얻게 되 는 이들 영역간의 유사점과 차이점의 결과는 매우 의미 있는 결과를 얻었다고 볼 수 있다. 그리고 텍스트 마이닝에서 도출된 확인적 요인분석의 관측변수는 인과분석에서 수행하는 설문지의 측정 항목으로 도입될 수 있을 것으로 기대된다

Purpose: This study aimed to analyze the similarities and differences between each area using wordcloud analysis and semantic network analysis, which are text mining techniques. Further, confirmatory factor analysis will be conducted by crawling for word-of-mouth information on attribute reviews as satisfied, normal, or dissatisfied after purchases that are subjectively given by millennial generations. Methods: The R program version 4.1.2 was used as a big data collection and analysis tool, and text mining analysis was performed through preprocessing and stopword processing on the collected data. Further, using LISREL 8.80 we conducted confirmatory factor analysis on these results. Results: Wordcloud analysis revealed that the terms “skin,” “products,” and “skin” ranked first in the evaluation area of “satisfied,” “normal,” and “dissatisfied,” respectively. Additionally, using confirmatory factor analysis, the correlation between the three latent variables of satisfaction, normal, and dissatisfaction was differentiated. Conclusion: The similarities and differences between the domains obtained through wordcloud and semantic network analyses and derived by classifying individual emotional responses of millennial consumers in social media into satisfied, normal, and dissatisfied domains are considered very meaningful. The keywords derived with high centrality in the semantic network for each domain is then refined and introduced as an observation variable for confirmatory factor analysis in accordance with the purpose of the study; this is helpful in research development for causal analysis in the future.

目的: 本研究抓取千禧一代主观产生的购买后满意/正常/不满意的属性评论口碑信息，通过词云分析和语义网络 分析等文本挖掘技术分析各领域的异同，我们打算进行验证性因素分析。方法: 本研究使用R version 4.1.2程 序作为大数据收集分析工具，通过对收集到的数据进行预处理和停用词处理，进行适合研究目的的文本挖掘分 析。并且使用该结果使用LISREL 8.80程序进行验证性因素分析。结果: 词云分析结果发现，皮肤在“满意”评价 区排名第一，产品在“正常”评价区排名第一，在评价区排名第一。在“不满意”评价区，皮肤排在第一位。并且 在验证性因素分析中，发现满意/正常/不满意三个潜变量的相关性是有区别的。结论: 通过将千禧一代消费者在 社交媒体中的个体情绪反应分类为满意/正常/不满意区域得到的词云分析和语义网络分析得到的这些区域的异同 结果得到了非常有意义的结果。可以看到。此外，期望引入文本挖掘验证性因素分析的观测变量作为因果分析 问卷的测量项。

Online reviews play a significant role in consumer purchase decisions on e-commerce platforms. To address information overload in the context of online reviews, factors that drive review helpfulness have received considerable attention from scholars and practitioners. The purpose of this study is to explore the differential effects of discrete emotions (anger, disgust, fear, joy, sadness, and surprise) on perceived review helpfulness, drawing on cognitive appraisal theory of emotion and expectation-confirmation theory. Emotions embedded in 56,157 hotel reviews collected from TripAdvisor.com were extracted based on a transfer learning model to measure emotion variables as an alternative to dictionary-based methods adopted in previous research. We found that anger and fear have positive impacts on review helpfulness, while disgust and joy exert negative impacts. Moreover, hotel star-classification significantly moderates the relationships between several emotions (disgust, fear, and joy) and perceived review helpfulness. Our results extend the understanding of review assessment and have managerial implications for hotel managers and e-commerce vendors.

This study aims to explore how discrete contexts of activating national identity influence Korean consumers’ responses to patriotism-themed ads. Specifically, this study proposes that (1) national identity activation will influence Korean consumers in responding to patriotism-themed ads; and (2) positive versus negative context of activating national identity would have different impacts on consumer responses to patriotism-themed ads. Findings from this study suggest that while both positive and negative context of activating national identity improve consumer evaluation of ads with a patriotic theme, such an effect was significantly stronger in the positive context.