Coding Method Research Articles

Application of amplified damped outrigger in seismic design of high‐rise buildings

SummaryThe application of the outrigger technology effectively improves the lateral stiffness of buildings, reduces harmful deformation, enhances the seismic resistance of structures, and contributes to the rapid development of high‐rise buildings. To improve the response speed and energy dissipation of a viscous damping outrigger under seismic excitation, a viscous damping outrigger with an amplifier was proposed, and its effectiveness was verified by combining it with the seismic design of a 149.2 m high‐rise building in an 8.5‐degree intensity area. To determine the additional damping ratio of the building structure, investigations were carried out using both the code method and energy ratio method to evaluate the contribution of the damping outrigger. The damped outrigger equivalent stiffness determination method was studied, and the simplified engineering calculation method was compared against the refined finite element analysis results for engineering design purposes. The displacement amplification technique incorporated into the viscously damped outrigger can enhance the damper response speed, and increase the energy dissipation of the damped outrigger system. The application of an enlarged damped outrigger in engineering can result in an additional damping ratio of approximately 1% while simplifying the calculation method based on the additional damping and equivalent damper cut‐line stiffness, which can be useful in engineering design.

Analisis Perbandingan Kompresi File Audio Menggunakan Algoritma Shannon Fano Dengan Algoritma Fibonacci Code

Compression is a technique used to reduce the size of the data that serves to reduce memory capacity and speed up the data transfer process. In this study, the method used is the Shannon Fano method and the Fibonacci Code. In the Shannon Fano method the compression process is carried out by knowing the frequency of occurrence of each symbol which will then be sorted from the largest to the smallest frequency, while the Fibonacci Code method uses the Fibonacci integer series to encode the bit value of the data or file to be compressed. The file to be compressed is an audio file with an MP3 extension, to perform compression in reducing the size of the audio file, the technique used is lossless. Lossless technique is a compression technique that can restore compressed files converted to their original form (decompression). The algorithms used in file compression both use lossless techniques. Files that have been compressed using the Shannon Fano and Fibonacci Code methods will be compared to find out which method is more efficient in compressing audio files. The results showed that the method of Shannon Fano and Fibonacci can compress audio files. Based on the analysis of the compression ratio results generated using the Shannon Fano algorithm, there was a 69% change using 48 data samples, while the compression ratio results generated using the Fibonacci algorithm experienced a 66% change using the same 48 data samples as the Shannon Fano algorithm

Application of Quasi-Continuous Waveform Coding in Spaceborne Synthetic Aperture Radar

Quasi-continuous wave radar is an attempt to give consideration to the performance of pulse and continuous wave radar signals. However, it also has the shortcomings of both. This paper aims to add a new quasi-continuous-wave coding method to the spaceborne synthetic aperture radar (SAR) system. The technology of improving spaceborne SAR imaging performance by coding quasi-continuous-wave pulses is studied, and some shortcomings of this algorithm are improved. Firstly, the application of quasi-continuous-wave radar in the SAR system is studied, and the coding and reconstruction scheme is provided so that this technology can be successfully applied in spaceborne SAR. Secondly, the effects of different quasi-continuous-wave coding methods on SAR imaging performance are evaluated, including signal-to-noise ratio, resolution, and integration time. Then, several coding schemes are given, and the characteristic changes of the signal after quasi-continuous-wave coding are analyzed. The transmit–receive conversion loss function and azimuth Doppler ambiguity function of the design scheme are analyzed, which proves the advantages of the scheme. Finally, we design the hardware implementation scheme and carry out the practical test.

Development of Dynamic Channel Coding Strategy for Multi-User MIMO-NOMA 5G Downlink Communication by Concatenation of Coding Method

Development of Dynamic Channel Coding Strategy for Multi-User MIMO-NOMA 5G Downlink Communication by Concatenation of Coding Method

Secure Steganography Model over Cloud Environment using Adaptive ABC and Optimum Pixel Adjustment Algorithm

An effective security model with low computational complexity, minimal quality-compromised, and improved security robustness is essential due to the rapid expansion of multimedia data communication through different cloud services. An image steganography model has been proposed for the security of multimedia data in an unreliable cloud environment. This study's main goal is to provide efficient steganography with barely hidden information. A secure data communication model has been developed over a cloud environment using the Adaptive Artificial Bee Colony Algorithm and the Optimum Pixel Adjustment Algorithm Based Image Steganography Method. An adaptive ABC (artificial bee colony) technique is applied to select the optimal pixel positions in the cover image because the goal of this investigation is to increase PSNR. The Optimal Pixel Adjustment approach is used to minimise embedding errors while maintaining the stego image's appearance identical to the cover image after embedding. The MATLAB platform is used to implement the proposed method. The results show that the proposed AABC-based OPA is more efficient across all measures investigated during the embedding and extraction processes.

A novel method for linguistic steganography by English translation using attention mechanism and probability distribution theory.

To enhance our ability to model long-range semantical dependencies, we introduce a novel approach for linguistic steganography through English translation. This method leverages attention mechanisms and probability distribution theory, known as NMT-stega (Neural Machine Translation-steganography). Specifically, to optimize translation accuracy and make full use of valuable source text information, we employ an attention-based NMT model as our translation technique. To address potential issues related to the degradation of text quality due to secret information embedding, we have devised a dynamic word pick policy based on probability variance. This policy adaptively constructs an alternative set and dynamically adjusts embedding capacity at each time step, guided by variance thresholds. Additionally, we have incorporated prior knowledge into the model by introducing a hyper-parameter that balances the contributions of the source and target text when predicting the embedded words. Extensive ablation experiments and comparative analyses, conducted on a large-scale Chinese-English corpus, validate the effectiveness of the proposed method across several critical aspects, including embedding rate, text quality, anti-steganography, and semantical distance. Notably, our numerical results demonstrate that the NMT-stega method outperforms alternative approaches in anti-steganography tasks, achieving the highest scores in two steganalysis models, NFZ-WDA (with score of 53) and LS-CNN (with score of 56.4). This underscores the superiority of NMT-stega in the anti-steganography attack task. Furthermore, even when generating longer sentences, with average lengths reaching 47 words, our method maintains strong semantical relationships, as evidenced by a semantic distance of 87.916. Moreover, we evaluate the proposed method using two metrics, Bilingual Evaluation Understudy and Perplexity, and achieve impressive scores of 42.103 and 23.592, respectively, highlighting its exceptional performance in the machine translation task.

Algorithm of information stability in hydroacoustic control channel for aquaculture

Increasing attention is being paid to the mechanisms of data transfer between ocean research devices and data collection and analysis centers for the subsequent study and theorization of ocean evolution. All transmitted data are vulnerable to interception by unauthorized parties, so one of the main challenges is to protect the transmitted information. The proposed algorithm is based on steganographic method and solves the authentication problem by embedding additional data into the original signal in such a way that it is not empirically detectable. Among the first and best- known methods for hidden data embedding is a technique based on spread spectrum technology and its various adaptations, which incorporate additional parameters into the mathematical equation to improve the efficiency of the method. However, when auxiliary information is encoded into the original audio signal, these parameters affect both the covertness and robustness of the embedded data, potentially compromising the integrity of the steganographic system. Consequently, the development of steganographic techniques is aimed at simultaneously improving stealth and robustness.

A comparative analysis of chaos theory based medical image steganography to enhance data security

The security of patient data is a critical problem for health networks due to the rising popularity of telehealth services and the requirements for clinical data sharing between surgeons, consultants, and medical groups. In contrast to protecting medical data, which includes the cover (i.e., clinical picture), the requirements for protecting other pertinent data are more general. The paper advocates for data encryption before concealment as a robust strategy to uphold patient privacy during medical information exchange. The primary focus of this analysis revolves around a comprehensive exploration of different steganography methods. Through a meticulous examination of various steganographic techniques, including LSB, PVD, and transform domain approaches, this paper provides a detailed analysis of their strengths and limitations. Objective metrics like PSNR and SSIM are employed to dissect the trade-offs between data security and visual fidelity. The research leads to the conclusion that the diagonal queue-based steganog-raphy methodology, supported by chaotic methods, the Linear Feedback Shift Register (LFSR), and the durable Rabin encryption system, is the best course of action. This method enables autonomous data transmission among numerous contacts while ensuring the highest level of confidentiality and integrity of patient data inside e-health networks. In summary, this study provides a comprehensive solution that protects patient data and speeds data transmission inside the expanding framework of e-health networks in order to meet urgent data security concerns in telemedicine and healthcare data exchange.

MULTIPARENT FRACTAL IMAGE CODING-BASED METHODS FOR SALT-AND-PEPPER NOISE REMOVAL

Salt-and-pepper noise consists of outlier pixel values which significantly impair image structure and quality. Multiparent fractal image coding (MFIC) methods substantially exploit image redundancy by utilizing multiple domain blocks to approximate the range block, partially compensating for the information loss caused by noise. Motivated by this, we propose two novel image restoration methods based on MFIC to remove salt-and-pepper noise. The first method integrates Huber M-estimation into MFIC, resulting in an improved anti-salt-and-pepper noise robust fractal coding approach. The second method incorporates MFIC into a total variation (TV) regularization model, including a data fidelity term, an MFIC term and a TV regularization term. An alternative iterative method based on proximity operator is developed to effectively solve the proposed model. Experimental results demonstrate that these two proposed approaches achieve significantly enhanced performance compared to traditional fractal coding methods.

A Method of Cover Audio Selection for Embedding Based on Various Criteria

The main goal of an audio steganography method is to improve the capacity, im-perceptibility, and robustness. Several methods of audio steganography have been proposed to enhance its capabilities. To further optimize the efficiency of the audio steganography method, this paper proposes to select the appropriate audio cover for concealing the message. The selection of an appropriate cover can significantly improve the quality of the output and facilitate the development of innovative audio steganography techniques. This paper proposed a new audio cover selection method, which can further enhance the characteristics of the resulting output. This method ranked each cover according to the qualities that need to be boosted using various measurements. These measurements are the Maximum Available Space (MAS), Peak Signal to Noise Ratio (PSNR) and Bit Error Rate (BER) for capacity, imperceptibility, and robustness respectively. Based on the experiment conducted using five cover audios stored in the self-created database, each audio is ranked differently based on the measurement used to determine its characteristic level. In conclusion, the proposed cover selection method can be used to select the most proper cover, hence improving the characteristics of audio steganography.

Mixed quantum/classical theory (MQCT) approach to the dynamics of molecule-molecule collisions in complex systems.

We developed a general theoretical approach and a user-ready computer code that permit study of the dynamics of collisional energy transfer and ro-vibrational energy exchange in complex molecule-molecule collisions. The method is a mixture of classical and quantum mechanics. The internal ro-vibrational motion of collision partners is treated quantum mechanically using a time-dependent Schrödinger equation that captures many quantum phenomena including state quantization and zero-point energy, propensity and selection rules for state-to-state transitions, quantum symmetry and interference phenomena. A significant numerical speed up is obtained by describing the translational motion of collision partners classically, using the Ehrenfest mean-field trajectory approach. Within this framework a family of approximate methods for collision dynamics is developed. Several benchmark studies for diatomic and triatomic molecules, such as H2O and ND3 collided with He, H2 and D2, show that the results of MQCT are in good agreement with full-quantum calculations in a broad range of energies, especially at high collision energies where they become nearly identical to the full quantum results. Numerical efficiency of the method and massive parallelism of the MQCT code permit us to embrace some of the most complicated collisional systems ever studied, such as C6H6 + He, CH3COOH + He and H2O + H2O. Application of MQCT to the collisions of chiral molecules such as CH3CHCH2O + He, and to molecule-surface collisions is also possible and will be pursued in the future.

Несохранение импульса в методе FMM в коде PHANTOM

The article discusses the implementation of the fast multipole method (FMM) in the PHANTOM code. It has been demonstrated that for any given pair of mutual interaction cells in a kd-tree, Newton's third law holds. However, momentum is not preserved for the entire system as a whole.

Achievement Goal Orientations of Iranian EFL Teachers in Postmethod Pedagogy Expertise

Purpose: The efficacy of postmethod pedagogy (PMP) in Iran remains undetermined despite the growing attention being paid to it. A multitude of factors may contribute to differing levels of motivation among teachers in effectively implementing postmethod principles. The Achievement Goal Theory (AGT), rooted in a socio-cognitive perspective, provides a framework for understanding the types of goals individuals tend to pursue in achievement situations. Hence, this study aims to investigate the goal orientations of experienced English as a Foreign Language (EFL) teachers who are practicing postmethod tenets. Methodology: The current study employed an applied qualitative approach to explore the goal orientations of 18 experienced EFL teachers from various language institutes in Kermanshah, Iran. Participants were selected in two phases: first, a postmethod questionnaire was administered to identify respondents familiar with Postmethod Pedagogy (PMP) principles. Next, a semi-structured interview was conducted to elicit their goal orientations while adopting PMP conditions. Field notes were also used to document the researcher’s reflections and opinions, facilitating data analysis. The researchers utilized a three-stage approach for data analysis, following the inductive data coding method of open, axial, and selective coding. Findings: After analyzing the interview transcripts, it became apparent that the implementation of postmethod pedagogy tenets in teachers' teaching practice was influenced by their achievement goal orientations. This included learning, relational, and performance-approach goal orientations. The findings revealed that expert teachers predominantly exhibited learning goal orientations. In contrast, performance-approach goal orientations were the least prevalent among these educators. Conclusion: Examining teachers’ goal orientations through the socio-cognitive lens of postmethod language teaching can benefit the growth and development of teacher training programs, curriculum planning, and policymakers.

Sizzle or Fizzle? Supply and Consumption Dynamics of Home-Cooked Food on Sharing Platform

To address the growing obesity crisis, governments are promoting home cooking to improve dietary habits. Home-cooked food-sharing platforms, a manifestation of the sharing economy, offer consumers healthy food options. While the economic benefits of the sharing economy have been extensively studied, little is known about its impact on non-economic factors, such as consumers’ health. To address this gap, we conduct an empirical study using data from a mobile kitchen-sharing platform and four controlled experiments to investigate whether the sharing economy helps consumers develop healthy eating habits. We use manual coding and machine learning methods to evaluate the healthiness of over 180,000 unique dishes and examine food provision and consumption on the platform. Our findings indicate that as consumers use the platform more frequently, they tend to consume more unhealthy food. Additionally, sellers who receive more orders and earn more revenue tend to offer less healthy food over time. Two controlled experiments prove consumers are more likely to order unhealthy food online. Furthermore, these experiments provide causal evidence that consumer food consumption patterns drive seller food provision rather than vice versa. Our results suggest that the sharing economy may have negative consequences due to misaligned interests between sellers and consumers. Fortunately, we identify conditions that may mitigate these effects in empirical analyses and two experiments. Specifically, consumers who choose dine-in options (as opposed to takeaway) and those who order for groups (as opposed to individual orders) tend to make healthier food choices on the platform due to impression management motivation.

Developing a synthetic news corpus to validate generic frame detection methods

Frames are a central concept in communication research. Based on our literature review, we propose that frame identification is an act of identifying selected reality and communicative intention. We then highlight the conceptual and methodological issues of frame identification using computational methods. To avoid the correlation between topics and frames, we provide a synthetic dataset for evaluating frames found in multi-topical news content, using the detection of generic frames as a test case. With this dataset, for the first time, we benchmark manual coding and various automatic and semi-supervised methods. Based on the preliminary benchmark results, this study provides evidence that generic frame identification using both manual coding and automatic methods might not be accurate.

The Relationship between Employee Absenteeism and Occupational Psychosocial Hazards in Construction Work Site

As the introduction of human resources especially construction workers is very important in the construction sector especially when the construction industry in Malaysia has grown rapidly in recent years and is largely dependent on human labor to work. Although human labor is important to the construction industry, human labor is also considered the most complex management resource. One of the challenges faced on construction sites is employee absenteeism as the construction sector is experiencing the negative effects of absenteeism. Thus, the objective of the study is to identify the factors of employee absence at the construction site, the impact of employee absence at the construction site on the organization and determine the strategies used in managing employee absence at the construction site. The research methodology is through a qualitative method with a case study where a total of five construction projects respondents have been selected from Grade 7 (G7) main contractors or subcontractor firms and this research is focused on construction sites in the Johor area. A qualitative research approach with a semi-structured interview instrument was conducted with the respondents to ensure their perspectives were analyzed. The data collected was analyzed using content analysis where coding and frequency distribution methods were used to achieve the objectives of the study. Respondents focused on employers and employees working under the construction project site. Employers refer to management level personnel such as project managers or those responsible for managing the presence of workers at the construction site while workers refer to skilled, semi-skilled and unskilled workers working at the construction site. The findings of the study show that work fatigue which is classified as occupational psychosocial hazards is the most significant factor that causes workers not to attend the construction site and has caused a loss of productivity at the construction site that needs to be solved by providing welfare measures to the workers.

Medical color image concealing for IoMT services

Steganography (or Data Concealing, Data Masking, or Data Hiding) is the art of concealing information within other data, structures, or media to avoid detection or access by unauthorized users. Various domains and contexts can be used to hide data. By hiding sensitive data, you can prevent unauthorized access, tampering, or theft, protect your privacy, or even protect your intellectual property. Using images as cover media is the most effective method of steganography. A new method based on the modified technique described by the authors for grayscale images is presented in this manuscript for comparing the color images performance. Data can be hidden in color images by blocking them. Our calculation of the detail coefficients of the secret image uses an approximation of the blue, green, and red components of the cover image. As an alternative to block coefficients, we substitute approximation coefficients for root mean square errors. The best matching blocks are stored using a key. A single image hides a large amount of data, so the work is expected to be successful. A better peak signal-to-noise ratio is provided by Stego Medical Image (StMdIg).

Cryptographic image-based data security strategies in wireless sensor networks

There is need to develop and create new data protection mechanisms aimed at the compensating for the lack of security of WSNs. This paper introduces new cryptographic image-based techniques aimed at improving data security in WSNs. The solution also integrates imaging processing techniques with advanced cryptographic principles to merge a two-layered security architecture. This work provides a new WSN-specific encryption algorithm that delivers low energy consumption and smaller computational burden. Likewise, this is connected to an image-based authentication approach which employs steganographic methods in the information hiding technique. Intensive simulations allow the approach that supports methodology, naming increased security metrics obtained without decreasing in network performance. This study seeks to fill the gap in current practice in WSN security and provides a foundation for future research on image-based techniques integrated with cryptographic algorithms aiming at more secure data protection under limited resources.

Robust Image Steganography Against General Downsampling Operations With Lossless Secret Recovery

Resisting the operations in lossy channels is a challenge for image steganography. In this paper, we propose a novel robust steganographic method to resist the image downsampling operation. Unlike the existing schemes, our method guarantees lossless secret recovery from the stego-image after general image downsampling operations, which considers the undetectability of the stego-images on both sides (sender and receiver) of the lossy channel. We first downsample the cover image to get its downsampled version on the receiver side, and select a set of embeddable pixels (i.e., the pixels that can be modified for data embedding) from the downsampled image. Then, we generate a stego-image on the receiver side (termed as the receiver stego-image) such that the distortion caused by the data embedding is minimized. Based on the receiver stego-image, we modify the cover image to produce the stego-image on the sender side (termed as the sender stego-image). The modification takes the embedding cost into account and makes sure that the downsampled version of the sender stego-image produces the same embeddable pixels as the receiver stego-image. Experimental results show that our method performs significantly better than the existing schemes in terms of robustness and undetectability for resisting general image downsampling operations.

Parallel steganographic algorithm based on least significant bit

The paper suggests a parallel algorithm for the implementation of the LSB steganographic method. The possibilities of parallel programming are presented. The proposed steganographic parallel algorithm is compared to an algorithm using sequential embedding of the hidden message (using one-core processor). It is established that the algorithm produces accurate statistical results.