Coding Techniques Research Articles

Bi-orthogonality recovery and MIMO transmission for FBMC systems based on non-sinusoidal orthogonal transformation

Filter Bank Multi-Carrier (FBMC) system based on offset Quadrature Amplitude Modulation (offset-QAM) combined with Multiple-Input-Multiple-Output (MIMO) technique faces great challenges. The inherent imaginary interference of FBMC seriously impacts the performance of the Maximum Likelihood (ML) detection technique in MIMO transmission. The application of the Alamouti code is also hindered. In this paper, we present a data-compressed transmission method based on non-sinusoidal orthogonal transformation, which can recover the bi-orthogonality of FBMC and eliminate the imaginary interference. Thereby, the combination of FBMC and MIMO as well as the application of ML technique and Alamouti code are realized. Specifically, we first consider the Walsh transform, which belongs to the non-sinusoidal orthogonal transform, and utilize its property that can reduce the transmission bandwidth to recover the orthogonality of the FBMC in the frequency domain. Secondly, we construct the discrete transmission model of the system and generate the orthogonal compression matrix utilizing the fast Walsh transform. Then, we analyze the multi-frame transmission, calculate the frames interference, and improve the signal-to-interference ratio again by adding guard time slots. Finally, we construct the MIMO transmission model and complete the theoretical analysis. Simulation results show that the proposed scheme has a robust MIMO transmission performance. ML and Alamouti code techniques perform the same as Orthogonal Frequency Division Multiplex in bi-orthogonal FBMC.

Adaptive Combined Channel Network Coding for Cognitive Radio Networks with Cooperative Relay

Cognitive radio is one of the new technologies for 4G/5G applications, so cooperative relay communication and network coding are considered as certain methods to help improve their re-spective applications. A primary broadcast system for multimedia video streaming applications that broad¬casts data to primary users and an auxiliary cooperative relay secondary cognitive ra-dio system are considered. The secondary cooperative overlay system can use multiple error control coding methods for point-to-point data retransmission, such as channel coding, network coding, and combi¬ned coding methods to improve system performance under variable link con-ditions. A new technique of adaptive coding of AC2NC combined channel network for data re-transmission is proposed. The new AC2NC first analyzes the channel feedback information and then selects the best retransmission coding technique based on the target bandwidth or trans-mission time optimization. This is instead of using a single static channel or a network coding technique with dynamic channel conditions. The proposed AC2NC improves system through-put, reduces retransmission time, and provides more spectrum access opportunities for the sec-ondary sys¬tem's own data transmissions. AC2NC's relative throughput and time saving capabil-ities for cognitive radio users have been shown to exceed ninety percent, under certain channel conditions, compared to some static coding methods.

Development of GPU-Paralleled multi-resolution techniques for Lagrangian-based CFD code in nuclear thermal-hydraulics and safety

In this study, we propose a fully parallelized adaptive particle refinement (APR) algorithm for smoothed particle hydrodynamics (SPH) to construct a stable and efficient multi-resolution computing system for nuclear safety analysis. The APR technique, widely employed by SPH research groups to adjust local particle resolutions, currently operates on a serialized algorithm. However, this serialized approach diminishes the computational efficiency of the system, negating the advantages of acceleration achieved through high-performance computing devices. To address this drawback, we propose a fully parallelized APR algorithm designed to enhance both efficiency and computational accuracy, facilitated by a new adaptive smoothing length model. For model validation, we simulated both hydrostatic and hydrodynamic benchmark cases in 2D and 3D environments. The results demonstrate improved computational efficiency compared to the conventional SPH method and APR with a serialized algorithm, and the model's accuracy was confirmed, revealing favorable outcomes near the resolution interface. Through the analysis of jet breakup, we verified the performance and accuracy of the model, emphasizing its applicability in practical nuclear safety analysis.

A comparative analysis of convolutional coding and block coding techniques over satellite communication

Reliable data transmission is crucial in the field of satellite communication, and many coding schemes are used to improve this reliability. Two popular coding techniques: convolutional codes and block codes were investigated and compared in this paper. Utilizing a simulated environment, the author investigates the bit error rate (BER) performance of both coding strategies along with a baseline case of no coding. The analysis reveals distinct characteristics and performance attributes of the two coding techniques across a range of signal-to-noise rate (SNR) values. Convolutional codes, with their inherent memory, offer error protection across sequences, while block codes, particularly a Hamming-like 7,3 implementation, provide localized protection for individual blocks. The findings of this study contribute to the understanding of error control strategies in satellite communication, guiding the selection and design of coding methods suitable for various operational scenarios and requirements.

Coding techniques for diversity enhancement of dense wavelength division multiplexing MIMO‐FSO fault protection protocols systems over atmospheric turbulence channels

AbstractAn enhanced transmission is presented in a multiple‐input‐multiple‐output (MIMO) dense‐wavelength division multiplexed (DWDM) free‐space‐optical (FSO) communication link using diversity coding techniques under the effect of turbulent weather phenomenon. The findings show good performance with an (8 channels × 2.5 Gbps data rate/channel) 20 Gbps 1500 m transmission distance. The bit‐error‐rate (BER), outage probability (OP), and signal‐to‐noise ratio (SNR) of the diversity combining techniques using maximum‐ratio combining (MRC), selection combining (SC), and equal‐gain combining (EGC) technique are evaluated in this work. The obtained results illustrate that Alamouti, space‐time coding (STC), space‐time block coding (STBC), space‐time trellis code (STTC), orthogonal STBC (O‐STBC), and quasi‐orthogonal STBC (QO‐STBC) on the minimum mean‐square‐error, and MRC are worth implementing on the DWDM‐FSO wireless communication systems. The mitigation of atmospheric turbulence is achieved using MIMO diversity combining techniques coding. The simulation results for diversity coding techniques using QO‐STBC/STTC and SC/MRC in the MIMO‐DWDM FSO communication system can improve BER performance, OP, and SNR. The MRC exhibits the lowest OP and BER when compared with the SC and EGC. The numerical results demonstrate that the FSO communication link using DWDM QO‐STBC/STTC improves the power penalty at both BER values under varying atmospheric turbulence conditions for ST, MT, and WT, in comparison to FSO systems without DWDM QO‐STBC/STTC diversity coding techniques.

Wireless Powered Cooperative NOMA With Alamouti Coding and Selection Relaying

Nonorthogonal multiple access (NOMA) can facilitate simultaneous data transmissions towards multiple users by using the superposition coding and successive interference cancelation techniques, which can greatly improve the spectrum efficiency. Cooperative relaying and space-time coding can promisingly improve the communication robustness of poor-quality links by achieving the space-diversity gain. Energy harvesting (EH) can prolong the lifetime of energy-limited terminals and make them work continuously. In order to enhance the spectrum efficiency as well as the communication quality, we enable a cluster of EH relays to assist the data transmissions from a base station (BS) to two far-users by using the Alamouti coding based cooperative NOMA strategy. The relays are capable of harvesting wireless energy from a power beacon as well as BS by using time-switching or power-splitting method. According to the energy status and the data decoding status, one relay is selected in a distributed manner according to either Max-min, Max-sum, or Random criterion. We analyze the transmission success probability and the system throughput performance. Extensive simulations are performed to compare the performance of different EH-based space-time coded cooperative NOMA with various relay selection schemes as well as the counterpart orthogonal transmission schemes.

Fellowship Accreditation: Experiences From Health Care Simulation Experts.

Background The field of health care simulation continues to grow, accompanied by a proliferation of fellowship programs, leading to fellowship accreditation efforts. There is controversy around the best approach to accreditation. Objective The authors sought to understand perspectives of simulation leaders on fellowship accreditation to best inform the growth and maturation of fellowship accreditation. Methods In 2020, simulation leaders identified through snowball sampling were invited to participate in a qualitative study. During one-on-one semistructured interviews, participants were asked about experiences as simulation leaders and their perspective on the purpose and impact of accreditation. The interviews were audio recorded and transcribed. Thematic analysis informed by a phenomenology framework was performed using a masked open coding technique with iterative refinement. The resulting codes were organized into themes and subthemes. Results A total of 45 simulation experts participated in interviews ranging from 25 to 67 minutes. Participants described discord and lack of consensus regarding simulation fellowship accreditation, which included a spectrum of opinions ranging from readiness for accreditation pathways to concern and avoidance. Participants also highlighted how context drove the perception of accreditation value for programs and individuals, including access to resources and capital. Finally, potential impacts from accreditation included standardization of training programs, workforce concerns, and implications for professional societies. Conclusions Simulation leaders underscored how the value of accreditation is dependent on context. Additional subthemes included reputation and resource variability, balancing standardization with flexibility and innovation, and implications for professional societies.

A qualitative focus group analysis: Increasing fieldwork capacity in genetic counseling training programs.

Genetic counselors are an integral part of the healthcare system; however, the number of genetic counselors in many parts of the United States is limited, impacting access to comprehensive healthcare for all patients. One solution to addressing this deficit includes modifying genetic counseling training programs to increase student enrollment. Fieldwork capacity, driven by a limited number of rotation sites and supervisors, produces a significant bottleneck to entering the profession. Other professions have reported on techniques to increase fieldwork capacity; however, the practicality of these techniques for genetic counseling training has yet to be explored. This study seeks to investigate the perspectives of key stakeholders in genetic counseling training programs on the practicality of techniques already posited in the literature from other allied health professions. Semi-structured focus group interviews with 25 participants were conducted at the 2019 National Society of Genetic Counselors conference. Participants included program directors and supervisors from clinical, industry, and laboratory backgrounds. The focus group responses were analyzed using directed content analysis and a split coding technique, after which several themes emerged within the larger domains of rotation structures, systems infrastructure, skill-building methods, and other novel techniques to increase fieldwork capacity. Emerging themes included the importance of finding quality student placements rather than maximizing the quantity of participatory cases; a need for transparency about the transferability of skills learned from novel experiences; scaffolding student entrustment to expand supervisor capacity; and recognizing nuances in implementation for individual programs. Overall, the results emphasize the importance of openness in communication to manage expectations for students and supervisors, who may be more hesitant to try novel rotation placements and skill-building techniques. Genetic counseling programs may use these results to address the bottleneck of fieldwork capacity, increasing student enrollment.

Exploring the Shifting Understanding of Jihad Among Former Terrorists in their Journey Towards Disengagement: Transforming the Sword

Purpose: This article explores the transformation of former terrorists' understanding of jihad verses to promote non-violence and disengagement. Method: The research uses a qualitative, narrative-phenomenological approach to analyze this shift. Data collection techniques with interviews (in deph interview), observation, and documentation. The depth of the data was obtained by searching for additional informants with snowball sampling techniques.Conventional content analysis techniques for open coding in this study. Open coding is obtained from the narration of informants. Result: The findings indicate a change in perception among former terrorists, but it does not completely eliminate their desire for holy war. Instead, they now view global jihad as defensive rather than offensive, and the law of jihad has shifted from an individual to a collective obligation. Former terrorists have replaced acts of terror with peaceful, humanistic actions. This transformation occurs during the process of indoctrination and later reflection on their perceived jihad actions. The informants' reflections are influenced by holistic interpretations of jihad verses, considering the impact of terror acts and social interactions with outgroups, family, and humanity. Ultimately, the research recommends a contextual examination of jihad verses to form the basis of deradicalization programs. Providing ongoing support to former terrorists during their reflection is crucial. Conclusion: Based on previous discussions, it can be concluded that a shift in understanding the meaning of jihadi verses occurred in all informants in this study. The shift in understanding of global jihad to defensive jihad; the law of jihad from fard 'ain (individual obligation) to the law of fard kifayah (collective obligation); jihad with acts of terror to jihad with peaceful and humanist action. This shift in understanding occurs in two stages, namely when the process of indoctrination of terror and when they reflect on actions that have been believed to be jihad.

An Investigation on Reed-Solomon Codes as Erasure Coding Technique on Its Properties and Utilizations

Erasure coding is an essential part of cloud computing, which is an important technology for effective data storage for recovering data that may be lost due to various reasons, there are various erasure coding techniques in the market. In this paper, linear MDS codes, which is a branch of erasure coding, will be investigated on their performance and usage. This paper will focus on the Reed-Solomon Code, which is the most implemented form of linear MDS codes, on three different aspects: 1) the methodologies of the encoding and decoding operations; 2) the pros and cons of different forms of Reed-Solomon Codes; 3) the different ways that different Reed-Solomon Codes are being employed. Moreover, the paper includes the definition of general Cloud Computing for the audience to understand its importance, how the erasure coding acts like a fault tolerance system of Cloud Computing, and how different kinds of Reed-Solomon code perform on tolerating erasures in cloud storage failures.

The Exploration of Modelling for The Student Achievement Predictor

The project is rooted in the analysis of historical student data. It encompasses a comprehensive approach involving data observation, meticulous analysis, thorough comparison, systematic processing, and efficient coding techniques. The ultimate goal is to harness the power of machine learning to predict students' academic achievements and discern the key features that exert the most significant influence on their learning outcomes. In terms of the machine learning model, this study explored and assessed several machine learning algorithms, including but not limited to the K-Neighbors Classifier, Logistic Regression, and Decision Tree Classifier. These models are scrutinized and fine-tuned to ensure their suitability for the task at hand. Furthermore, a pivotal aspect of this project is identifying the features that wield the greatest impact on students' learning achievements. By employing feature selection techniques, this study aims to uncover the critical factors that can make a difference in educational outcomes. This information can guide educational institutions in designing targeted interventions to support student success. The experimental results obtained from this study demonstrated the effectiveness of the employed machine learning methods.

Exploring the psycho-social burden of infertility: Perspectives of infertile couples in Cape Coast, Ghana.

Infertility is a complex and often sensitive issue with far-reaching psycho-social ramifications for couples and their families. This study therefore seeks to delve into the psycho-social burden of infertility in Cape Coast, a major city in Ghana. Specifically, we explored the impact of infertility on the psychological and social health of infertile couples receiving fertility treatment. It also delves into the strategies they adopt to cope with their conditions. The study employs a qualitative approach to inquiry using phenomenology as a study design to explore the experiences of the study participants. In-depth interviews were conducted using interview guides, voice recorded and transcribed verbatim. Both inductive and deductive/framework coding techniques were used to code the data leading to the generation of themes and sub-themes. The results show that most of the study participants dealing with infertility faced psychological burdens from different sources including their families, society and themselves. These burdens take a toll on their mental health, pushing them into a state of desperation and depression. It was, however, revealed that infertile couples are able to cope with the help of their family, spouses and the church. Curiously, some of them opt for withdrawal from social events as a coping mechanism. Infertility exerts an enormous negative psycho-social impact on affected couples, especially women. The family and society serve as the main sources of stressors for infertile couples. Therefore, programmes that are aimed at fertility treatment should deliberately consider addressing the psychosocial burden of infertility through education targeting actors, especially interpersonal-level actors.

Reflective Questions Effectively Measure Impact, Stimulate Content Integration, and Support Future Planning

We share a case study on our use of three reflective questions to demonstrate ways in which simple questions can be coded to reveal rich evidence of impact and engagement. At the end of a three-hour inclusive teaching practices workshop for 23 faculty and administrators from a single science department, 22 participants completed an anonymous three-question survey. Simple coding techniques facilitated a thorough evaluation of knowledge acquisition, the integration of new content with current knowledge, the robustness of individual plans for implementing changes, and the identification of potential departmental future actions.

High-school students’ demonstration of systems thinking in the context of sustainable food systems

ABSTRACT Systems thinking abilities are needed to help solve complex food systems problems. However, high-school instruction does not typically support students in developing these abilities, and most students have limited knowledge and awareness of food and its significance. In this study, we used sustainable food systems as the context for the learning experience to offer complex and relatable content to students. We used a qualitative case study design to describe how students demonstrated systems thinking during the learning experience. Participants in this case study were six high-school students located in the suburban area of Indiana. They participated in the learning experience using self-directed lessons, worksheets, reflections, real-world examples, and hands-on activities. We collected data from pre- and posttest assignments and interviews and analyzed data using qualitative coding techniques. Findings suggested that systems thinking is a combination of abilities in three domains: describing a system, understanding a system, and viewing a system, rather than one domain or hierarchical. Students extensively explained about a food system’s complexity, wholeness, changeability, cyclic nature, and feedback loops in temporal and spatial dimensions using multiple perspectives and making connections with other systems. We also shared the attributes of systems thinkers and the model for practical implications.

Bonding, bridging, and linking social capital combinations in maize agribusiness system

The development of the maize agribusiness system is highly dependent on the role of social capital in facilitating interaction among actors in the chain of activities ranging from the provision of farm supplies to marketing. Therefore, this research aimed to characterize the key elements of social capital specifically bonding, bridging, and linking, as well as to demonstrate their respective roles. Data were collected from farmers and non-farmers actors engaged in various activities in the maize agribusiness system. The data obtained were processed using ATLAS Ti, applying open, axial, and selective coding techniques. The results showed the roles played by bonding, bridging, and linking social capital in the interaction between farmers and multiple actors in activities such as providing farm supplies, farming production, harvesting, post-harvest, and marketing. The combination of these social capital forms acted as the glue and wires that facilitated access to resources, collective decision-making, and reduced transaction costs. These results have theoretical implications, suggesting that bonding, bridging, and linking should be combined with the appropriate role composition for each activity in the agribusiness system.

LDPC Code-based Distributed Source Coding with An Efficient Message Passing Mechanism for the Compression of Correlated Image Sources.

Different from traditional source coding techniques, distributed source coding (DSC) techniques rely on independent encoding at the encoding end but joint decoding at the decoding end to compress image sources which exhibit correlation. Channel code-based DSC techniques compress correlated image sources by fully utilizing such correlation. However, in addition to this correlation information, the current symbol of most real image sources is correlated to the preceding or subsequent symbols. Such correlation information should also play an important role for improving the compression performance of channel code-based DSC schemes. To this end, we present an efficient message passing mechanism for LDPC Code-based DSC schemes (ELCDSC) to compress correlated image sources. By utilizing this message passing mechanism, we enable LDPC code-based DSC techniques to not only make full use of the inter-source correlation to assist compression, but also integrate the intra-source correlation in each message passing iteration to improve the compression performance. It is the first that enables LDPC code-based DSC techniques to achieve the utilization of both intra- and inter-source correlations in the message passing mechanism. Experimental results reveal that ELCDSC significantly enhances the compression ratio of correlated image sources, surpassing other DSC schemes.

Twelve Times Faster yet Accurate: A New State‐Of‐The‐Art in Radiation Schemes via Performance and Spectral Optimization

AbstractRadiation schemes are critical components of Earth system models that need to be both efficient and accurate. Despite the use of approximations such as 1D radiative transfer, radiation can account for a large share of the runtime of expensive climate simulations. Here we seek a new state‐of‐the‐art in speed and accuracy by combining code optimization with improved algorithms. To fully benefit from new spectrally reduced gas optics schemes, we restructure code to avoid short vectorized loops where possible by collapsing the spectral and vertical dimensions. Our main focus is the ecRad radiation scheme, where this requires batching of adjacent cloudy layers, trading some simplicity for improved vectorization and instruction‐level parallelism. When combined with common optimization techniques for serial code and porting widely used two‐stream kernels fully to single precision, we find that ecRad with the TripleClouds solver becomes 12 times faster than the operational radiation scheme in ECMWF's Integrated Forecast System (IFS) cycle 47r3, which uses a less accurate gas optics model (RRMTG) and a more noisy solver (McICA). After applying the spectral reduction and extensive optimizations to the more sophisticated SPARTACUS solver, we find that it’s 2.5 times faster than IFS cy47r3 radiation, making cloud 3D radiative effects affordable to compute in large‐scale models. The code optimization itself gave a threefold speedup for both solvers. While SPARTACUS is still under development, preliminary experiments show slightly improved medium‐range forecasts of 2‐m temperature in the tropics, and in year‐long coupled atmosphere‐ocean simulations the 3D effects warm the surface substantially.

Multithreading ATLAS offline software: A retrospective

For Run 3, ATLAS redesigned its offline software, Athena, so that the main workflows run completely multithreaded. The resulting substantial reduction in the overall memory requirements allows for better use of machines with many cores. This note will discuss the performance achieved by the multithreaded reconstruction, the process of migrating the large ATLAS code base, and tools and techniques that were useful in debugging threading-related problems.

Barriers and Facilitators Experienced During the Implementation of Web-Based Teleradiology System in Public Hospitals of the Northwest Ethiopia: An Interpretive Description Study.

Introduction: Teleradiology allows distant facilities to electronically transmit images for interpretation, thereby bridging the radiology service gap between urban and rural areas. The technology improves healthcare quality, treatment options, and diagnostic accuracy. However, in low resource settings like Ethiopia, teleradiology services are limited, posing challenges for implementation. Therefore, this study is aimed at exploring the factors that facilitated or hindered the implementation of web-based teleradiology in the public hospitals of the South Gondar Zone, Northwest Ethiopia. Methods: In this study, a purposive sampling method was employed to select seventeen participants, including hospital managers, physicians, emergency surgeons, and radiologists, for an in-depth interview (IDI). The interviews were conducted from March to May 2023. A reflexive thematic analysis was conducted using an abductive coding technique at the semantic/explicit level. Data were collected through semistructured interviews conducted face-to-face and virtually, with audio recordings transcribed, translated, and analyzed using Open Code version 4.02 software. Trustworthiness was ensured through prolonged engagement, reflective journaling, and review by coauthors. Results: The study examined eight main themes, with barriers to sustainable teleradiology implementation falling into five categories: technological, organizational, environmental, individual, and workflow and communication. Conversely, identified facilitators included improved radiology service efficiency, system accessibility, collaboration opportunities, and user trust in the radiology ecosystem. Within each theme, factors with potential impacts on teleradiology system sustainability were identified, such as the lack of system handover mechanisms, absence of a central image consultation center, and inadequate staffing of full-time radiologists and technical personnel. Conclusions: The study highlights the positive user perception of a web-based teleradiology system's user-friendliness and efficiency. Overcoming challenges and leveraging facilitators are crucial for optimizing teleradiology and improving service delivery and patient outcomes. A centralized consultation center with dedicated radiologists and technical personnel is recommended for maximizing efficiency.

Facial Image Compression via Neural Image Manifold Compression

Although the recent learning-based image and video coding techniques achieve rapid development, the signal fidelity-driven target in these methods leads to the divergence to a highly effective and efficient coding framework for both human and machine. In this paper, we aim to address the issue by making use of the power of generative models to bridge the gap between full fidelity (for human vision) and high discrimination (for machine vision). Therefore, relying on existing pretrained generative adversarial networks (GAN), we build a GAN inversion framework that projects the image into a low-dimensional natural image manifold. In this manifold, the feature is highly discriminative and also encodes the appearance information of the image, named as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">latent code</i> . Taking a variational bit-rate constraint with a hyperprior model to model/suppress the entropy of image manifold code, our method is capable of fulfilling the needs of both machine and human visions at very low bit-rates. To improve the visual quality of image reconstruction, we further propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiple latent codes</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scalable inversion</i> . The former gets several latent codes in the inversion, while the latter additionally compresses and transmits a shallow compact feature to support visual reconstruction. Experimental results demonstrate the superiority of our method in both human vision tasks, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> . image reconstruction, and machine vision tasks, including semantic parsing and attribute prediction.