Multiple Coding Research Articles

Effect of timeframes to define long term conditions and sociodemographic factors on prevalence of multimorbidity using disease code frequency in primary care electronic health records: retrospective study

ObjectiveTo determine the extent to which the choice of timeframe used to define a long term condition affects the prevalence of multimorbidity and whether this varies with sociodemographic factors.DesignRetrospective study...

Abstract TP63: Eliminate Delays: Utility of a Cross-Trained Nurse Responder Team in Acute Stroke

Background: Over the past year, it was noted that having two separate teams (Rapid Response (RRT) and Code Stroke) delayed the care of multiple stroke patients. Challenges encountered included: waiting for the Code Stroke Team to arrive, delays in essential stroke care metrics (door to needle, door to groin, & door to start of device), and waiting for Interventional Radiology (IR) personnel to begin IR procedures. Purpose: The purpose of this project was to determine if a cross-trained Nurse Responder Team would decrease the time to essential nursing stroke care interventions and wait times to neuro-interventional acute stroke treatment. Methods: Utilizing the Plan-Do-Check-Act quality improvement method, we cross-trained our Rapid Response Nurses to various types of emergency responses including Code Stroke. Thus, the evolution a Rapid Response Team to a Nurse Responder Team. Training consisted of on-line learning management system courses, preceptorship, and simulation training. Data was collected and analyzed at various times throughout the Code Stroke process. Time markers collected included: time RRT call was changed to Code Stroke, time the Stroke Team arrived, and time between when a Code Stroke patient arrived in IR without an available IR nurse to initial groin puncture. Results: Implementing a multiple code cross-trained Nurse Responder Team reduced the need to call another nursing response team to begin the Code Stroke process. This resulted in a decrease in treatment times, the number of patient hand-offs, wait times for IR endovascular procedures, door to needle time, door to groin time and door to start of device time. The median door to needle time before the nurse responder team was 90 minutes and after the nurse responder team the median was 52.5. The before median door to groin time was 104 minutes and after door to groin time was 91.3. The percentage of time, the door to start of device within 60 minutes for patients transferred from outside hospital or 90 minutes in presented directly, was increased from 16.7 to 53.8% with initiation of the Nurse Responder Team. Conclusions: A cross-trained Nurse Responder Team improved stroke quality indicators.

A construction of multiple Z-complementary code sets with inter-set low correlation

This paper presents a construction of multiple Z-complementary code sets (ZCCSs) of prime power length with low inter-set cross-correlation values using extended generalized Boolean functions (EGBFs). By collecting the proposed multiple Z-complementary code sets (ZCCSs), a low correlation zone complementary sequence set (LCZ-CSS) with new parameters is also achieved as a byproduct of this construction. Furthermore, we propose a new multi-cell multi-carrier code-division multiple-access (MC-CDMA) system for the downlink scenario, which has the ability to reduce multiple access interference (MAI) completely and decrease inter-cell interference (ICI) to a very low level in quasi-synchronous (QS) scenarios. Similarly, the proposed code can also be used for uplink MC-CDMA system. We provide the bit error rate (BER) performance of the proposed system and compared with the traditional system model. Moreover, we demonstrate that some of the existing constructions are special cases of the proposed construction.

Transmission of Physical Layer Network Coding Based on Massive MIMO over Millimeter Wave Channel

Massive Multiple Input Multiple Output system and physical layer network coding (PNC) are two important technologies that are considered in new generation networks. In this paper we investigate the effect of increasing the number of antenna elements at user nodes and relay node in the presence of PNC. Two-way wireless relay transmission is considered in conjunction with massive number of antennas at the relay node assuming millimeter wave (mmWave) band channel environment. End-to-end transmission is considered using 3-D QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) channel model. The performance measures used are the bit error rate (BER) and throughput. Up to 100% increase in throughput of PNC coded system is obtained. The BER performance is improved only when the number of relay node antennas is much higher than that of the user node. Combining mMIMO with PNC gives better throughput without affecting the BER at high SNR. This is achieved with reasonable number of antennas at the user nodes.

PRIMIS: Privacy-preserving medical image sharing via deep sparsifying transform learning with obfuscation

Objective:The primary objective of our study is to address the challenge of confidentially sharing medical images across different centers. This is often a critical necessity in both clinical and research environments, yet restrictions typically exist due to privacy concerns. Our aim is to design a privacy-preserving data-sharing mechanism that allows medical images to be stored as encoded and obfuscated representations in the public domain without revealing any useful or recoverable content from the images. In tandem, we aim to provide authorized users with compact private keys that could be used to reconstruct the corresponding images. Method:Our approach involves utilizing a neural auto-encoder. The convolutional filter outputs are passed through sparsifying transformations to produce multiple compact codes. Each code is responsible for reconstructing different attributes of the image. The key privacy-preserving element in this process is obfuscation through the use of specific pseudo-random noise. When applied to the codes, it becomes computationally infeasible for an attacker to guess the correct representation for all the codes, thereby preserving the privacy of the images. Results:The proposed framework was implemented and evaluated using chest X-ray images for different medical image analysis tasks, including classification, segmentation, and texture analysis. Additionally, we thoroughly assessed the robustness of our method against various attacks using both supervised and unsupervised algorithms. Conclusion:This study provides a novel, optimized, and privacy-assured data-sharing mechanism for medical images, enabling multi-party sharing in a secure manner. While we have demonstrated its effectiveness with chest X-ray images, the mechanism can be utilized in other medical images modalities as well.

Exploring private sector perspectives on barriers and facilitators in availing tuberculosis care cascade services: a qualitative study from the Indian state

IntroductionThe private sector plays an important role in tuberculosis (TB) elimination by providing access to quality TB care services like diagnosis and treatment, advocacy for preventive measures, innovation to address challenges in TB elimination, vaccines etc. The study aims to understand the perspectives of private practitioners on patients’ TB care cascade to reinforce existing interventions by assuring the quality of care to TB patients.MethodsThe study utilized a qualitative design through in-depth interviews of private practitioners and was conducted in Ranchi and Purbi Singhbhum District of Jharkhand State from March-August 2021. The pilot-tested, semi-structured, open-ended interview guide questionnaire collected information from private practitioners on various aspects of the TB care cascade. The data from the provider interviews were transcribed into multiple codes and themes on the TB program. An inductive analysis was carried out with a focus on content credibility to eliminate bias. Ethical approval was received from the Institutional Ethics Committee of the Indian Institute of Public Health Gandhinagar (IIPHG), India. Written consent was taken from the private practitioners involved in the study. ResultIn-depth interviews of 17 private practitioners reveal various factors contributing to delays in TB care cascades, especially delay in access to TB diagnosis and TB Care, delay in providing treatment once after diagnosis and poor adherence to the TB treatment. According to the perception of private practitioners, there was an array of client, provider and system side factors affecting the TB care cascade gaps positively and negatively. Positive aspects mainly emerged from interviews: strong governance, consistent supply chain management, innovative PPP models and financial schemes reducing out-of-pocket expenditure (OOPE). Various factors affecting the TB care cascade negatively include awareness among the patient, socio-economic status, approach and decision-making power of providers, adverse effects of drugs, staff capacity building, etc. ConclusionsEngaging private practitioner in TB elimination efforts is critical to achieving global targets and reducing the burden of TB. The study helps to determine geography-specific barriers and facilitators of the TB care cascade to achieve the aim of providing universal access to TB healthcare with the inclusion of private practitioners.

Tighter list-size bounds for list-decoding and recovery of folded Reed-Solomon and multiplicity codes

Tighter list-size bounds for list-decoding and recovery of folded Reed-Solomon and multiplicity codes

Detection and Recognition of Multiple QR Codes Based on YOLO_CBAM Algorithm

Detection and Recognition of Multiple QR Codes Based on YOLO_CBAM Algorithm

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.

Detection and recognition of multiple QR codes based on YOLO_CBAM algorithm

Detection and recognition of multiple QR codes based on YOLO_CBAM algorithm

IMAGE ENCRYPTION TECHNIQUE BASED ON A BINARY COMBINATION OF MULTIPLE CHAOTIC MAPS AND DNA SEQUENCE OPERATIONS

The huge advance of digital communication and networks has led to enormous storage and transmission of information over public networks. Nevertheless, the assurance of information security remains incomplete across these unsecured networks. Digital images are the primary means for sharing information over open networks. Consequently, the confidentiality of digital images during storage and transmission has become a crucial concern, particularly when sharing sensitive information. Image encryption has emerged as a solution to this problem. This paper presents an image encryption technique based on multiple one-dimensional chaotic maps and DNA coding. The method employs three one-dimensional chaotic maps, including the Logistic map, Tent map, and piecewise map, multiple times to produce 18 random sequences with different initial values and parameters. SHA-512 hash function is used to indicate the initial values of chaotic maps. For encrypting images, the binary elements from various sequences of chaotic maps are amalgamated to alter the pixel intensities of the image in the diffusion process. Dynamic DNA coding is performed through a random selection of DNA rules and operations (XOR, XNOR, and Addition) to each pixel in the image. The technique is enforced using circular rotations which are applied randomly to each key. The proposed technique is evaluated using many standard images. Different performance metrics have been measured. The empirical findings illustrate the security and resilience of the suggested method and its ability to resist statistical and differential attacks.

On the impact of multiple source code representations on software engineering tasks — An empirical study

Efficiently representing source code is crucial for various software engineering tasks such as code classification and clone detection. Existing approaches primarily use Abstract Syntax Tree (AST), and only a few focus on semantic graphs such as Control Flow Graph (CFG) and Program Dependency Graph (PDG), which contain information about source code that AST does not. Even though some works tried to utilize multiple representations, they do not provide any insights about the costs and benefits of using multiple representations. The primary goal of this paper is to discuss the implications of utilizing multiple source code representations, specifically AST, CFG, and PDG. We modify an AST path-based approach to accept multiple representations as input to an attention-based model. We do this to measure the impact of additional representations (such as CFG and PDG) over AST. We evaluate our approach on three tasks: Method Naming, Program Classification, and Clone Detection. Our approach increases the performance on these tasks by 11% (F1), 15.7% (Accuracy), and 9.3% (F1), respectively, over the baseline. In addition to the effect on performance, we discuss timing overheads incurred with multiple representations. We envision that this work can provide a base for researchers to explore and experiment with a variety of source code representations for software engineering tasks.

MULTIMODAL UKRAINIAN BRAND NARRATIVE: SEMIOTICS, STRUCTURE, ARCHETYPES

The aim of the study is to identify the structural-narrative, semiotic, and archetypal properties of the Ukrainian multimodal narrative as a semiotic space of secondary signification and social mythologization. The data for analysis include slogans and promotional multimodal videos (video narratives) of the Ukrainian brand “Золотий вік” (Golden Age). Based on multimodal research, semiotics and advertising mythology theories, as well as the theories of cultural archetypes, and utilizing multimodal, narrative, narrative-semiotic, and archetypal analysis, in conjunction with conceptual integration tools, the article has achieved the following key results. The Ukrainian brand narrative is a multimodal discursive construct formed by a combination of multiple semiotic codes realized through verbal and non-verbal sign systems via auditory and visual channels. The modules are integrated through multimodal video narratives, constructing a semiotic world integrated with the secondary signified “love” and the associated concepts that replace the denotative meaning of the brand as a jewelry company and its products as ornaments. The secondary signified is verbalized through slogans, visualized through plots, voiced by background songs or voice-over narrators, and encoded by cultural codes in their intertextual and archetypal aspects. Multimodal video-narratives, featuring various characters, narrative plots, and formal-narrative structures, exhibit isomorphism with respect to the possible worlds they construct, archetypal images, motifs, and characters, as well as analogous narrative plots with differing levels of reduction in structural narrative elements. The verbal module, based on a slogan, as well as invariant auditory accompaniment common to all video narratives – the song “Love” and off-screen narrative, supports a hermeneutic code because it contains a key metaphor based on the slogan and peripheral metaphorical components that reveal the conceptual features of its target space. The audio-visual module forms a proaritic code based on the narrative plots of advertising clips in a three-component possible world: extratextual frame narrative, textual pseudoreal narrative, and fairytale narrative. The cultural code is realized through various multimodal resources. The slogan and the brand name include explicit references to the source intertext based on the song. In the video narratives, techniques of interdiscursivity are used, combining elements of melodrama, a romantic story, and a fairy tale, as well as references to archetypal images, motifs, and elements of the archetypal cyclical time. Central to these are the archetypal images of dreams, magic, hearts, and motifs of the magical helper-giver, the journey, crossroads, and magical transformation of those who receive a branded gift. The main archetypes are those of gold and the ring-circle, associated with the symbolism of the sun. Cyclical temporality, associated with mythological time, is actualized by recurring motifs and underpins the unity of love and preciousness from the perspective of the connotations of “eternity” – as eternal spiritual and material values. The semantic code of connotations is related to the secondary signification meanings, which associate the brand’s products with “embodied” love and is based on all the brand’s narrative modules, constructing its social mythology. The symbolic code is based on archetypal symbols and the core value of the brand in its implicit opposition to values foreign to the brand, appealing to the motivational value of “love and the need for belonging” in the hierarchy of human motivations. The perspective for further research is the analysis of the pragmatics of multimodal narratives in Ukrainian brands.

NOEMA reveals the true nature of luminous red JWST z &gt; 10 galaxy candidates

The first year of JWST has revealed a surprisingly large number of luminous galaxy candidates beyond z &gt; 10. While some galaxies have already been spectroscopically confirmed, there is mounting evidence that a subsample of the candidates with particularly red inferred UV colours are, in fact, lower redshift contaminants. These interlopers are often found to be ‘HST-dark’ or ‘optically faint’ galaxies at z ∼ 2 − 6, a population that is key to improving our understanding of dust-obscured star formation throughout cosmic time. This paper demonstrates the complementarity of ground-based mm-interferometry and JWST infrared imaging to unveil the true nature of red 1.5–2.0 μm dropouts that have been selected as ultra-high-redshift galaxy candidates. We present NOEMA Polyfix follow-up observations of four JWST red 1.5–2.0 μm dropouts selected by Yan et al. (ApJ, 942, L8) as ultra-high-redshift candidates in the PEARLS-IDF field. The new NOEMA observations constrain the rest-frame far-infrared continuum emission and efficiently discriminate between intermediate- and high-redshift solutions. We report &gt; 10σ NOEMA continuum detections of all our target galaxies at observed frequencies of ν = 236 and 252 GHz, with FIR slopes indicating a redshift of z &lt; 5. We modelled their optical-to-FIR spectral energy distribution (SED) with multiple SED codes, finding that they are not z &gt; 10 galaxies but dust-obscured, massive star-forming galaxies at z ∼ 2 − 4 instead. The contribution to the cosmic star formation rate density (CSFRD) of such sources is not negligible at z ≃ 3.5 (ϕ ≳ (1.9 − 4.4) × 10−3 cMpc−3; or &gt; 3 − 6% of the total CSFRD), in line with previous studies of optically faint and sub-millimeter galaxies. This work showcases a new way to select intermediate- to high-redshift dust-obscured galaxies in JWST fields with minimal wavelength coverage. This approach opens up a new window onto obscured star formation at intermediate redshifts, whilst removing contaminants with red colours from searches at ultra-high redshifts.

BSMArt: Simple and fast parameter space scans

We introduce BSMArt, a python program for the exploration of parameter spaces of theories Beyond the Standard Model. Especially designed for use with the SARAH family of tools, it is also sufficiently flexible to be used with a wide variety of external codes. BSMArt contains the first public release of the Active Learning scan by the same authors; but contains several additional scanning algorithms, ranging from the very simple to MultiNest and Diver. A BSMArt scan can be set up in a matter of minutes with only minimal editing of configuration files; installation scripts for all relevant tools and examples are provided. Program summaryProgram Title: BSMArtCPC Library link to program files:https://doi.org/10.17632/f6kwjvg8gw.1Developer's repository link:https://goodsell.pages.in2p3.fr/bsmart/Licensing provisions: GNU General Public License 3Programming language: pythonNature of problem: Exploring the parameter spaces of new physics models involves setting up, compiling and running multiple codes together. Then an algorithm must be chosen to select which parameter points to inspect in the simplest and quickest manner. Further, this code is required for the active machine learning algorithm by the same authors.Solution method: Automatic creation and compilation of the codes integrated with SARAH, and simple creation and management of input and output files allowing multithreaded running. Use of python facilitates machine learning applications. Multiple search algorithms are included including original ones.

Assessing shielding material Performance: Benchmarking of Monte Carlo codes for oil shale and Basalt-Boron fiber concretes

Cement-based concretes are commonly used for managing radioactive waste due to their low cost and radiation shielding properties. However, the potential of using oil shale ash as an additive in waste packaging material has been overlooked. This study focuses on benchmarking and developing a Monte Carlo based modeling methodology using multiple transport codes (MCNP, SERPENT, SCALE, OpenMC, and EGSnrc) to assess the effects of these additives on the gamma and neutron shielding properties of concrete. The cross-code comparison showed that all transport codes are in excellent agreement with each other. Investigations into oil shale ash demonstrated similar properties to fly ash. The addition of oil shale ash had a negligible effect on low-level waste (LLW) gamma shielding properties and a minor negative effect on neutron shielding properties. The addition of basalt-boron fibers indicated a minor negative effect on LLW gamma shielding properties but a significant positive effect on neutron shielding properties. The presence of basalt-boron fibers considerably decreased the photon flux resulting from the activation of concrete. In conclusion, this study offers valuable insights into utilizing radiation transport codes to analyze the interactions between radiation particles and innovative concrete additives.

Function-Level Code Obfuscation Detection Through Self-Attention-Guided Multi-Representation Fusion

Malware developers often employ code obfuscation techniques to conceal their malicious functionality, making it challenging to detect and analyze such software. While various de-obfuscation techniques exist, the majority of them require prior knowledge of the obfuscation tools and techniques in use. Identifying the specific obfuscation tools or algorithms applied to the obfuscated code is thus of vital importance, which, however, typically demands in-depth expert knowledge and substantial efforts. Therefore, this paper presents DeObA, a deep learning (DL) driven approach for the precise and efficient detection of obfuscation algorithms on the fine-grained function-level code snippets. To comprehensively capture unique patterns or features of different obfuscation algorithms from code, DeObA works on multiple distinct code views, encompassing token sequences, abstract syntax trees (AST) and program dependency graphs (PDG), which will reflect the code’s lexical morphology, syntactic and structural aspects. After individually collecting obfuscation-indicative features with well-matched DL encoder from each code view, a self-attention-based fusion strategy is performed on these features to produce an integrated, dense, yet feature-rich vector. This vector is then fed into a softmax classification layer for prediction. Due to the lack of a moderately sized dataset, a large obfuscation corpus is curated with 7 different obfuscation tools and a total of 12 obfuscation algorithms on 39,070 C/C[Formula: see text] functions. The experimental evaluations conducted on the dataset exhibit a distinguished detection performance of DeObA, which achieve accuracy rates of 99.90% and 99.19% on the obfuscation tool detection and obfuscation algorithm detection tasks, respectively. The ablation study also confirms the active role of considering multiple distinct code views and the effectiveness of the designed self-attention-based fusion strategy.

CPT 2024: Reporting Unlisted Procedure Codes

Current Procedural Terminology (CPT®) includes multiple sections and categories of codes to report services. However, when a service is provided in a manner that is not accurately described by a specific code, unlisted procedure codes are reported. CPT 2024 brings new guidelines for appropriate use of unlisted procedure codes. This article reviews the guidelines for reporting unlisted procedure codes, including the following topics: Identifying and locating unlisted procedure codes Reporting unlisted procedure codes in conjunction with Category I and/or Category III codes Reporting multiple unlisted codes Using modifiers with unlisted procedure codes

Concatenative Complete Complementary Code Division Multiple Access and Its Fast Transform

Over multipath channels, complete complementary code division multiple access and convolutional spreading code division multiple access provide inter-channel interference free transmission with an enhanced spectral efficiency. However, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">convolutional spreading</i> (CS) operation of the systems is computationally complex and involves a high peak-to-average power ratio. To address such issues, we propose the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">concatenative complete complementary code</i> (CCCC) division multiple access, named (CCC-CDMA). Since the CCCCs can be generated from the rows of the Walsh-Hadamard or discrete Fourier transform matrices, the CS operation can be implemented using corresponding fast transforms to reduce computational complexity. Simulation results show that the enlargement of the spreading factor strengthens the robustness against clipping noise. The binary CCCC generated by Walsh-Hadamard matrix exhibited excellent robustness against Doppler frequency shifts.

Retracted: FastQR: Fast Pose Estimation of Objects Based on Multiple QR Codes and Monocular Vision in Mobile Embedded Devices

Retracted: FastQR: Fast Pose Estimation of Objects Based on Multiple QR Codes and Monocular Vision in Mobile Embedded Devices