Relevant bibliographies by topics / Codes

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Codes'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Codes"

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Mitra, Indu, Tass Malik, Jarrod J. Homer, and Sean Loughran. "Audit of Clinical Coding of Major Head and Neck Operations." Annals of The Royal College of Surgeons of England 91, no. 3 (April 2009): 245–48. http://dx.doi.org/10.1308/003588409x391884.

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INTRODUCTION Within the NHS, operations are coded using the Office of Population Censuses and Surveys (OPCS) classification system. These codes, together with diagnostic codes, are used to generate Healthcare Resource Group (HRG) codes, which correlate to a payment bracket. The aim of this study was to determine whether allocated procedure codes for major head and neck operations were correct and reflective of the work undertaken. HRG codes generated were assessed to determine accuracy of remuneration. PATIENTS AND METHODS The coding of consecutive major head and neck operations undertaken in a tertiary referral centre over a retrospective 3-month period were assessed. Procedure codes were initially ascribed by professional hospital coders. Operations were then recoded by the surgical trainee in liaison with the head of clinical coding. The initial and revised procedure codes were compared and used to generate HRG codes, to determine whether the payment banding had altered. RESULTS A total of 34 cases were reviewed. The number of procedure codes generated initially by the clinical coders was 99, whereas the revised codes generated 146. Of the original codes, 47 of 99 (47.4%) were incorrect. In 19 of the 34 cases reviewed (55.9%), the HRG code remained unchanged, thus resulting in the correct payment. Six cases were never coded, equating to £15,300 loss of payment. CONCLUSIONS These results highlight the inadequacy of this system to reward hospitals for the work carried out within the NHS in a fair and consistent manner. The current coding system was found to be complicated, ambiguous and inaccurate, resulting in loss of remuneration.
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Skorokhod, Sergey, and Andrey Barlit. "Software optimization for fast encoding and decoding of Reed-Solomon codes." Telfor Journal 14, no. 2 (2022): 56–60. http://dx.doi.org/10.5937/telfor2202056s.

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In this work, we propose a software library written in C for encoding and decoding Reed-Solomon codes. Library consists of one scalar CODEC and two vectorized codecs for x86 architecture. Vectorized codecs use the benefits of SSSE3 or AVX2 instruction sets. We compare the performance of our three codecs with the JPWL RS CODEC from the Open JPEG library. The performance comparison methodology is described, and it is based on the measuring of the encoding and decoding speed. The results demonstrate a 4.1x speed gain with the scalar CODEC and a 19.6x gain with the vectorized CODEC. Based on testing results and supported instruction sets, a dynamic selection of CODEC version is proposed.
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P, Shahnas. "Performance Analysis of Regular and Irregular LDPC Codes on SPIHT Coded Image Data." International Journal of Computer Communication and Informatics 2, no. 2 (October 30, 2020): 1–5. http://dx.doi.org/10.34256/ijcci2021.

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The LDPC (Low Density Parity Check Code) has Shown interesting results for transmitting embedded bit streams over noisy communication channels. Performance comparison of regular and irregular LDPC codes with SPIHT coded image is done here. Different Error Sensitive classes of image data are obtained by using SPIHT algorithm as an image coder. Irregular LDPC codes map the more important class of data into a higher degree protection class to provide more protection. Different degree protection classes of an LDPC code improves the overall performance of data transmission against channel errors. Simulation results show the superiority of irregular LDPC over regular LDPC codes.
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Glory, V., and S. Domnic. "Re-Ordered FEGC and Block Based FEGC for Inverted File Compression." International Journal of Information Retrieval Research 3, no. 1 (January 2013): 71–88. http://dx.doi.org/10.4018/ijirr.2013010105.

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Data compression has been widely used in many Information Retrieval based applications like web search engines, digital libraries, etc. to enable the retrieval of data to be faster. In these applications, universal codes (Elias codes (EC), Fibonacci code (FC), Rice code (RC), Extended Golomb code (EGC), Fast Extended Golomb code (FEGC) etc.) have been preferably used than statistical codes (Huffman codes, Arithmetic codes etc). Universal codes are easy to be constructed and decoded than statistical codes. In this paper, the authors have proposed two methods to construct universal codes based on the ideas used in Rice code and Fast Extended Golomb Code. One of the authors’ methods, Re-ordered FEGC, can be suitable to represent small, middle and large range integers where Rice code works well for small and middle range integers. It is also competing with FC, EGC and FEGC in representing small, middle and large range integers. But it could be faster in decoding than FC, EGC and FEGC. The authors’ another coder, Block based RFEGC, uses local divisor rather than global divisor to improve the performance (both compression and decompression) of RFEGC. To evaluate the performance of the authors’ coders, the authors have applied their methods to compress the integer values of the inverted files constructed from TREC, Wikipedia and FIRE collections. Experimental results show that their coders achieve better performance (both compression and decompression) for those files which contain significant distribution of middle and large range integers.
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Albagmi, Salem. "Impact of Inaccurate Clinical Coding on Financial Outcome: A Study in a local hospital in Najran, Saudi Arabia." F1000Research 13 (July 22, 2024): 820. http://dx.doi.org/10.12688/f1000research.149154.1.

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Background Coding in medical procedures is crucial for patients, and errors made by hospital administration during the coding process can have an impact on both the financial results and the course of therapy. The present study aims to assess the accuracy of diagnostic and procedural codes as recorded by the hospital’s coders and to also evaluate their impact on the hospital’s revenue. Methods In a local hospital in Najran, Saudi Arabia, a cross-sectional observational analysis was conducted on patients with a clinical coder. The percentage of precision and error following the re-coding of cases was calculated using a statistical analysis. Results Primary diagnosis was incorrectly coded in 57 (26 per cent) records, and secondary diagnosis was incorrectly coded in 21 (9.9 per cent) records. Inaccurate medical labelling has been seen in emergency rooms, operating rooms, and gynaecology facilities. Discussion The percentage of records with the most incorrect coding was found to be 16 (7.5 per cent) in the emergency room, 10 (4.7 per cent) in the surgical clinic, and 5 (2.3 per cent) in the gynaecology/OBS clinic. Six (2.8 per cent) records in the private clinic had inaccurate secondary diagnoses, followed by four (1.9 per cent) and two (1 per cent) records in nephrology. Conclusion The percentage of inaccurate clinical codes in primary diagnoses reached (26.8 per cent) and the percentage of incorrect clinical codes in secondary diagnoses reached (9.9 per cent).
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Ma, Shang-Chih. "Trellis-Coded Multilevel Coset Codes." IETE Journal of Research 65, no. 6 (April 9, 2018): 887–90. http://dx.doi.org/10.1080/03772063.2018.1454346.

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Abdulla, Suha, Natalie Simon, Kelvin Woodhams, Carla Hayman, Mohamed Oumar, Lucy Rose Howroyd, and Gulshan Cindy Sethi. "Improving the quality of clinical coding and payments through student doctor–coder collaboration in a tertiary haematology department." BMJ Open Quality 9, no. 1 (March 2020): e000723. http://dx.doi.org/10.1136/bmjoq-2019-000723.

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Hospitals within the UK are paid for services provided by ‘Payment-by-Results’. In a system that rewards productivity, effective collaboration between coders and clinicians is crucial. However, clinical coding is frequently error prone and has been shown to impact negatively on departmental revenue. Our aim was to increase the median number of diagnostic codes per sickle cell inpatient admission at Guy’s Hospital by 3. Three interventions were implemented using the Plan, Do, Study, Act structure. This consisted of student doctors searching for diagnoses along with comorbidities that clinical coders had missed, distributing laminated cards with common clinical codes and implementing discharge pro formas. Through auditing, student doctors generated a total of £58 813 over 16 weeks. We observed an increase in the median number of codes by ≥2 additional codes. We improved coding accuracy where we identified errors in an average of 32.5% of admissions each month, improving the quality of patient documentation. We have demonstrated student doctor involvement in clinical coding as a potentially sustainable means of achieving accurate payment for services provided; increasing departmental revenue. We are the first to report the efficacy of student–coder collaboration in improving the accuracy of clinical coding.
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Ma, X., and L. Ping. "Coded Modulation Using Superimposed Binary Codes." IEEE Transactions on Information Theory 50, no. 12 (December 2004): 3331–43. http://dx.doi.org/10.1109/tit.2004.838104.

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Robertson, P., and T. Wörz. "Coded modulation scheme employing turbo codes." Electronics Letters 31, no. 18 (August 31, 1995): 1546–47. http://dx.doi.org/10.1049/el:19951064.

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Syafrawati, Syafrawati, Rizanda Machmud, Prof Syed Mohammed Aljunid, and Rima Semiarty. "INCIDENCE AND ROOT CAUSE OF UPCODING IN THE IMPLEMENTATION OF SOCIAL HEALTH INSURANCE IN RURAL PROVINCE HOSPITAL IN INDONESIA." Asia Pacific Fraud Journal 5, no. 1 (June 20, 2020): 56. http://dx.doi.org/10.21532/apfjournal.v5i1.135.

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Upcoding is one of important indicators of moral hazard and fraud in Social Health Insurance scheme. However, there seems to be little evidence about incidence of upcoding and how upcoding occurs in hospital, especially in rural province hospital. The objective of this study is to determine incidence and root cause of upcoding in the implementation of Social Health Insurance in Rural Province Hospital in Indonesia. The data used in this study were both qualitative and quantitative data (mixed method). Three hundred and sixty (360) inpatient medical records from six rural province hospitals were examined in this study. Diagnosis and procedure codes recorded in these medical records were re-coded by an independent senior coder (ISC). Codes from hospitals’ coders and codes from ISC were then re-grouped using INA-CBG casemix grouper to determine the casemix groups and the hospital tariffs. If the hospital tariff obtained by hospital coder is higher than that obtained by ISC, it is considered as upcoding. This qualitative study was conducted using Focus Group Discussion (FGD) and in-depth interviews in hospitals located in a rural province of Indonesia. In depth interview was held for two hospital directors and two officers from the Social Security Administrator (Indonesia: BadanPenyelenggaraJaminanSosial/BPJS), an agent that manages the Statutory Health Insurance (SHI). Six clinicians and six coders attended the FGD. We asked open-ended questions about their perceptions on upcoding in hospitals. The interviews were recorded and transcribed verbatim. The transcripts were then thematically analyzed. Upcoding cases were found in 11.9% (43/360) medical records. Upcoding cases were dominated by Deliveries Group 2.8% (10/360) and Female reproductive system Groups 1.7% (6/360). The potential loss of income due to upcoding was IDR 154.626.000 or 9% of hospital revenue. Appointment of non-medical doctors as internal verifiers, lack of clear coding guidelines, lack of training for doctors and coders, and poor coordination between hospital and BPJS to resolve coding disagreement were root causes of upcoding in hospital. Policies to prevent and manage upcoding should be urgently developed and implemented in the Statutory Health Insurance (SHI) program in Indonesia especially to prepare upcoding guidelines, enhance medical coding trainingregularly, increase number of coders and verification staff from medical background, and strengthen coordination for coding problem solving in hospital.
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Dissertations / Theses on the topic "Codes"

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Xu, Danfeng. "Iterative coded multiuser detection using LDPC codes." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27939.

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Multiuser detection (MUD) has been regarded as an effective technique for combating cochannel interference (CCI) in time-division multiple access (TDMA) systems and multiple access interference (MAI) in code-division multiple access (CDMA) systems. An optimal multiuser detector for coded multiuser systems is usually practically infeasible due to the associated complexity. An iterative receiver consisting of a soft-input soft-output (SISO) multiuser detector and a bank of SISO single user decoders can provide a system performance which approaches to that of single user system after a few iterations. In this thesis, MUD and LDPC decoding are combined to improve the multiuser receiver performance. The soft output of the LDPC decoder is fed back to the multiuser detector to improve the detection. This leads to decision variables that have a smaller MAI component. These decision variables are then returned to the decoder and the decoding process benefits from the improvement to the decision variables. The process can be repeated many times. The resulting iterative multiuser receiver is designed based on the soft parallel interference cancellation (PIC) algorithm. For the interference reconstruction, the LDPC decoder is improved to produce the log-likelihood ratios (LLR) of the information bits as well as the parity bits. A sub-optimal approach is proposed to output the LLR of the parity bits with very low complexity. Thanks to the powerful error-correction ability of the LDPC decoder, the LDPC multiuser receiver can achieve a satisfactory convergence, and substantially outperforms non-iterative receivers. Three types of SISO multiuser detectors are provided. They are: Soft Interference Cancellation (SIC) detector, SISO decorrelating detector and SISO minimum mean square error (MMSE) detector. The resulting system performance converges very quickly. The comparison of these three types of detectors is also shown in this thesis.
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Ozadam, Hakan. "Repeated-root Cyclic Codes And Matrix Product Codes." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615304/index.pdf.

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We study the Hamming distance and the structure of repeated-root cyclic codes, and their generalizations to constacyclic and polycyclic codes, over finite fields and Galois rings. We develop a method to compute the Hamming distance of these codes. Our computation gives the Hamming distance of constacyclic codes of length $np^s$ in many cases. In particular, we determine the Hamming distance of all constacyclic, and therefore cyclic and negacyclic, codes of lengths p^s and 2p^s over a finite field of characteristic $p$. It turns out that the generating sets for the ambient space obtained by torsional degrees and strong Groebner basis for the ambient space are essentially the same and one can be obtained from the other. In the second part of the thesis, we study matrix product codes. We show that using nested constituent codes and a non-constant matrix in the construction of matrix product codes with polynomial units is a crucial part of the construction. We prove a lower bound on the Hamming distance of matrix product codes with polynomial units when the constituent codes are nested. This generalizes the technique used to construct the record-breaking examples of Hernando and Ruano. Contrary to a similar construction previously introduced, this bound is not sharp and need not hold when the constituent codes are not nested. We give a comparison of this construction with a previous one. We also construct new binary codes having the same parameters, of the examples of Hernando and Ruano, but non-equivalent to them.
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Al, Kharoosi Fatma Salim Ali. "Describing quaternary codes using binary codes." Thesis, Queen Mary, University of London, 2011. http://qmro.qmul.ac.uk/xmlui/handle/123456789/1312.

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For a quaternary code C of length n, de ne a pair of binary codes fC1;C2g as: -C1 = C mod 2 -C2 = h(C \ 2Zn 4 ) where h is a bijection from 2Z4 to Z2 mapping 0 to 0 and 2 to 1 and for the extension to a map acting coordinatewise. Here C1 C2. For a pair of binary codes fC1;C2g with C1 C2, let C(C1;C2) be the set of Z4-codes giving rise to this binary pair as de ned above. Our main goal is to describe the set C(C1;C2) using the binary pair of codes fC1;C2g. In Chapter 1, we give some preliminaries. In Chapter 2, we start with a general description of codes fC1;C2g which give cardinality of C(C1;C2). Then we show that C(C1;C2) ' C 1 Zn 2 =C2. The cohomology of C(C1;C2) is given in Section (2:2). Then we end chapter 2 with a description of dual codes of C(C1;C2). Chapter 3 is about weight enumerators of codes in C(C1;C2). The average swe is given in terms of weight enumerators of C1 and C2 in Section(3:1) as swe(x; y; z) = jC2j 2n (weC1(x + z; 2y) (x + z)n) + weC2(x; z) Detailed computations of swe's of codes in C(C1;C2) using codes fC1;C2g is then given. Information about di erent weight enumerators of codes in C(C1;C2) is given in Section (3:2). These weight enumerators are included in an a ne space of polynomials. Then we end chapter 3 with a description of weight enumerators of self dual codes. Chapter 4 deals with actions of 2 the automorphism group G = Aut(C1) \ Aut(C2) Sn on C(C1;C2) which preserves cwe of codes. Corresponding action on C 1 Zn 2 =C2 is explained in this chapter. Changing signs of coordinates can be de ned as an action of Zn 2 on C(C1;C2). This action preserves swe of codes. Corresponding action on C 1 Zn 2 =C2 is provided in this chapter. In the appendix, we give a complete description of Z4-codes in C(C1;C2) with C1 = C2 = Extended Hamming Code of length 8. A programming code in GAP for computing derivations is given. And a description of the a ne space containing the swe's of Z4-codes is given with examples of di erent C1 = C2 having same weight enumerator.
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Skoglund, Isabell. "Reed-Solomon Codes - Error Correcting Codes." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-97343.

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In the following pages an introduction of the error correcting codes known as Reed-Solomon codes will be presented together with different approaches for decoding. This is supplemented by a Mathematica program and a description of this program that gives an understanding in how the choice of decoding algorithms affect the time it takes to find errors in stored or transmitted information.
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Harrington, James William Preskill John P. "Analysis of quantum error-correcting codes : symplectic lattice codes and toric codes /." Diss., Pasadena, Calif. : California Institute of Technology, 2004. http://resolver.caltech.edu/CaltechETD:etd-05122004-113132.

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Xia, Bo. "Importance sampling for LDPC codes and turbo-coded CDMA." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/290093.

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Low-density parity-check (LDPC) codes have shown capacity-approaching performance with soft iterative decoding algorithms. Simulating LDPC codes at very low error rates normally takes an unacceptably long time. We consider importance sampling (IS) schemes for the error rate estimation of LDPC codes, with the goal of dramatically reducing the necessary simulation time. In IS simulations, the sample distribution is biased to emphasize the occurrence of error events and efficiency can be achieved with properly biased sample distributions. For LDPC codes, we propose an IS scheme that overcomes a difficulty in traditional IS designs that require codebook information. This scheme is capable of estimating both codeword and bit error rates. As an example, IS gains on the order of 105 are observed at a bit error rate (BER) of 10-15 for a (96, 48) code. We also present an importance sampling scheme for the decoding of loop-free multiple-layer trees. This scheme is asymptotically efficient in that, for an arbitrary tree and a given estimation precision, the required number of simulations is inversely proportional to the noise standard deviation. The motivation of this study is to shed light on an asymptotically efficient IS design for LDPC code simulations. For an example depth-3 regular tree, we show that only 2400 simulation runs are needed to achieve a 10% estimation precision at a BER of 10-75. Similar promising results are also shown for a length-9 rate-1/3 regular code after being converted to a decoding tree. Finally, we consider a convolutionally coded CDMA system with iterative multiuser detection and decoding. In contrast to previous work in this area, a differential encoder is inserted to effect an interleaver gain. We view the CDMA channel as a periodically time-varying ISI channel. The receiver jointly decodes the differential encoders and the CDMA channel with a combined trellis, and shares soft output information with the convolutional decoders in an iterative (turbo) fashion. Dramatic gains over conventional convolutionally coded systems are demonstrated via simulation. We also show that there exists an optimal code rate under a bandwidth constraint. The performance and optimal code rates are also demonstrated via density evolution analysis.
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Tixier, Audrey. "Reconnaissance de codes correcteurs." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066554.

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Dans cette thèse, nous nous intéressons au problème de la reconnaissance de code. Ce problème se produit principalement lorsqu'une communication est observée dans un milieu non-coopératif. Une liste de mots bruités issus d'un code inconnu est obtenue, l'objectif est alors de retrouver l'information contenue dans ces mots bruités. Pour cela, le code utilisé est reconstruit afin de décoder les mots observés. Nous considérons ici trois instances de ce problème et proposons pour chacune d'elle une nouvelle méthode. Dans la première, nous supposons que le code utilisé est un turbo-code et nous proposons une méthode pour reconstruire la permutation interne (les autres éléments du turbo-codeur pouvant être facilement reconstruits grâce aux méthodes existantes). Cette permutation est reconstruite pas à pas en recherchant l'indice le plus probable à chaque instant. Plus précisément, la probabilité de chaque indice est déterminée avec l'aide de l'algorithme de décodage BCJR. Dans la seconde, nous traitons le problème de la reconnaissance des codes LDPC en suggérant une nouvelle méthode pour retrouver une liste d'équations de parité de petits poids. Celle-ci généralise et améliore les méthodes existantes. Finalement, avec la dernière méthode, nous reconstruisons un code convolutif entrelacé. Cette méthode fait appel à la précédente pour retrouver une liste d'équations de parité satisfaites par le code entrelacé. Puis, en introduisant une représentation sous forme de graphe de l'intersection de ces équations de parité, nous retrouvons simultanément l'entrelaceur et le code convolutif
In this PhD, we focus on the code reconstruction problem. This problem mainly arises in a non-cooperative context when a communication consisting of noisy codewords stemming from an unknown code is observed and its content has to be retrieved by recovering the code that is used for communicating and decoding with it the noisy codewords. We consider here three possible scenarios and suggest an original method for each case. In the first one, we assume that the code that is used is a turbo-code and we propose a method for reconstructing the associated interleaver (the other components of the turbo-code can be easily recovered by the existing methods). The interleaver is reconstructed step by step by searching for the most probable index at each time and by computing the relevant probabilities with the help of the BCJR decoding algorithm. In the second one, we tackle the problem of reconstructing LDPC codes by suggesting a new method for finding a list of parity-check equations of small weight that generalizes and improves upon all existing methods. Finally, in the last scenario we reconstruct an unknown interleaved convolutional code. In this method we used the previous one to find a list of parity-check equations for this code. Then, by introducing a graph representing how these parity-check equations intersect we recover at the same time the interleaver and the convolutional code
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Wang, Xuesong. "Cartesian authentication codes from error correcting codes /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?COMP%202004%20WANGX.

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Dicuangco, Lilibeth. "On duadic codes and split group codes." Nice, 2006. http://www.theses.fr/2006NICE4098.

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Kim, Han Jo. "Improving turbo codes through code design and hybrid ARQ." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0012169.

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Books on the topic "Codes"

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1937-, Lin Shu, and United States. National Aeronautics and Space Administration., eds. Coset codes viewed as terminated convolutional codes. [Washington, DC: National Aeronautics and Space Administration, 1996.

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Berrou, Claude, ed. Codes and Turbo Codes. Paris: Springer Paris, 2010. http://dx.doi.org/10.1007/978-2-8178-0039-4.

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Berrou, Claude. Codes and Turbo Codes. Paris: Springer-Verlag Paris, 2010.

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Nelson, Nigel. Codes. New York: Thomson Learning, 1994.

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Gerardus Joannes Maria Van Wee. Covering codes, perfect codes, and codes from algebraic curves. Helmond [Netherlands]: Wibro Dissertatiedrukkerij, 1991.

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Barker, Bruce A. The complete guide to codes for homeowners: Your photo guide to electrical codes, plumbing codes, building codes, mechanical codes. Minneapolis, Minn: Creative Pub. International, 2010.

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Barker, Bruce A. The complete guide to codes for homeowners: Your photo guide to electrical codes, plumbing codes, building codes, mechanical codes. Minneapolis, Minn: Creative Pub. International, 2010.

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(Firm), Prima Games. Codes & cheats. 2nd ed. Roseville, CA: Prima Games, 2009.

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Yang, Shenghao, and Raymond W. Yeung. BATS Codes. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-79278-6.

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Gazi, Orhan. Polar Codes. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-0737-9.

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Book chapters on the topic "Codes"

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Corsini, Piergiulio, and Violeta Leoreanu. "Codes." In Applications of Hyperstructure Theory, 257–66. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3714-1_9.

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Borucki, Lorenz. "Codes." In Digitaltechnik, 16–34. Wiesbaden: Vieweg+Teubner Verlag, 1989. http://dx.doi.org/10.1007/978-3-322-91800-0_3.

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Borucki, Lorenz. "Codes." In Digitaltechnik, 16–34. Wiesbaden: Vieweg+Teubner Verlag, 2000. http://dx.doi.org/10.1007/978-3-663-05780-2_3.

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Gosavi, Abhijit. "Codes." In Simulation-Based Optimization, 433–535. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3766-0_15.

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Borucki, Lorenz. "Codes." In Digitaltechnik, 16–34. Wiesbaden: Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-322-92704-0_3.

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Dougherty, Steven T. "Codes." In Springer Undergraduate Mathematics Series, 263–93. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56395-0_11.

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Shoenfield, Joseph R. "Codes." In Lecture Notes in Logic, 16–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-22378-9_7.

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Taillard, Éric D. "Codes." In Design of Heuristic Algorithms for Hard Optimization, 247–58. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13714-3_12.

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Fisher, Thomas. "Codes." In The Architecture of Ethics, 19–22. New York : Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9781351065740-5.

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Tsfasman, Michael, Serge Vlǎduţ, and Dmitry Nogin. "Codes." In Mathematical Surveys and Monographs, 1–68. Providence, Rhode Island: American Mathematical Society, 2007. http://dx.doi.org/10.1090/surv/139/01.

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Conference papers on the topic "Codes"

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MacKay, D. J. C. "Fountain codes." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040504.

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Pyndiah, R. "Block turbo codes: ten years later." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040505.

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Urbanke, R. "The quest for capacity-achieving codes." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040506.

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Ng, S. X. "Integrated wireless multimedia turbo-transceiver design approaching the Rayleigh channel's capacity: interpreting Shannon's lessons in the turbo-era." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040507.

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Peng, X. H. "Coding for distributed networks." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040508.

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Markarian, G. "Hierarchical modulation and DVB-S2." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040509.

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Zhao, Dongfeng, and Daoben Li. "Coded cooperation using LDPC codes." In 2009 Global Mobile Congress. IEEE, 2009. http://dx.doi.org/10.1109/gmc.2009.5295871.

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Sodha. "Code synchronization for convolutional codes." In Proceedings of Canadian Conference on Electrical and Computer Engineering CCECE-94. IEEE, 1994. http://dx.doi.org/10.1109/ccece.1994.405759.

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Pierrot, Alexandre J., and Matthieu R. Bloch. "LDPC-based coded cooperative jamming codes." In 2012 IEEE Information Theory Workshop (ITW 2012). IEEE, 2012. http://dx.doi.org/10.1109/itw.2012.6404716.

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Durisi, Giuseppe, Libero Dinoi, and Sergio Benedetto. "eIRA Codes for Coded Modulation Systems." In 2006 IEEE International Conference on Communications. IEEE, 2006. http://dx.doi.org/10.1109/icc.2006.254898.

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Reports on the topic "Codes"

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Hale, Christie, Norman Abrahamson, and Yousef Bozorgnia. Probabilistic Seismic Hazard Analysis Code Verification. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, March 2018. http://dx.doi.org/10.55461/kjzh2652.

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Over the past decade, the use of Probabilistic Seismic Hazard Analysis (PSHA) to assess seismic hazards has expanded, leading to the creation of a number of new PSHA computer codes throughout the industry. Additionally, recent seismic source and ground-motion characterization studies have led to more complex source and ground-motion models, which necessitate implementation in PSHA codes. This project was undertaken to update previous PSHA computer code verification efforts by running an expanded set of verification tests on codes currently in use for PSHA calculations. Following an announcement to the community, fifteen owners of PSHA codes from private consulting companies, academic institutions, risk analysis firms, and government agencies participated in the verification project by running verification tests on their own codes. The project included three sets of tests that increased in complexity from the first test in Set 1 to the last test in Set 3. Over the course of the project the group held ten meetings to discuss and finalize the results. Tests were often re-run several times before the results for all codes were finalized. This report documents the specifications and benchmark answers for the verification tests. Common issues and programming errors are also summarized, along with standard modeling approaches and key discussion points from the meetings. Where differences in modeling approaches lead to differences in reported hazard, those different modeling approaches are described. Through participation in the project, code owners verified the primary functions of their codes as benchmark answers were reached. The PSHA codes developed in the future can be verified by running the tests and comparing the results to the benchmark answers documented in this report. Note: the scope of this project is PSHA computer code verification. This project does not make recommendations on how to model earthquake scenarios from the specified source-characterization or ground-motion characterization inputs.
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Wasserman, David. Polar Codes. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada613962.

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Knill, E., and R. Laflamme. Concatenated quantum codes. Office of Scientific and Technical Information (OSTI), July 1996. http://dx.doi.org/10.2172/369608.

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Gulbrandsen, A. IMAP Response Codes. RFC Editor, May 2009. http://dx.doi.org/10.17487/rfc5530.

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Nelson, R. N., ed. Report number codes. Office of Scientific and Technical Information (OSTI), May 1985. http://dx.doi.org/10.2172/5815623.

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Nelson, Gena. Proportional Reasoning Interventions in Special Education Synthesis Coding Protocol. Boise State University, April 2021. http://dx.doi.org/10.18122/sped136.boisestate.

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The purpose of document is to provide readers with the coding protocol that authors used to code nine group and single case design intervention studies focused on proportional reasoning interventions for students (grades 5-9) with learning disabilities (LD) or mathematics difficulty (MD). The studies yielded intervention effects ranging from g = −0.10 to 1.87 and from Tau-U = 0.88 to 1.00. We coded all of the studies for variables in the following categories: study information, intervention features, dependent measures, participant demographics, LD and MD criteria and definitions, instructional content, study results, and quality indicators for group and single case design. The study quality indicator coding portion of this coding protocol was adapted from Gersten et al. (2005) and Horner et al. (2005). This code book contains variable names, code options, and code definitions. The mean interrater reliability across all codes using this protocol was 91% (range across categories = 82%–96%). The publication associated with this coding protocol is Nelson et al. (2020).
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Macula, Anthony, and Morgan Bishop. Superimposed Code Theoretic Analysis of DNA Codes and DNA Computing. Fort Belvoir, VA: Defense Technical Information Center, January 2008. http://dx.doi.org/10.21236/ada477311.

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Macula, Anthony J. Encoding Cooperative DNA Codes. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada435544.

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Jow, Hong-Nian, W. B. Murfin, and J. D. Johnson. XSOR codes users manual. Office of Scientific and Technical Information (OSTI), November 1993. http://dx.doi.org/10.2172/10108295.

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Nottingham, M., and R. Fielding. Additional HTTP Status Codes. RFC Editor, April 2012. http://dx.doi.org/10.17487/rfc6585.

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