Relevant bibliographies by topics / Mood and information processing

Academic literature on the topic 'Mood and information processing'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Mood and information processing"

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Zhong, Bu. "Readers' Mood Affects News Information Processing." Newspaper Research Journal 32, no. 3 (June 2011): 52–65. http://dx.doi.org/10.1177/073953291103200305.

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Schmid, Petra C., Marianne Schmid Mast, Dario Bombari, Fred W. Mast, and Janek S. Lobmaier. "How Mood States Affect Information Processing During Facial Emotion Recognition: An Eye Tracking Study." Swiss Journal of Psychology 70, no. 4 (December 2011): 223–31. http://dx.doi.org/10.1024/1421-0185/a000060.

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Existing research shows that a sad mood hinders emotion recognition. More generally, it has been shown that mood affects information processing. A happy mood facilitates global processing and a sad mood boosts local processing. Global processing has been described as the Gestalt-like integration of details; local processing is understood as the detailed processing of the parts. The present study investigated how mood affects the use of information processing styles in an emotion recognition task. Thirty-three participants were primed with happy or sad moods in a within-subjects design. They performed an emotion recognition task during which eye movements were registered. Eye movements served to provide information about participants’ global or local information processing style. Our results suggest that when participants were in a happy mood, they processed information more globally compared to when they were in a sad mood. However, global processing was only positively and local processing only negatively related to emotion recognition when participants were in a sad mood. When they were in a happy mood, processing style was not related to emotion recognition performance. Our findings clarify the mechanism that underlies accurate emotion recognition, which is important when one is aiming to improve this ability (i.e., via training).
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Turner, Jim. "Incidental Information Processing: Effects of Mood, Sex and Caffeine." International Journal of Neuroscience 72, no. 1-2 (January 1993): 1–14. http://dx.doi.org/10.3109/00207459308991619.

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Saito, H., H. Matsuoka, T. Ueno, T. Inosaka, and M. Sato. "Information processing deficits in mood disorder: An ERP study." Biological Psychiatry 35, no. 9 (May 1994): 672. http://dx.doi.org/10.1016/0006-3223(94)90864-8.

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Carter, Frances A., Cynthia M. Bulik, Rachel H. Lawson, Patrick F. Sullivan, and Jenny S. Wilson. "Effect of Mood and Food Cues on Information Processing in Women with Bulimia Nervosa and Controls." Behaviour Change 14, no. 2 (June 1997): 113–20. http://dx.doi.org/10.1017/s0813483900003570.

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Information-processing speed and cue reactivity were evaluated in women with bulimia nervosa and controls in response to neutral, mood, and food cues in isolation, and mood and food cues in combination. Significant differences were consistently observed between women with bulimia nervosa and control women on information-processing speed for food/body-related words, but not for words unrelated to food/body concerns. As expected, women with bulimia nervosa demonstrated slower processing of information related to food/body concerns. In addition, the presentation of mood and food cues affected speed of information processing. Especially for women with bulimia nervosa, information processing was slowest when either mood or food cues were presented in isolation. Significant cue reactivity was also observed, again especially for women with bulimia nervosa. In conclusion, both transient and more enduring subject characteristics affected information-processing speed. Moreover, the way transient factors were presented significantly affected speed of information processing. This suggests a more complex relationship between cue presentation and information processing than was anticipated.
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Bless, Herbert, and Axel M. Burger. "Mood and the Regulation of Mental Abstraction." Current Directions in Psychological Science 26, no. 2 (April 2017): 159–64. http://dx.doi.org/10.1177/0963721417690456.

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Individuals can apply different processing strategies to deal with situations they encounter. One central question in social-cognition research refers to the factors that determine reliance on different processing strategies. Parting from a functional perspective, which holds that processing strategies need to be adjusted to the requirements of the situation, we argue that individuals’ mood carries information about the benign versus problematic nature of the situation and thus that mood can regulate cognitive processing. Focusing on mental abstraction, we propose that positive mood contributes to a processing style characterized by reliance on prior knowledge in the form of general knowledge structures, whereas negative mood elicits a processing style characterized by attention to details and consideration of new situation-specific information.
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Forgas, Joseph P., and Diana Matovic. "Mood Effects on Humor Production: Positive Mood Improves the Verbal Ability to Be Funny." Journal of Language and Social Psychology 39, no. 5-6 (May 21, 2020): 701–15. http://dx.doi.org/10.1177/0261927x20917994.

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Can mood influence people’s ability to produce humorous verbal messages? Based on recent theories linking affect to social cognition and information-processing strategies, this experiment predicted and found that positive mood increased people’s ability to generate more creative, humorous, and elaborate verbal contents. Participants viewed positive, neutral, or negative videos, then produced verbal captions to fit four different cartoon images. Their messages were rated for creativity, humor, and elaboration by two trained raters, and the processing latency to produce each message was also recorded. Results showed that positive mood resulted in more creative and humorous messages, and that this effect was significantly mediated by mood-induced differences in information-processing strategies. The results are interpreted as supporting recent theories linking affect to cognition, and the theoretical and practical implications of the findings for everyday verbal communication are considered.
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Mohanty, Sachi Nandan, and Damodar Suar. "Decision Making under Uncertainty and Information Processing in Positive and Negative Mood States." Psychological Reports 115, no. 1 (August 2014): 91–105. http://dx.doi.org/10.2466/20.04.pr0.115c16z2.

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This study examines whether mood states (a) influence decision making under uncertainty and (b) affect information processing. 200 students at the Indian Institute of Technology Kharagpur participated in this study. Positive mood was induced by showing comedy movie clips to 100 participants and negative mood was induced by showing tragedy movie clips to another 100 participants. The participants were administered a questionnaire containing hypothetical situations of financial gains and losses, and a health risk problem. The participants selected a choice for each situation, and stated the reasons for their choice. Results suggested that the participants preferred cautious choices in the domain of gain and in health risk problems and risky choices in the domain of loss. Analysis of the reasons for the participants' choices suggested more fluency, originality, and flexibility of information in a negative mood compared to a positive mood. A negative (positive) mood state facilitated systematic (heuristic) information processing.
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Ohtomo, Shoji, Kumiko Takeshima, and Yukio Hirose. "The effects of mood state on the information processing of advertisement." Journal of Human Environmental Studies 8, no. 2 (2010): 123–32. http://dx.doi.org/10.4189/shes.8.123.

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Grol, Maud, and Rudi De Raedt. "The effect of positive mood on flexible processing of affective information." Emotion 18, no. 6 (September 2018): 819–33. http://dx.doi.org/10.1037/emo0000355.

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Dissertations / Theses on the topic "Mood and information processing"

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Hamilton, Kate E. "Mood and cognition, mood state dependence and information processing in remitted depression." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ55283.pdf.

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Dumitrascu, Nicolae. "The Impact of Induced Mood on Visual Information Processing." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1321490234.

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Fisher, Daniel Joseph. "Effects of mood and cognition on the social information-processing mechanisms underlying aggression /." Electronic version (PDF), 2007. http://dl.uncw.edu/etd/2007-1/fisherd/danielfisher.pdf.

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Cheng, Clara Michelle. "Self-reference in mystery moods consequences for information processing and self-enhancement /." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1147729556.

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Lamar, Marlys Camille. "The Effects of Mood State and Intensity on Cognitive Processing Modes." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc331434/.

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To investigate the effects of emotional arousal on information processing strategy, three different moods (sadness, anger, and happiness) were hypnotically induced at three different levels of intensity (high, medium, and low) in 29 male and female undergraduate students, while engaging them in a visual information processing task. Subjects were screened for hypnotic susceptibility and assigned to either a high susceptibility group or low susceptibility group to account for the attentional bias associated with this trait. All subjects were trained to access the three emotions at the three levels of intensity. During separate experimental sessions, subjects were hypnotized, and asked to access a mood and experience each level of intensity while being administered the Navon Design Discrimination Task, a measure of global and analytic visual information processing. Scores were derived for global processing, analytic processing, and a percentage of global to analytic processing for each level of mood and intensity. Two (hypnotic susceptibility) x 3 (emotion) x 3 (intensity level) repeated measures ANOVAs were computed on the global, analytic, and percentage scores. In addition, two separate ANCOVAs were computed on each dependent measure to account for the effects of handedness, and cognitive style. None of these analyses revealed significant main effects or interactions. The analysis of the percentage scores revealed a trend toward differences between the emotions, but in a direction opposite to that hypothesized. Hypnotic susceptibility does not appear to mediate global and analytic responses to the Navon visual information processing task when emotions are being experienced. Results regarding emotions and emotional intensity were discussed in terms of the problems with adequate control and manipulation of mood and intensity level. Difficulties with the Navon measure were also explored with regard to the exposure duration in the Navon task, and its adequacy in measuring shifts in information processing associated with transient mood states. Implications for future research were discussed.
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Briks, Jeffrey Edward. "The Influence of Emotions on Interviewers’ Information Search Behaviors: A Test of an Information Processing Model." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1258051753.

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East, Rebekah Psychology Faculty of Science UNSW. "Happy and gullible, sad and wise? Mood effects on factual and interpersonal skepticism." Awarded by:University of New South Wales. Psychology, 2006. http://handle.unsw.edu.au/1959.4/24371.

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The primary aim of this research was to examine the influence of temporary mood states on factual and interpersonal skepticism. Based on recent affect-cognition theorising and research on credibility judgment, 7 studies predicted that negative moods increase and positive moods decrease skepticism, because of the information-processing consequences of these affective states. First, three studies examined the influence of mood on factual skepticism toward urban myths and legends (Study 1) and novel and familiar general knowledge claims (Studies 2-3). Contrary to predictions, Study 1 found that sad participants were less skeptical than happy participants towards urban legends, possibly due to the negative valence of the claims. Because the feeling of familiarity has been shown to be an important determinant of truth, Studies 2-3 examined the influence of mood and familiarity on skepticism. Consistent with information processing theories of mood, happy participants were more likely than sad participants to give credence to familiar general knowledge claims (Study 2), even when given explicit feedback about their actual truth or falsity during initial exposure to claims (Study 3). The remainder of this thesis extended these findings to interpersonal judgments. Studies 4-5 found that sad participants were more skeptical of the genuineness of facial expressions of emotion compared to happy participants. Studies 6-7 examined whether sad participants might also show greater lie detection accuracy. In Study 6, happy, sad and neutral-mood participants judged the credibility of targets honestly or deceptively describing their emotional reaction to an affectively-laden film, but no evidence was found of mood induced differences in deception detection accuracy. However, in Study 7, sad participants were more skeptical than happy participants about the veracity of videotaped individuals honestly or deceptively denying their involvement in a mock crime (a theft), and showed greater accuracy at discerning lies from truths. This dissertation contributes to the affect-cognition literature by demonstrating that not only may sad moods lead people to be more skeptical, but they may also confer an advantage at detecting deception. The implications of these findings for everyday credibility judgment and for contemporary theories of affect and cognition are considered.
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久木山, 健一, and Kenichi KUKIYAMA. "大学生の社会的情報処理と友人関係適応の関連." 名古屋大学大学院教育発達科学研究科, 2001. http://hdl.handle.net/2237/3069.

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Ellenbogen, Mark Alexander. "Stress and selective attention, the impact of a stressful challenge on mood, cortisol, and the processing of emotional information." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ59221.pdf.

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Svensson, Peter, and Youssef Taoudi. "Labeling Moods of Movies by Processing Subtitles." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254547.

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Labeling movies by moods is a feature that is useful for recommendation engines in modern movie streaming applications. Movie recommendation based on moods is a feature that could improve user experience for movie streaming platforms by recommending more relevant movies to users. This thesis describes the development of a mood labeling feature that labels movies by processing movie subtitles through Natural Language Processing. Movies are processed by analysing subtitles to predict the mood of a movie through computational methods. The prototype utilizes movies pre-labeled with moods to construct a lexicon that contains information of the defining attributes for moods in movie subtitles. Using the constructed lexicon, the similarities between a movie subtitle and a lexicon can be compared to calculate the probability that a movie belongs to a specific mood. Four moods were chosen for analysis in the prototype: fear, sadness, joy, and surprise.The Naive Bayes method was chosen as the classifier for the prototype. A Naive Bayes classifier observes each occurring word in a movie without consideration to the context of the word in a text or sentence. The results showed that the classifier had trouble distinguishing between the moods. However, for all configurations of the prototype, the classifier showed higher precision for the mood fear compared to the other moods. Overall the classifier performed poorly and did not produce a reliable result.
Klassificering av filmer via stämning är en funktion som är användbar för rekommendationsmotorer i moderna filmströmmingsprogram. Filmrekommendation baserad på stämning är en funktion som kan förbättra användarupplevelsen på filmströmmande plattformar genom att rekommendera mer relevanta filmer till användarna. Denna uppsats beskriver utvecklingen av en prototyp för att klassificera filmer efter deras stämning genom att bearbeta filmens undertexter med hjälp av metoder inom språkteknologi. Filmer bearbetas genom att analysera undertexter för att avgöra stämningen hos en film. Prototypen använder filmer som är fördefinierade med stämning för att konstruera ett lexikon som innehåller information om de definierande egenskaperna för en stämning i filmtexter. Med hjälp av ett konstruerat lexikon kan likheterna mellan en filmtextning och ett lexikon jämföras för att beräkna sannolikheten för att en film tillhör en viss stämning. Fyra stämningar valdes för analys i prototypen: rädsla, sorg, glädje och överraskning.Navie Bayes-metoden valdes som klassificeringsmedel för prototypen. En Naive Bayes-klassificerare observerar varje förekommande ord utan hänsyn till ordets sammanhang i en mening eller text. Resultaten visade att klassificeringen hade problem att skilja mellan stämningarna. För samtliga konfigurationer av prototypen visade klassificeringsenheten dock högre precision för rädsla jämfört med de andra stämningarna. Sammantaget presterade klassificeraren dåligt och gav inte ett tillförlitligt resultat.
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Books on the topic "Mood and information processing"

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Nunn, Jean Dyan. Cognitive processing of mood and personally relavant information in depression. Birmingham: University of Birmingham, 1996.

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Mullins, Elaine. Information processing. Harlow: Addison Wesley Longman, 1992.

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Arden, Trevor. Information processing. London: Pitman, 1989.

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Program, Alberta Alberta Education Career and Technology Studies. Information processing. Edmonton, Alta: Alberta Education, Career and Technology Studies, 1992.

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Knott, Geoffrey. Information processing. 3rd ed. Sunderland: Business Educational Publishers Limited, 1997.

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The mood of information: Online behavioural advertising. New York, NY: Continuum International Pub. Group, 2011.

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Lunde, Ken. CJKV information processing. Beijing: O'Reilly, 1999.

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Tahara, I. Cognitive information processing. Tokyo: Ohmsha, 1994.

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NATO Advanced Research Workshop on Information Processing of Chemical Sensory Stimuli in Biological and Artificial Systems (1989 Göttingen, Germany). Chemosensory information processing. Berlin: Springer-Verlag, 1989.

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Tao, Jianhua. Affective information processing. London: Springer, 2009.

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Book chapters on the topic "Mood and information processing"

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Johnson, F. N. "Effects of Lithium on Information Processing: Evidence from Partial Responders and Nonresponders." In Recurrent Mood Disorders, 174–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-76646-6_20.

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Abro, Altaf Hussain, Michel C. A. Klein, Adnan R. Manzoor, Seyed Amin Tabatabaei, and Jan Treur. "A Computational Model of the Relation between Regulation of Negative Emotions and Mood." In Neural Information Processing, 59–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12637-1_8.

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Bless, Herbert. "The Consequences of Mood on the Processing of Social Information." In Blackwell Handbook of Social Psychology: Intraindividual Processes, 391–412. Malden, Massachusetts, USA: Blackwell Publishers Inc., 2007. http://dx.doi.org/10.1002/9780470998519.ch18.

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Both, Fiemke, Mark Hoogendoorn, Michel C. A. Klein, and Jan Treur. "Computational Modeling and Analysis of the Role of Physical Activity in Mood Regulation and Depression." In Neural Information Processing. Theory and Algorithms, 270–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17537-4_34.

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Feng, Lin, Guochao Liu, Sen Luo, and Shenglan Liu. "A Transferable Framework: Classification and Visualization of MOOC Discussion Threads." In Neural Information Processing, 377–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70093-9_39.

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Clark, Margaret S. "Some Effects of Everyday Moods and Possible Individual Differences in these Effects." In Energetics and Human Information Processing, 299–310. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4448-0_20.

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Bouzayane, Sarra, and Inès Saad. "How to Help a Pedagogical Team of a MOOC Identify the “Leader Learners”?" In Lecture Notes in Business Information Processing, 140–51. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52624-9_11.

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Ma, Chao, Guanghong Gong, and Yaofei Ma. "An Information Processing Model for Emotional Agents Based on the OCC Model and the Mood Congruent Effect." In Lecture Notes in Computer Science, 98–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24918-1_13.

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Huang, Nen-Fu, Chia-An Lee, Yi-Wei Huang, Po-Wen Ou, How-Hsuan Hsu, So-Chen Chen, and Jian-Wei Tzengßer. "On the Automatic Construction of Knowledge-Map from Handouts for MOOC Courses." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 107–14. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63856-0_13.

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Ciborra, Claudio U. "Improvisation as Mood." In Bricolage, Care and Information, 53–69. London: Palgrave Macmillan UK, 2009. http://dx.doi.org/10.1057/9780230250611_3.

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Conference papers on the topic "Mood and information processing"

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Khanna, Abhirup, Ananya Bansal, Amit Agarwal, and Piyush Maheshwari. "Reading Political Sentiment and Mood of the Electorate Through Twitter Data." In 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS). IEEE, 2020. http://dx.doi.org/10.1109/icspis51252.2020.9340147.

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Huang, Kun-Yi, Chung-Hsien Wu, Ming-Hsiang Su, and Chia-Hui Chou. "Mood disorder identification using deep bottleneck features of elicited speech." In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2017. http://dx.doi.org/10.1109/apsipa.2017.8282296.

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Yuan, Ting, Huaigang Wu, Jingjie Zhu, Lingling Shen, and Gang Qian. "MS-UCF: A reliable recommendation method based on mood-sensitivity identification and user credit." In 2018 International Conference on Information Management and Processing (ICIMP). IEEE, 2018. http://dx.doi.org/10.1109/icimp1.2018.8325834.

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Wang, Song, Lin Xiao, Maureen J. Simmonds, and Ling Zhang. "The influence of playing computer games on pain threshold, mood, and physical performances between fibromyalgia patients and healthy individuals." In 2013 International Conference on Advanced Materials and Information Technology Processing. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/amitp130871.

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Chang, Fuh-Yu, Hung-Yi Lin, Wen-Lang Lai, Chia-Jen Ting, Jen-Hui Tsai, Shuo-Hung Chang, and Tung-Chuan Wu. "Roll to Roll Processing for Flexible Nanophotonics." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34722.

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This article discusses the current status and achievements of R2R technology for large area nano-scaled optical devices developed at MSL/ITRI. Firstly, a single layer of nanostructure on polymer film is designed for anti-reflection purpose by finite difference time domain (FDTD) method in the visible light spectrum. The conical array with around 1 aspect ratio, like moth-eye shape and showing superior performance in the optical simulation, has been adapted for the R2R experiments. The development of R2R process includes roller machine design and fabrication, roller mold design and making, development of rolling imprint process, characterization of rolled devices. In this study, large area (200mm *200mm) Ni template was fabricated with DUV exposure, followed by dry etching and electroforming process, respectively. Then, the template was bonded on the roller mold with magnetic film to make nanostructure roller mold. With the delicate nanostructure roller mold, systematic experiments have been conducted on the home-made roller machine with various parameters, such as linear speed, dose rate, and material modifications. The duplicated nanostructure films show very good optical quality of anti-reflection (AR < 1%) and are in good agreement with the theoretical predictions. Besides, the duration of the roller mold has been highly promoted to hundreds of imprint in the UV embossing process.
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Venkatraman, Santhi, Arunaanand, and Sharanya. "Real Time Mold Quality Inspection in Foundries using Image Processing Techniques." In 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). IEEE, 2020. http://dx.doi.org/10.1109/ic-etite47903.2020.215.

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Ortac, Gizem, Ahmet Seckin Bilgi, Yusuf Erkan Gorgulu, Ali Gunes, Habil Kalkan, and Kadim Tasdemir. "Classification of black mold contaminated figs by hyperspectral imaging." In 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2015. http://dx.doi.org/10.1109/isspit.2015.7394332.

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Sinha, Tanmay, Patrick Jermann, Nan Li, and Pierre Dillenbourg. "Your click decides your fate: Inferring Information Processing and Attrition Behavior from MOOC Video Clickstream Interactions." In Proceedings of the EMNLP 2014 Workshop on Analysis of Large Scale Social Interaction in MOOCs. Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/w14-4102.

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Zhang, Zhiqiang, Changshui Zhang, and Shifeng Weng. "Music playlist prediction via detecting song moods." In 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2013. http://dx.doi.org/10.1109/chinasip.2013.6625322.

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Hui, Qu. "The New Role of College English Teachers in MOOC Learning Model." In 2020 International Conference on Computers, Information Processing and Advanced Education (CIPAE). IEEE, 2020. http://dx.doi.org/10.1109/cipae51077.2020.00091.

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Reports on the topic "Mood and information processing"

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DiVincenzo, David P., and Charles H. Bennett. Quantum Information Processing. Fort Belvoir, VA: Defense Technical Information Center, December 2001. http://dx.doi.org/10.21236/ada414217.

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Vazirani, Umesh, Christos Papadimitriou, and Alistair Sinclair. Quantum Information Processing. Fort Belvoir, VA: Defense Technical Information Center, November 2004. http://dx.doi.org/10.21236/ada428699.

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Pirog, John M. Advanced Information Processing. Fort Belvoir, VA: Defense Technical Information Center, October 1992. http://dx.doi.org/10.21236/ada260245.

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Ball, Eugene, Jon Bentley, Nico Habermann, Peter Hibbard, and Takeo Kanade. Information Processing Research. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada173028.

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Levis, Alexander H., M. M. Tomovic, and P. H. Cothier. Information Processing Organizations with Acyclical Information Structures. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada188980.

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Cory, David G., and Chandrasekhar Ramanathan. Electron-Nuclear Quantum Information Processing. Fort Belvoir, VA: Defense Technical Information Center, November 2008. http://dx.doi.org/10.21236/ada499318.

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Girolami, Davide. Quantum Resources for Information Processing. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1489935.

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Girolami, Davide. Quantum Resources for Information Processing. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1489936.

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Girolami, Davide. Quantum Resources for Information Processing. Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1498025.

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Russell, David L. Modelling, Information Processing and Control. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada250571.

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