Search results for: memory analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27794

Search results for: memory analysis

27494 Re-Creating Women of the Past in Historical Series on Mexican Television: The Work of Patricia Arriaga Jordan

Authors: Maria De Los Angeles Rodriguez Cadena

Abstract:

This paper discusses how the fictional versions of women of the past contribute to advance today’s ideas of social justice, personal freedom and emancipation as well as to highlight the creative challenge of constructing people and events on fictional narratives on television that incorporate multiple and simultaneous layers of meaning and complexity. This project builds on existing scholarship on audiovisual texts by exploring an influential but under-studied director. In two Mexican television series, Patricia Arriaga Jordan, an award-winning television producer, scriptwriter and director, constructs the life of two outstanding women that have played an influential role in national history and captured Mexican’s popular imagination for generations: Sor Juana Inés de la Cruz, and Malinche. Malinche (2018) tells the story of an extraordinary indigenous woman, Malintzin, during the Spanish Conquest (1511-1550) that is considered to have played a key role in the fall of the Aztec empire by acting as translator, negotiator and cultural mediator for the Spanish conquerors. Juana Ines (2016) portrays Sor Juana, a poet, essayist, playwright, theologian, philosopher, nun, of XVII century colonial Mexico, one of the brightest minds of her time, and now recognized as the first feminist of the Americas who wrote on the rights of women to an education, religious authority and feminist advocacy. Both series, as fictional narratives that recreate defining historical periods, specific events and relevant characters in the History of Mexico can be read as an example of what is called texts of cultural memory. A cultural memory text is a narrative that bonds the concepts of history, identity and belonging, and that is realized and disseminated through symbolic systems such as written documents, visual images, and dramatic representation. Cultural memory, through its narratives of historical fiction, emphasizes memory processes (historiography) and its implications and artifacts (cultural memory) mainly through the medial frameworks of remembering, which are the medial process by which memories (narratives, documents) participate in public knowledge and become collective memory. Historical fiction on television not only creates a portrayal of the past related to the real lives of protagonists, but it also significantly contributes to understand the past as an ever-evolving entity that highlights both, the necessary connection with the present as part of a developing sense of collective identity and belonging, as well as the relevance of the medium in which the past is represented and that ultimately supports the process of historical awareness. Through the emblematic recreation of national heroines and historical events in the unique context of historical drama on television, those texts constitute a venue where concepts of the past and the traditionally established ideas about history and heroines are highlighted, questioned and transformed.

Keywords: cultural memory, historical fiction, Mexico, television, women directors

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27493 Analysis of Anti-Tuberculosis Immune Response Induced in Lungs by Intranasal Immunization with Mycobacterium indicus pranii

Authors: Ananya Gupta, Sangeeta Bhaskar

Abstract:

Mycobacterium indicus pranii (MIP) is a saprophytic mycobacterium. It is a predecessor of M. avium complex (MAC). Whole genome analysis and growth kinetics studies have placed MIP in between pathogenic and non-pathogenic species. It shares significant antigenic repertoire with M. tuberculosis and have unique immunomodulatory properties. MIP provides better protection than BCG against pulmonary tuberculosis in animal models. Immunization with MIP by aerosol route provides significantly higher protection as compared to immunization by subcutaneous (s.c.) route. However, mechanism behind differential protection has not been studied. In this study, using mice model we have evaluated and compared the M.tb specific immune response in lung compartments (airway lumen / lung interstitium) as well as spleen following MIP immunization via nasal (i.n.) and s.c. route. MIP i.n. vaccination resulted in increased seeding of memory T cells (CD4+ and CD8+ T-cells) in the airway lumen. Frequency of CD4+ T cells expressing Th1 migratory marker (CXCR3) and activation marker (CD69) were also high in airway lumen of MIP i.n. group. Significantly high ex vivo secretion of cytokines- IFN-, IL-12, IL-17 and TNF- from cells of airway luminal spaces provides evidence of antigen-specific lung immune response, besides generating systemic immunity comparable to MIP s.c. group. Analysis of T cell response on per cell basis revealed that antigen specific T-cells of MIP i.n. group were functionally superior as higher percentage of these cells simultaneously secreted IFN-gamma, IL-2 and TNF-alpha cytokines as compared to MIP s.c. group. T-cells secreting more than one of the cytokines simultaneously are believed to have robust effector response and crucial for protection, compared with single cytokine secreting T-cells. Adoptive transfer of airway luminal T-cells from MIP i.n. group into trachea of naive B6 mice revealed that MIP induced CD8 T-cells play crucial role in providing long term protection. Thus the study demonstrates that MIP intranasal vaccination induces M.tb specific memory T-cells in the airway lumen that results in an early and robust recall response against M.tb infection.

Keywords: airway lumen, Mycobacterium indicus pranii, Th1 migratory markers, vaccination

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27492 Working Memory in Children: The Relationship with Father-Child Rough-and-Tumble Play

Authors: Robinson, E. L., Freeman, E. E.

Abstract:

Over the last few decades, the social movement of involved fatherhood has stimulated a research focus on fathers, leading to an increase in the body of evidence into the paternal contributions to child development. Past research has suggested that rough-and-tumble play, which involves wrestling, chasing and tumbling, is the preferred play type of western fathers. This type of play remains underutilized and underrepresented in child developmental research as it’s perceived to be dangerous or too aggressive. The limited research available has shown a relationship between high quality rough-and-tumble play interactions, lower childhood aggression and improved child emotional regulation. The aim of this study was to examine father-child rough-and-tumble play and assess the impact on cognitive development in children aged 4-7 years. Father-child dyads completed a 10-minute rough-and-tumble play interaction, which consisted of 2 games, at the University of Newcastle. Children then completed the Wechsler Preschool & Primary Scale of Intelligence - Fourth Edition Australian and New Zealand Standardized Edition (WPPSI-IV A&NZ). Fathers reported on their involvement in various caregiving activities and on their child’s development. Analyses revealed that fathers-child play quality was positively related to working memory outcomes in children. Furthermore, the amount of rough-and-tumble play father and child did together on a regular basis was also related to working memory outcomes. While father-child play interactions remain an understudied area of research, this study outlines the importance of examining the paternal play role in children’s cognitive development.

Keywords: children, development, father, executive function

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27491 The Test of Memory Malingering and Offence Severity

Authors: Kenji Gwee

Abstract:

In Singapore, the death penalty remains in active use for murder and drug trafficking of controlled drugs such as heroin. As such, the psychological assessment of defendants can often be of high stakes. The Test of Memory Malingering (TOMM) is employed by government psychologists to determine the degree of effort invested by defendants, which in turn inform on the veracity of overall psychological findings that can invariably determine the life and death of defendants. The purpose of this study was to find out if defendants facing the death penalty were more likely to invest less effort during psychological assessment (to fake bad in hopes of escaping the death sentence) compared to defendants facing lesser penalties. An archival search of all forensic cases assessed in 2012-2013 by Singapore’s designated forensic psychiatric facility yielded 186 defendants’ TOMM scores. Offence severity, coded into 6 rank-ordered categories, was analyzed in a one-way ANOVA with TOMM score as the dependent variable. There was a statistically significant difference (F(5,87) = 2.473, p = 0.038). A Tukey post-hoc test with Bonferroni correction revealed that defendants facing lower charges (Theft, shoplifting, criminal breach of trust) invested less test-taking effort (TOMM = 37.4±12.3, p = 0.033) compared to those facing the death penalty (TOMM = 46.2±8.1). The surprising finding that those facing death penalties actually invested more test taking effort than those facing relatively minor charges could be due to higher levels of cooperation when faced with death. Alternatively, other legal avenues to escape the death sentence may have been preferred over the mitigatory chance of a psychiatric defence.

Keywords: capital sentencing, offence severity, Singapore, Test of Memory Malingering

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27490 Optical Multicast over OBS Networks: An Approach Based on Code-Words and Tunable Decoders

Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

Abstract:

In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory

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27489 Memory Consolidation: Application of Retrieval Strategies in the Classroom

Authors: Eric Tardif, Nicolas Meylan

Abstract:

Recent studies suggest that the consolidation of episodic memory is better achieved through repeated retrieval than with the use of concept mapping or repeated study. Although such laboratory results highly appeal to educationalists, it remains to be shown whether they can be directly used in a classroom setting. Forty-five college students (42 girls; mean age 16.1 y/o) were asked to remember pairs of biology-related words (e.g. mitochondria-energy) in two configurations. The first configuration consisted of a three-minute study of pairs of words followed by a final one-minute test in which the first word of a pair was shown and the subject asked to write down the second associated word. This procedure was repeated three times. The second configuration consisted of a one-minute study of a list of pairs of words, which was immediately followed by a one-minute test. This procedure was repeated 6 times. Subjects filled out a small questionnaire assessing their general mood, level of fatigue, stress and motivation to do the exercise. One week later, subjects were given a final test using the same words. A total of 8 lists of words were studied and tested during the semester. Results showed that subjects recalled more correct words when using the second configuration, both within the study period and one week later, confirming laboratory findings. However, the general performance (mean items recalled) as well as the motivation to do the exercise gradually decreased during the semester. Motivation was positively correlated with performance (r=0.77, p<0.05). The results suggest that laboratory findings may provide some applications in education but other variables inherent to the classroom setting must also be considered.

Keywords: long-term, episodic memory, consolidation, retrieval, school setting

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27488 Effect of Perceived Importance of a Task in the Prospective Memory Task

Authors: Kazushige Wada, Mayuko Ueda

Abstract:

In the present study, we reanalyzed lapse errors in the last phase of a job, by re-counting near lapse errors and increasing the number of participants. We also examined the results of this study from the perspective of prospective memory (PM), which concerns future actions. This study was designed to investigate whether perceiving the importance of PM tasks caused lapse errors in the last phase of a job and to determine if such errors could be explained from the perspective of PM processing. Participants (N = 34) conducted a computerized clicking task, in which they clicked on 10 figures that they had learned in advance in 8 blocks of 10 trials. Participants were requested to click the check box in the start display of a block and to click the checking off box in the finishing display. This task was a PM task. As a measure of PM performance, we counted the number of omission errors caused by forgetting to check off in the finishing display, which was defined as a lapse error. The perceived importance was manipulated by different instructions. Half the participants in the highly important task condition were instructed that checking off was very important, because equipment would be overloaded if it were not done. The other half in the not important task condition was instructed only about the location and procedure for checking off. Furthermore, we controlled workload and the emotion of surprise to confirm the effect of demand capacity and attention. To manipulate emotions during the clicking task, we suddenly presented a photo of a traffic accident and the sound of a skidding car followed by an explosion. Workload was manipulated by requesting participants to press the 0 key in response to a beep. Results indicated too few forgetting induced lapse errors to be analyzed. However, there was a weak main effect of the perceived importance of the check task, in which the mouse moved to the “END” button before moving to the check box in the finishing display. Especially, the highly important task group showed more such near lapse errors, than the not important task group. Neither surprise, nor workload affected the occurrence of near lapse errors. These results imply that high perceived importance of PM tasks impair task performance. On the basis of the multiprocess framework of PM theory, we have suggested that PM task performance in this experiment relied not on monitoring PM tasks, but on spontaneous retrieving.

Keywords: prospective memory, perceived importance, lapse errors, multi process framework of prospective memory.

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27487 Switching Studies on Ge15In5Te56Ag24 Thin Films

Authors: Diptoshi Roy, G. Sreevidya Varma, S. Asokan, Chandasree Das

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Germanium Telluride based quaternary thin film switching devices with composition Ge15In5Te56Ag24, have been deposited in sandwich geometry on glass substrate with aluminum as top and bottom electrodes. The bulk glassy form of the said composition is prepared by melt quenching technique. In this technique, appropriate quantity of elements with high purity are taken in a quartz ampoule and sealed under a vacuum of 10-5 mbar. Then, it is allowed to rotate in a horizontal rotary furnace for 36 hours to ensure homogeneity of the melt. After that, the ampoule is quenched into a mixture of ice - water and NaOH to get the bulk ingot of the sample. The sample is then coated on a glass substrate using flash evaporation technique at a vacuum level of 10-6 mbar. The XRD report reveals the amorphous nature of the thin film sample and Energy - Dispersive X-ray Analysis (EDAX) confirms that the film retains the same chemical composition as that of the base sample. Electrical switching behavior of the device is studied with the help of Keithley (2410c) source-measure unit interfaced with Lab VIEW 7 (National Instruments). Switching studies, mainly SET (changing the state of the material from amorphous to crystalline) operation is conducted on the thin film form of the sample. This device is found to manifest memory switching as the device remains 'ON' even after the removal of the electric field. Also it is found that amorphous Ge15In5Te56Ag24 thin film unveils clean memory type of electrical switching behavior which can be justified by the absence of fluctuation in the I-V characteristics. The I-V characteristic also reveals that the switching is faster in this sample as no data points could be seen in the negative resistance region during the transition to on state and this leads to the conclusion of fast phase change during SET process. Scanning Electron Microscopy (SEM) studies are performed on the chosen sample to study the structural changes at the time of switching. SEM studies on the switched Ge15In5Te56Ag24 sample has shown some morphological changes at the place of switching wherein it can be explained that a conducting crystalline channel is formed in the device when the device switches from high resistance to low resistance state. From these studies it can be concluded that the material may find its application in fast switching Non-Volatile Phase Change Memory (PCM) Devices.

Keywords: Chalcogenides, Vapor deposition, Electrical switching, PCM.

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27486 Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

Abstract:

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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27485 Grounding Chinese Language Vocabulary Teaching and Assessment in the Working Memory Research

Authors: Chan Kwong Tung

Abstract:

Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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27484 Cache Analysis and Software Optimizations for Faster on-Chip Network Simulations

Authors: Khyamling Parane, B. M. Prabhu Prasad, Basavaraj Talawar

Abstract:

Fast simulations are critical in reducing time to market in CMPs and SoCs. Several simulators have been used to evaluate the performance and power consumed by Network-on-Chips. Researchers and designers rely upon these simulators for design space exploration of NoC architectures. Our experiments show that simulating large NoC topologies take hours to several days for completion. To speed up the simulations, it is necessary to investigate and optimize the hotspots in simulator source code. Among several simulators available, we choose Booksim2.0, as it is being extensively used in the NoC community. In this paper, we analyze the cache and memory system behaviour of Booksim2.0 to accurately monitor input dependent performance bottlenecks. Our measurements show that cache and memory usage patterns vary widely based on the input parameters given to Booksim2.0. Based on these measurements, the cache configuration having least misses has been identified. To further reduce the cache misses, we use software optimization techniques such as removal of unused functions, loop interchanging and replacing post-increment operator with pre-increment operator for non-primitive data types. The cache misses were reduced by 18.52%, 5.34% and 3.91% by employing above technology respectively. We also employ thread parallelization and vectorization to improve the overall performance of Booksim2.0. The OpenMP programming model and SIMD are used for parallelizing and vectorizing the more time-consuming portions of Booksim2.0. Speedups of 2.93x and 3.97x were observed for the Mesh topology with 30 × 30 network size by employing thread parallelization and vectorization respectively.

Keywords: cache behaviour, network-on-chip, performance profiling, vectorization

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27483 Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks

Authors: Jiajun Wang, Xiaoge Li

Abstract:

The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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27482 Long Short-Time Memory Neural Networks for Human Driving Behavior Modelling

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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27481 Draw Me Close: Queering Virtual Reality through (Re)Performances of Memory

Authors: Camille Intson

Abstract:

This paper endeavors to explore the opportunities, challenges, and ethics of reconstructing and re-enacting archives of memory through virtual reality (VR) performance, using Jordan Tannahill’s Draw Me Close as an exemplary case study. Draw Me Close is a 1:1 virtual reality (VR) performance in which the artist’s childhood memories, experiences, and interactions with his mother are reconstructed in the wake of her passing. Solo audience members are positioned as Jordan (the subject and character) and taken through a series of narratives, (virtual) spaces, and interactions with his “mother,” played by a live actor. Piece by piece, audiences are brought into the world of the “shifting” archive, inhabiting Jordan’s reconstructed virtual world from his early explorations of queer sexuality through to his mother’s cancer diagnosis and passing. This paper will explore how the world of Draw Me Close represents a “touching” and/or “queering” of time within its archive, blurring and transgressing the boundaries between the animate and the inanimate, life and death. On a philosophical level, considering foundational queer performance scholarship and archival theory, it will also examine how performance’s ephemerality rewards its artists with the dual advantages of visibility and protection, allowing for an ethical exploration of traumatic memory and loss within a disappearing medium. Finally, this provocation will use Draw Me Close as a point of departure from which to outline future possibilities for performance and emerging technologies’ engagements with archival theory and practice. By positioning virtual reality (VR) as an archive-constructing medium, it aims to move beyond the question of how we can take performances seriously as archives towards how personal archive construction is itself a performative act.

Keywords: intermedial theatre, new media arts, queer performance, virtual reality

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27480 Graph-Oriented Summary for Optimized Resource Description Framework Graphs Streams Processing

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

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27479 Offloading Knowledge-Keeping to Digital Technology and the Attrition of Socio-Cultural Life

Authors: Sophia Melanson Ricciardone

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Common vexations concerning the impact of contemporary media technology on our daily lives tend to conjure mental representations of digital specters that surreptitiously invade the privacy of our most intimate spaces. While legitimacy assuredly sustains these concerns, examining them in isolation from other attributable phenomena to the problems created by our hyper-mediated conditions does not supply a complete account of the deleterious cost of integrating digital affordances into the banal cadence of our shared socio-cultural realities. As we continue to subconsciously delegate facets of our social and cognitive lives to digital technology, the very faculties that have enabled our species to thrive and invent technology in the first place are at risk of attrition – namely our capacity to sustain attention while synthesizing information in working memory to produce creative and inventive constructions for our shared social existence. Though the offloading of knowledge-keeping to fellow social agents belonging to our family and community circles is an enduring intuitive phenomenon across human societies – what social psychologists refer to as transactive memory – in offloading our various socio-cognitive faculties to digital technology, we may plausibly be supplanting the visceral social connections forged by transactive memory. This paper will present related research and literature produced across the disciplines of sociobiology, socio-cultural anthropology, social psychology, cognitive semiotics and communication and media studies that directly and indirectly address the social precarity cultivated by digital technologies. This body of scholarly work will then be situated within common areas of interest belonging to digital anthropology, including the groundbreaking work of Pavel Curtis, Christopher Kelty, Lynn Cherny, Vincent Duclos, Nick Seaver, and Sherry Turkle. It is anticipated that in harmonizing these overlapping areas of intradisciplinary interest, this paper can weave together the disparate connections across spheres of knowledge that help delineate the conditions of our contemporary digital existence.

Keywords: cognition, digital media, knowledge keeping, transactive memory

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27478 Measurements of Recovery Stress and Recovery Strain of Ni-Based Shape Memory Alloys

Authors: W. J. Kim

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The behaviors of the recovery stress and strain of an ultrafine-grained Ni-50.2 at.% Ti alloy prepared by high-ratio differential speed rolling (HRDSR) were examined by a specially designed tensile-testing set up, and the factors that influence the recovery stress and strain were studied. After HRDSR, both the recovery stress and strain were enhanced compared to the initial condition. The constitutive equation showing that the maximum recovery stress is a sole function of the recovery strain was developed based on the experimental data. The recovery strain increased as the yield stress increased. The maximum recovery stress increased with an increase in yield stress. The residual recovery stress was affected by the yield stress as well as the austenite-to-martensite transformation temperature. As the yield stress increased and as the martensitic transformation temperature decreased, the residual recovery stress increased.

Keywords: high-ratio differential speed rolling, tensile testing, severe plastic deformation, shape memory alloys

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27477 Finite Element and Split Bregman Methods for Solving a Family of Optimal Control Problem with Partial Differential Equation Constraint

Authors: Mahmoud Lot

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In this article, we will discuss the solution of elliptic optimal control problem. First, by using the nite element method, we obtain the discrete form of the problem. The obtained discrete problem is actually a large scale constrained optimization problem. Solving this optimization problem with traditional methods is difficult and requires a lot of CPU time and memory. But split Bergman method converts the constrained problem to an unconstrained, and hence it saves time and memory requirement. Then we use the split Bregman method for solving this problem, and examples show the speed and accuracy of split Bregman methods for solving these types of problems. We also use the SQP method for solving the examples and compare with the split Bregman method.

Keywords: Split Bregman Method, optimal control with elliptic partial differential equation constraint, finite element method

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27476 An Indoor Positioning System in Wireless Sensor Networks with Measurement Delay

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

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In the current paper, an indoor positioning system is proposed with consideration of measurement delay. Firstly, an estimation filter with a measurement delay is designed for the indoor positioning mechanism under a weighted least square criterion, which utilizes only finite measurements on the most recent window. The proposed estimation filtering based scheme gives the filtered estimates for position, velocity and acceleration of moving target in real-time, while removing undesired noisy effects and preserving desired moving positions. Secondly, the proposed scheme is shown to have good inherent properties such as unbiasedness, efficiency, time-invariance, deadbeat, and robustness due to the finite memory structure. Finally, computer simulations shows that the performance of the proposed estimation filtering based scheme can outperform to the existing infinite memory filtering based mechanism.

Keywords: indoor positioning system, wireless sensor networks, measurement delay

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27475 Non-Linear Load-Deflection Response of Shape Memory Alloys-Reinforced Composite Cylindrical Shells under Uniform Radial Load

Authors: Behrang Tavousi Tehrani, Mohammad-Zaman Kabir

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Shape memory alloys (SMA) are often implemented in smart structures as the active components. Their ability to recover large displacements has been used in many applications, including structural stability/response enhancement and active structural acoustic control. SMA wires or fibers can be embedded with composite cylinders to increase their critical buckling load, improve their load-deflection behavior, and reduce the radial deflections under various thermo-mechanical loadings. This paper presents a semi-analytical investigation on the non-linear load-deflection response of SMA-reinforced composite circular cylindrical shells. The cylinder shells are under uniform external pressure load. Based on first-order shear deformation shell theory (FSDT), the equilibrium equations of the structure are derived. One-dimensional simplified Brinson’s model is used for determining the SMA recovery force due to its simplicity and accuracy. Airy stress function and Galerkin technique are used to obtain non-linear load-deflection curves. The results are verified by comparing them with those in the literature. Several parametric studies are conducted in order to investigate the effect of SMA volume fraction, SMA pre-strain value, and SMA activation temperature on the response of the structure. It is shown that suitable usage of SMA wires results in a considerable enhancement in the load-deflection response of the shell due to the generation of the SMA tensile recovery force.

Keywords: airy stress function, cylindrical shell, Galerkin technique, load-deflection curve, recovery stress, shape memory alloy

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27474 Experimental Evaluation of Succinct Ternary Tree

Authors: Dmitriy Kuptsov

Abstract:

Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

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27473 A Case Report on Cognitive-Communication Intervention in Traumatic Brain Injury

Authors: Nikitha Francis, Anjana Hoode, Vinitha George, Jayashree S. Bhat

Abstract:

The interaction between cognition and language, referred as cognitive-communication, is very intricate, involving several mental processes such as perception, memory, attention, lexical retrieval, decision making, motor planning, self-monitoring and knowledge. Cognitive-communication disorders are difficulties in communicative competencies that result from underlying cognitive impairments of attention, memory, organization, information processing, problem solving, and executive functions. Traumatic brain injury (TBI) is an acquired, non - progressive condition, resulting in distinct deficits of cognitive communication abilities such as naming, word-finding, self-monitoring, auditory recognition, attention, perception and memory. Cognitive-communication intervention in TBI is individualized, in order to enhance the person’s ability to process and interpret information for better functioning in their family and community life. The present case report illustrates the cognitive-communicative behaviors and the intervention outcomes of an adult with TBI, who was brought to the Department of Audiology and Speech Language Pathology, with cognitive and communicative disturbances, consequent to road traffic accident. On a detailed assessment, she showed naming deficits along with perseverations and had severe difficulty in recalling the details of the accident, her house address, places she had visited earlier, names of people known to her, as well as the activities she did each day, leading to severe breakdowns in her communicative abilities. She had difficulty in initiating, maintaining and following a conversation. She also lacked orientation to time and place. On administration of the Manipal Manual of Cognitive Linguistic Abilities (MMCLA), she exhibited poor performance on tasks related to visual and auditory perception, short term memory, working memory and executive functions. She attended 20 sessions of cognitive-communication intervention which followed a domain-general, adaptive training paradigm, with tasks relevant to everyday cognitive-communication skills. Compensatory strategies such as maintaining a dairy with reminders of her daily routine, names of people, date, time and place was also recommended. MMCLA was re-administered and her performance in the tasks showed significant improvements. Occurrence of perseverations and word retrieval difficulties reduced. She developed interests to initiate her day-to-day activities at home independently, as well as involve herself in conversations with her family members. Though she lacked awareness about her deficits, she actively involved herself in all the therapy activities. Rehabilitation of moderate to severe head injury patients can be done effectively through a holistic cognitive retraining with a focus on different cognitive-linguistic domains. Selection of goals and activities should have relevance to the functional needs of each individual with TBI, as highlighted in the present case report.

Keywords: cognitive-communication, executive functions, memory, traumatic brain injury

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27472 Subspace Rotation Algorithm for Implementing Restricted Hopfield Network as an Auto-Associative Memory

Authors: Ci Lin, Tet Yeap, Iluju Kiringa

Abstract:

This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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27471 Modeling Visual Memorability Assessment with Autoencoders Reveals Characteristics of Memorable Images

Authors: Elham Bagheri, Yalda Mohsenzadeh

Abstract:

Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

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27470 Another Beautiful Sounds: Building the Memory of Sound of Peddling in Beijing with Digital Technology

Authors: Dan Wang, Qing Ma, Xiaodan Wang, Tianjiao Qi

Abstract:

The sound of peddling in Beijing, also called “yo-heave-ho” or “cry of one's ware”, is a unique folk culture and usually found in Beijing hutong. For the civilians in Beijing, sound of peddling is part of their childhood. And for those who love the traditional culture of Beijing, it is an old song singing the local conditions and customs of the ancient city. For example, because of his great appreciation, the British poet Osbert Stewart once put sound of peddling which he had heard in Beijing as a street orchestra performance in the article named "Beijing's sound and color".This research aims to collect and integrate the voice/photo resources and historical materials of sound concerning peddling in Beijing by digital technology in order to protect the intangible cultural heritage and pass on the city memory. With the goal in mind, the next stage is to collect and record all the materials and resources based on the historical documents study and interviews with civilians or performers. Then set up a metadata scheme (which refers to the domestic and international standards such as "Audio Data Processing Standards in the National Library", DC, VRA, and CDWA, etc.) to describe, process and organize the sound of peddling into a database. In order to fully show the traditional culture of sound of peddling in Beijing, web design and GIS technology are utilized to establish a website and plan holding offline exhibitions and events for people to simulate and learn the sound of peddling by using VR/AR technology. All resources are opened to the public and civilians can share the digital memory through not only the offline experiential activities, but also the online interaction. With all the attempts, a multi-media narrative platform has been established to multi-dimensionally record the sound of peddling in old Beijing with text, images, audio, video and so on.

Keywords: sound of peddling, GIS, metadata scheme, VR/AR technology

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27469 Spatial Data Mining by Decision Trees

Authors: Sihem Oujdi, Hafida Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 596
27468 Dynamic Variation in Nano-Scale CMOS SRAM Cells Due to LF/RTS Noise and Threshold Voltage

Authors: M. Fadlallah, G. Ghibaudo, C. G. Theodorou

Abstract:

The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.

Keywords: low-frequency noise, random telegraph noise, dynamic variation, SRRV

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27467 Deep Learning-Based Channel Estimation for RIS-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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27466 Analyze of Nanoscale Materials and Devices for Future Communication and Telecom Networks in the Gas Refinery

Authors: Mohamad Bagher Heidari, Hefzollah Mohammadian

Abstract:

New discoveries in materials on the nanometer-length scale are expected to play an important role in addressing ongoing and future challenges in the field of communication. Devices and systems for ultra-high speed short and long range communication links, portable and power efficient computing devices, high-density memory and logics, ultra-fast interconnects, and autonomous and robust energy scavenging devices for accessing ambient intelligence and needed information will critically depend on the success of next-generation emerging nonmaterials and devices. This article presents some exciting recent developments in nonmaterials that have the potential to play a critical role in the development and transformation of future intelligent communication and telecom networks in the gas refinery. The industry is benefiting from nanotechnology advances with numerous applications including those in smarter sensors, logic elements, computer chips, memory storage devices, optoelectronics.

Keywords: nonmaterial, intelligent communication, nanoscale, nanophotonic, telecom

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27465 Visitor Discourses of European Holocaust Heritage: A Netnography

Authors: Craig Wight

Abstract:

This presentation will identify the key findings from a recent netnographic discourse analysis of social media content generated in response to visits to three iconic European Holocaust Heritage sites: Ann Frank’s House in Amsterdam, the Netherlands, the Auschwutz-Birkenau Memorial Museum and Memorial in Poland, and the Jewish Museum in Berlin, Germany. Four major discourses are identified under the headings of Holocaust heritage as social memory, reactions to Holocaust heritage, obligation and ritual, and transgressive visitor behaviour. Together, these discourses frame the values, existential anxieties, emotions, priorities, and expectations of visitors. The findings will interest those involved in the planning and management of Holocaust heritage for tourism purposes since they provide unique access to an archive of unmediated visitor feedback on European Holocaust heritage experiences.

Keywords: foucault, european holocaust heritage, discourse analysis, netnography, social media, dark tourism

Procedia PDF Downloads 119