Search results for: memory effect

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

Procedia PDF Downloads 590

Authors: Parker Townes, Aisouda Savadlou, Shoshana Weiss, Marina Jarenova, Suzzane Ferris, Dan Devoe, Russel Schachar, Scott Patten, Tomas Lange, Marlena Colasanto, Holly McGinn, Paul Arnold

Abstract:

Some research suggests obsessive-compulsive disorder (OCD) is associated with impaired executive functioning: higher-level mental processes involved in carrying out tasks and solving problems. Relevant literature was identified systematically through online databases. Meta-analyses were conducted for task performance metrics reported by at least two articles. Results were synthesized by the executive functioning domain measured through each performance metric. Heterogeneous literature was identified, typically involving few studies using consistent measures. From 29 included studies, analyses were conducted on 33 performance metrics from 12 tasks. Results suggest moderate associations of working memory (two out of five tasks presented significant findings), planning (one out of two tasks presented significant findings), and visuospatial abilities (one out of two tasks presented significant findings) with OCD in youth. There was inadequate literature or contradictory findings for other executive functioning domains. These findings suggest working memory, planning, and visuospatial abilities are impaired in pediatric OCD, with mixed results. More work is needed to identify the effect of age and sex on these results. Acknowledgment: This work was supported by the Alberta Innovates Translational Health Chair in Child and Youth Mental Health. The funders had no role in the design, conducting, writing, or decision to submit this article for publication.

Keywords: obsessive-compulsive disorder, neurocognition, executive functioning, adolescents, children

Procedia PDF Downloads 81

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

Procedia PDF Downloads 327

Authors: Samil Ozcan

Abstract:

Airlines companies target different customer segments in consideration of pricing, service quality, flight network, etc. and their brand positioning accords with the marketization strategies developed in the same direction. The object of this study, Turkish Airlines, has many peculiarities regarding its brand positioning as compared to its rivals in the sector. In the first place, it appeals to a global customer group because of its Star Alliance membership and its broad flight network with 315 destination points. The second group in its customer segmentation includes domestic customers. For this group, the company follows a marketing strategy that plays to local culture and accentuates the image of Turkishness as an emotional allurement. The advertisements and publicity projects designed in this regard put little emphasis on the service quality the company offers to its clients; it addresses the emotions of the consumers rather than individual benefits and relies on the historical memory of the nation and shared cultural values. This study examines the publicity work which aims at the second segment customer group focusing on Turkish Airlines’ 85th Anniversary Commercial through a symbolic meaning analysis approach. The commercial presents six stories with undertones of nationalism in its theme. Nationalism is not just the product of collective interests based on reason but a result of patriotism in the sense of loyalty to state and nation and love of ethnic belonging. While nationalism refers to concrete notions such as blood tie, common ancestor, shared history, it is not the actuality of these notions that it draws its real strength but the emotions invested in them. The myths of origin, the idea of common homeland, boundary definitions, and symbolic acculturation have instrumental importance in the development of these commonalities. The commercial offers concrete examples for an analysis of Connor’s definition of nationalism based on emotions. Turning points in the history of the Turkish Republic and the historical mission Turkish Airlines undertook in these moments are narrated in six stories in the commercial with a highly emotional theme. These emotions, in general, depend on collective memory generated by national consciousness. Collective memory is not simply remembering the past. It is constructed through the reconstruction and reinterpretation of the past in the present moment. This study inquires the motivations behind the nationalist emotions generated within the collective memory by engaging with the commercial released for the 85th anniversary of Turkish Airlines as the object of analysis. Symbols and myths can be read as key concepts that reveal the relation between 'identity and memory'. Because myths and symbols do not merely reflect on collective memory, they reconstruct it as well. In this sense, the theme of the commercial defines the image of Turkishness with virtues such as self-sacrifice, helpfulness, humanity, and courage through a process of meaning creation based on symbolic mythologizations like flag and homeland. These virtues go beyond describing the image of Turkishness and become an instrument that defines and gives meaning to Turkish identity.

Keywords: collective memory, emotions, identity, nationalism

Procedia PDF Downloads 141

Authors: Heidi Ahonen

Abstract:

Since antiquity, many cultures have seemingly known the power of low frequencies, incorporating them in healing practices through drumming, singing, humming, etc. Many music therapists recognize there is something in music that is transformative enough to make a difference in people’s lives. This paper summarizes the key findings of several low-frequency research with various client populations conducted by the author. Utilizing low-frequency sound (30 or 40 Hz) may have diverse therapeutic impacts: (1) Calming effect – decreased agitation (autism, brain injury, AD, dementia) (2) Muscle relaxation (CP & spasticity & pain/after surgery patients, MS, fibromyalgia) (3) Relaxation/stress release (anxiety, stress, PTSD, trauma, insomnia) (4) Muscular/motor functioning/ decrease of tremor (CP, MS, Parkinson) (5) Increase in alertness, cognitive awareness & short-term memory function (brain injury, severe global developmental delay, AD) (6) Increased focus (AD, PTSD, trauma). The paper will conclude by presenting ideas informing the clinical practice. Future studies need to investigate what frequencies are effective for particular client populations and why, what theories can explain the effect, and finally, something that has been long debated - is it auditive or kinaesthetic stimulation or the combination of both that is effective?

Keywords: low frequency, 40 Hz, sound, neuro disability

Procedia PDF Downloads 90

Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

Abstract:

The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

Procedia PDF Downloads 204

Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

Abstract:

Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

Procedia PDF Downloads 189

Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

Procedia PDF Downloads 256

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

Procedia PDF Downloads 324

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

Abstract:

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

Procedia PDF Downloads 231

Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

Abstract:

The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

Procedia PDF Downloads 44

Authors: Peter Robinson, Milka Ivanova

Abstract:

Despite the growing interest in the Cold War period and heritage, little attention has been paid to the presentation and curatorship of Cold War heritage in eastern or western Europe. In 2021 Leeds Beckett University secured a British Academy Grant to explore visitor experiences, curatorship, emotion, and memory at Cold War-related tourist sites, comparing the perspectives of eastern and western European sites through research carried out in the UK and Bulgaria. The research explores the themes of curatorship, experience, and memory. Many of the sites included in the research in the UK-based part of the project are nuclear bunkers that have been decommissioned and are now open to visitors. The focus of this conference abstract is one of several perspectives drawn from a British Academy Grant-funded project exploring curatorship, visitor experience and nostalgia and memory in former cold war spaces in the UK, bringing together critical comparisons between western and eastern European sites. The project identifies specifically the challenges of ownership, preservation and presentation and discusses the challenges facing those who own, manage, and provide access to cold war museums and sites. The research is underpinned by contested issues of authenticity and ownership, discussing narrative accounts of those involved in caring for and managing these sites. The research project draws from interviews with key stakeholders, site observations, visitor surveys, and content analysis of Trip advisor posts. Key insights from the project include the external challenges owners and managers face from a lack of recognition of and funding for important Cold War sites in the UK that are at odds with interest shown in cold war sites by visitors to Cold War structures and landmarks. The challenges center on the lack of consistent approaches toward cold war heritage conservation, management, and ownership, lack of curatorial expertise and over-reliance on no-expert interpretation and presentation of heritage, the effect of the passage of time on personal connections to cold war heritage sites, the dissipating technological knowledge base, the challenging structure that does not lend themselves easily as visitor attractions or museums, the questionable authenticity of artifacts, the limited archival material, and quite often limited budgets. A particularly interesting insight focusing on nuclear bunkers has been on the difficulties in site reinterpretation because of the impossibility of fully exploring the enormity of nuclear war as a consistent threat of the Cold War. Further insights from the research highlight the secrecy of many of the sites as a key marketing strategy, particularly in relation to the nuclear bunker sites included in the project.

Keywords: cold war, curatorship, heritage, nuclear bunkers.

Procedia PDF Downloads 65

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

Procedia PDF Downloads 76

Authors: Sophia Melanson Ricciardone

Abstract:

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

Procedia PDF Downloads 116

Authors: W. J. Kim

Abstract:

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

Procedia PDF Downloads 348

Authors: Kalai Lamia, Jilani Faouzi

Abstract:

Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behaviour of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.

Keywords: asymmetry volatility, clustering, stylised facts, leverage effect

Procedia PDF Downloads 286

Authors: Swati Bajpai, S. P. K Jena

Abstract:

Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

Procedia PDF Downloads 473

Authors: Koustav Pal, Indranil Das

Abstract:

In recent times, perovskite and double perovskite (DP) systems attracts lot of interest as they provide a rich material platform for studying emergent functionalities like near-room-temperature ferromagnetic (FM) insulators, exchange bias (EB), magnetocaloric effects, colossal magnetoresistance, anisotropy, etc. These interesting phenomena emerge because of complex couplings between spin, charge, orbital, and lattice degrees of freedom in these systems. Various magnetic phenomena such as exchange bias, spin glass, memory effect, colossal magneto-resistance, etc. can be modified and controlled through antisite (B-site) disorder or controlling oxygen concentration of the material. By controlling oxygen concentration in SrFe0.5Co0.5O3 – δ (SFCO) (δ ∼ 0.3), we achieve intrinsic exchange bias effect with a large exchange bias field (∼1.482 Tesla) and giant coercive field (∼1.454 Tesla). Now we modified the B-site by introducing 10% iridium in the system. This modification give rise to the exchange bias field as high as 1.865 tesla and coercive field 1.863 tesla. Our work aims to investigate the effect of oxygen deficiency and B-site effect on exchange bias in oxide materials for potential technological applications. Structural characterization techniques including X-ray diffraction, scanning tunneling microscopy, and transmission electron microscopy were utilized to determine crystal structure and particle size. X-ray photoelectron spectroscopy was used to identify valence states of the ions. Magnetic analysis revealed that oxygen deficiency resulted in a large exchange bias due to a significant number of ionic mixtures. Iridium doping was found to break interaction paths, resulting in various antiferromagnetic and ferromagnetic surfaces that enhance exchange bias.

Keywords: coercive field, disorder, exchange bias, spin glass

Procedia PDF Downloads 60

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

Procedia PDF Downloads 146

Authors: Mahmoud Lot

Abstract:

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

Procedia PDF Downloads 139

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

Abstract:

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

Procedia PDF Downloads 466

Authors: Mohamad Khairi Ishak

Abstract:

Conventional public key crypto systems such as RSA (Ron Rivest, Adi Shamir and Leonard Adleman), DSA (Digital Signature Algorithm), and Elgamal are no longer efficient to be implemented in the small, memory constrained devices. Elliptic Curve Cryptography (ECC), which allows smaller key length as compared to conventional public key crypto systems, has thus become a very attractive choice for many applications. This paper describes implementation of an elliptic curve cryptography (ECC) encryption engine on a FPGA. The system has been implemented in 2 different key sizes, which are 131 bits and 163 bits. Area and timing analysis are provided for both key sizes for comparison. The crypto system, which has been implemented on Altera’s EPF10K200SBC600-1, has a hardware size of 5945/9984 and 6913/9984 of logic cells for 131 bits implementation and 163 bits implementation respectively. The crypto system operates up to 43 MHz, and performs point multiplication operation in 11.3 ms for 131 bits implementation and 14.9 ms for 163 bits implementation. In terms of speed, our crypto system is about 8 times faster than the software implementation of the same system.

Keywords: elliptic curve cryptography, FPGA, key sizes, memory

Procedia PDF Downloads 300

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

Procedia PDF Downloads 148

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

Procedia PDF Downloads 329

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

Procedia PDF Downloads 102

Authors: Merrylord Harb-Azar

Abstract:

Traditionally, PTSD treatment has involved trauma-focused cognitive behaviour therapy (TF CBT) to consolidate traumatic memories. A piloted integrated treatment of TF CBT and eye movement desensitisation reprocessing therapy (EMDR) of eight phases will fasten the rate memory is being consolidated and enhance cognitive functioning in patients with PTSD. Patients spend a considerable amount of time in treatment managing their traumas experienced firsthand, or from aversive details ranging from war, assaults, accidents, abuse, hostage related, riots, or natural disasters. The time spent in treatment or as inpatient affects overall quality of life, relationships, cognitive functioning, and overall sense of identity. EMDR is being offered twice a week in conjunction with the standard prolonged exposure as an inpatient in a private hospital. Prolonged exposure for up to 5 hours per day elicits the affect response required for EMDR sessions in the afternoon to unlock unprocessed memories and facilitate consolidation in the amygdala and hippocampus. Results are indicating faster consolidation of memories, reduction in symptoms in a shorter period of time, reduction in admission time, which is enhancing the quality of life and relationships, and improved cognition. The impact of events scale (IES) results demonstrate a significant reduction in symptoms, trauma symptoms inventory (TSI), and posttraumatic stressor disorder check list (PCL) that demonstrates large effect sizes to date. An integrated treatment approach for PTSD achieves a faster resolution of memories, improves cognition, and reduces the amount of time spent in therapy.

Keywords: EMDR enhances cognitive functioning, faster consolidation of trauma memory, integrated treatment of TF CBT and EMDR, reduction in inpatient admission time

Procedia PDF Downloads 131

Authors: Rahele Mesbah, Nic Van Der Wee, Manja Koenders, Erik Giltay, Albert Van Hemert, Max De Leeuw

Abstract:

Introduction: Patients with bipolar disorder (BD), characterized by depressive and manic episodes, often suffer from cognitive dysfunction. An up-to-date meta-analysis of functional Magnetic Resonance Imaging (fMRI) studies examining cognitive function in BD is lacking. Objective: The aim of the current fMRI meta-analysis is to investigate brain functioning of bipolar patients compared with healthy subjects within three domains of emotion processing, reward processing, and working memory. Method: Differences in brain regions activation were tested within whole-brain analysis using the activation likelihood estimation (ALE) method. Separate analyses were performed for each cognitive domain. Results: A total of 50 fMRI studies were included: 20 studies used an emotion processing (316 BD and 369 HC) task, 9 studies a reward processing task (215 BD and 213 HC), and 21 studies used a working memory task (503 BD and 445 HC). During emotion processing, BD patients hyperactivated parts of the left amygdala and hippocampus as compared to HC’s, but showed hypoactivation in the inferior frontal gyrus (IFG). Regarding reward processing, BD patients showed hyperactivation in part of the orbitofrontal cortex (OFC). During working memory, BD patients showed increased activity in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Conclusions: This meta-analysis revealed evidence for activity disturbances in several brain areas involved in the cognitive functioning of BD patients. Furthermore, most of the found regions are part of the so-called fronto-limbic network which is hypothesized to be affected as a result of BD candidate genes' expression.

Keywords: cognitive functioning, fMRI analysis, bipolar disorder, fronto-limbic network

Procedia PDF Downloads 442

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

Procedia PDF Downloads 284

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 600

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

Procedia PDF Downloads 33