Search results for: memory analysis

Authors: Swati Tyagi, Syed Abbas

Abstract:

Fractional-order Hopfield neural networks are generally used to model the information processing among the interacting neurons. To show the constancy of the processed information, it is required to analyze the stability of these systems. In this work, we perform Mittag-Leffler stability for the corresponding Caputo fractional-order bidirectional associative memory (BAM) neural networks with various time-delays. We derive sufficient conditions to ensure the existence and uniqueness of the equilibrium point by using the theory of topological degree theory. By applying the fractional Lyapunov method and Mittag-Leffler functions, we derive sufficient conditions for the global Mittag-Leffler stability, which further imply the global asymptotic stability of the network equilibrium. Finally, we present two suitable examples to show the effectiveness of the obtained results.

Keywords: bidirectional associative memory neural network, existence and uniqueness, fractional-order, Lyapunov function, Mittag-Leffler stability

Procedia PDF Downloads 337

Authors: Gaurav Bansod, Swapnil Sutar, Abhijit Patil, Jagdish Patil

Abstract:

This paper proposes an ultra-lightweight cipher NUX. NUX is a generalized Feistel network. It supports 128/80 bit key length and block length of 64 bit. For 128 bit key length, NUX needs only 1022 GEs which is less as compared to all existing cipher design. NUX design results into less footprint area and minimal memory size. This paper presents security analysis of NUX cipher design which shows cipher’s resistance against basic attacks like Linear and Differential Cryptanalysis. Advanced attacks like Biclique attack is also mounted on NUX cipher design. Two different F function in NUX cipher design results in high diffusion mechanism which generates large number of active S-boxes in minimum number of rounds. NUX cipher has total 31 rounds. NUX design will be best-suited design for critical application like smart grid, IoT, wireless sensor network, where memory size, footprint area and the power dissipation are the major constraints.

Keywords: lightweight cryptography, Feistel cipher, block cipher, IoT, encryption, embedded security, ubiquitous computing

Procedia PDF Downloads 325

Authors: Lulu Wang, Yongjun Xu, Xiaoyang Qiao

Abstract:

The Forbidden City is well known for being full of Chinese cultural and historical relics. However, the Masters in the Forbidden City, a documentary film, doesn’t just dwell on the stories of the past. Instead, it focuses on ordinary people—the restorers of the relics and antiquities, which has caught the sight of Chinese audiences. From this popular documentary film, a new way can be considered, that is to show the relics, antiquities and painting with a character of modern humanities by films and TV programs. Of course, it can’t just like a simple explanation from tour guides in museums. It should be a perfect combination of scenes, heritages, stories, storytellers and background music. All we want to do is trying to dig up the humanity behind the heritages and then create a virtual scene for the audience to have emotional resonance from the humanity. It is believed that there are two problems. One is that compared with the entertainment shows, why people prefer to see the boring restoration work. The other is that what the interaction is between those history documentary films, the heritages, the audiences and collective memory. This paper mainly used the methods of text analysis and data analysis. The audiences’ comment texts were collected from all kinds of popular video sites. Through analyzing those texts, there was a word cloud chart about people preferring to use what kind of words to comment the film. Then the usage rate of all comments words was calculated. After that, there was a Radar Chart to show the rank results. Eventually, each of them was given an emotional value classification according their comment tone and content. Based on the above analysis results, an interaction model among the audience, history films/TV programs and the collective memory can be summarized. According to the word cloud chart, people prefer to use such words to comment, including moving, history, love, family, celebrity, tone... From those emotional words, we can see Chinese audience felt so proud and shared the sense of Collective Identity, so they leave such comments: To our great motherland! Chinese traditional culture is really profound! It is found that in the construction of collective memory symbology, the films formed an imaginary system by organizing a ‘personalized audience’. The audience is not just a recipient of information, but a participant of the documentary films and a cooperator of collective memory. At the same time, it is believed that the traditional background music, the spectacular present scenes and the tone of the storytellers/hosts are also important, so it is suggested that the museums could try to cooperate with the producers of movie and TV program to create a vivid scene for the people. Maybe it’s a more artistic way for heritages to be open to all the world.

Keywords: audience, heritages, history movies, TV programs

Procedia PDF Downloads 121

Authors: Sneha Thakur, Sanjeev Karmakar

Abstract:

This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

Procedia PDF Downloads 44

Authors: Isari Pairoa, Proud Arunrangsiwed

Abstract:

Celebrity and brand mascot endorsement have been explored for more than three decades. Both endorsers can effectively transfer their reputation to corporate image and can influence the customers to purchase the product. However, there was little known about the mediators between the level of endorsement and its effect on buying behavior. The objective of the current study is to identify the gab of the previous studies and to seek possible mediators. It was found that consumer’s memory and identification are the mediators, of source credibility and endorsement effect. A future study should confirm the model of endorsement, which was established in the current study.

Keywords: product endorsement, memory, identification theory, source credibility, unintentional effect

Procedia PDF Downloads 199

Authors: Krzysztof Skiba, Zbigniew Czyz, Ksenia Siadkowska, Piotr Borowiec

Abstract:

The article presents selected concepts of technologies that use intelligent materials in aircraft in order to improve their performance. Most of the research focuses on solutions that improve the performance of fixed wing aircraft due to related to their previously dominant market share. Recently, the development of the rotorcraft has been intensive, so there are not only helicopters but also gyroplanes and unmanned aerial vehicles using rotors and vertical take-off and landing. There are many different technologies to change a shape of the aircraft or its elements. Piezoelectric, deformable actuator systems can be applied in the system of an active control of vibration dampening in the aircraft tail structure. Wires made of shape memory alloys (SMA) could be used instead of hydraulic cylinders in the rear part of the aircraft flap. The aircraft made of intelligent materials (piezoelectrics and SMA) is one of the NASA projects which provide the possibility of changing a wing shape coefficient by 200%, a wing surface by 50%, and wing deflections by 20 degrees. Active surfaces made of shape memory alloys could be used to control swirls in the flowing stream. An intelligent control system for helicopter blades is a method for the active adaptation of blades to flight conditions and the reduction of vibrations caused by the rotor. Shape memory alloys are capable of recovering their pre-programmed shapes. They are divided into three groups: nickel-titanium-based, copper-based, and ferromagnetic. Due to the strongest shape memory effect and the best vibration damping ability, a Ni-Ti alloy is the most commercially important. The subject of this work was to prepare a conceptual design of a rotor blade with SMA actuators. The scope of work included 3D design of the supporting rotor blade, 3D design of beams enabling to change the geometry by changing the angle of rotation and FEM (Finite Element Method) analysis. The FEM analysis was performed using NX 12 software in the Pre/Post module, which includes extended finite element modeling tools and visualizations of the obtained results. Calculations are presented for two versions of the blade girders. For FEM analysis, three types of materials were used for comparison purposes (ABS, aluminium alloy 7057, steel C45). The analysis of internal stresses and extreme displacements of crossbars edges was carried out. The internal stresses in all materials were close to the yield point in the solution of girder no. 1. For girder no. 2 solution, the value of stresses decreased by about 45%. As a result of the displacement analysis, it was found that the best solution was the ABS girder no. 1. The displacement of about 0.5 mm was obtained, which resulted in turning the crossbars (upper and lower) by an angle equal to 3.59 degrees. This is the largest deviation of all the tests. The smallest deviation was obtained for beam no. 2 made of steel. The displacement value of the second girder solution was approximately 30% lower than the first solution. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: aircraft, helicopters, shape memory alloy, SMA, smart material, unmanned aerial vehicle, UAV

Procedia PDF Downloads 103

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 32

Authors: Thomas Heffernan, Nick Neave, Colin Hamilton, Gill Case

Abstract:

Hoarding is the acquisition of and failure to discard possessions, leading to excessive clutter and significant psychological/emotional distress. From a cognitive-behavioural approach, excessive hoarding arises from information-processing deficits, as well as from problems with emotional attachment to possessions and beliefs about the nature of possessions. In terms of information processing, hoarders have shown deficits in executive functions, including working memory, planning, inhibitory control, and cognitive flexibility. However, this previous research is often confounded by co-morbid factors such as anxiety, depression, or obsessive-compulsive disorder. The current study adopted a cognitive-behavioural approach, specifically assessing executive deficits and working memory in a non-clinical sample of hoarders, compared with non-hoarders. In this study, a non-clinical sample of 40 hoarders and 73 non-hoarders (defined by The Savings Inventory-Revised) completed the Adult Executive Functioning Inventory, which measures working memory and inhibition, Dysexecutive Questionnaire-Revised, which measures general executive function and the Hospital Anxiety and Depression Scale, which measures mood. The participant sample was made up of unpaid young adult volunteers who were undergraduate students and who completed the questionnaires on a university campus. The results revealed that, after observing no differences between hoarders and non-hoarders on age, sex, and mood, hoarders reported significantly more deficits in inhibitory control and general executive function when compared with non-hoarders. There was no between-group difference on general working memory. This suggests that non-clinical hoarders have a specific difficulty with inhibition-control, which enables you to resist repeated, unwanted urges. This might explain the hoarder’s inability to resist urges to buy and keep items that are no longer of any practical use. These deficits may be underpinned by general executive function deficiencies.

Keywords: hoarding, memory, executive, deficits

Procedia PDF Downloads 159

Authors: Priya Varma, Denis John McKeown

Abstract:

Psychological time, unlike physical time, is believed to be ‘compressive’ in the sense that the mental representations of a series of events may be internally arranged with ever decreasing inter-event spacing (looking back from the most recently encoded event). If this is true, the record within immediate memory of recent events is severely temporally distorted. Although this notion of temporal distortion of the memory record is captured within some theoretical accounts of human forgetting, notably temporal distinctiveness accounts, the way in which the fundamental nature of the distortion underpins memory and forgetting broadly is barely recognised or at least directly investigated. Our intention here was to manipulate the spacing of items for recall in order to ‘reverse’ this supposed natural compression within the encoding of the items. In Experiment 1 three schedules of presentation (expanding, contracting and fixed irregular temporal spacing) were created using logarithmic spacing of the words for both free and serial recall conditions. The results of recall of lists of 7 words showed statistically significant benefits of temporal isolation, and more excitingly the contracting word series (which we may think of as reversing the natural compression within the mental representation of the word list) showed best performance. Experiment 2 tested for effects of active verbal rehearsal in the recall task; this reduced but did not remove the benefits of our temporal scheduling manipulation. Finally, a third experiment used the same design but with Chinese characters as memoranda, in a further attempt to subvert possible verbal maintenance of items. One change to the design here was to introduce a probe item following the sequence of items and record response times to this probe. Together the outcomes of the experiments broadly support the notion of temporal compression within immediate memory.

Keywords: memory, serial position curves, temporal isolation, temporal schedules

Procedia PDF Downloads 191

Authors: Boris Ershov

Abstract:

Depression is the most common mood disorder experienced by patients who have sustained a traumatic brain injury (TBI) and is associated with poorer cognitive functional outcomes. However, in some cases, similar cognitive impairments can also be observed in depression. There is not enough information about the features of the cognitive deficit in patients with TBI in relation to patients with depression. TBI patients without depressive symptoms (TBInD, n25), TBI patients with depressive symptoms (TBID, n31), and 28 patients with bipolar II disorder (BP) were included in the study. There were no significant differences in participants in respect to age, handedness and educational level. The patients clinical status was determined by using Montgomery–Asberg Depression Rating Scale (MADRS). All participants completed a cognitive battery (The Brief Assessment of Cognition in Affective Disorders (BAC-A)). Additionally, the Rey–Osterrieth Complex Figure (ROCF) was used to assess visuospatial construction abilities and visual memory, as well as planning and organizational skills. Compared to BP, TBInD and TBID showed a significant impairments in visuomotor abilities, verbal and visual memory. There were no significant differences between BP and TBID groups in working memory, speed of information processing, problem solving. Interference effect (cognitive inhibition) was significantly greater in TBInD and TBID compared to BP. Memory bias towards mood-related information in BP and TBID was greater in comparison with TBInD. These results suggest that depressive symptoms are associated with impairments some executive functions in combination at decrease of speed of information processing.

Keywords: bipolar II disorder, depression, neurocognitive deficits, traumatic brain injury

Procedia PDF Downloads 329

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 464

Authors: María Isabel Núñez-Peña, Macarena Suárez Pellicioni

Abstract:

In the present study, we used event-related potentials (ERP) to address the question of whether high (HMA) and low math-anxious (LMA) individuals differ on a complex addition verification task, which involved both carrying and non-carrying additions. ERPs were recorded while seventeen HMA and seventeen LMA individuals performed the verification task. Groups did not differ in trait anxiety or gender distribution. Participants were presented with two-digit additions and were asked to decide whether the proposed solution was correct or incorrect. Behavioral data showed a significant Carrying x Proposed solution x Group interaction for accuracy, showing that carrying additions were more error prone than non-carrying ones for both groups, although the difference non-carrying minus carrying was larger for the HMA group. As for ERPs, a P2 component larger in HMA individuals than in their LMA peers was found both for carrying and non-carrying additions. The P2 was followed by a sustained negative slow wave at parietal positions. Because the negative slow waves are thought to reflect the updating of working memory, these results give support to the relationship among working memory, math performance and math anxiety.

Keywords: math anxiety, carrying, working memory, P2

Procedia PDF Downloads 405

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

Procedia PDF Downloads 54

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 184

Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

Abstract:

The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

Procedia PDF Downloads 152

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

Abstract:

In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

Procedia PDF Downloads 188

Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

Abstract:

Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

Procedia PDF Downloads 87

Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko

Abstract:

The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.

Keywords: sparse matrix, compressed format, Hubbard model, Anderson model

Procedia PDF Downloads 365

Authors: Reza Khani, Ziba Hosseini

Abstract:

This study was an attempt to investigate the difference between learners of Iranian Kurdish–Persian bilingual language and Persian monolinguals, regarding language strategy use (LLS). The participants of the study were 120 monolingual Persian and 120 bilingual Kurdish studying English as a foreign language (EFL). Data were collected using strategy inventory for language learning SILL. The results show bilingual reported higher use of language learning strategies in all categories of SILL except memory strategies.

Keywords: language learning, memory, monolingual, comparative study

Procedia PDF Downloads 373

Authors: Q. Raza

Abstract:

Getting old is inevitable, tasks which were once simple are now a daily struggle. This paper is a study of how older users interact with web application based upon a series of experiments. The experiments conducted involved 12 participants and the experiments were split into two parts. The first set gives the users a feel of current social networks and the second set take into considerations from the participants and the results of the two are compared. This paper goes in detail on the psychological aspects such as social exclusion, Metacognition memory and Therapeutic memories and how this relates to users becoming isolated from society, social networking can be the roof on a foundation of successful computer interaction. The purpose of this paper is to carry out a study and to propose new ideas to help users to be able to use social networking sites easily and efficiently.

Keywords: cognitive psychology, special memory, social networking and human computer interaction

Procedia PDF Downloads 411

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 97

Authors: Mahmut Yildirim

Abstract:

This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

Procedia PDF Downloads 27

Authors: Nurcihan Kiris

Abstract:

Restricted sleep is common in young adults and adolescents. The results of a few objective studies of sleep deprivation on cognitive performance were not clarified. In particular, the effect of sleep deprivation on the cognitive functions associated with frontal lobe such as attention, executive functions, working memory is not well known. The aim of this study is to investigate the effect of partial sleep deprivation experimentally in adolescents on the cognitive tasks of frontal lobe including working memory, strategic thinking, simple attention, continuous attention, executive functions, and cognitive flexibility. Subjects of the study were recruited from voluntary students of Cukurova University. Eighteen adolescents underwent four consecutive nights of monitored sleep restriction (6–6.5 hr/night) and four nights of sleep extension (10–10.5 hr/night), in counterbalanced order, and separated by a washout period. Following each sleep period, cognitive performance was assessed, at a fixed morning time, using a computerized neuropsychological battery based on frontal lobe functions task, a timed test providing both accuracy and reaction time outcome measures. Only the spatial working memory performance of cognitive tasks was found to be statistically lower in a restricted sleep condition than the extended sleep condition. On the other hand, there was no significant difference in the performance of cognitive tasks evaluating simple attention, constant attention, executive functions, and cognitive flexibility. It is thought that especially the spatial working memory and strategic thinking skills of adolescents may be susceptible to sleep deprivation. On the other hand, adolescents are predicted to be optimally successful in ideal sleep conditions, especially in the circumstances requiring for the short term storage of visual information, processing of stored information, and strategic thinking. The findings of this study may also be associated with possible negative functional effects on the processing of academic social and emotional inputs in adolescents for partial sleep deprivation. Acknowledgment: This research was supported by Cukurova University Scientific Research Projects Unit.

Keywords: attention, cognitive functions, sleep deprivation, working memory

Procedia PDF Downloads 115

Authors: Israel B. Bitton

Abstract:

“Memory” is associated with various phenomena, from physical to mental, personal to collective and historical to cultural. As part of a broader exploration of memory studies in philosophy and science (slated for academic publication October 2021), this specific study employs analytical methods of cognitive psychology and philosophy of memory to theorize that A) the primary human will (drive) is to significance, in that every human action and expression can be rooted in a most primal desire to be cosmically significant (however that is individually perceived); and B) that the will to significance manifests as the will to memorability, an innate desire to be remembered by others after death. In support of these broad claims, a review of various popular culture “touchpoints”—historic and contemporary records spanning literature, film and television, traditional news media, and social media—is presented to demonstrate how this very theory is repeatedly and commonly expressed (and has been for a long time) by many popular public figures as well as “everyday people.” Though developed before COVID, the crisis only increased the theory’s relevance: so many people were forced to die alone, leaving them and their loved ones to face even greater existential angst than what ordinarily accompanies death since the usual expectations for one’s “final moments” were shattered. To underscore this issue of, and response to, what can be considered a sociocultural “memory gap,” this study concludes with a summary of several projects launched by journalists at the height of the pandemic to document the memorable human stories behind COVID’s tragic warped speed death toll that, when analyzed through the lens of Viktor E. Frankl’s psychoanalytical perspective on “existential meaning,” shows how countless individuals were robbed of the last wills and testaments to their self-significance and memorability typically afforded to the dying and the aggrieved. The resulting insight ought to inform how government and public health officials determine what is truly “non-essential” to human health, physical and mental, at times of crisis.

Keywords: cognitive psychology, covid, neuroscience, philosophy of memory

Procedia PDF Downloads 149

Authors: Rahimah Akbar, Abdullah Al-Hashemi, Hanan Taqi, Taiba Sadeq

Abstract:

As technology continues to develop, teaching curriculums in both schools and universities have begun adopting a more computer/digital based approach to the transmission of knowledge and information, as opposed to the more old-fashioned use of textbooks. This gives rise to the question: Are there any differences in learning from a digital source over learning from a printed source, as in from a textbook? More specifically, which medium of information results in better long-term retention? A review of the confounding factors implicated in understanding the relationship between learning from the two different mediums was done. Alongside this, a 4-week cohort study involving 76 1st year English Language female students was performed, whereby the participants were divided into 2 groups. Group A studied material from a paper source (referred to as the Print Medium), and Group B studied material from a digital source (Digital Medium). The dependent variables were grading of memory recall indexed by a 4 point grading system, and total frequency of item repetition. The study was facilitated by advanced computer software called Super Memo. Results showed that, contrary to prevailing evidence, the Digital Medium group showed no statistically significant differences in terms of the shift from Remember (Episodic) to Know (Semantic) when all confounding factors were accounted for. The shift from Random Guess and Familiar to Remember occurred faster in the Digital Medium than it did in the Print Medium.

Keywords: digital medium, print medium, long-term memory recall, episodic memory, semantic memory, super memo, forgetting index, frequency of repetitions, total time spent

Procedia PDF Downloads 250

Authors: Rema Vazhappilly, Tapas Das

Abstract:

Oleic acid is a cis unsaturated fatty acid and is known to be a partially essential fatty acid due to its limited endogenous synthesis during pregnancy and lactation. Previous studies have demonstrated the role of oleic acid in neuronal differentiation and brain phospholipid synthesis. These evidences indicate a major role for oleic acid in learning and memory. Interestingly, oleic acid has been shown to enhance hippocampal long term potentiation (LTP), the physiological correlate of long term synaptic plasticity. However the effect of oleic acid on short term synaptic plasticity has not been investigated. Short term potentiation (STP) is the physiological correlate of short term synaptic plasticity which is the key underlying molecular mechanism of short term memory and neuronal information processing. STP in the hippocampal CA1 region has been known to require the activation of N-methyl-D-aspartate receptors (NMDARs). The NMDAR dependent hippocampal STP as a potential mechanism for short term memory has been a subject of intense interest for the past few years. Therefore in the present study the effect of oleic acid on NMDAR dependent hippocampal STP was determined in mouse hippocampal slices (in vitro) using Multi-electrode array system. STP was induced by weak tetanic Stimulation (one train of 100 Hz stimulations for 0.1s) of the Schaffer collaterals of CA1 region of the hippocampus in slices treated with different concentrations of oleic acid in presence or absence of NMDAR antagonist D-AP5 (30 µM) . Oleic acid at 20 (mean increase in fEPSP amplitude = ~135 % Vs. Control = 100%; P<0.001) and 30 µM (mean increase in fEPSP amplitude = ~ 280% Vs. Control = 100%); P<0.001) significantly enhanced the STP following weak tetanic stimulation. Lower oleic acid concentrations at 10 µM did not modify the hippocampal STP induced by weak tetanic stimulation. The hippocampal STP induced by weak tetanic stimulation was completely blocked by the NMDA receptor antagonist D-AP5 (30µM) in both oleic acid and control treated hippocampal slices. This lead to the conclusion that the hippocampal STP elicited by weak tetanic stimulation and enhanced by oleic acid was NMDAR dependent. Together these findings suggest that oleic acid may enhance the short term memory and neuronal information processing through the modulation of NMDAR dependent hippocampal short-term synaptic plasticity. In conclusion this study suggests the possible role of oleic acid to prevent the short term memory loss and impaired neuronal function throughout development.

Keywords: oleic acid, short-term potentiation, memory, field excitatory post synaptic potentials, NMDA receptor

Procedia PDF Downloads 307

Authors: Gulcan Ozerim, Gunay Anlas

Abstract:

In shape memory alloys, upon loading, stress increases around crack tip and a martensitic phase transformation occurs in early stages. In many studies the stress distribution in the vicinity of the crack tip is represented by using linear elastic fracture mechanics (LEFM) although the pseudo-elastic behavior results in a nonlinear stress-strain relation. In this study, the HRR singularity (Hutchinson, Rice and Rosengren), that uses Rice’s path independent J-integral, is tried to formulate the stress distribution around the crack tip. In HRR approach, the Ramberg-Osgood model for the stress-strain relation of power-law hardening materials is used to represent the elastic-plastic behavior. Although it is recoverable, the inelastic portion of the deformation in martensitic transformation (up to the end of transformation) resembles to that of plastic deformation. To determine the constants of the Ramberg-Osgood equation, the material’s response is simulated in ABAQUS using a UMAT based on ZM (Zaki-Moumni) thermo-mechanically coupled model, and the stress-strain curve of the material is plotted. An edge cracked shape memory alloy (Nitinol) plate is loaded quasi-statically under mode I and modeled using ABAQUS; the opening stress values ahead of the cracked tip are calculated. The stresses are also evaluated using the asymptotic equations of both LEFM and HRR. The results show that in the transformation zone around the crack tip, the stress values are much better represented when the HRR singularity is used although the J-integral does not show path independent behavior. For the nodes very close to the crack tip, the HRR singularity is not valid due to the non-proportional loading effect and high-stress values that go beyond the transformation finish stress.

Keywords: crack, HRR singularity, shape memory alloys, stress distribution

Procedia PDF Downloads 303

Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

Abstract:

Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

Procedia PDF Downloads 160

Authors: M. M. Essa, S. Subash, M. Akbar, S. Al-Adawi, A. Al-Asmi, G. J. Guillemein

Abstract:

Objective: Transgenic (tg) mice which contain an amyloid precursor protein (APP) gene mutation, develop extracellular amyloid beta (Aβ) deposition in the brain, and severe memory and behavioural deficits with age. These mice serve as an important animal model for testing the efficacy of novel drug candidates for the treatment and management of symptoms of Alzheimer's disease (AD). Several reports have suggested that oxidative stress is the underlying cause of Aβ neurotoxicity in AD. Pomegranates contain very high levels of antioxidants and several medicinal properties that may be useful for improving the quality of life in AD patients. In this study, we investigated the effect of dietary supplementation of Omani pomegranate extract on the memory, anxiety and learning skills along with inflammation in an AD mouse model containing the double Swedish APP mutation (APPsw/Tg2576). Methods: The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 4% pomegranate. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in Tg and wild-type mice at the age of 4-5 months and 18-19 months using the Morris water maze test, rota rod test, elevated plus maze test, and open field test. Further, inflammatory parameters also analysed. Results: APPsw/Tg2576 mice that were fed a standard chow diet without pomegranates showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination along with increased inflammation compared to the wild type mice on the same diet, at the age of 18-19 months In contrast, APPsw/Tg2576 mice that were fed a diet containing 4% pomegranates showed a significant improvements in memory, learning, locomotor function, and anxiety with reduced inflammatory markers compared to APPsw/Tg2576 mice fed the standard chow diet. Conclusion: Our results suggest that dietary supplementation with pomegranates may slow the progression of cognitive and behavioural impairments in AD. The exact mechanism is still unclear and further extensive research needed.

Keywords: Alzheimer's disease, pomegranates, oman, cognitive decline, memory loss, anxiety, inflammation

Procedia PDF Downloads 507

Authors: Ahmed Emara, Maged Ghoneima, Mohamed Dessouky

Abstract:

Demand for low power fast memories is increasing with the increase in IC’s complexity, in this paper we introduce a proposal for a compact SRAM based on memristor devices. The compact size of the proposed cell (1T2M compared to 6T of traditional SRAMs) allows denser memories on the same area. In this paper, we will discuss the proposed memristor memory cell for single/multi bit data storing configurations along with the writing and reading operations. Stored data stability across successive read operation will be illustrated, operational simulation results and a comparison of our proposed design with previously conventional SRAM and previously proposed memristor cells will be provided.

Keywords: memristor, multi-bit, single-bit, circuits, systems

Procedia PDF Downloads 347