Search results for: shuttle memory

Authors: Ramesh Bhat, Ammu Somanath, A. K. Nayanatara

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Background: The increasing prevalence of overweight and obesity is a critical public health problem for women. The negative effect of stress on memory and cognitive functions has been widely explored for decades in numerous research projects using a wide range of methodology. Deterioration of memory and other brain functions are hallmarks of Alzheimer’s disease. Estrogen fluctuations and withdrawal have myriad direct effects on the central nervous system that have the potential to influence cognitive functions. Aim: The present study aims to compare the effect of stress on the cognitive functions in overweight/obese women before and after menopause. Material and Methods: A total of 142 female subjects constituting women before menopause between the age group of 18–44 years and women after menopause between the age group of 45–60 years were included in the sample. Participants were categorized into overweight/obese groups based on the body mass index. The Perceived Stress Scale (PSS) the major tool was used for measuring the perception of stress. Based on the stress scale measurement each group was classified into with stress and without stress. Addenbrooke’s cognitive Examination-III was used for measuring the cognitive functions. Results: Premenopausal women with stress showed a significant (P<0.05) decrease in the cognitive parameters such as attention and orientation Fluency, language and visuospatial ability. Memory did not show any significant change in this group. Whereas, in the postmenopausal stressed women all the cognitive functions except fluency showed a significant (P<0.05) decrease after menopause stressed group. Conclusion: Stress is a significant factor on the cognitive functions of obese and overweight women before and after menopause. Practice of Yoga, Encouragement in activities like gardening, embroidery, games and relaxation techniques should be recommended to prevent stress. Insights into the neurobiology before and after menopause can be gained from future studies examining the effect on the HPA axis in relation to cognition and stress.

Keywords: cognition, stress, premenopausal, body mass index

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Ahemd Sameer, Braj Bhushan

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The objective of our study was to compare wayfinding strategies to remember route while navigation in an unfamiliar homogenous environment. Two videos developed using free ware Trimble Sketchup© each having nine identical turns (3 right, 3 left, 3 straight) with no distinguishing feature at any turn. Thirt-two male post-graduate students of IIT Kanpur participated in the study. The experiment was conducted in three phases. In the first phase participant generated a list of personally known items to be used as landmarks. In the second phase participant saw the first video and was required to remember the sequence of turns. In the second video participant was required to imagine a landmark from the list generated in the first phase at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. In the third phase, which was 20 minutes after the second phase, participants again recalled the sequence of turns. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: Wayfinding, Landmark, Homogenous Environment, Memory

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Using longitudinal data from three waves of Young Lives Study and Ordinary Least Square methods, study has investigated the effect of birth order and arrival of younger siblings on child development in India. Study used child’s height for age z-score, weight for age z-score, BMI for age z-score, Peabody Picture Vocabulary Test (PPVT-Score)c, maths score, Early Grade Reading Assessment Test (ERGA) score, and memory score to measure the physical and cognitive development of child during wave-3. Findings suggest that having a high birth order is detrimental for child development and the gap between adjacent siblings is larger for children late in the birth sequences than early in the birth sequences. Study also reported that not only older siblings but arrival of younger siblings before assessment of test also reduces the development of a child. The effects become stronger in case of female children than male children.

Keywords: height for age z-score, weight for age z-score, BMI for z-score, PPVT score, math score, EGRA score, memory score, birth order, siblings, Young Lives Study, India

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Authors: Chih Hung Shih

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Eyewitness identification is one of the efficient information to identify suspects during criminal investigation. However eyewitness identification is improved frequently, inaccurate and plays vital roles in wrongful convictions. Most eyewitness misidentifications are made during police criminal investigation stage and then accepted by juries. Four failure investigation case studies in Taiwan are conduct to demonstrate how misidentifications are caused during the police investigation context. The result shows that there are several common grounds among these cases: (1) investigators lacked for knowledge about eyewitness memory so that they couldn’t evaluate the validity of the eyewitnesses’ accounts and identifications, (2) eyewitnesses were always asked to filter out several suspects during the investigation, and received investigation information which contaminated the eyewitnesses’ memory, (3) one to one live individual identifications were made in most of cases, (4) eyewitness identifications were always used to support the hypotheses of investigators, and exaggerated theirs powers when conform with the investigation lines, (5) the eyewitnesses’ confidence didn’t t reflect the validity of their identifications , but always influence the investigators’ beliefs for the identifications, (6) the investigators overestimated the power of the eyewitness identifications and ignore the inconsistency with other evidence. Recommendations have been proposed for future academic research and police practice of eyewitness identification in Taiwan.

Keywords: criminal investigation, eyewitness identification, investigative bias, investigative failures

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: Mai Hussein

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'Littoral' is an original voice in Québécois theatre, spanning the cultural gaps that can exist between the playwrights’ native Lebanon, North America, Quebec, and Europe. Littoral is a 'crossroad' of cultures and themes, a 'bridge' connecting cultures and languages. It represents a new form of theatrical writing that combines the verbal, the vocal and the pantomimic, calling upon the stage to question the real, to engage characters in a quest, in a journey of mourning, of reconstructing identity and a collective memory despite ruins and wars. A theatre of witness, a theatre denouncing irrationality of racism and war, a theatre 'performing' the symptoms of the stress disorders of characters passing from resistance and anger to reconciliation and giving voice to the silenced victims, these are some of the pillars that this play has to offer. In this corrida between life and death, the identity seems like a work-in-progress that is shaped in the presence of the Self and the Other. This trajectory will lead to re-open widely the door to questions, interrogations, and reflections to show how this play is at the nexus of contemporary preoccupations of the 21st century: the importance of memory, the search for meaning, the pursuit of the infinite. It also shows how a play can create bridges between languages, cultures, societies, and movements. To what extent does it mediate between the words and the silence, and how does it burn the bridges or the gaps between the textual and the performative while investigating the power of intermediality to confront racism and segregation. It also underlines the centrality of confrontation between cultures, languages, writing and representation techniques to challenge the characters in their quest to restructure their shattered, but yet intertwined identities. The goal of this theatre would then be to invite everyone involved in the process of a journey of self-discovery away from their comfort zone. Everyone will have to explore the liminal space, to read in between the lines of the written text as well as in between the text and the performance to explore the gaps and the tensions that exist between what is said, and what is played, between the 'parole' and the performative body.

Keywords: identity, memory, performance, testimony, trauma

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Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

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Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Van Son Nguyen, Van Huy Mai, Alec Moradpour, Pascale Auban Senzier, Claude Pasquier, Kang Wang, Pierre-Antoine Albouy, Marcelo J. Rozenberg, John Giapintzakis, Christian N. Mihailescu, Charis M. Orfanidou, Thomas Maroutian, Philippe Lecoeur, Guillaume Agnus, Pascal Aubert, Sylvain Franger, Raphaël Salot, Nathalie Brun, Katia March, David Alamarguy, Pascal ChréTien, Olivier Schneegans

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In the field of Nanoelectronics, a major research activity is being developed towards non-volatile memories. To face the limitations of existing Flash memory cells (endurance, downscaling, rapidity…), new approaches are emerging, among them resistive switching memories (Re-RAM). In this work, we analysed the behaviour of LixCoO2 oxide thin films in electrode/film/electrode devices. Preliminary results have been obtained concerning the influence of bias pulses characteristics (duration, value) on some performance parameters, such as endurance and resistance ratio (ROFF/RON). Besides, Conducting Probe Atomic Force Microscopy (CP-AFM) characterizations of the devices have been carried out to better understand some causes of performance failure, and thus help optimizing the switching performance of such devices.

Keywords: non volatile resistive memories, resistive switching, thin films, endurance

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Authors: Aditya, Ganapati Joshi, Vinod Kumar

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IN THE MODERN-WARFARE ERA, THE PRIME REQUIREMENT IS A HIGH SPEED AND MACH NUMBER. WHEN THE MISSILES STRIKE IN THE HYPERSONIC REGIME THE OPPONENT CAN DETECT IT WITH THE ANTI-DEFENSE SYSTEM BUT CAN NOT STOP IT FROM CAUSING DAMAGE. SO, TO ACHIEVE THE SPEEDS OF THIS LEVEL THERE ARE TWO ENGINES THAT ARE AVAILABLE WHICH CAN WORK IN THIS REGION ARE RAMJET AND SCRAMJET. THE PROBLEM WITH RAMJET STARTS TO OCCUR WHEN MACH NUMBER EXCEEDS 4 AS THE STATIC PRESSURE AT THE INLET BECOMES EQUAL TO THE EXIT PRESSURE. SO, SCRAMJET ENGINE DEALS WITH THIS PROBLEM AS IT NEARLY HAS THE SAME WORKING BUT HERE THE FLOW IS NOT MUCH SLOWED DOWN AS COMPARED TO RAMJET IN THE DIFFUSER BUT IT SUFFERS FROM THE PROBLEMS SUCH AS INLET BUZZ, THERMAL CHOCKING, MIXING OF FUEL AND OXIDIZER, THERMAL HEATING, AND MANY MORE. HERE THE NEW ENGINE IS DEVELOPED ON THE SAME PRINCIPLE AS THE SCRAMJET ENGINE BUT BURNING HAPPENS DUE TO DETONATION INSTEAD OF DEFLAGRATION. THE PROBLEM WITH THE ENGINE STARTS WHEN THE MACH NUMBER BECOMES VARIABLE AND THE INLET GEOMETRY IS FIXED AND THIS LEADS TO INLET SPILLAGE WHICH WILL AFFECT THE THRUST ADVERSELY. SO, HERE ADAPTIVE INLET IS MADE OF SHAPE MEMORY ALLOYS WHICH WILL ENHANCE THE INLET MASS FLOW RATE AS WELL AS THRUST.

Keywords: detonation, ramjet engine, shape memory alloy, ignition delay, shock-boundary layer interaction, eddy dissipation, asymmetric nozzle

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Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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Authors: Insiya Bhalloo

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It is quite common in the Muslim faith for non-Arabic speakers to be able to convert written Arabic, especially Quranic Arabic, into a phonological code without significant semantic or syntactic knowledge. This is due to prior experience learning to read the Quran (a religious text written in Classical Arabic), from a very young age such as via enrolment in Quranic Arabic classes. As compared to native speakers of Arabic, these Arabic readers do not have a comprehensive morpho-syntactic knowledge of the Arabic language, nor can understand, or engage in Arabic conversation. The study seeks to investigate whether mere phonological experience (as indicated by the Arabic readers’ experience with Arabic phonology and the sound-system) is sufficient to cause phonological-interference during word recognition of previously-heard words, despite the participants’ non-native status. Both native speakers of Arabic and non-native speakers of Arabic, i.e., those individuals that learned to read the Quran from a young age, will be recruited. Each experimental session will include two phases: An exposure phase and a test phase. During the exposure phase, participants will be presented with Arabic words (n=40) on a computer screen. Half of these words will be common words found in the Quran while the other half will be words commonly found in Modern Standard Arabic (MSA) but either non-existent or prevalent at a significantly lower frequency within the Quran. During the test phase, participants will then be presented with both familiar (n = 20; i.e., those words presented during the exposure phase) and novel Arabic words (n = 20; i.e., words not presented during the exposure phase. ½ of these presented words will be common Quranic Arabic words and the other ½ will be common MSA words but not Quranic words. Moreover, ½ the Quranic Arabic and MSA words presented will be comprised of nouns, while ½ the Quranic Arabic and MSA will be comprised of verbs, thereby eliminating word-processing issues affected by lexical category. Participants will then determine if they had seen that word during the exposure phase. This study seeks to investigate whether long-term phonological memory, such as via childhood exposure to Quranic Arabic orthography, has a differential effect on the word-recognition capacities of native Arabic speakers and Arabic readers; we seek to compare the effects of long-term phonological memory in comparison to short-term phonological exposure (as indicated by the presentation of familiar words from the exposure phase). The researcher’s hypothesis is that, despite the lack of lexical knowledge, early experience with converting written Quranic Arabic text into a phonological code will help participants recall the familiar Quranic words that appeared during the exposure phase more accurately than those that were not presented during the exposure phase. Moreover, it is anticipated that the non-native Arabic readers will also report more false alarms to the unfamiliar Quranic words, due to early childhood phonological exposure to Quranic Arabic script - thereby causing false phonological facilitatory effects.

Keywords: modern standard arabic, phonological facilitation, phonological memory, Quranic arabic, word recognition

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

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Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease

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Authors: Zainurrasyid Abdullah, Mohamed Fadzlee Sulaiman, Muhammad Fadzlan Zainal, M. Zabri Adil Talib, Aswami Fadillah M. Ariffin

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The Onion Router (Tor) browser is a well-known tool and widely used by people who seeking for web anonymity when browsing the internet. Criminals are taking this advantage to be anonymous over the internet. Accessing the dark web could be the significant reason for the criminal in order for them to perform illegal activities while maintaining their anonymity. For a digital forensic analyst, it is crucial to extract the trail of evidence in proving that the criminal’s computer has used Tor browser to conduct such illegal activities. By applying the digital forensic methodology, several techniques could be performed including application analysis, memory analysis, and registry analysis. Since Windows 10 is the latest operating system released by Microsoft Corporation, this study will use Windows 10 as the operating system platform that running Tor browser. From the analysis, significant artifacts left by Tor browser were discovered such as the execution date, application installation date and browsing history that can be used as an evidence. Although Tor browser was designed to achieved anonymity, there is still some trail of evidence can be found in Windows 10 platform that can be useful for investigation.

Keywords: artifacts analysis, digital forensics, forensic analysis, memory analysis, registry analysis, tor browser, Windows 10

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Authors: Mohammad Ahangari

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Schizophrenia is a psychiatric disorder with symptoms that include cognitive deficits and nicotine has been suggested to have an effect on cognition. In recent years, the advents of Genome-Wide Association Studies(GWAS) has evolved our understanding about the genetic causes of complex disorders such as schizophrenia and studying the role of genome-wide significant genes could potentially lead to the development of new therapeutic agents for treatment of cognitive deficits in schizophrenia. The current study identified six Single Nucleotide Polymorphisms (SNP) from schizophrenia and smoking GWAS that are located on or in close proximity to the nicotinic receptor gene cluster (CHRN) and studied their association with cognition in an Irish sample of 1297 cases and controls using linear regression analysis. Further on, the interaction between CHRN gene cluster and Dopamine receptor D2 gene (DRD2) during working memory was investigated. The effect of these polymorphisms on nicotinic and dopaminergic neurotransmission, which is disrupted in schizophrenia, have been characterized in terms of their effects on memory, attention, social cognition and IQ as measured by a neuropsychological test battery and significant effects in two polymorphisms were found across global IQ domain of the test battery.

Keywords: cognition, dopamine, GWAS, nicotine, schizophrenia, SNPs

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Authors: Shourav Chowdhury, Subrata Barua, K. M. Naimuddin, Imam Hassan Sajib, Md. Hasan, Shudipta Banik, Muna Das

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Traffic accidents stand as a leading cause of fatalities worldwide, significantly impacting global mortality rates. Accurate classification of road accidents through advanced technological solutions presents a crucial opportunity to revolutionize accident prevention and emergency response strategies. This paper presents an advanced deep-learning methodology customized for the classification of road accidents using CCTV surveillance footage. This real-time dataset, comprising approximately 18,000 frames, has been amassed, which is pivotal for enabling comprehensive research in this field. This substantial dataset is the foundation for these investigative efforts, providing a rich and diverse source for conducting an in-depth analysis of the features. It has achieved a remarkable accuracy of 97% on this dataset through the strategic utilization of transfer learning in conjunction with LSTM (Long short-term memory) techniques. This accomplishment underscores the efficacy of our approach, combining the strengths of transfer learning and LSTM models, resulting in a highly accurate classification system for road accident events.

Keywords: accident, CCTV, footage, long short-term memory, surveillance

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Authors: E. U. Dampage, Ovindi D. Bandara, Vinushi S. Waraketiya, Samitha S. R. De Silva, Yasiru S. Gunarathne

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The knowledge of water inflow figures is paramount in decision making on the allocation for consumption for numerous purposes; irrigation, hydropower, domestic and industrial usage, and flood control. The understanding of how reservoir inflows are affected by different climatic and hydrological conditions is crucial to enable effective water management and downstream flood control. In this research, we propose a method using a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) to assist the aforesaid decision-making process. The Kotmale reservoir, which is the uppermost reservoir in the Mahaweli reservoir complex in Sri Lanka, was used as the test bed for this research. The ANN uses the runoff in the Kotmale reservoir catchment area and the effect of Sea Surface Temperatures (SST) to make a forecast for seven days ahead. Three types of ANN are tested; Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and LSTM. The extensive field trials and validation endeavors found that the LSTM ANN provides superior performance in the aspects of accuracy and latency.

Keywords: convolutional neural network, CNN, inflow, long short-term memory, LSTM, multi-layer perceptron, MLP, neural network

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Authors: YuPei Chang

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In recent years, moral judgement tasks have served as an increasingly popular plot mechanism in digital gameplay. As a moral agency, the player's choice judgment in digital games is to shuttle between the real world and the game world. The purpose of the research is to explore the moral difficulties brewed by the interactive mechanism of the game and the moral choice of players. In the theoretical level, this research tries to combine moral disengagement, moral foundations theory, and gameplay as an aesthetic experience. And in the methodical level, this research tries to use methods that combine text analysis, diary method, and in-depth interviews. There are three research problems that will be solved in three stages. In the first stage, this project will explore how moral dilemmas are represented in game mechanics. In the second stage, this project will analyze the appearance and conflicts of moral dilemmas in game mechanics based on the five aspects of moral foundations theory. In the third stage, this project will try to understand the players' choices when they face the choices of moral dilemmas, as well as their explanations and reflections after making the decisions.

Keywords: morality, moral disengagement, moral foundations theory, PC game, gameplay, moral dilemmas, player

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Authors: Abegunde Linda, Adedeji Oluwatayo, Tope-Ajayi Opeyemi

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Maize constitutes a major agrarian production for use by the vast population but despite its economic importance, it has not been produced to meet the economic needs of the country. Achieving optimum yield in maize can meaningfully be supported by land suitability analysis in order to guarantee self-sufficiency for future production optimization. This study examines land suitability for maize production through the analysis of the physic-chemical variations in soil properties over space using a Geographic Information System (GIS) framework. Physic-chemical parameters of importance selected include slope, landuse, and physical and chemical properties of the soil. Landsat imagery was used to categorize the landuse, Shuttle Radar Topographic Mapping (SRTM) generated the slope and soil samples were analyzed for its physical and chemical components. Suitability was categorized into highly, moderately and marginally suitable based on Food and Agricultural Organisation (FAO) classification using the Analytical Hierarchy Process (AHP) technique of GIS. This result can be used by small scale farmers for efficient decision making in the allocation of land for maize production.

Keywords: AHP, GIS, MCE, suitability, Zea mays

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Authors: Pailin Klinkesorn

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The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

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Authors: Lulu Wang, Yongjun Xu, Xiaoyang Qiao

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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

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Authors: Sharun Akter Khushbu

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‘SOS’ addresses text summary such as feasibility study and allows more comprehensive methods on text of language resources. Resources language has been exploited by the importance of text documental procedure. Throughout this key idea will come out a machine interpreter called an SOS that has built an argumentative as an employed model is LSTM-CNN(long short-term memory- recurrent neural network). Summarization of Bengali text formulated by the information of latent structure instead of brief input string counting as text. Text summarization is the proper utilization of optimal solutions being time reduction, and easy interpretation whenever human-generated summary and machine targeted summary remain similar and without degrading the semantic summarization quality. According to the problem affirmation key idea has advanced an algorithm with the method of encoder and decoder describing a sequential structure that is rigorously connected with actual predicted and meaningful output. Regarding the seq2seq approach aimed in the future with high semantic summarization similarity on behalf of the large data samples that are also enlisted by the method. Thus, the SOS method assigns a discriminator over Bengali text documents where encoded input sequences such as summary and decoded the targeted summary of gist will be an error-free machine.

Keywords: LSTM-CNN, NN, SOS, text summarization

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Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Yashas Bedre Raghavendra, Pim Vullers

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This study presents the design and implementation of an abstract cryptographic coprocessor, leveraging AMBA(Advanced Microcontroller Bus Architecture) protocols - APB (Advanced Peripheral Bus) and AHB (Advanced High-performance Bus), to enable seamless integration with the main CPU(Central processing unit) and enhance the coprocessor’s algorithm flexibility. The primary objective is to create a versatile coprocessor that can execute various cryptographic algorithms, including ECC(Elliptic-curve cryptography), RSA(Rivest–Shamir–Adleman), and AES (Advanced Encryption Standard) while providing a robust and secure solution for modern secure embedded systems. To achieve this goal, the coprocessor is equipped with a tightly coupled memory (TCM) for rapid data access during cryptographic operations. The TCM is placed within the coprocessor, ensuring quick retrieval of critical data and optimizing overall performance. Additionally, the program memory is positioned outside the coprocessor, allowing for easy updates and reconfiguration, which enhances adaptability to future algorithm implementations. Direct links are employed instead of DMA(Direct memory access) for data transfer, ensuring faster communication and reducing complexity. The AMBA-based communication architecture facilitates seamless interaction between the coprocessor and the main CPU, streamlining data flow and ensuring efficient utilization of system resources. The abstract nature of the coprocessor allows for easy integration of new cryptographic algorithms in the future. As the security landscape continues to evolve, the coprocessor can adapt and incorporate emerging algorithms, making it a future-proof solution for cryptographic processing. Furthermore, this study explores the addition of custom instructions into RISC-V ISE (Instruction Set Extension) to enhance cryptographic operations. By incorporating custom instructions specifically tailored for cryptographic algorithms, the coprocessor achieves higher efficiency and reduced cycles per instruction (CPI) compared to traditional instruction sets. The adoption of RISC-V 128-bit architecture significantly reduces the total number of instructions required for complex cryptographic tasks, leading to faster execution times and improved overall performance. Comparisons are made with 32-bit and 64-bit architectures, highlighting the advantages of the 128-bit architecture in terms of reduced instruction count and CPI. In conclusion, the abstract cryptographic coprocessor presented in this study offers significant advantages in terms of algorithm flexibility, security, and integration with the main CPU. By leveraging AMBA protocols and employing direct links for data transfer, the coprocessor achieves high-performance cryptographic operations without compromising system efficiency. With its TCM and external program memory, the coprocessor is capable of securely executing a wide range of cryptographic algorithms. This versatility and adaptability, coupled with the benefits of custom instructions and the 128-bit architecture, make it an invaluable asset for secure embedded systems, meeting the demands of modern cryptographic applications.

Keywords: abstract cryptographic coprocessor, AMBA protocols, ECC, RSA, AES, tightly coupled memory, secure embedded systems, RISC-V ISE, custom instructions, instruction count, cycles per instruction

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Authors: Abdel Rahman Altakhaineh

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This paper has analysed the conceptual relations between the elements of NN compounds in Arabic and compared them to those found in English based on the framework of Conceptual Semantics and a modified version of Parallel Architecture referred to as Relational Morphology. The analysis revealed that the repertoire of possible semantic relations between the two nouns in Arabic NN compounds reproduces that in English NN compounds and that, therefore, the main difference is in headedness (right-headed in English, left-headed in Arabic). Adopting RM allows productive and idiosyncratic elements to interweave with each other naturally. Semantically transparent compounds can be stored in memory or produced and understood online, while compounds with different degrees of semantic idiosyncrasy are stored in memory. Furthermore, the predictable parts of idiosyncratic compounds are captured by general schemas. In compounds, such schemas pick out the range of possible semantic relations between the two nouns. Finally, conducting a cross-linguistic study of the systematic patterns of possible conceptual relationships between compound elements is an area worthy of further exploration. In addition, comparing and contrasting compounding in Arabic and Hebrew, especially as they are both Semitic languages, is another area that needs to be investigated thoroughly. It will help morphologists understand the extent to which Jackendoff’s repertoire of semantic relations in compounds is universal. That is, if a language as distant from English as Arabic displays a similar range of cases, this is evidence for a (relatively) universal set of relations from which individual languages may pick and choose.

Keywords: conceptual semantics, morphology, compounds, arabic, english

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