Search results for: memory stimulation

Authors: Chetan Gupta, Ramesh Gupta

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Unmanned aerial vehicles, of all sizes, are prime targets of the wing morphing concept as their lightweight structures demand high aerodynamic stability while traversing unsteady atmospheric conditions. In this research study, a hybrid morphing technology is developed to aid the trailing edge of the aircraft wing to alter its camber as a monolithic element rather than functioning as conventional appendages like flaps. Kinematic tailoring, actuation techniques involving shape memory alloys (SMA), piezoelectrics – individually fall short of providing a simplistic solution to the conundrum of morphing aircraft wings. On the other hand, the feature of negligible hysteresis while actuating using compliant mechanisms has shown higher levels of applicability and deliverability in morphing wings of even large aircrafts. This research paper delves into designing a wing section model with a periodic, multi-stable compliant structure requiring lower orders of topological optimization. The design is sub-divided into three smaller domains with external hyperelastic connections to achieve deflections ranging from -15° to +15° at the trailing edge of the wing. To facilitate this functioning, a hybrid actuation system by combining the larger bandwidth feature of piezoelectric macro-fibre composites and relatively higher work densities of shape memory alloy wires are used. Finite element analysis is applied to optimize piezoelectric actuation of the internal compliant structure. A coupled fluid-surface interaction analysis is conducted on the wing section during morphing to study the development of the velocity boundary layer at low Reynold’s numbers of airflow.

Keywords: compliant mechanism, hybrid morphing, piezoelectrics, shape memory alloys

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Authors: Vijaya Kumar, Vidayasagar Pagilla, Abraham Joshua, Rakshith Kedambadi, Prasanna Mithra

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Background: Post stroke rehabilitation are aimed to accelerate for optimal sensorimotor recovery, functional gain and to reduce long-term dependency. Intensive physical therapy interventions can enhance this recovery as experience-dependent neural plastic changes either directly act at cortical neural networks or at distal peripheral level (muscular components). Neuromuscular Electrical Stimulation (NMES), a traditional bottom-up approach, mirror therapy (MT), a relatively new top down approach have found to be an effective adjuvant treatment methods for lower extremity motor and functional recovery in stroke rehabilitation. However there is a scarcity of evidence to compare their therapeutic gain in stroke recovery.Aim: To compare the efficacy of neuromuscular electrical stimulation (NMES) and mirror therapy (MT) in very early phase of post stroke rehabilitation addressed to lower extremity motor recovery and balance. Design: observer blinded Randomized Clinical Trial. Setting: Neurorehabilitation Unit, Department of Physical Therapy, Tertiary Care Hospitals. Subjects: 32 acute stroke subjects with first episode of unilateral stroke with hemiparesis, referred for rehabilitation (onset < 3 weeks), Brunnstorm lower extremity recovery stages ≥3 and MMSE score more than 24 were randomized into two group [Group A-NMES and Group B-MT]. Interventions: Both the groups received eclectic approach to remediate lower extremity recovery which includes treatment components of Roods, Bobath and Motor learning approaches for 30 minutes a day for 6 days. Following which Group A (N=16) received 30 minutes of surface NMES training for six major paretic muscle groups (gluteus maximus and medius,quadriceps, hamstrings, tibialis anterior and gastrocnemius). Group B (N=16) was administered with 30 minutes of mirror therapy sessions to facilitate lower extremity motor recovery. Outcome measures: Lower extremity motor recovery, balance and activities of daily life (ADLs) were measured by Fugyl Meyer Assessment (FMA-LE), Berg Balance Scale (BBS), Barthel Index (BI) before and after intervention. Results: Pre Post analysis of either group across the time revealed statistically significant improvement (p < 0.001) for all the outcome variables for the either group. All parameters of NMES had greater change scores compared to MT group as follows: FMA-LE (25.12±3.01 vs. 23.31±2.38), BBS (35.12±4.61 vs. 34.68±5.42) and BI (40.00±10.32 vs. 37.18±7.73). Between the groups comparison of pre post values showed no significance with FMA-LE (p=0.09), BBS (p=0.80) and BI (p=0.39) respectively. Conclusion: Though either groups had significant improvement (pre to post intervention), none of them were superior to other in lower extremity motor recovery and balance among acute stroke subjects. We conclude that eclectic approach is an effective treatment irrespective of NMES or MT as an adjunct.

Keywords: balance, motor recovery, mirror therapy, neuromuscular electrical stimulation, stroke

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Yibei Ye, Lei Xu, Zhenyu Cao

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Ancient town is a unique carrier of urban culture, maintaining the core culture of a region and continuing the urban context. Fengqiao, a nearly 2000-year-old town was on the brink of dilapidation in the past few decades. The town faced such problems as poor construction quality, environmental degeneration, inadequate open space, cultural characteristics and industry vitality. Therefore, the research upholds the principle of ‘organic renewal’ and puts forward three practical updated strategies which are ‘Repair Old as Ever,' ‘Activate Function’ and ‘Fill in with The New’. Also as a participant in updating the design, the author aims to ‘keep the memory of the history and see the development of the present’ as the goal of updating the design and regards the process of town renewal as the experimental venue for realizing this purpose. The research will sum up innovations on the designing process and the engineering progress in the past two years, and find out the innovation experiment and the effect of its implementation on the methodological level of the organic renewal design in Fengqiao ancient town. From here, we can also enjoy the very characteristic development trend presented by China in the design practice of the organic renewal in the ancient town.

Keywords: characteristic town, Fengqiao, organic renewal, urban memory

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Authors: Khayra Zerrouki, Noureddine Djebli, Esra Eroglu, Afife Mat, Ozhan Gul

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Neurodegenerative diseases of the human brain comprise a variety of disorders that affect an increasing percentage of the population. Alzheimer’s disease (AD) is a complex, multifactorial, heterogeneous mental illness, which is characterized by an age-dependent loss of memory and an impairment of multiple cognitive functions, but this 10 last years it concerns the population most and most young. Hypericum perforatum has traditionally been used as an external anti-inflammatory and healing remedy for the treatment of swellings, wounds and burns, diseases of the alimentary tract and psychological disorders. It is currently of great interest due to new and important therapeutic applications. In this study, the chemical composition of methanolic extract of Hypericum perforatum (HPM) was analysed by using high performance liquid chromatography – diode array detector (HPLC-DAD). The in vitro antioxidant activity of HPM was evaluated by using several antioxidant tests. HSM exhibits inhibitory capacity against posphatidylcholine liposome peroxidation, induced with iron and ascorbic acid, scavenge DPPH and superoxide radicals and act as reductants. The cytotoxic activity of HSM was also determined by using MTT cell viability assay on HeLa and NRK-52E cell lines. The in vivo activity studies in Swiss mice were determined by using behavioral, memory tests and histological study. According to tests results HPM that may be relevant to the treatment of cognitive disorders. The results of chemical analysis showed a hight level of hyperforin and quercitin that had an important antioxidant activity proved in vitro with the DPPH, anti LPO and SOD; this antioxidant activity was confirmed in vivo after the non-toxic results by means of improvement in behavioral and memory than the reducing shrunken in pyramidal cells of mice brains.

Keywords: AlCl3, alzheimer, mice, neuroprotective, neurotoxicity, phytotherapy

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Authors: Srishti Bhatt, Vaibhav Bhavsar, Adil Hussain, Aashay Mhaske, S. C. Bali, T. S. Srikanth

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Shape Memory Alloys (SMA) are widely known for their unique shape recovery properties. SMA based actuation systems have high-force to weight ratio, light weight and also bio-compatible material. Which is why they are being used in different fields of aerospace, robotics, automotive and biomedical industries. However, in the automotive industry plenty of patents are available but commercially viable products are very few in market. This could be due to SMA material limitations like small stroke, direct dependability of lifecycle on stroke, pull load of the wire and high cycle time. In automotive sector, SMA being considered as an actuator which is required to have high stroke and constraint arises to accommodate a long length of wire (to compensate maximum 4 % strain as per better fatigue life cycle) not only increases complexity but also adds on the cost. More than 200 different types of actuators are used in an automobile, few of them whose efficiency can highly increase by replacing them with SMA based actuators which include latch lock mechanism, glove box, Head lamp leveling, side mirror and rear mirror leveling, tailgate opener and fuel lid cap actuator. To overcome the limitation of available space for required stroke of an actuator which leads to study the effect of different loading positions on SMA wires, different orientations of SMA wire by using pulleys and lever based systems to achieve maximum stroke. This investigation summarizes the loading under the V shape orientation the required stroke and carrying load capacity in more compact in comparison with straight orientation of wire. Similarly, the U shape orientation its showing higher load carrying capacity but reduced stroke which is aligned with concept of bundled wire method. Life-cycle of these orientations were also evaluated.

Keywords: actuators, automotive, nitinol, shape memory alloy, SMA wire orientations

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Authors: Dzunisani Sibuyi

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This article demonstrates how corruption is revealed in Mandla Langa’s Memory of Stones (2000) through the deployment of narrational strategies by applying narrative theories by Gerard Genette’s Narrative Discourse and Narrative Discourse Revisited, as well as Mikhail Bakhtin’s Dialogic Imagination to the text. This is accomplished by analysing Langa’s use of extradiegetic-heterodiegetic and intradiegetic-homodiegetic narrational strategies respectively employed by the anonymous narrator and character narrator Mpanza. The narration provided by these narrators is multi-voiced in its approach to the events depicting corruption from various completing and explanatory perspectives. In addition, Langa also employs narrative techniques of narrating times such as simultaneous, subsequent, and interpolated narration to highlight corruption taking place, which is highlighted by situating the story in its presentness moments coinciding with the corruption action. As a result, by emphasising the events portraying the plight of the main characters and their struggle to resist and defeat corrupt leaders, the narration strategically reveals corruption.

Keywords: narrational strategies, narrating voice, dialogism, corruption, Gérard Genette, Mandla Langa, Mikhail Bakhtin, time(s) of the narration

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Yu-Ping Chiu, Dung-Ying Lin

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Traditional staff scheduling methods, relying on employee experience, often lead to inefficiencies and resource waste. The challenges of transferring scheduling expertise and adapting to changing labor regulations further complicate this process. Manual approaches become increasingly impractical as companies accumulate complex scheduling rules over time. This study proposes an algorithmic optimization approach to address these issues, aiming to expedite scheduling while ensuring strict compliance with labor regulations and company policies. The method focuses on generating optimal schedules that minimize weighted company objectives within a compressed timeframe. Recognizing the limitations of conventional commercial software in modeling and solving complex real-world scheduling problems efficiently, this research employs Tabu Search with both long-term and short-term memory structures. The study will present numerical results and managerial insights to demonstrate the effectiveness of this approach in achieving intelligent and efficient staff scheduling.

Keywords: intelligent memory structures, mixed integer programming, meta-heuristics, staff scheduling problem, tabu search

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: Yuheng Tao

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Rapid urbanization has brought the consequences of incompatible and excessive homogeneity of urban system, and urban color planning has become one of the most effective ways to restore the characteristics of cities. Among the many urban color design research, the establishment of urban theme colors has rarely been discussed. This study took the "New Taipei City Environmental Aesthetic Color” project as a research case and conducted mixed-method research that included expert interviews and quantitative survey data. This study introduces how theme colors were selected by the experts and investigates public’s perception and preference of the selected theme colors. Several findings include 1) urban memory plays a significant role in determining urban theme colors; 2) When establishing urban theme colors, areas/cities with relatively weak urban memory are given priority to be defined; 3) Urban theme colors that imply cultural attributes are more widely accepted by the public; 4) A representative city theme color helps conserve culture rather than guiding innovation. In addition, this research rearranges the urban color symbolism and specific content of urban theme colors and provides a more scientific urban theme color selection scheme for urban planners.

Keywords: urban theme color, urban color attribute, public perception, public preferences

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Authors: Golam Saklayen, Sheikh Rashel al Ahmed, Ferdous Rahman, Ismail Abu Bakar

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Investigation on Lanthanum Fluoride LaF3 layer embedding Silicon Nanocrystals (Si-NCs) fabricated using a novel one-step chemical method has been reported in this presentation. Application of this material has been tested for low-voltage operating non-volatile memory and Schottkey-junction solar cell. Colloidal solution of Si-NCs in hydrofluoric acid (HF) was prepared from meso-porous silicon by ultrasonic vibration (sonication). This solution prevents the Si-NCs to be oxidized. On a silicon (Si) substrate, LaCl3 solution in HCl is allowed to react with the colloidal solution of prepared Si-NCs. Since this solution contains HF, LaCl3 reacts with HF and produces LaF3 crystals that deposits on the silicon substrate as a layer embedding Si-NCs. This a novel single step chemical way of depositing LaF3 insulating layer embedding Si-NCs. The X-Ray diffraction of the deposited layer shows a polycrystalline LaF3 deposition on silicon. A non-stoichiometric LaF3 layer embedding Si-NCs was found by EDX analysis. The presence of Si-NCs was confirmed by SEM. FTIR spectroscopy of the deposited LaF3 powder also confirmed the presence of Si-NCs. The size of Si-NCs was found to be inversely proportional to the ultrasonic power. After depositing proper contacts on the back of Si and LaF3, the devices have been tested as a non-volatile memory and solar cell. A memory window of 525 mV was obtained at a programming and erasing bias of 2V. The LaF3 films with Si NCs showed strong absorption and was also found to decrease optical transmittance than pure LaF3 film of same thickness. The I-V characteristics of the films showed a dependency on the incident light intensity where current changed under various light illumination. Experimental results show a lot of promise for Si-NCs-embedded LaF3 layer to be used as an insulating layer in MIS devices as well as an photoactive material in Schottkey junction solar cells.

Keywords: silicon nanocrystals (Si NCs), LaF3, colloidal solution, Schottky junction solar cell

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Authors: S. S. Kharintsev, E. A. Chernykh, S. K. Saikin, A. I. Fishman, S. G. Kazarian

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Recent advances in improving information storage performance are inseparably linked with circumvention of fundamental constraints such as the supermagnetic limit in heat assisted magnetic recording, charge loss tolerance in solid-state memory and the Abbe’s diffraction limit in optical storage. A substantial breakthrough in the development of nonvolatile storage devices with dimensional scaling has been achieved due to phase-change chalcogenide memory, which nowadays, meets the market needs to the greatest advantage. A further progress is aimed at the development of versatile nonvolatile high-speed memory combining potentials of random access memory and archive storage. The well-established properties of light at the nanoscale empower us to use them for recording optical information with ultrahigh density scaled down to a single molecule, which is the size of a pit. Indeed, diffraction-limited optics is able to record as much information as ~1 Gb/in2. Nonlinear optical effects, for example, two-photon fluorescence recording, allows one to decrease the extent of the pit even more, which results in the recording density up to ~100 Gb/in2. Going beyond the diffraction limit, due to the sub-wavelength confinement of light, pushes the pit size down to a single chromophore, which is, on average, of ~1 nm in length. Thus, the memory capacity can be increased up to the theoretical limit of 1 Pb/in2. Moreover, the field confinement provides faster recording and readout operations due to the enhanced light-matter interaction. This, in turn, leads to the miniaturization of optical devices and the decrease of energy supply down to ~1 μW/cm². Intrinsic features of light such as multimode, mixed polarization and angular momentum in addition to the underlying optical and holographic tools for writing/reading, enriches the storage and encryption of optical information. In particular, the finite extent of the near-field penetration, falling into a range of 50-100 nm, gives the possibility to perform 3D volume (layer-to-layer) recording/readout of optical information. In this study, we demonstrate a comprehensive evidence of isotropic-to-homeotropic phase transition of the azobenzene-functionalized polymer thin film exposed to light and dc electric field using near-field optical microscopy and scanning capacitance microscopy. We unravel a near-field Raman dichroism of a sub-10 nm thick epoxy-based side-chain azo-polymer films with polarization-controlled tip-enhanced Raman scattering. In our study, orientation of azo-chromophores is controlled with a bias voltage gold tip rather than light polarization. Isotropic in-plane and homeotropic out-of-plane arrangement of azo-chromophores in glassy environment can be distinguished with transverse and longitudinal optical near-fields. We demonstrate that both phases are unambiguously visualized by 2D mapping their local dielectric properties with scanning capacity microscopy. The stability of the polar homeotropic phase is strongly sensitive to the thickness of the thin film. We make an analysis of α-transition of the azo-polymer by detecting a temperature-dependent phase jump of an AFM cantilever when passing through the glass temperature. Overall, we anticipate further improvements in optical storage performance, which approaches to a single molecule level.

Keywords: optical memory, azo-dye, near-field, tip-enhanced Raman scattering

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Authors: Durvi Yogesh Vagani

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This research paper explores the effectiveness of Research-informed teaching and Case-based teaching in enhancing the retention and recall of memory during discussions among university students. Additionally, it investigates the impact of using Artificial Intelligence (AI) tools on the quality of research conducted by students and its correlation with better recollection. The study hypothesizes that Case-based teaching will lead to greater recall and storage of information. The research gap in the use of AI in educational settings, particularly with actual participants, is addressed by leveraging a multi-method approach. The hypothesis is that the use of AI, such as ChatGPT and Bard, would lead to better retention and recall of information. Before commencing the study, participants' attention levels and IQ were assessed using the Digit Span Test and the Wechsler Adult Intelligence Scale, respectively, to ensure comparability among participants. Subsequently, participants were divided into four conditions, each group receiving identical information presented in different formats based on their assigned condition. Following this, participants engaged in a group discussion on the given topic. Their responses were then evaluated against a checklist. Finally, participants completed a brief test to measure their recall ability after the discussion. Preliminary findings suggest that students who utilize AI tools for learning demonstrate improved grasping of information and are more likely to integrate relevant information into discussions compared to providing extraneous details. Furthermore, Case-based teaching fosters greater attention and recall during discussions, while Research-informed teaching leads to greater knowledge for application. By addressing the research gap in AI application in education, this study contributes to a deeper understanding of effective teaching methodologies and the role of technology in student learning outcomes. The implication of the present research is to tailor teaching methods based on the subject matter. Case-based teaching facilitates application-based teaching, and research-based teaching can be beneficial for theory-heavy topics. Integrating AI in education. Combining AI with research-based teaching may optimize instructional strategies and deepen learning experiences. This research suggests tailoring teaching methods in psychology based on subject matter. Case-based teaching suits practical subjects, facilitating application, while research-based teaching aids understanding of theory-heavy topics. Integrating AI in education could enhance learning outcomes, offering detailed information tailored to students' needs.

Keywords: artificial intelligence, attention, case-based teaching, memory recall, memory retention, research-informed teaching

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Jalil Boudjadar

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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: Anastasiya Paltarzhitskaya

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Subjective time plays an important role in consciousness processes and self-awareness at the moment. The concept of intrinsic neural timescales (INT) explains the difference in perceiving various time intervals. The capacity to experience the present builds on the fundamental properties of temporal cognition. The challenge that both philosophy and neuroscience try to answer is how the brain differentiates the present from the past and future. In our work, we analyze papers which describe mechanisms involved in the perception of ‘present’ and ‘non-present’, i.e., future and past moments. Taking into account that we perceive time intervals even during rest or relaxation, we suppose that the default-mode network activity can code time features, including the present moment. We can compare some results of time perceptual studies, where brain activity was shown in states with different flows of time, including resting states and during “mental time travel”. According to the concept of mental traveling, we employ a range of scenarios which demand episodic memory. However, some papers show that the hippocampal region does not activate during time traveling. It is a controversial result that is further complicated by the phenomenological aspect that includes a holistic set of information about the individual’s past and future.

Keywords: temporal consciousness, time perception, memory, present

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Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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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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