Search results for: intelligent memory structures

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

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

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

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Authors: Akankunda Veronicah Karuhanga

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Dementia is an age mental disorder that makes victims lose normal functionality that needs delicate attention. It has been technically defined as a clinical syndrome that presents a number of difficulties in speech and other cognitive functions that change someone’s behaviors and can also cause impairments in activities of daily living, not forgetting a range of neurological disorders that bring memory loss and cognitive impairment. Family members are the primary healthcare givers and therefore, the way how they handle the situation in its early stages determines future deterioration syndromes like total memory loss. Unfortunately, most family members are ignorant about this condition and in most cases, the patients are brought to our facilities when their condition was already mismanaged by family members and we thus cannot do much. For example, incontinence can be managed at early stages through potty training or toilet scheduling before resorting to 24/7 diapers which are also not good. Professional Elderly care should be understood and practiced as an extension of homes, not a dumping place for people considered “abnormal” on account of ignorance. Immediate relatives should therefore be sensitized concerning the normalcy of dementia in the context of old age so that they can be understanding and supportive of dementia patients rather than discriminating against them as present-day lepers. There is a need to skill home-based caregivers on how to handle dementia in its early stages. Unless this is done, many of our elderly homes shall be filled with patients who should have been treated and supported from their homes. This skilling of home-based caregivers is a vital intervention because until elderly care is appreciated as a human moral obligation, many transactional rehabilitation centers will crop up and this shall be one of the worst moral decadences of our times.

Keywords: dementia, family, Alzheimers, relevancy

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Authors: Ali Algryani

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Ellipsis involves the omission of an item or items that can be recovered from the preceding clause. Ellipsis is used as a cohesion marker; it enhances the cohesiveness of a text/discourse as a clause is interpretable only through making reference to an antecedent clause. The present study attempts to investigate the linguistic phenomenon of ellipsis from a translation perspective. It is mainly concerned with how ellipsis is translated from English into Arabic. The study covers different forms of ellipsis, such as noun phrase ellipsis, verb phrase ellipsis, gapping, pseudo-gapping, stripping, and sluicing. The primary aim of the study, apart from discussing the use and function of ellipsis, is to find out how such ellipsis phenomena are dealt with in English-Arabic translation and determine the implications of the translations of elliptical structures into Arabic. The study is based on the analysis of Dhofar University (DU) students' translations of sentences containing different forms of ellipsis. The initial findings of the study indicate that due to differences in syntactic structures and stylistic preferences between English and Arabic, Arabic tends to use lexical repetition in the translation of some elliptical structures, thus achieving a higher level of explicitness. This implies that Arabic tends to prefer lexical repetition to create cohesion more than English does. Furthermore, the study also reveals that the improper translation of ellipsis leads to interpretations different from those understood from the source text. Such mistranslations can be attributed to student translators’ lack of awareness of the use and function of ellipsis as well as the stylistic preferences of both languages. This has pedagogical implications on the teaching and training of translation students at DU. Students' linguistic competence needs to be enhanced through teaching linguistics-related issues with reference to translation and both languages, .i.e. source and target languages and with special emphasis on their use, function and stylistic preferences.

Keywords: cohesion, ellipsis, explicitness, lexical repetition

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Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

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Authors: Vinícius L. L. Morrone, David Douek, Helder M. F. Pereira, Bernadete L. M. Grandolpho

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This work aimed to identify the relationships between the level of consumer environmental awareness and their search for sustainable properties, as well as to understand the main sustainability structures considered by these consumers during the decision process. Additionally, the paper looked up to the influence environmental awareness and financial status have over the disposition of buyers to pay more for sustainable properties. To achieve these objectives, 318 questionnaires were answered electronically, after being sent to the Green Building Brazil email basis, as to other Real Estate developers client basis. From all the questionnaires answered, 71 were discarded, leaving a total amount of 247 admitted questionnaires to be analyzed. The responses were evaluated based on the theory of consumer decision making, especially on the influence factors of this process. The data were processed using a PLS model, using the R software. The results have shown that the level of consumer environmental awareness effectively affects the consumer’s will of acquiring a sustainable property or, at least, a property with some environmental friendly structures. The consumer’s environmental awareness also positively impacts the importance consumers give to individual environmental friendly structures. Also, as a consumer value to those individual structures raises, it is also observed a raise in his will to buy a sustainable property. Additionally, the impact of consumer’s environmental awareness and financial status over the willingness to pay more for a property with those attributes. The results indicate that there was no relationship between consumers' environmental awareness and their willingness to pay more for a sustainable property. On the other hand, the financial status and the family income of the consumers showed a positive relation with the willingness to pay more for a sustainable property. This indicates that consumers with better financial conditions, which according to the analysis do not necessarily have a greater environmental awareness, are those who are willing to pay more for a sustainable property. Thus, this study indicates that, even if the environmental awareness impact positively the demand for sustainable structures and properties, this impact is not price reflected, due to the price elasticity of the consumption, especially for a category of lower income consumers. This paper adds to the literature in the way it projects some guidelines to the consumer’s decision process in the Real Estate market in emerging economies, as well as it presents some drivers to pricing decisions.

Keywords: consumer behavior, environmental awareness, real estate pricing, sustainable buildings

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Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

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

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

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

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Authors: Maria Korman, Carmit Gal, Ella Gabitov, Avi Karni

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The main question addressed in this study was whether the time-of-day wherein training is afforded is a significant factor for motor skill ('how-to', procedural knowledge) acquisition and consolidation into long term memory in the healthy elderly population. Twenty-nine older adults (60-75 years) practiced an explicitly instructed 5-element key-press sequence by repeatedly generating the sequence ‘as fast and accurately as possible’. Contribution of three parameters to acquisition, 24h post-training consolidation, and 1-week retention gains in motor sequence speed was assessed: (a) time of training (morning vs. evening group) (b) sleep quality (actigraphy) and (c) chronotype. All study participants were moderately morning type, according to the Morningness-Eveningness Questionnaire score. All participants had sleep patterns typical of age, with average sleep efficiency of ~ 82%, and approximately 6 hours of sleep. Speed of motor sequence performance in both groups improved to a similar extent during training session. Nevertheless, evening group expressed small but significant overnight consolidation phase gains, while morning group showed only maintenance of performance level attained at the end of training. By 1-week retention test, both groups showed similar performance levels with no significant gains or losses with respect to 24h test. Changes in the tapping patterns at 24h and 1-week post-training were assessed based on normalized Pearson correlation coefficients using the Fisher’s z-transformation in reference to the tapping pattern attained at the end of the training. Significant differences between the groups were found: the evening group showed larger changes in tapping patterns across the consolidation and retention windows. Our results show that morning-oriented older adults effectively acquired, consolidated, and maintained a new sequence of finger movements, following both morning and evening practice sessions. However, time-of-training affected the time-course of skill evolution in terms of performance speed, as well as the re-organization of tapping patterns during the consolidation period. These results are in line with the notion that motor training preceding a sleep interval may be beneficial for the long-term memory in the elderly. Evening training should be considered an appropriate time window for motor skill learning in older adults, even in individuals with morning chronotype.

Keywords: time-of-day, elderly, motor learning, memory consolidation, chronotype

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Authors: Valencia Fernandes, Dharmendra Kumar Khatri, Shashi Bala Singh

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Background and Aim: Epigenetics are the inaudible signatures of several pathological processes in the brain. This study understands the influence of DNA methylation, a major epigenetic modification, in the prefrontal cortex and hippocampus of the diabetic brain and its notable effect on the cellular chaperones and synaptic proteins. Method: Chronic high fat diet and STZ-induced diabetic mice were studied for cognitive dysfunction, and global DNA methylation, as well as DNA methyltransferase (DNMT) activity, were assessed. Further, the cellular chaperones and synaptic proteins were examined using DNMT inhibitor, 5-aza-2′-deoxycytidine (5-aza-dC)-via intracerebroventricular injection. Moreover, % methylation of these synaptic proteins were also studied so as to correlate its epigenetic involvement. Computationally, its interaction with the DNMT enzyme were also studied using bioinformatic tools. Histological studies for morphological alterations and neuronal degeneration were also studied. Neurogenesis, a characteristic marker for new learning and memory formation, was also assessed via the BrdU staining. Finally, the most important behavioral studies, including the Morris water maze, Y maze, passive avoidance, and Novel object recognition test, were performed to study its cognitive functions. Results: Altered global DNA methylation and increased levels of DNMTs within the nucleus were confirmed in the cortex and hippocampus of the diseased mice, suggesting hypermethylation at a genetic level. Treatment with AzadC, a global DNA demethylating agent, ameliorated the protein and gene expression of the cellular chaperones and synaptic fidelity. Furthermore, the methylation analysis profile showed hypermethylation of the hsf1 protein, a master regulator for chaperones and thus, confirmed the epigenetic involvement in the diseased brain. Morphological improvements and decreased neurodegeneration, along with enhanced neurogenesis in the treatment group, suggest that epigenetic modulations do participate in learning and memory. This is supported by the improved behavioral test battery seen in the treatment group. Conclusion: DNA methylation could possibly accord in dysregulating the memory-associated proteins at chronic stages in type 2 diabetes. This could suggest a substantial contribution to the underlying pathophysiology of several metabolic syndromes like insulin resistance, obesity and also participate in transitioning this damage centrally, such as cognitive dysfunction.

Keywords: epigenetics, cognition, chaperones, DNA methylation

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

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Authors: Rahmathulla Noufal E.

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Investigating the dynamic responses of high rise structures under the effect of siesmic ground motion is extremely important for the proper analysis and design of multitoried structures. Since the presence of infilled walls strongly influences the behaviour of frame systems in multistoried buildings, there is an increased need for developing guidelines for the analysis and design of infilled frames under the effect of dynamic loads for safe and proper design of buildings. In this manuscript, we evaluate the natural frequencies and natural periods of single bay single storey frames considering the effect of infill walls by using the Eigen value analysis and validating with SAP 2000 (free vibration analysis). Various parameters obtained from the diagonal strut model followed for the free vibration analysis is then compared with the Finite Element model, where infill is modeled as shell elements (four noded). We also evaluated the effect of various parameters on the natural periods of vibration obtained by free vibration analysis in SAP 2000 comparing them with those obtained by the empirical expressions presented in I.S. 1893(Part I)-2002.

Keywords: infilled frame, eigen value analysis, free vibration analysis, diagonal strut model, finite element model, SAP 2000, natural period

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Authors: Axel Thallemer, Aleksandar Kostadinov, Abel Fam, Alex Teo

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For centuries, the forming processes in nature served as a source of inspiration for both architects and designers. It seems as most human artifacts are based on ideas which stem from the observation of the biological world and its principles of growth. As a fact, in the cultural history of Homo faber, materials have been mostly used in their solid state: From hand axe to computer mouse, the principle of employing matter has not changed ever since the first creation. In the scope of history only recently and by the help of additive-generative fabrication processes through Computer Aided Design (CAD), designers were enabled to deconstruct solid artifacts into an outer skin and an internal lattice structure. The intention behind this approach is to create a new topology which reduces resources and integrates functions into an additively manufactured component. However, looking at the currently employed lattice structures, it is very clear that those lattice structure geometries have not been thoroughly designed, but rather taken out of basic-geometry libraries which are usually provided by the CAD. In the here presented study, a group of 20 industrial design students created new and unique lattice structures using natural paragons as their models. The selected natural models comprise both the animate and inanimate world, with examples ranging from the spiraling of narwhal tusks, off-shooting of mangrove roots, minimal surfaces of soap bubbles, up to the rhythmical arrangement of molecular geometry, like in the case of SiOC (Carbon-Rich Silicon Oxicarbide). This ideation process leads to a design of a geometric cell, which served as a basic module for the lattice structure, whereby the cell was created in visual analogy to its respective natural model. The spatial lattices were fabricated additively in mostly [X]3 by [Y]3 by [Z]3 units’ volumes using selective powder bed melting in polyamide with (z-axis) 50 mm and 100 µm resolution and subdued to mechanical testing of their elastic zone in a biomedical laboratory. The results demonstrate that additively manufactured lattice structures can acquire different properties when they are designed in analogy to natural models. Several of the lattices displayed the ability to store and return kinetic energy, while others revealed a structural failure which can be exploited for purposes where a controlled collapse of a structure is required. This discovery allows for various new applications of functional lattice structures within industrially created objects.

Keywords: bio-inspired, biomimetic, lattice structures, additive manufacturing

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Authors: Asmaa Zaraq

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In the present work we report X-ray powder diffraction measurements of SrCaCoTeO6 and SrCaNiTeO6, at different temperatures. The crystal structures at room temperature of both compounds are determined; and results showing the existence of high-temperature phase transitions in them are presented. Both compounds have double perovskite structure with 1:1 ordered arrangement of the B site cations. At room temperature their symmetries are described with the P21/n space group, that correspond to the (a+b-b-) tilt system. The evolution with temperature of the structure of both compounds shows the presence of three phase transitions: a continuous one, at 450 and 500 K, a discontinuous one, at 700 and 775 K, and a continuous one at 900 and 950 K for SrCaCoTeO6 and SrCaNiTeO6, respectively with the following phase-transition sequence: P21/n → I2/m → I4/m → Fm-3m.

Keywords: double perovskites, caracterisation DRX, transition de phase

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Authors: Mircea Pastrav, Horia Constantinescu

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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.

Keywords: modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Mom Bishwakarma

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This research traces out how the Dalit in Nepal evolved from the early 1950s to the current day, from invoking Dalit against caste discrimination through to the asserting proportional representation in state structures. The research focused most closely on the formation of Dalit association and resistance, as well as on the different struggles throughout this period. It then discusses the expansion of Dalit movement in NGOs, its internationalization and responses. The research sees that Dalit movement has been influenced by its network with the national and international civil rights movement particularly Dalit movement in India and argues that Dalit movement in Nepal have in many ways, challenged the orthodox based caste stratification for Dalit equality and justice. It can be seen that at the same time as Dalit participation was increasing, divisions by caste line also emerged. Rather reshaping the power structures, Dalit movement encircled into division and contentious politics.

Keywords: Dalit, equality, justice, movements, Nepal

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Authors: Miao Sabrina Wang

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This paper examines the impact of grammatical differences on simultaneous interpreting from English into Mandarin Chinese by drawing upon an empirical study of professional and student interpreters. The research focuses on the effects of three grammatical categories including passives, adverbial components and noun phrases on simultaneous interpreting. For each category, interpretations of instances in which the grammatical structures are the same across the two languages are compared with interpretations of instances in which the grammatical structures differ across the two languages in terms of content accuracy and delivery appropriateness. The results indicate that grammatical differences have a significant impact on the interpreting performance of both professionals and students.

Keywords: content accuracy, delivery appropriateness, grammatical differences, simultaneous interpreting

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Authors: Yo-Seph Byun, Gyu-Phil Lee, Young-Bin Park, Gye-Chun Cho, Seong-Won Lee

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In Korea, a study on Limit State Design (LSD) for underground structures is being conducted in order to perform more effective design. In this study, as a result of MCS (Monte-Carlo Simulation) technique, failure probabilities of the structure during normal and earthquake are estimated in reliability analysis. Target reliability indexes are determined depending on load combinations for underground structure, and then, design variables such as load and material factors in LSD are decided. As a result, through the research in order to determine more reliable design variables, a specification of LSD for underground structures is able to be developed.

Keywords: design variable, limit state design, target reliability index, underground structure

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Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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

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

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

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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Authors: Yalçın Kılıç, İbrahim Kani

Abstract:

In recent years, interest in the synthesis of coordination compounds has greatly increased due to various application areas (such as catalysis, gas storage, luminescence). Dicarboxylic acids are often used in the synthesis of metal complexes. Bis-thiosalicylate derivative ligands contribute to the synthesis of structures of crystal engineering interest, as they can have both rigid and flexible properties. In addition, these ligands have great potential in terms of catalytic applications with the sulfur and oxygen donor atoms in their structures. In this study, we synthesized a Cu(II) complex [Cu(tsaxyl)(phen)2]•CH3OH (where tsaxyl = 2,2'-(1,2-phylenebis(methylene))bis(sulfanedyl)dibenzoate, phen = 1,10-phenantroline) and characterized through X-ray crystallography. The catalytic activities of Cu(II) complex on oxidation of ethylbenzene, cyclohexane, diphenylmethane, p-xylene were performed in acetonitrile with t-BuOOH as the source of oxygen.

Keywords: complex, crystallography, catalysis, oxidation

Procedia PDF Downloads 100

Authors: Zbigniew Czyz, Ksenia Siadkowska, Krzysztof Skiba, Karol Scislowski

Abstract:

Today’s progress in the rotorcraft is mostly associated with an optimization of aircraft performance achieved by active and passive modifications of main rotor assemblies and a tail propeller. The key task is to improve their performance, improve the hover quality factor for rotors but not change in specific fuel consumption. One of the tasks to improve the helicopter is an active optimization of the main rotor providing for flight stages, i.e., an ascend, flight, a descend. An active interference with the airflow around the rotor blade section can significantly change characteristics of the aerodynamic airfoil. The efficiency of actuator systems modifying aerodynamic coefficients in the current solutions is relatively high and significantly affects the increase in strength. The solution to actively change aerodynamic characteristics assumes a periodic change of geometric features of blades depending on flight stages. Changing geometric parameters of blade warping enables an optimization of main rotor performance depending on helicopter flight stages. Structurally, an adaptation of shape memory alloys does not significantly affect rotor blade fatigue strength, which contributes to reduce costs associated with an adaptation of the system to the existing blades, and gains from a better performance can easily amortize such a modification and improve profitability of such a structure. In order to obtain quantitative and qualitative data to solve this research problem, a number of numerical analyses have been necessary. The main problem is a selection of design parameters of the main rotor and a preliminary optimization of its performance to improve the hover quality factor for rotors. This design concept assumes a three-bladed main rotor with a chord of 0.07 m and radius R = 1 m. The value of rotor speed is a calculated parameter of an optimization function. To specify the initial distribution of geometric warping, a special software has been created that uses a numerical method of a blade element which respects dynamic design features such as fluctuations of a blade in its joints. A number of performance analyses as a function of rotor speed, forward speed, and altitude have been performed. The calculations were carried out for the full model assembly. This approach makes it possible to observe the behavior of components and their mutual interaction resulting from the forces. The key element of each rotor is the shaft, hub and pins holding the joints and blade yokes. These components are exposed to the highest loads. As a result of the analysis, the safety factor was determined at the level of k > 1.5, which gives grounds to obtain certification for the strength of the structure. The construction of the joint rotor has numerous moving elements in its structure. Despite the high safety factor, the places with the highest stresses, where the signs of wear and tear may appear, have been indicated. The numerical analysis carried out showed that the most loaded element is the pin connecting the modular bearing of the blade yoke with the element of the horizontal oscillation joint. The stresses in this element result in a safety factor of k=1.7. The other analysed rotor components have a safety factor of more than 2 and in the case of the shaft, this factor is more than 3. However, it must be remembered that the structure is as strong as the weakest cell is. Designed rotor for unmanned aerial vehicles adapted to work with blades with intelligent materials in its structure meets the requirements for certification testing. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: main rotor, rotorcraft aerodynamics, shape memory alloy, materials, unmanned helicopter

Procedia PDF Downloads 154

Authors: Akram Khelaifia, Salah Guettala, Nesreddine Djafar Henni, Rachid Chebili

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Recent seismic events have underscored the significant influence of masonry infill walls on the resilience of structures. The irregular positioning of these walls exacerbates their adverse effects, resulting in substantial material and human losses. Research and post-earthquake evaluations emphasize the necessity of considering infill walls in both the design and assessment phases. This study delves into the presence of soft stories in reinforced concrete structures with infill walls. Employing an approximate method relying on pushover analysis results, fiber-section-based macro-modeling is utilized to simulate the behavior of infill walls. The findings shed light on the presence of soft first stories, revealing a notable 240% enhancement in resistance for weak column—strong beam-designed frames due to infill walls. Conversely, the effect is more moderate at 38% for strong column—weak beam-designed frames. Interestingly, the uniform distribution of infill walls throughout the structure's height does not influence soft-story emergence in the same seismic zone, irrespective of column-beam strength. In regions with low seismic intensity, infill walls dissipate energy, resulting in consistent seismic behavior regardless of column configuration. Despite column strength, structures with open-ground stories remain vulnerable to soft first-story emergence, underscoring the crucial role of infill walls in reinforced concrete structural design.

Keywords: masonry infill walls, soft Storey, pushover analysis, fiber section, macro-modeling

Procedia PDF Downloads 61

Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

Abstract:

Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

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Authors: Lourens Millard, Gerrit Jan Breukelman, Nonkululeko Mathe

Abstract:

Aim: The research aims to investigate the differences in visio-spatial skills (VSS) between athletes and non-athletes, as well as variations across sports, presenting conflicting findings. Therefore, the objective of this study was to determine if there exist significant differences in visio-spatial intelligence skills between rugby players and netball players, and whether such disparities are present when comparing both groups to non-athletes. Methods: Participants underwent an optometric assessment, followed by an evaluation of VSS using six established tests: the Hart Near Far Rock, saccadic eye movement, evasion, accumulator, flash memory, and ball wall toss tests. Results: The results revealed that rugby players significantly outperformed netball players in speed of recognition, peripheral awareness, and hand-eye coordination (p=.000). Moreover, both rugby players and netball players performed significantly better than non-athletes in five of the six tests (p=.000), with the exception being the visual memory test (p=.809). Conclusion: This discrepancy in performance suggests that certain VSS are superior in athletes compared to non-athletes, highlighting potential implications for theories of vision, test selection, and the development of sport-specific VSS testing batteries. Furthermore, the use of a hand-eye coordination-specific VSS test battery effectively differentiated between different sports. However, this pattern was not consistent across all VSS tests, indicating that further research should explore the training methods employed by both sports, as these factors may contribute to the observed differences.

Keywords: visio-spatial intelligence (VSI), rugby vision, netball vision, visual skills, sport vision.

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Authors: N. Ourabia, M. Boubaker Ourabia

Abstract:

An approach for modeling and numerical simulation of passive planar structures using the edge line concept is developed. With this method, we develop an efficient modeling technique for microstrip discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then, it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Keywords: optimization, CAD analysis, microwave circuits, S-parameters

Procedia PDF Downloads 448

Authors: Keisuke Fujioka, Yuta Itoh, Masaru Minagawa, Shunji Kusayanagi

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In this study, building information models of the underground temporary structures and adjacent embedded pipes were constructed to show the importance of the information on underground pipes adjacent to the structures to enhance the productivity of execution of construction. Next, the bar chart used in actual construction process were employed to make the Gantt chart, and the critical pass analysis was carried out to show that accurate information on the arrangement of underground existing pipes can be used for the enhancement of the productivity of the construction of underground structures. In the analyzed project, significant construction delay was not caused by unforeseeable existence of underground pipes by the management ability of the construction manager. However, in many cases of construction executions in the developing countries, the existence of unforeseeable embedded pipes often causes substantial delay of construction. Design change based on uncertainty on the position information of embedded pipe can be also important risk for contractors in domestic construction. So CPM analyses were performed by a project-management-software to the situation that influence of the tasks causing construction delay was assumed more significant. Through the analyses, the efficiency of information management on underground pipes and BIM analysis in the design stage for workability improvement was indirectly confirmed.

Keywords: building-information modelling, construction information modelling, design improvement, infrastructure

Procedia PDF Downloads 306

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

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A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: analogy-making, categorization, learning of categories, abstraction, hierarchical structure

Procedia PDF Downloads 184