Search results for: memory types

Authors: Zhicheng Han

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This study examines the correlation between knowledge of formulaic language, working memory (WM), and phonological short-term memory (PSTM) in Chinese L2 learners of English. This study investigates if WM and PSTM correlate differently to the acquisition of formulaic language, which may be relevant for the discourse around the conceptualization of formulas. Connectionist approaches have lead scholars to argue that formulas are form-meaning connections stored whole, making PSTM significant in the acquisitional process as it pertains to the storage and retrieval of chunk information. Generativist scholars, on the other hand, argued for active participation of interlanguage grammar in the acquisition and use of formulaic language, where formulas are represented in the mind but retain the internal structure built around a lexical core. This would make WM, especially the processing component of WM an important cognitive factor since it plays a role in processing and holding information for further analysis and manipulation. The current study asked L1 Chinese learners of English enrolled in graduate programs in China to complete a preference raking task where they rank their preference for formulas, grammatical non-formulaic expressions, and ungrammatical phrases with and without the lexical core in academic contexts. Participants were asked to rank the options in order of the likeliness of them encountering these phrases in the test sentences within academic contexts. Participants’ syntactic proficiency is controlled with a cloze test and grammar test. Regression analysis found a significant relationship between the processing component of WM and preference of formulaic expressions in the preference ranking task while no significant correlation is found for PSTM or syntactic proficiency. The correlational analysis found that WM, PSTM, and the two proficiency test scores have significant covariates. However, WM and PSTM have different predictor values for participants’ preference for formulaic language. Both storage and processing components of WM are significantly correlated with the preference for formulaic expressions while PSTM is not. These findings are in favor of the role of interlanguage grammar and syntactic knowledge in the acquisition of formulaic expressions. The differing effects of WM and PSTM suggest that selective attention to and processing of the input beyond simple retention play a key role in successfully acquiring formulaic language. Similar correlational patterns were found for preferring the ungrammatical phrase with the lexical core of the formula over the ones without the lexical core, attesting to learners’ awareness of the lexical core around which formulas are constructed. These findings support the view that formulaic phrases retain internal syntactic structures that are recognized and processed by the learners.

Keywords: formulaic language, working memory, phonological short-term memory, academic language

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Authors: Amatulraheem Al-Abassi, K. Khanafer, Ibrahim Deiab

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The coronary artery stent is a promising technology that can treat various coronary diseases. Materials used for manufacturing medical stents should have high biocompatible properties. Stent alloys, in particular, are remarkably promising good clinical outcomes, however, there is threaten of restenosis (reoccurring of artery narrowing due to fatty plaque), stent recoiling, or in long-term the occurrence of stent fracture. However, stents that are made of Nickel-titanium (Nitinol) can bare extensive plastic deformation and resist restenosis. This shape memory alloy has outstanding mechanical properties. Nitinol is a unique shape memory alloy as it has unique mechanical properties such as; biocompatibility, super-elasticity, and recovery to original shape under certain loads. Stent failure may cause complications in vascular diseases and possibly blockage of blood flow. Thus, studying the behaviors of the stent under different medical conditions will help the doctors and cardiologists to predict when it is necessary to change the stent in order to prevent any severe morbidity outcomes. To the best of our knowledge, there are limited published papers that analyze the stent behavior with regards to the contact surfaces of plaque layer and blood vessel. Thus, stent material properties will be discussed in this investigation to highlight the mechanical and clinical differences between various stents. This research analyzes the performance of Nitinol stent in well-known stent design to determine its bearing with stress and its dislocation in blood vessels, in comparison to stents made of different biocompatible materials. In addition, a study of its performance will be represented in the system. Finite Element Analysis is the core of this study. Thus, a physical representative model will be discussed to show the distribution of stress and strain along the interaction surface between the stent and the artery. The reaction of vascular tissue to the stent will be evaluated to predict the possibility of restenosis within the treated area.

Keywords: shape memory alloy, stent, coronary artery, finite element analysis

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Authors: Duygu Kan, Mehmet Cayoren

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Sommerfeld-integrals (SIs) are commonly encountered in electromagnetics problems involving analysis of antennas and scatterers embedded in planar multilayered media. Generally speaking, the analytical solution of SIs is unavailable, and it is well known that numerical evaluation of SIs is very time consuming and computationally expensive due to the highly oscillating and slowly decaying nature of the integrands. Therefore, fast computation of SIs has a paramount importance. In this paper, a parallel code has been developed to speed up the computation of SI in the framework of calculation of dyadic Green’s function in multilayered media. OpenMP shared memory approach is used to parallelize the SI algorithm and resulted in significant time savings. Moreover accelerating the computation of dyadic Green’s function is discussed based on the parallel SI algorithm developed.

Keywords: Sommerfeld-integrals, multilayer dyadic Green’s function, OpenMP, shared memory parallel programming

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: N. Hadjigeorgiou, A. C. Tsalikidou, E. Hristoforou, P. P. Sotiriadis

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During the last few decades, the continuously increasing demand for accurate and reliable magnetic measurements has paved the way for the development of different types of magnetic sensing systems as well as different measurement techniques. Sensor sensitivity and linearity, signal-to-noise ratio, measurement range, cross-talk between sensors in multi-sensor applications are only some of the aspects that have been examined in the past. In this paper, a fully analog closed loop system in order to optimize the performance of AMR sensors has been developed. The operation of the proposed system has been tested using a Helmholtz coil calibration setup in order to control both the amplitude and direction of magnetic field in the vicinity of the AMR sensor. Experimental testing indicated that improved linearity of sensor response, as well as low noise levels can be achieved, when the system is employed.

Keywords: AMR sensor, closed loop, memory effects, chopper, linearity improvement, sensitivity improvement, magnetic noise, electronic noise

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Authors: Felib Ayman Shawky Salem

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Nowadays crypto currency has become a global phenomenon known to most people. People using this alternative digital money to do a transaction in many ways (e.g. Used for online shopping, wealth management, and fundraising). However, this digital asset also widely used in criminal activities since its use decentralized control as opposed to centralized electronic money and central banking systems and this makes a user, who used this currency invisible. The high-value exchange of these digital currencies also has been a target to criminal activities. The crypto currency crimes have become a challenge for the law enforcement to analyze and to proof the evidence as criminal devices. In this paper, our focus is more on bitcoin crypto currency and the possible artifacts that can be obtained from the different type of digital wallet, which is software and browser-based application. The process memory and physical hard disk are examined with the aims of identifying and recovering potential digital evidence. The stage of data acquisition divided by three states which are the initial creation of the wallet, transaction that consists transfer and receiving a coin and the last state is after the wallet is being deleted. Findings from this study suggest that both data from software and browser type of wallet process memory is a valuable source of evidence, and many of the artifacts found in process memory are also available from the application and wallet files on the client computer storage.

Keywords: cryptocurrency, bitcoin, payment methods, blockchain, appropriation, online retailers, TOE framework, disappropriation, non-appropriationBitCoin, financial protection, crypto currency, money laundering cryptocurrency, digital wallet, digital forensics

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Authors: Sheikha Ali Salim Al-Breiki

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The purpose of this study was to explore the types of the spelling errors students of grade ten make and to find out whether there were any significant differences between males and females with respect to the types of the spelling errors made. The sample of the study included 90 grade ten students from four different schools in North Batinah. The researcher manipulated the use of a test that consisted of two questions: an oral dictation test of 70 words with a contextualizing sentence and a free writing task. The misspellings were classified into nine different types. The findings revealed that the most common spelling errors among Omani grade ten students were vowel substitution, then came vowel omission in the second place and consonant substitution in the third place. Male students omitted more vowels than female students while females made more true word errors than their male counterparts. In light of the findings, the study presents some recommendations and suggestions for further studies.

Keywords: types of spelling errors, errors, ESL/EFL, error analysis

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Authors: Bernhard Bauer, Thomas Meixner, Amir Dini, Detlef Heck

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The inner city building stock is characterized by different types of buildings of different decades and centuries and different types of historical constructions. Depending on the natural growth of a city, those types are often located in downtown areas and the surrounding suburbs. Since the population is becoming older and the variation of the different social requirements spread with the so-called 'Silver Society', city quarters have to be seen alternatively. If an area is very attractive for young students to live there because of the busy nightlife, it might not be suitable for the older society. To identify 'Location Types A, B, C' for different user groups, qualitative interviews with 24 citizens of the city of Graz (Austria) have been carried out, in order to identify the most important values for making a location or city quarter 'A', 'B', or 'C'. Furthermore these acknowledgements have been put into a softwaretool for predicting locations that are the most suitable for certain user groups. On the other hands side, investors or owners of buildings can use the tool for determining the most suitable user group for the location of their building or construction project in order to adapt the project or building stock to the requirements of the users.

Keywords: building stock, location parameters, inner city population, built environment

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Zhanfeng Ma, Zhiping Xiong, Hu Yin, Zhengwei She, Aditya P. Gurajada, Tianlun Chen, Ying Li

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Many RDBMS vendors use B-tree index to achieve high performance for point queries and range queries, and some of them also employ hash index to further enhance the performance as hash table is more efficient for point queries. However, there are extra overheads to maintain a separate hash index, for example, hash mapping for all data records must always be maintained, which results in more memory space consumption; locking, logging and other mechanisms are needed to guarantee ACID, which affects the concurrency and scalability of the system. To relieve the overheads, Hash Cached B-tree (HCB) index is proposed in this paper, which consists of a standard disk-based B-tree index and an additional in-memory lock-free hash table. Initially, only the B-tree index is constructed for all data records, the hash table is built on the fly based on runtime workload, only data records accessed by point queries are indexed using hash table, this helps reduce the memory footprint. Changes to hash table are done using compare-and-swap (CAS) without performing locking and logging, this helps improve the concurrency and avoid contention. The hash table is also optimized to be cache conscious. HCB index is implemented in SAP ASE database, compared with the standard B-tree index, early experiments and customer adoptions show significant performance improvement. This paper provides an overview of the design of HCB index and reports the experimental results.

Keywords: B-tree, compare-and-swap, lock-free hash table, point queries, range queries, SAP ASE database

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Bin Liu

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Prokaryotic promoter, consisted of two short DNA sequences located at in -35 and -10 positions, is responsible for controlling the initiation and expression of gene expression. Different types of promoters have different functions, and their consensus sequences are similar. In addition, their consensus sequences may be different for the same type of promoter, which poses difficulties for promoter identification. Unfortunately, all existing computational methods treat promoter identification as a binary classification task and can only identify whether a query sequence belongs to a specific promoter type. It is desired to develop computational methods for effectively identifying promoters and their types. Here, a two-layer predictor is proposed to try to deal with the problem. The first layer is designed to predict whether a given sequence is a promoter and the second layer predicts the type of promoter that is judged as a promoter. Meanwhile, we also analyze the importance of feature and sequence conversation in two aspects: promoter identification and promoter type identification. To the best knowledge of ours, it is the first computational predictor to detect promoters and their types.

Keywords: promoter, promoter type, random forest, sequence information

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Authors: Belbaly Nassim

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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

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The skew detection and correction form an important part of digital document analysis. This is because uncompensated skew can deteriorate document features and can complicate further document image processing steps. Efficient text document analysis and digitization can rarely be achieved when a document is skewed even at a small angle. Once the documents have been digitized through the scanning system and binarization also achieved, document skew correction is required before further image analysis. Research efforts have been put in this area with algorithms developed to eliminate document skew. Skew angle correction algorithms can be compared based on performance criteria. Most important performance criteria are accuracy of skew angle detection, range of skew angle for detection, speed of processing the image, computational complexity and consequently memory space used. The standard Hough Transform has successfully been implemented for text documentation skew angle estimation application. However, the standard Hough Transform algorithm level of accuracy depends largely on how much fine the step size for the angle used. This consequently consumes more time and memory space for increase accuracy and, especially where number of pixels is considerable large. Whenever the Hough transform is used, there is always a tradeoff between accuracy and speed. So a more efficient solution is needed that optimizes space as well as time. In this paper, an improved Hough transform (HT) technique that optimizes space as well as time to robustly detect document skew is presented. The modified algorithm of Hough Transform presents solution to the contradiction between the memory space, running time and accuracy. Our algorithm starts with the first step of angle estimation accurate up to zero decimal place using the standard Hough Transform algorithm achieving minimal running time and space but lacks relative accuracy. Then to increase accuracy, suppose estimated angle found using the basic Hough algorithm is x degree, we then run again basic algorithm from range between ±x degrees with accuracy of one decimal place. Same process is iterated till level of desired accuracy is achieved. The procedure of our skew estimation and correction algorithm of text images is implemented using MATLAB. The memory space estimation and process time are also tabulated with skew angle assumption of within 00 and 450. The simulation results which is demonstrated in Matlab show the high performance of our algorithms with less computational time and memory space used in detecting document skew for a variety of documents with different levels of complexity.

Keywords: hough-transform, skew-detection, skew-angle, skew-correction, text-document

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Authors: Cristina Greco

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The spread of the digital and we-based technologies has led to a transformation process, which has coincided with an increase in the number of cases who are beyond the mainstream storytelling and its codes on the interaction with the user. On the base of a previous research on i-docs and virtual museums, this study analyses interactive and immersive online Graphic Novel – one-page, animated, illustrated, and hybrid – to reflect on the transformational implications of this expressive form on the user perception, remembrance, and awareness. The way in which the user experiences a certain level of interaction with the story and immersion in the semantic and figurative universe would bring user’s attention, activating introspection and self-reflection processes, perception, imagination, and creativity. This would have to do with the involvement of different senses – visual, proprioceptive, tactile, auditory, and vestibular – and the activation of a phenomenon of synaesthesia (involuntary cross-modal sensory association) – where, for example, the aural reconnect the user to another sense, providing a multisensory experience. The case studies show specific forms of interactive and immersive graphic novel and reflect on application that has sought to engage innovative ways to communicate different messages and stimulate cultural memory and collective awareness. The visual semiotic and narrative analysis of the distinctive traits of such a complex textuality, along with a study of the user’s experience through observation in naturalistic settings and interviews, allows us to question the functioning of these configurations, with regard to the relationships between the figurative dimension, the perceptive activity, and their impact on the user’s engagement.

Keywords: collective awareness, cultural memory, graphic novel, interactive and immersive storytelling

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Authors: Mi-Hye Hwang, Young Min Son, Kichan Lee, Bang-Hun Hyun, Byeong Yeal Jung

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Botulism is a paralytic disease of human beings and animals caused by neurotoxin produced by Clostridium botulinum. The neurotoxins are genetically distinguished into 8 types, A to H. Ingestion of performed toxin, usually types B, C, and D, have been shown to produce diseases in most cases of cattle botulism. Vaccination is the best measure to prevent cattle botulism. However, the commercially available toxoid-based vaccines are difficult and hazardous to produce. We produced recombinant protein using gene of heavy chain domain of botulinum toxin B of which binds to cellular receptor of neuron cells and used as immunogen. In this study, we evaluated the safety and efficacy of botulism vaccine composed of recombinant types B. Safety test was done by National Regulation for Veterinary Biologicals. For efficacy test, female ICR mice (5 weeks old) were subcutaneously injected, intraperitoneally challenged, and examined the survival rates compared with vaccination and non-vaccination group. Mouse survival rate of recombinant types B vaccine was above 80%, while one of non-vaccination group was 0%. A vaccine composed of recombinant types B was safe and efficacious in mouse. Our results suggest that recombinant heavy chain receptor binding domain can be used as an effective vaccine candidate for type B botulism.

Keywords: botulism, livestock, vaccine, recombinant protein, toxin

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Authors: Arpan Bera, Rini Ganguly, Raja Chakraborty, Amlan J. Pal

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To deal with the increasing demands for the high-density non-volatile memory devices, we need nano-sites with efficient and stable charge storage capabilities. We prepared nanocrystals (NCs) of inorganic perovskite, CsPbCl₃ coated with Cs₄PbCl₆, by colloidal synthesis. Due to the type-I band alignment at the junction, this core-shell composite is expected to behave as a charge trapping site. Using Scanning Tunneling Spectroscopy (STS), we investigated voltage-controlled resistive switching in this heterostructure by tracking the change in its current-voltage (I-V) characteristics. By applying voltage pulse of appropriate magnitude on the NCs through this non-invasive method, different resistive states of this system were systematically accessed. For suitable pulse-magnitude, the response jumped to a branch with enhanced current indicating a high-resistance state (HRS) to low-resistance state (LRS) switching in the core-shell NCs. We could reverse this process by using a pulse of opposite polarity. These two distinct resistive states can be considered as two logic states, 0 and 1, which are accessible by varying voltage magnitude and polarity. STS being a local probe in space enabled us to capture this switching at individual NC site. Hence, we claim a bright prospect of these core-shell NCs made of inorganic halide perovskites in future high density memory application.

Keywords: Core-shell perovskite, CsPbCl₃-Cs₄PbCl₆, resistive switching, Scanning Tunneling Spectroscopy

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Authors: Osman Adiguzel

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Shape-memory alloys are a new class of functional materials with a peculiar property known as shape memory effect. These alloys return to a previously defined shape on heating after deformation in low temperature product phase region and take place in a class of functional materials due to this property. The origin of this phenomenon lies in the fact that the material changes its internal crystalline structure with changing temperature. Shape memory effect is based on martensitic transitions, which govern the remarkable changes in internal crystalline structure of materials. Martensitic transformation, which is a solid state phase transformation, occurs in thermal manner in material on cooling from high temperature parent phase region. This transformation is governed by changes in the crystalline structure of the material. Shape memory alloys cycle between original and deformed shapes in bulk level on heating and cooling, and can be used as a thermal actuator or temperature-sensitive elements due to this property. Martensitic transformations usually occur with the cooperative movement of atoms by means of lattice invariant shears. The ordered parent phase structures turn into twinned structures with this movement in crystallographic manner in thermal induced case. The twinned martensites turn into the twinned or oriented martensite by stressing the material at low temperature martensitic phase condition. The detwinned martensite turns into the parent phase structure on first heating, first cycle, and parent phase structures turn into the twinned and detwinned structures respectively in irreversible and reversible memory cases. On the other hand, shape memory materials are very important and useful in many interdisciplinary fields such as medicine, pharmacy, bioengineering, metallurgy and many engineering fields. The choice of material as well as actuator and sensor to combine it with the host structure is very essential to develop main materials and structures. Copper based alloys exhibit this property in metastable beta-phase region, which has bcc-based structures at high temperature parent phase field, and these structures martensitically turn into layered complex structures with lattice twinning following two ordered reactions on cooling. Martensitic transition occurs as self-accommodated martensite with inhomogeneous shears, lattice invariant shears which occur in two opposite directions, <110 > -type directions on the {110}-type plane of austenite matrix which is basal plane of martensite. This kind of shear can be called as {110}<110> -type mode and gives rise to the formation of layered structures, like 3R, 9R or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper based alloys which have the chemical compositions in weight; Cu-26.1%Zn 4%Al and Cu-11%Al-6%Mn. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit super lattice reflections inherited from parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that locations and intensities of diffraction peaks change with the aging time at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close each other.

Keywords: Shape memory effect, martensite, twinning, detwinning, self-accommodation, layered structures

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Authors: Musaab Riyadh, Norwati Mustapha, Dina Riyadh

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Trajectory similarity can be defined as the cost of transforming one trajectory into another based on certain similarity method. It is the core of numerous mining tasks such as clustering, classification, and indexing. Various approaches have been suggested to measure similarity based on the geometric and dynamic properties of trajectory, the overlapping between trajectory segments, and the confined area between entire trajectories. In this article, an evaluation of these approaches has been done based on computational cost, usage memory, accuracy, and the amount of data which is needed in advance to determine its suitability to stream mining applications. The evaluation results show that the stream mining applications support similarity methods which have low computational cost and memory, single scan on data, and free of mathematical complexity due to the high-speed generation of data.

Keywords: global distance measure, local distance measure, semantic trajectory, spatial dimension, stream data mining

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

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This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: Ya-Hsuan Wang

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This project of intercultural education aimed to explore pluricultural people’s interpretation and evaluation of the transnational community in Taiwan. Based on transnationalism and transculturalism, this study concerns the human right issues for immigrants and pluricultural people. Research participants as immigrants in Taiwan were asked about their typical thinking styles in the transnational community, their cultural integration in terms of transnational behaviors, and their collective memory of the transnational community. Interview questions included what key factors were involved in their identity negotiation, what roles the transnational community and collective memory would be for their identity negotiation and what were the positive or negative aspects impacting cross-border identity. Based on the experiences of pluricultural people and transnational communities, this project expected to enhance the depth and width of developing transcultural knowledge in textbook reform on History in K-12 schools. It is to transform cross-border identity into knowledge embedded with local culture in response to globalization and localization. The purpose of this paper is to portrait the cross-cultural practice of transnational community for Taiwan’s immigrants. It is to report their external socio-cultural expectation of ethnic economics, to understand their internal life course of national identity, and to clarify transnational community in relation to their cross-border identity. In conclusion, the cross-cultural practice of transnational community combined the external contexts such as ethnic economic interaction among transnational communities, social report and ethnic industry, and the internal contexts such as ethnic identity, language use, and collective memory in ethnic history.

Keywords: cross-cultural practice, immigrants, pluricultural people, transnational community

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Authors: Takahiro Hino, Michiharu Maeda

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Particle swarm optimization (PSO) is an optimization approach that achieves the social model of bird flocking and fish schooling. PSO works in continuous space and can solve continuous optimization problem with high quality. Set-based particle swarm optimization (SPSO) functions in discrete space by using a set. SPSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In this paper, we present an algorithm of SPSO with status memory to decide the position based on the previous position for solving traveling salesman problem (TSP). In order to show the effectiveness of our approach. We examine SPSOSM for TSP compared to the existing algorithms.

Keywords: combinatorial optimization problems, particle swarm optimization, set-based particle swarm optimization, traveling salesman problem

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Authors: Maria De Los Angeles Rodriguez Cadena

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This paper discusses how the fictional versions of women of the past contribute to advance today’s ideas of social justice, personal freedom and emancipation as well as to highlight the creative challenge of constructing people and events on fictional narratives on television that incorporate multiple and simultaneous layers of meaning and complexity. This project builds on existing scholarship on audiovisual texts by exploring an influential but under-studied director. In two Mexican television series, Patricia Arriaga Jordan, an award-winning television producer, scriptwriter and director, constructs the life of two outstanding women that have played an influential role in national history and captured Mexican’s popular imagination for generations: Sor Juana Inés de la Cruz, and Malinche. Malinche (2018) tells the story of an extraordinary indigenous woman, Malintzin, during the Spanish Conquest (1511-1550) that is considered to have played a key role in the fall of the Aztec empire by acting as translator, negotiator and cultural mediator for the Spanish conquerors. Juana Ines (2016) portrays Sor Juana, a poet, essayist, playwright, theologian, philosopher, nun, of XVII century colonial Mexico, one of the brightest minds of her time, and now recognized as the first feminist of the Americas who wrote on the rights of women to an education, religious authority and feminist advocacy. Both series, as fictional narratives that recreate defining historical periods, specific events and relevant characters in the History of Mexico can be read as an example of what is called texts of cultural memory. A cultural memory text is a narrative that bonds the concepts of history, identity and belonging, and that is realized and disseminated through symbolic systems such as written documents, visual images, and dramatic representation. Cultural memory, through its narratives of historical fiction, emphasizes memory processes (historiography) and its implications and artifacts (cultural memory) mainly through the medial frameworks of remembering, which are the medial process by which memories (narratives, documents) participate in public knowledge and become collective memory. Historical fiction on television not only creates a portrayal of the past related to the real lives of protagonists, but it also significantly contributes to understand the past as an ever-evolving entity that highlights both, the necessary connection with the present as part of a developing sense of collective identity and belonging, as well as the relevance of the medium in which the past is represented and that ultimately supports the process of historical awareness. Through the emblematic recreation of national heroines and historical events in the unique context of historical drama on television, those texts constitute a venue where concepts of the past and the traditionally established ideas about history and heroines are highlighted, questioned and transformed.

Keywords: cultural memory, historical fiction, Mexico, television, women directors

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Authors: Robinson, E. L., Freeman, E. E.

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Over the last few decades, the social movement of involved fatherhood has stimulated a research focus on fathers, leading to an increase in the body of evidence into the paternal contributions to child development. Past research has suggested that rough-and-tumble play, which involves wrestling, chasing and tumbling, is the preferred play type of western fathers. This type of play remains underutilized and underrepresented in child developmental research as it’s perceived to be dangerous or too aggressive. The limited research available has shown a relationship between high quality rough-and-tumble play interactions, lower childhood aggression and improved child emotional regulation. The aim of this study was to examine father-child rough-and-tumble play and assess the impact on cognitive development in children aged 4-7 years. Father-child dyads completed a 10-minute rough-and-tumble play interaction, which consisted of 2 games, at the University of Newcastle. Children then completed the Wechsler Preschool & Primary Scale of Intelligence - Fourth Edition Australian and New Zealand Standardized Edition (WPPSI-IV A&NZ). Fathers reported on their involvement in various caregiving activities and on their child’s development. Analyses revealed that fathers-child play quality was positively related to working memory outcomes in children. Furthermore, the amount of rough-and-tumble play father and child did together on a regular basis was also related to working memory outcomes. While father-child play interactions remain an understudied area of research, this study outlines the importance of examining the paternal play role in children’s cognitive development.

Keywords: children, development, father, executive function

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Authors: Francesco Scarpati

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Because of their long history, ranging from ancient times to the present day, European cities feature many historical layers, whose single identities are represented by traces surviving in the urban design. However, urban transformations, in particular, the ones that have been produced by the property speculation phenomena of the 20th century, often compromised the readability of these traces, resulting in a loss of the historical identities of the single layers. The purpose of this research is, therefore, a reflection on the theme of the reenactment of the historical memory in the stratified European contexts and on how contemporary architecture can help to reveal past signs of the cities. The research work starts from an analysis of a series of emblematic examples that have already provided an original solution to the described problem, going from the architectural detail scale to the urban and landscape scale. The results of these analyses are then applied to the case study of the city of Naples, as an emblematic example of a stratified city, with an ancient Greek origin; a city where it is possible to read most of the traces of its transformations. Particular consideration is given to the trace of the medieval walls of the city, which a long time ago clearly divided the city itself from the outer fields, and that is no longer readable at the current time. Finally, solutions and methods of intervention are proposed to ensure that the trace of the walls, read as a boundary, can be revealed through the contemporary project.

Keywords: contemporary project, historic memory, historic urban contexts, medieval walls, naples, stratified cities, urban traces

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Authors: Mohamed Omar

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Steel bracing members are widely used in steel structures to reduce lateral displacement and dissipate energy during earthquake motions. Concentric steel bracing provide an excellent approach for strengthening and stiffening steel buildings. Using these braces the designer can hardly adjust the stiffness together with ductility as needed because of buckling of braces in compression. In this study the use of SMA bracing and steel bracing (Mega) utilized in steel frames are investigated. The effectiveness of these two systems in rehabilitating a mid-rise eight-storey steel frames were examined using time-history nonlinear analysis utilizing Seismo-Struct software. Results show that both systems improve the strength and stiffness of the original structure but due to excellent behavior of SMA in nonlinear phase and under compressive forces this system shows much better performance than the rehabilitation system of Mega bracing.

Keywords: finite element analysis, seismic response, shapes memory alloy, steel frame, mega bracing

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Authors: Kenji Gwee

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In Singapore, the death penalty remains in active use for murder and drug trafficking of controlled drugs such as heroin. As such, the psychological assessment of defendants can often be of high stakes. The Test of Memory Malingering (TOMM) is employed by government psychologists to determine the degree of effort invested by defendants, which in turn inform on the veracity of overall psychological findings that can invariably determine the life and death of defendants. The purpose of this study was to find out if defendants facing the death penalty were more likely to invest less effort during psychological assessment (to fake bad in hopes of escaping the death sentence) compared to defendants facing lesser penalties. An archival search of all forensic cases assessed in 2012-2013 by Singapore’s designated forensic psychiatric facility yielded 186 defendants’ TOMM scores. Offence severity, coded into 6 rank-ordered categories, was analyzed in a one-way ANOVA with TOMM score as the dependent variable. There was a statistically significant difference (F(5,87) = 2.473, p = 0.038). A Tukey post-hoc test with Bonferroni correction revealed that defendants facing lower charges (Theft, shoplifting, criminal breach of trust) invested less test-taking effort (TOMM = 37.4±12.3, p = 0.033) compared to those facing the death penalty (TOMM = 46.2±8.1). The surprising finding that those facing death penalties actually invested more test taking effort than those facing relatively minor charges could be due to higher levels of cooperation when faced with death. Alternatively, other legal avenues to escape the death sentence may have been preferred over the mitigatory chance of a psychiatric defence.

Keywords: capital sentencing, offence severity, Singapore, Test of Memory Malingering

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Authors: Maha Sliti, Walid Abdallah, Noureddine Boudriga

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In the frame of this work, we present an optical multicasting approach based on optical code-words. Our approach associates, in the edge node, an optical code-word to a group multicast address. In the core node, a set of tunable decoders are used to send a traffic data to multiple destinations based on the received code-word. The use of code-words, which correspond to the combination of an input port and a set of output ports, allows the implementation of an optical switching matrix. At the reception of a burst, it will be delayed in an optical memory. And, the received optical code-word is split to a set of tunable optical decoders. When it matches a configured code-word, the delayed burst is switched to a set of output ports.

Keywords: optical multicast, optical burst switching networks, optical code-words, tunable decoder, virtual optical memory

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Authors: Eric Tardif, Nicolas Meylan

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Recent studies suggest that the consolidation of episodic memory is better achieved through repeated retrieval than with the use of concept mapping or repeated study. Although such laboratory results highly appeal to educationalists, it remains to be shown whether they can be directly used in a classroom setting. Forty-five college students (42 girls; mean age 16.1 y/o) were asked to remember pairs of biology-related words (e.g. mitochondria-energy) in two configurations. The first configuration consisted of a three-minute study of pairs of words followed by a final one-minute test in which the first word of a pair was shown and the subject asked to write down the second associated word. This procedure was repeated three times. The second configuration consisted of a one-minute study of a list of pairs of words, which was immediately followed by a one-minute test. This procedure was repeated 6 times. Subjects filled out a small questionnaire assessing their general mood, level of fatigue, stress and motivation to do the exercise. One week later, subjects were given a final test using the same words. A total of 8 lists of words were studied and tested during the semester. Results showed that subjects recalled more correct words when using the second configuration, both within the study period and one week later, confirming laboratory findings. However, the general performance (mean items recalled) as well as the motivation to do the exercise gradually decreased during the semester. Motivation was positively correlated with performance (r=0.77, p<0.05). The results suggest that laboratory findings may provide some applications in education but other variables inherent to the classroom setting must also be considered.

Keywords: long-term, episodic memory, consolidation, retrieval, school setting

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