Search results for: memory recall
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1368

Search results for: memory recall

678 To Investigate the Effects of Potassium Ion Doping and Oxygen Vacancies in Thin-Film Transistors of Gallium Oxide-Indium Oxide on Their Electrical

Authors: Peihao Huang, Chun Zhao

Abstract:

Thin-film transistors(TFTs) have the advantages of low power consumption, short reaction time, and have high research value in the field of semiconductors, based on this reason, people have focused on gallium oxide-indium oxide thin-film transistors, a relatively common thin-film transistor, elaborated and analyzed his production process, "aqueous solution method", explained the purpose of each step of operation, and finally explored the influence of potassium ions doped in the channel layer on the electrical properties of the device, as well as the effect of oxygen vacancies on its switching ratio and memory, and summarized the conclusions.

Keywords: aqueous solution, oxygen vacancies, switch ratio, thin-film transistor(TFT)

Procedia PDF Downloads 105
677 The Rehabilitation of Drug Addiction by Thai Indigenous Knowledge: A Case Study of Thamkrabok Monastery

Authors: Wanwimon Mekwimon

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Drug addiction is a serious problem in Thailand which has occurred continuously and repeatedly and enormously impacting health and economy of drug users. The indigenous wisdom and folk medicine is an attractive alternative choice, especially in detoxification and rehabilitation period. There are two objectives: First is to study about rehabilitation process and the curing for drug eaters and 2nd is to investigate the effectiveness of the curing and rehabilitation process by indigenous wisdom at Tamkrabok monastery, Pra-Puttabat district, Saraburi province. The main informants are 10 curers, 15 patients and 17 after-1-year rehabilitators. In the process, the semi-structured questionnaire is administered, the data are analyzed and proved by triangulation. The curing and rehabilitation process which use herbal remedies has a period of 15 days (5 days for detoxification and 10 days for recovery period) and the occupational training and self-consciousness awakening were delivered. The follow-up process includes twice-a-month recall for 6 months, follow-up letters and in depth interview with their families. The outcome of 1 year post-treatment was 94% (16 from 17). There are many reasons for not relapsing: the recovering patients have drawn on their inner strength, self-awareness and coping skill as well as their family and social support while rehabilitation process which includes difficulties in contacting with family members. They can void themselves from high risk situations to relapse. Recommendations: The follow-up system should be improved for continuous quality improvement, there should be the qualification standard for herbal remedies and the comparison among rehabilitation process of Tamkrabok and another methods are to be guideline for the further development.

Keywords: rehabilitation, drug addiction, Thai indigenous knowledge, herbal remedies

Procedia PDF Downloads 241
676 A Recommender System Fusing Collaborative Filtering and User’s Review Mining

Authors: Seulbi Choi, Hyunchul Ahn

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Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.

Keywords: Recommender system, Collaborative filtering, Text mining, Review mining

Procedia PDF Downloads 346
675 Analyzing Large Scale Recurrent Event Data with a Divide-And-Conquer Approach

Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

Procedia PDF Downloads 159
674 Mask-Prompt-Rerank: An Unsupervised Method for Text Sentiment Transfer

Authors: Yufen Qin

Abstract:

Text sentiment transfer is an important branch of text style transfer. The goal is to generate text with another sentiment attribute based on a text with a specific sentiment attribute while maintaining the content and semantic information unrelated to sentiment unchanged in the process. There are currently two main challenges in this field: no parallel corpus and text attribute entanglement. In response to the above problems, this paper proposed a novel solution: Mask-Prompt-Rerank. Use the method of masking the sentiment words and then using prompt regeneration to transfer the sentence sentiment. Experiments on two sentiment benchmark datasets and one formality transfer benchmark dataset show that this approach makes the performance of small pre-trained language models comparable to that of the most advanced large models, while consuming two orders of magnitude less computing and memory.

Keywords: language model, natural language processing, prompt, text sentiment transfer

Procedia PDF Downloads 75
673 Improved Impossible Differential Cryptanalysis of Midori64

Authors: Zhan Chen, Wenquan Bi, Xiaoyun Wang

Abstract:

The Midori family of light weight block cipher is proposed in ASIACRYPT2015. It has attracted the attention of numerous cryptanalysts. There are two versions of Midori: Midori64 which takes a 64-bit block size and Midori128 the size of which is 128-bit. In this paper an improved 10-round impossible differential attack on Midori64 is proposed. Pre-whitening keys are considered in this attack. A better impossible differential path is used to reduce time complexity by decreasing the number of key bits guessed. A hash table is built in the pre-computation phase to reduce computational complexity. Partial abort technique is used in the key seiving phase. The attack requires 259 chosen plaintexts, 214.58 blocks of memory and 268.83 10-round Midori64 encryptions.

Keywords: cryptanalysis, impossible differential, light weight block cipher, Midori

Procedia PDF Downloads 343
672 Stock Price Prediction Using Time Series Algorithms

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 135
671 Introduction to Buddhist Archaeology of Haryana, India

Authors: Chander Shekhar, Manoj Kumar

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The present research paper is based on the explorations and excavations of Buddhist sites of the Indian state Haryana. It is a small state in north India. Earlier it was part of greater Punjab. Haryana has a very rich ancient history right from the Stone Age. It is known as the cradle of civilization. During the Buddha period, Haryana was very prosperous. Buddha also visited this region during the travel of the northwest province of British India. In this research work, the authors describe the Buddhist trail in Haryana and the tangible heritage of Buddhism, which were built in the respect and memory of the Buddha's journey like Stupa, Monasteries, Pillar, sculptures, etc. Several stupas like Chaneti Stupa, Thanesar Stupa, Agroha stupa, Adibadri, Katrawali, Assandh Stupa, and many monasteries were come into light during the excavation and exploration in Haryana as well as a lot of Buddhist sculptures also found.

Keywords: archaeology, Buddhism, exploration, excavations, stupa

Procedia PDF Downloads 239
670 Synthesis of Metal Curcumin Complexes with Iron(III) and Manganese(II): The Effects on Alzheimer's Disease

Authors: Emel Yildiz, Nurcan Biçer, Fazilet Aksu, Arash Alizadeh Yegani

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Plants provide the wealth of bioactive compounds, which exert a substantial strategy for the treatment of neurological disorders such as Alzheimer's disease. Recently, a lot of studies have explored the medicinal properties of curcumin, including antitumoral, antimicrobial, anti-inflammatory, antioxidant, antiviral, and anti-Alzheimer's disease effects. Metal complexes of curcumin (1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione) were synthesized with Mn(II) and Fe(III). The structures of synthesized metal complexes have been characterized by using spectroscopic and analytic methods such as elemental analysis, magnetic susceptibility, FT-IR, AAS, TG and argentometric titration. It was determined that the complexes have octahedral geometry. The effects of the metal complexes on the disorder of memory, which is an important symptom of Alzheimer's Disease were studied on lab rats with Plus-Maze Tests at Behavioral Pharmacology Laboratory.

Keywords: curcumin, Mn(II), Fe(III), Alzheimer disease, beta amyloid 25-35

Procedia PDF Downloads 299
669 Harrison’s Stolen: Addressing Aboriginal and Indigenous Islanders Human Rights

Authors: M. Shukry

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According to the United Nations Declaration of Human Rights in 1948, every human being is entitled to rights in life that should be respected by others and protected by the state and community. Such rights are inherent regardless of colour, ethnicity, gender, religion or otherwise, and it is expected that all humans alike have the right to live without discrimination of any sort. However, that has not been the case with Aborigines in Australia. Over a long period of time, the governments of the State and the Territories and the Australian Commonwealth denied the Aboriginal and Indigenous inhabitants of the Torres Strait Islands such rights. Past Australian governments set policies and laws that enabled them to forcefully remove Indigenous children from their parents, which resulted in creating lost generations living the trauma of the loss of cultural identity, alienation and even their own selfhood. Intending to reduce that population of natives and their Aboriginal culture while, on the other hand, assimilate them into mainstream society, they gave themselves the right to remove them from their families with no hope of return. That practice has led to tragic consequences due to the trauma that has affected those children, an experience that is depicted by Jane Harrison in her play Stolen. The drama is the outcome of a six-year project on lost children and which was first performed in 1997 in Melbourne. Five actors only appear on the stage, playing the role of all the different characters, whether the main protagonists or the remaining cast, present or non-present ones as voices. The play outlines the life of five children who have been taken from their parents at an early age, entailing a disastrous negative impact that differs from one to the other. Unknown to each other, what connects between them is being put in a children’s home. The purpose of this paper is to analyse the play’s text in light of the 1948 Declaration of Human Rights, using it as a lens that reflects the atrocities practiced against the Aborigines. It highlights how such practices formed an outrageous violation of those natives’ rights as human beings. Harrison’s dramatic technique in conveying the children’s experiences is through a non-linear structure, fluctuating between past and present that are linked together within each of the five characters, reflecting their suffering and pain to create an emotional link between them and the audience. Her dramatic handling of the issue by fusing tragedy with humour as well as symbolism is a successful technique in revealing the traumatic memory of those children and their present life. The play has made a difference in commencing to address the problem of the right of all children to be with their families, which renders the real meaning of having a home and an identity as people.

Keywords: aboriginal, audience, Australia, children, culture, drama, home, human rights, identity, Indigenous, Jane Harrison, memory, scenic effects, setting, stage, stage directions, Stolen, trauma

Procedia PDF Downloads 297
668 Prediction Modeling of Alzheimer’s Disease and Its Prodromal Stages from Multimodal Data with Missing Values

Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

Procedia PDF Downloads 184
667 Low Power CNFET SRAM Design

Authors: Pejman Hosseiniun, Rose Shayeghi, Iman Rahbari, Mohamad Reza Kalhor

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CNFET has emerged as an alternative material to silicon for high performance, high stability and low power SRAM design in recent years. SRAM functions as cache memory in computers and many portable devices. In this paper, a new SRAM cell design based on CNFET technology is proposed. The proposed SRAM cell design for CNFET is compared with SRAM cell designs implemented with the conventional CMOS and FinFET in terms of speed, power consumption, stability, and leakage current. The HSPICE simulation and analysis show that the dynamic power consumption of the proposed 8T CNFET SRAM cell’s is reduced about 48% and the SNM is widened up to 56% compared to the conventional CMOS SRAM structure at the expense of 2% leakage power and 3% write delay increase.

Keywords: SRAM cell, CNFET, low power, HSPICE

Procedia PDF Downloads 402
666 The Impact of Artificial Intelligence on Marketing Principles and Targets

Authors: Felib Ayman Shawky Salem

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Experiential marketing means an unforgettable experience that remains deeply anchored in the customer's memory. Furthermore, customer satisfaction is defined as the emotional response to the experiences provided that relate to specific products or services purchased. Therefore, experiential marketing activities can influence the level of customer satisfaction and loyalty. In this context, the study aims to examine the relationship between experiential marketing, customer satisfaction and loyalty of beauty products in Konya. The results of this study showed that experiential marketing is an important indicator of customer satisfaction and loyalty and that experiential marketing has a significant positive impact on customer satisfaction and loyalty.

Keywords: sponsorship, marketing communication theories, marketing communication tools internet, marketing, tourism, tourism management corporate responsibility, employee organizational performance, internal marketing, internal customer experiential marketing, customer satisfaction, customer loyalty, social sciences.

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665 The Impact on the Network Deflectometry

Authors: Djamel–Eddine Yassine Boutiba

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In this present memory, we present the various impacts deflectometer leading to the sizing by strengthening of existing roadways. It reminds that the road network in Algeria plays a major role with regard to drainage in major strategic areas and especially in the fringe northern Algeria. Heavy traffic passing through the northern fringe (between 25% and 30% heavy vehicles) causes substantial degradations at both the surface layer and base layer. The work on site by means within the laboratory CTTP such as deflectographe Lacroix, allowed us to record a large number of deflection localized bending on RN19A (Carrefour CW73-Ain- Merane), whose analysis of the results led us to opt for a building throughout the band's project . By the recorder against HWD (Heavy Weight déflectometer) allowed us to learn about the behavior of the pavement on the banks. In addition, the Software Alize III has been essential in the verification of the increase in the thickness dimensioned.

Keywords: capacity, deflection, deflectograph lacroix, degradation, hwd

Procedia PDF Downloads 278
664 Feature Selection of Personal Authentication Based on EEG Signal for K-Means Cluster Analysis Using Silhouettes Score

Authors: Jianfeng Hu

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Personal authentication based on electroencephalography (EEG) signals is one of the important field for the biometric technology. More and more researchers have used EEG signals as data source for biometric. However, there are some disadvantages for biometrics based on EEG signals. The proposed method employs entropy measures for feature extraction from EEG signals. Four type of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE) and spectral entropy (PE), were deployed as feature set. In a silhouettes calculation, the distance from each data point in a cluster to all another point within the same cluster and to all other data points in the closest cluster are determined. Thus silhouettes provide a measure of how well a data point was classified when it was assigned to a cluster and the separation between them. This feature renders silhouettes potentially well suited for assessing cluster quality in personal authentication methods. In this study, “silhouettes scores” was used for assessing the cluster quality of k-means clustering algorithm is well suited for comparing the performance of each EEG dataset. The main goals of this study are: (1) to represent each target as a tuple of multiple feature sets, (2) to assign a suitable measure to each feature set, (3) to combine different feature sets, (4) to determine the optimal feature weighting. Using precision/recall evaluations, the effectiveness of feature weighting in clustering was analyzed. EEG data from 22 subjects were collected. Results showed that: (1) It is possible to use fewer electrodes (3-4) for personal authentication. (2) There was the difference between each electrode for personal authentication (p<0.01). (3) There is no significant difference for authentication performance among feature sets (except feature PE). Conclusion: The combination of k-means clustering algorithm and silhouette approach proved to be an accurate method for personal authentication based on EEG signals.

Keywords: personal authentication, K-mean clustering, electroencephalogram, EEG, silhouettes

Procedia PDF Downloads 278
663 Investigating Chinese Students' Engagement with Teacher Feedback: Multiple Case Studies in a UK University

Authors: Fangfei Li

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This research was conducted to explore how Chinese overseas students, who rarely received teacher feedback during their undergraduate studies in China, engaged in a different feedback provision context in the UK universities. In particular, this research provides some insights into Chinese students’ perspectives on how they made sense of the teacher feedback they obtained and how they took it on board in their assignments. Research questions in this study are 1) What are Chinese overseas students’ perceptions of teacher feedback on courses in UK higher education? 2) How do they respond to the teacher feedback they obtained? 3) What factors might influence their engagement with teacher feedback? Multiple case studies of five Chinese overseas students in a UK university have been carried out to address the research questions. The main data collection instruments are various types of semi-structured interviews, consisting of background interviews, scenario-based activities, stimulated recall sessions and retrospective interviews. Research findings indicate that student engagement with teacher feedback is a complex learning process incorporating several stages: from initial teacher input to ultimate transformational learning. Apart from students interpreting teachers’ comments/suggestions by themselves, students’ understandings of and responses to teacher feedback could also be influenced by pre-submission guidance, peer discussion, use of exemplars and post-submission discussion with teachers. These are key factors influencing students to make use of teacher feedback. Findings also reveal that the level of students’ reflections on tutor feedback influences the quality of their assignments and even their future learning. To sum up, this paper will discuss the current concepts of teacher feedback in existing studies and research findings of this study from which reconceptualization of teacher feedback has occurred.

Keywords: Chinese students, student engagement, teacher feedback, the UK higher education

Procedia PDF Downloads 342
662 Exploring Influence Range of Tainan City Using Electronic Toll Collection Big Data

Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization

Procedia PDF Downloads 275
661 Dietary Habit and Anthropometric Status in Hypertensive Patients Compared to Normotensive Participants in the North of Iran

Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahbobeh Gholipour

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Hypertension is one of the important reasons of morbidity and mortality in countries, including Iran. It has been shown that hypertension is a consequence of the interaction of genetics and environment. Nutrients have important roles in the controlling of blood pressure. We assessed dietary habit and anthropometric status in patients with hypertension in the north of Iran, and that have special dietary habit and according to their culture. This study was conducted on 127 patients with newly recognized hypertension and the 120 normotensive participants. Anthropometric status was measured and demographic characteristics, and medical condition were collected by valid questionnaires and dietary habit assessment was assessed with 3-day food recall (two weekdays and one weekend). The mean age of participants was 58 ± 6.7 years. The mean level of energy intake, saturated fat, vitamin D, potassium, zinc, dietary fiber, vitamin C, calcium, phosphorus, copper and magnesium was significantly lower in the hypertensive group compared to the control (p < 0.05). After adjusting for energy intake, positive association was observe between hypertension and some dietary nutrients including; Cholesterol [OR: 1.1, P: 0.001, B: 0.06], fiber [OR: 1.6, P: 0.001, B: 1.8], vitamin D [OR: 2.6, P: 0.006, B: 0.9] and zinc [OR: 1.4, P: 0.006, B: 0.3] intake. Logistic regression analysis showed that there was not significant association between hypertension, weight and waist circumference. In our study, the mean intake of some nutrients was lower in the hypertensive individuals compared to the normotensive individual. Health training about suitable dietary habits and easier access to vitamin D supplementation in patients with hypertension are cost-effective tools to improve outcomes in Iran.

Keywords: hypertension, north of Iran, dietary intake, weight

Procedia PDF Downloads 176
660 Image Compression Using Block Power Method for SVD Decomposition

Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

Procedia PDF Downloads 379
659 Investigation of the Effects of Visually Disabled and Typical Development Students on Their Multiple Intelligence by Applying Abacus and Right Brain Training

Authors: Sidika Di̇lşad Kaya, Ahmet Seli̇m Kaya, Ibrahi̇m Eri̇k, Havva Yaldiz, Yalçin Kaya

Abstract:

The aim of this study was to reveal the effects of right brain development on reading, comprehension, learning and concentration levels and rapid processing skills in students with low vision and students with standard development, and to explore the effects of right and left brain integration on students' academic success and the permanence of the learned knowledge. A total of 68 students with a mean age of 10.01±0.12 were included in the study, 58 of them with standard development, 9 partially visually impaired and 1 totally visually disabled student. The student with a total visual impairment could not participate in the reading speed test due to her total visual impairment. The following data were measured in the participant students before the project; Reading speed measurement in 1 minute, Reading comprehension questions, Burdon attention test, 50 questions of math quiz timed with a stopwatch. Participants were trained for 3 weeks, 5 days a week, for a total of two hours a day. In this study, right-brain developing exercises were carried out with the use of an abacus, and it was aimed to develop both mathematical and attention of students with questions prepared with numerical data taken from fairy tale activities. Among these problems, the study was supported with multiple-choice, 5W (what, where, who, why, when?), 1H (how?) questions along with true-false and fill-in-the-blank activities. By using memory cards, students' short-term memories were strengthened, photographic memory studies were conducted and their visual intelligence was supported. Auditory intelligence was supported by aiming to make calculations by using the abacus in the minds of the students with the numbers given aurally. When calculating the numbers by touching the real abacus, the development of students' tactile intelligence is enhanced. Research findings were analyzed in SPSS program, Kolmogorov Smirnov test was used for normality analysis. Since the variables did not show normal distribution, Wilcoxon test, one of the non-parametric tests, was used to compare the dependent groups. Statistical significance level was accepted as 0.05. The reading speed of the participants was 83.54±33.03 in the pre-test and 116.25±38.49 in the post-test. Narration pre-test 69.71±25.04 post-test 97.06±6.70; BURDON pretest 84.46±14.35 posttest 95.75±5.67; rapid math processing skills pretest 90.65±10.93, posttest 98.18±2.63 (P<0.05). It was determined that the pre-test and post-test averages of students with typical development and students with low vision were also significant for all four values (p<0.05). As a result of the data obtained from the participants, it is seen that the study was effective in terms of measurement parameters, and the findings were statistically significant. Therefore, it is recommended to use the method widely.

Keywords: Abacus, reading speed, multiple intelligences, right brain training, visually impaired

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658 Design and Implementation of 2D Mesh Network on Chip Using VHDL

Authors: Boudjedra Abderrahim, Toumi Salah, Boutalbi Mostefa, Frihi Mohammed

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Nowadays, using the advancement of technology in semiconductor device fabrication, many transistors can be integrated to a single chip (VLSI). Although the growth chip density potentially eases systems-on-chip (SoCs) integrating thousands of processing element (PE) such as memory, processor, interfaces cores, system complexity, high-performance interconnect and scalable on-chip communication architecture become most challenges for many digital and embedded system designers. Networks-on-chip (NoCs) becomes a new paradigm that makes possible integrating heterogeneous devices and allows many communication constraints and performances. In this paper, we are interested for good performance and low area for implementation and a behavioral modeling of network on chip mesh topology design using VHDL hardware description language with performance evaluation and FPGA implementation results.

Keywords: design, implementation, communication system, network on chip, VHDL

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657 A Comparison of YOLO Family for Apple Detection and Counting in Orchards

Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

Procedia PDF Downloads 193
656 A New Perspective in Cervical Dystonia: Neurocognitive Impairment

Authors: Yesim Sucullu Karadag, Pinar Kurt, Sule Bilen, Nese Subutay Oztekin, Fikri Ak

Abstract:

Background: Primary cervical dystonia is thought to be a purely motor disorder. But recent studies revealed that patients with dystonia had additional non-motor features. Sensory and psychiatric disturbances could be included into the non-motor spectrum of dystonia. The Basal Ganglia receive inputs from all cortical areas and throughout the thalamus project to several cortical areas, thus participating to circuits that have been linked to motor as well as sensory, emotional and cognitive functions. However, there are limited studies indicating cognitive impairment in patients with cervical dystonia. More evidence is required regarding neurocognitive functioning in these patients. Objective: This study is aimed to investigate neurocognitive profile of cervical dystonia patients in comparison to healthy controls (HC) by employing a detailed set of neuropsychological tests in addition to self-reported instruments. Methods: Totally 29 (M/F: 7/22) cervical dystonia patients and 30 HC (M/F: 10/20) were included into the study. Exclusion criteria were depression and not given informed consent. Standard demographic, educational data and clinical reports (disease duration, disability index) were recorded for all patients. After a careful neurological evaluation, all subjects were given a comprehensive battery of neuropsychological tests: Self report of neuropsychological condition (by visual analogue scale-VAS, 0-100), RAVLT, STROOP, PASAT, TMT, SDMT, JLOT, DST, COWAT, ACTT, and FST. Patients and HC were compared regarding demographic, clinical features and neurocognitive tests. Also correlation between disease duration, disability index and self report -VAS were assessed. Results: There was no difference between patients and HCs regarding socio-demographic variables such as age, gender and years of education (p levels were 0.36, 0.436, 0.869; respectively). All of the patients were assessed at the peak of botulinum toxine effect and they were not taking an anticholinergic agent or benzodiazepine. Dystonia patients had significantly impaired verbal learning and memory (RAVLT, p<0.001), divided attention and working memory (ACTT, p<0.001), attention speed (TMT-A and B, p=0.008, 0.050), executive functions (PASAT, p<0.001; SDMT, p= 0.001; FST, p<0.001), verbal attention (DST, p=0.001), verbal fluency (COWAT, p<0.001), visio-spatial processing (JLOT, p<0.001) in comparison to healthy controls. But focused attention (STROOP-spontaneous correction) was not different between two groups (p>0.05). No relationship was found regarding disease duration and disability index with any neurocognitive tests. Conclusions: Our study showed that neurocognitive functions of dystonia patients were worse than control group with the similar age, sex, and education independently clinical expression like disease duration and disability index. This situation may be the result of possible cortical and subcortical changes in dystonia patients. Advanced neuroimaging techniques might be helpful to explain these changes in cervical dystonia patients.

Keywords: cervical dystonia, neurocognitive impairment, neuropsychological test, dystonia disability index

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655 A Deep Learning Approach to Detect Complete Safety Equipment for Construction Workers Based on YOLOv7

Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

Abstract:

In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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654 Developing a Place-Name Gazetteer for Singapore by Mining Historical Planning Archives and Selective Crowd-Sourcing

Authors: Kevin F. Hsu, Alvin Chua, Sarah X. Lin

Abstract:

As a multilingual society, Singaporean names for different parts of the city have changed over time. Residents included Indigenous Malays, dialect-speakers from China, European settler-colonists, and Tamil-speakers from South India. Each group would name locations in their own languages. Today, as ancestral tongues are increasingly supplanted by English, contemporary Singaporeans’ understanding of once-common place names is disappearing. After demolition or redevelopment, some urban places will only exist in archival records or in human memory. United Nations conferences on the standardization of geographic names have called attention to how place names relate to identity, well-being, and a sense of belonging. The Singapore Place-Naming Project responds to these imperatives by capturing past and present place names through digitizing historical maps, mining archival records, and applying selective crowd-sourcing to trace the evolution of place names throughout the city. The project ensures that both formal and vernacular geographical names remain accessible to historians, city planners, and the public. The project is compiling a gazetteer, a geospatial archive of placenames, with streets, buildings, landmarks, and other points of interest (POI) appearing in the historic maps and planning documents of Singapore, currently held by the National Archives of Singapore, the National Library Board, university departments, and the Urban Redevelopment Authority. To create a spatial layer of information, the project links each place name to either a geo-referenced point, line segment, or polygon, along with the original source material in which the name appears. This record is supplemented by crowd-sourced contributions from civil service officers and heritage specialists, drawing from their collective memory to (1) define geospatial boundaries of historic places that appear in past documents, but maybe unfamiliar to users today, and (2) identify and record vernacular place names not captured in formal planning documents. An intuitive interface allows participants to demarcate feature classes, vernacular phrasings, time periods, and other knowledge related to historical or forgotten spaces. Participants are stratified into age bands and ethnicity to improve representativeness. Future iterations could allow additional public contributions. Names reveal meanings that communities assign to each place. While existing historical maps of Singapore allow users to toggle between present-day and historical raster files, this project goes a step further by adding layers of social understanding and planning documents. Tracking place names illuminates linguistic, cultural, commercial, and demographic shifts in Singapore, in the context of transformations of the urban environment. The project also demonstrates how a moderated, selectively crowd-sourced effort can solicit useful geospatial data at scale, sourced from different generations, and at higher granularity than traditional surveys, while mitigating negative impacts of unmoderated crowd-sourcing. Stakeholder agencies believe the project will achieve several objectives, including Supporting heritage conservation and public education; Safeguarding intangible cultural heritage; Providing historical context for street, place or development-renaming requests; Enhancing place-making with deeper historical knowledge; Facilitating emergency and social services by tagging legal addresses to vernacular place names; Encouraging public engagement with heritage by eliciting multi-stakeholder input.

Keywords: collective memory, crowd-sourced, digital heritage, geospatial, geographical names, linguistic heritage, place-naming, Singapore, Southeast Asia

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653 Performance Analysis and Optimization for Diagonal Sparse Matrix-Vector Multiplication on Machine Learning Unit

Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

Procedia PDF Downloads 127
652 An Initial Evaluation of Newly Proposed Biomarker of Zinc Status in Humans: The Erythrocyte Linoleic Acid: Dihomo-γ-Linolenic Acid (LA:DGLA) Ratio

Authors: Marija Knez, James C.R. Stangoulis, Manja Zec, Zoran Pavlovic, Jasmina D. Martacic, Mirjana Gurinovic, Maria Glibetic

Abstract:

Background: Zinc is an essential micronutrient for humans with important physiological functions. A sensitive and specific biomarker for assessing Zn status is still needed. Objective: The major aim of this study was to examine if the changes in the content of plasma phospholipid LA, DGLA and LA: DGLA ratio can be used to efficiently predict the dietary Zn intake and plasma Zn status of humans. Methods: The study was performed on apparently healthy human volunteers. The dietary Zn intake was assessed using 24h recall questionnaires. Plasma phospholipid fatty acid analysis was done by gas chromatography and plasma analysis of minerals by atomic absorption spectrometry. Biochemical, anthropometrical and hematological parameters were assessed. Results: No significant relationship was found between the dietary and plasma zinc status (r=0.07; p=0.6). There is a statistically significant correlation between DGLA and plasma Zn (r=0.39, p=0.00). No relationship was observed between the linoleic acid and plasma Zn, while there was a significant negative correlation between LA: DGLA ratio and plasma Zn status (r=-0.35, p=0.01). Similarly, there were statistically significant difference in DGLA status (p=0.004) and LA: DGLA ratio (p=0.042) between the Zn formed groups. Conclusions: This study is an initial step in evaluating LA: DGLA ratio as a biomarker of Zn status in humans. The results are encouraging as they show that concentration of DGLA is decreased and LA: DGLA ratio increased in people with lower dietary Zn intake. However, additional studies are needed to fully examine the sensitivity of this biomarker.

Keywords: dietary Zn intake Zinc, fatty acid composition, LA: DGLA, healthy population, plasma Zn status, Zn biomarker

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651 Optimization Design of Single Phase Inverter Connected to the Grid

Authors: Linda Hassaine, Abdelhamid Mraoui, Mohamed Rida Bengourina

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In grid-connected photovoltaic systems, significant improvements can be carried out in the design and implementation of inverters: reduction of harmonic distortion, elimination of the DC component injected into the grid and the proposed control. This paper proposes a control strategy based on PWM switching patterns for an inverter for the photovoltaic system connected to the grid in order to control the injected current. The current injected must be sinusoidal with reduced harmonic distortion. An additional filter is designed to reduce high-order harmonics on the output side. This strategy exhibits the advantages: Simplicity, reduction of harmonics, the size of the line filter, reduction of the memory requirements and power calculation for the control.

Keywords: control, inverters, LCL filter, grid-connected photovoltaic system

Procedia PDF Downloads 319
650 The Associations between Self-Determined Motivation and Physical Activity in Patients with Coronary Heart Disease

Authors: I. Hua Chu, Hsiang-Chi Yu, Hsuan Su

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Purpose: To examine the associations between self-determined motivation and physical activity in patients with coronary heart disease (CHD) in a longitudinal study. Methods: Patients with CHD were recruited for this study. Their motivations for exercise were measured by the Behavioral Regulation in Exercise Questionnaire-2 (BREQ-2). Physical activity was assessed using the 7-day physical activity recall questionnaire. Duration and energy expenditure of moderate to vigorous physical activity (MVPA) were used in data analysis. All outcome measures were assessed at baseline and 12 months follow up. Data were analyzed using Pearson correlation analysis and regression analysis. Results: The results of the 45 participants (mean age 60.24 yr; 90.2% male) revealed that there were significant negative correlations between amotivation at baseline and duration (r=-.295, p=.049) and energy expenditure (r=-.300, p=.045) of MVPA at 12 months. In contrast, there were significant positive correlations between calculated relative autonomy index (RAI) at baseline and duration (r=.377, p=.011) and energy expenditure (r=.382, p=.010) of MVPA at 12 months. There was no significant correlation between other subscales of the BREQ-2 and duration or energy expenditure of MVPA. Regression analyses revealed that RAI was a significant predictor of duration (p=.011) and energy expenditure (p=.010) of MVPA at 12 months follow-up. Conclusions: These results suggest that the relative degree of self-determined motivation could predict long-term MVPA behaviors in CHD patients. Physical activity interventions are recommended to target enhancing one’s identified and intrinsic motivation to increase the likelihood of physical activity participation in this population.

Keywords: self-determined motivation, physical activity, coronary heart disease, relative autonomy index (RAI)

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649 Chemical vs Visual Perception in Food Choice Ability of Octopus vulgaris (Cuvier, 1797)

Authors: Al Sayed Al Soudy, Valeria Maselli, Gianluca Polese, Anna Di Cosmo

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Cephalopods are considered as a model organism with a rich behavioral repertoire. Sophisticated behaviors were widely studied and described in different species such as Octopus vulgaris, who has evolved the largest and more complex nervous system among invertebrates. In O. vulgaris, cognitive abilities in problem-solving tasks and learning abilities are associated with long-term memory and spatial memory, mediated by highly developed sensory organs. They are equipped with sophisticated eyes, able to discriminate colors even with a single photoreceptor type, vestibular system, ‘lateral line analogue’, primitive ‘hearing’ system and olfactory organs. They can recognize chemical cues either through direct contact with odors sources using suckers or by distance through the olfactory organs. Cephalopods are able to detect widespread waterborne molecules by the olfactory organs. However, many volatile odorant molecules are insoluble or have a very low solubility in water, and must be perceived by direct contact. O. vulgaris, equipped with many chemosensory neurons located in their suckers, exhibits a peculiar behavior that can be provocatively described as 'smell by touch'. The aim of this study is to establish the priority given to chemical vs. visual perception in food choice. Materials and methods: Three different types of food (anchovies, clams, and mussels) were used, and all sessions were recorded with a digital camera. During the acclimatization period, Octopuses were exposed to the three types of food to test their natural food preferences. Later, to verify if food preference is maintained, food was provided in transparent screw-jars with pierced lids to allow both visual and chemical recognition of the food inside. Subsequently, we tested alternatively octopuses with food in sealed transparent screw-jars and food in blind screw-jars with pierced lids. As a control, we used blind sealed jars with the same lid color to verify a random choice among food types. Results and discussion: During the acclimatization period, O. vulgaris shows a higher preference for anchovies (60%) followed by clams (30%), then mussels (10%). After acclimatization, using the transparent and pierced screw jars octopus’s food choices resulted in 50-50 between anchovies and clams, avoiding mussels. Later, guided by just visual sense, with transparent but not pierced jars, their food preferences resulted in 100% anchovies. With pierced but not transparent jars their food preference resulted in 100% anchovies as first food choice, the clams as a second food choice result (33.3%). With no possibility to select food, neither by vision nor by chemoreception, the results were 20% anchovies, 20% clams, and 60% mussels. We conclude that O. vulgaris uses both chemical and visual senses in an integrative way in food choice, but if we exclude one of them, it appears clear that its food preference relies on chemical sense more than on visual perception.

Keywords: food choice, Octopus vulgaris, olfaction, sensory organs, visual sense

Procedia PDF Downloads 215