Search results for: Fraudulent pattern recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4125

Search results for: Fraudulent pattern recognition

3435 Development of a Computer Vision System for the Blind and Visually Impaired Person

Authors: Rodrigo C. Belleza, Jr., Roselyn A. Maaño, Karl Patrick E. Camota, Darwin Kim Q. Bulawan

Abstract:

Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may result from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: algorithms, blind, computer vision, embedded systems, image analysis

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3434 Comparative Study of Amyloidogenic Potential of AgNO3 and Freund's Adjuvant (AF) with That of Vitamin Free Casein, on Spatio-Temporal Pattern of Experimental Amyloidosis in Mice

Authors: Alireza Javed, Keivan Jamshidi

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Reactive amyloidosis is a condition that complicates a long list of chronic inflammation, chronic infectious, malignant, and hereditary disorders. In the present study the potential effects of two amyloidogenic substances: ie. AgNO3 and Freund's Adjuvant (AF) with that of vitamin free casein, on spatio-temporal pattern of experimental amyloidosis in mice, were compared. For this purpose, a total of 40 male Swees mice, obtained from Pasteur Institute Tehran, after being weighted were randomly divided into 4 groups including 2 treatments, 1 control (vitamin free casein) and 1 positive control (normal saline). At the end of 3rd, 5th and 7th weeks of experiment 3 mice were randomly selected and euthnised. Spleen sample of each animal obtained and preserved in 10% neutral buffer formalin. Sample were then processed through different stages of dehydration, clearing and impregnation and finally embedded in paraffin blocks. Sections of 5µm thickness then cut and stained by alkaline Congo red techniques. Spleen weights and the data obtained from the microscopic quantitative analysis did show no significant differences between groups A and B, A and C, and B and C. However, significant differences were observed between groups A and D, B and D, and C and D respectively. It is concluded that two compounds ie; AgNO3 and Freund's Adjuvant have the same potential, as does vitamin free casein have, in spatio – temporal pattern of experimental amyloidosis in mice.

Keywords: amyloidosis, mice, AgNO3, Freund's Adjuvant

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3433 Financial Reporting Quality and International Financial Reporting

Authors: Matthias Nnadi

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Using samples of 250 large listed firms by market capitalization in China and Hong Kong, we conducted empirical test to determine the impact of regulatory environment on reporting quality following IFRS convergence using three financial reporting measures; earning management, timely loss recognition and value relevance. Our results indicate that accounting data are more value relevant for Hong Kong listed firms than the Chinese A-share firms. The empirical results for timely loss recognition further reveal that there is a larger coefficient estimate on bad news earnings, which suggests that Chines A-share firms are more likely to report losses in a timely manner. The results support the evidence that substantial convergence of IFRS can improve financial reporting quality in a regulated environment such as China. This further supports the expectation that IFRS are relevant to China and has positive effect on its accounting practice and quality.

Keywords: reporting, quality, earning, loss, relevance, financial, China, Hong Kong

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3432 Awareness of Turkish Cypriots on Domestic Violence: Exploratory Study of Cultural Influence on Public Health

Authors: Nazif Fuat Turkmen

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Domestic violence is the most common form of violence that risks the health and psychological well-being of victims and its witnesses. Psychology as a scientific field has made contributions in research, exploration, assessment, intervention, and prevention of domestic violence. The present study will be exploring the level of recognition of Turkish Cypriots on domestic violence and their understanding about it in general terms. While discussing the level of awareness of Turkish Cypriots on domestic violence and the effects of this level of awareness on the general well-being of the members of the society, the most common types of domestic violence as well as how Turkish Cypriots recognize and interpret these different types will be explored. The participants consisted of 224 Turkish Cypriots; 48.4% (n= 109) were female, 51.1% (n=115) were male. For the purpose of the study, a 28-item questionnaire was prepared and used for data collection. According to the results, there is a strong relationship between the education level of the respondents and their awareness on domestic violence. The study shows that cultural approaches on child rearing effect people’s recognition of violence in general and awareness on domestic violence in particular.

Keywords: culture, domestic violence, health psychology, public health, Turkish Cypriots, violence

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3431 A Preliminary Analysis of The Effect After Cochlear Implantation in the Unilateral Hearing Loss

Authors: Haiqiao Du, Qian Wang, Shuwei Wang, Jianan Li

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Purpose: The aim is to evaluate the effect of cochlear implantation (CI) in patients with unilateral hearing loss, with a view to providing data support for the selection of therapeutic interventions for patients with single-sided deafness (SSD)/asymmetric hearing loss (AHL) and the broadening of the indications for CI. Methods: The study subjects were patients with unilateral hearing loss who underwent cochlear implantation surgery in our hospital in August 2022 and were willing to cooperate with the test and were divided into 2 groups: SSD group and AHL group. The enrolled patients were followed up for hearing level, tinnitus changes, speech recognition ability, sound source localization ability, and quality of life at five-time points: preoperatively, and 1, 3, 6, and 12 months after postoperative start-up. Results: As of June 30, 2024, a total of nine patients completed follow-up, including four in the SSD group and five in the AHL group. The mean postoperative hearing aid thresholds on the CI side were 31.56 dB HL and 34.75 dB HL in the two groups, respectively. Of the four patients with preoperative tinnitus symptoms (three patients in the SSD group and one patient in the AHL group), all showed a degree of reduction in Tinnitus Handicap Inventory (THI) scores, except for one patient who showed no change. In both the SSD and AHL groups, the sound source localization results (expressed as RMS error values, with smaller values indicating better ability) were 66.87° and 77.41° preoperatively and 29.34° and 54.60° 12 months after postoperative start-up, respectively, which showed that the ability to localize the sound source improved significantly with longer implantation time. The level of speech recognition was assessed by 3 test methods: speech recognition rate of monosyllabic words in a quiet environment and speech recognition rate of different sound source directions at 0° and 90° (implantation side) in a noisy environment. The results of the 3 tests were 99.0%, 72.0%, and 36.0% in the preoperative SSD group and 96.0%, 83.6%, and 73.8% in the AHL group, respectively, whereas they fluctuated in the postoperative period 3 months after start-up, and stabilized at 12 months after start-up to 99.0%, 100.0%, and 100.0% in the SSD group and 99.5%, 96.0%, and 99.0%. Quality of life was subjectively evaluated by three tests: the Speech Spatial Quality of Sound Auditory Scale (SSQ-12), the Quality-of-Life Bilateral Listening Questionnaire (QLBHE), and the Nijmegen Cochlear Implantation Inventory (NCIQ). The results of the SSQ-12 (with a 10-point score out of 10) showed that the scores of preoperative and postoperative 12 months after start-up were 6.35 and 6.46 in the SSD group, while they were 5.61 and 9.83 in the AHL group. The QLBHE scores (100 points out of 100) were 61.0 and 76.0 in the SSD group and 53.4 and 63.7 in the AHL group for the preoperative versus the postoperative 12 months after start-up. Conclusion: Patients with unilateral hearing loss can benefit from cochlear implantation: CI implantation is effective in compensating for the hearing on the affected side and reduces the accompanying tinnitus symptoms; there is a significant improvement in sound source localization and speech recognition in the presence of noise; and the quality of life is improved.

Keywords: single-sided deafness, asymmetric hearing loss, cochlear implant, unilateral hearing loss

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3430 The Effect of Students’ Social and Scholastic Background and Environmental Impact on Shaping Their Pattern of Digital Learning in Academia: A Pre- and Post-COVID Comparative View

Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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3429 The Impact of Trait and Mathematical Anxiety on Oscillatory Brain Activity during Lexical and Numerical Error-Recognition Tasks

Authors: Alexander N. Savostyanov, Tatyana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Yulia V. Kovas

Abstract:

The present study compared spectral-power indexes and cortical topography of brain activity in a sample characterized by different levels of trait and mathematical anxiety. 52 healthy Russian-speakers (age 17-32; 30 males) participated in the study. Participants solved an error recognition task under 3 conditions: A lexical condition (simple sentences in Russian), and two numerical conditions (simple arithmetic and complicated algebraic problems). Trait and mathematical anxiety were measured using self-repot questionnaires. EEG activity was recorded simultaneously during task execution. Event-related spectral perturbations (ERSP) were used to analyze spectral-power changes in brain activity. Additionally, sLORETA was applied in order to localize the sources of brain activity. When exploring EEG activity recorded after tasks onset during lexical conditions, sLORETA revealed increased activation in frontal and left temporal cortical areas, mainly in the alpha/beta frequency ranges. When examining the EEG activity recorded after task onset during arithmetic and algebraic conditions, additional activation in delta/theta band in the right parietal cortex was observed. The ERSP plots reveled alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three (lexical, arithmetic and algebraic) conditions. The level of trait anxiety was positively correlated with the amplitude of alpha/beta desynchronization. The level of mathematical anxiety was negatively correlated with the amplitude of theta synchronization and of alpha/beta desynchronization. Overall, trait anxiety was related with an increase in brain activation during task execution, whereas mathematical anxiety was associated with increased inhibitory-related activity. We gratefully acknowledge the support from the №11.G34.31.0043 grant from the Government of the Russian Federation.

Keywords: anxiety, EEG, lexical and numerical error-recognition tasks, alpha/beta desynchronization

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3428 Prediction of SOC Stock using ROTH-C Model and Mapping in Different Agroclimatic Zones of Tamil Nadu

Authors: R. Rajeswari

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An investigation was carried out to know the SOC stock and its change over time in benchmark soils of different agroclimatic zones of Tamil Nadu. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern. Soil map prepared on 1:50,000 scale from Natural Resources Information System (NRIS) employed under satellite data (IRS-1C/1D-PAN sharpened LISS-III image) was used to estimate SOC stock in different agroclimatic zones of Tamil Nadu. Fifteen benchmark soils were selected in different agroclimatic zones of Tamil Nadu based on their land use and the areal extent to assess SOC level and its change overtime. This revealed that, between eleven years of period (1997 - 2007). SOC buildup was higher in soils under horticulture system, followed by soils under rice cultivation. Among different agroclimatic zones of Tamil Nadu hilly zone have the highest SOC stock, followed by north eastern, southern, western, cauvery delta, north western, and high rainfall zone. Although organic carbon content in the soils of North eastern, southern, western, North western, Cauvery delta were less than high rainfall zone, the SOC stock was high. SOC density was higher in high rainfall and hilly zone than other agroclimatic zones of Tamil Nadu. Among low rainfall regions of Tamil Nadu cauvery delta zone recorded higher SOC density. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern in viz., Periyanaickenpalayam series (western zone), Peelamedu series (southern zone), Vallam series (north eastern zone), Vannappatti series (north western zone) and Padugai series (cauvery delta zone). Padugai series recorded higher TOC, BIO, and HUM, followed by Periyanaickenpalayam series, Peelamedu series, Vallam series, and Vannappatti series. Vannappatti and Padugai series develop high TOC, BIO, and HUM under existing cropping pattern. Periyanaickenpalayam, Peelamedu, and Vallam series develop high TOC, BIO, and HUM under alternate cropping pattern. Among five selected soil series, Periyanaickenpalayam, Peelamedu, and Padugai series recorded 0.75 per cent TOC during 2025 and 2018, 2100 and 2035, 2013 and 2014 under existing and alternate cropping pattern, respectively.

Keywords: agro climatic zones, benchmark soil, land use, soil organic carbon

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3427 Named Entity Recognition System for Tigrinya Language

Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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3426 Pattern Discovery from Student Feedback: Identifying Factors to Improve Student Emotions in Learning

Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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3425 The Impact of Nutrition Education Intervention in Improving the Nutritional Status of Sickle Cell Patients

Authors: Lindy Adoma Dampare, Marina Aferiba Tandoh

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Sickle cell disease (SCD) is an inherited blood disorder that mostly affects individuals in sub-Saharan Africa. Nutritional deficiencies have been well established in SCD patients. In Ghana, studies have revealed the prevalence of malnutrition, especially amongst children with SCD and hence the need to develop an evidence-based comprehensive nutritional therapy for SCD to improve their nutritional status. The aim of the study was to develop and assess the effect of a nutrition education material on the nutritional status of SCD patients in Ghana. This was a pre-post interventional study. Patients between the ages of 2 to 60 years were recruited from the Tema General Hospital. Following a baseline nutrition knowledge (NK), beliefs, sanitary practice and dietary consumption pattern assessment, a twice-monthly nutrition education was carried out for 3 months, followed by a post-intervention assessment. Nutritional status of SCD patients was assessed using a 3-days dietary recall and anthropometric measurements. Nutrition education (NE) was given to SCD adults and caregivers of SCD children. Majority of the caregivers (69%) and SCD adult (82%) at baseline had low NK. The level of NK improved significantly in SCD adults (4.18±1.83 vs. 10.00±1.00, p<0.001) and caregivers (5.58 ± 2.25 vs.10.44± 0.846, p<0.001) after NE. Increase in NK improved dietary intake and dietary consumption pattern of SCD patients. Significant increase in weight (23.2±11.6 vs. 25.9±12.1, p=0.036) and height (118.5±21.9 vs. 123.5±22.2, p=0.011) was observed in SCD children at post intervention. Stunting (10.5% vs. 8.6%, p=0.62) and wasting (22.1% vs. 14.4%, p=0.30) reduced in SCD children after NE although not statistically significant. Reduction (18.2% vs. 9.1%) in underweight and an increase (18.2% vs. 27.3%) in overweight SCD adults was recorded at post intervention. Fat mass remained the same while high muscle mass increased (18.2% vs. 27.3%) at post intervention in SCD adult. Anaemic status of SCD patients improved at post intervention and the improvement was statistically significant amongst SCD children. Nutrition education improved the NK of SCD caregivers and adults hence, improving the dietary consumption pattern and nutrient intake of SCD patients. Overall, NE improved the nutritional status of SCD patients. This study shows the potential of nutrition education in improving the nutritional knowledge, dietary consumption pattern, dietary intake and nutritional status of SCD patients, and should be further explored.

Keywords: sickle cell disease, nutrition education, dietary intake, nutritional status

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3424 To Estimate the Association between Visual Stress and Visual Perceptual Skills

Authors: Vijay Reena Durai, Krithica Srinivasan

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Introduction: The two fundamental skills involved in the growth and wellbeing of any child can be categorized into visual motor and perceptual skills. Visual stress is a disorder which is characterized by visual discomfort, blurred vision, misspelling words, skipping lines, letters bunching together. There is a need to understand the deficits in perceptual skills among children with visual stress. Aim: To estimate the association between visual stress and visual perceptual skills Objective: To compare visual perceptual skills of children with and without visual stress Methodology: Children between 8 to 15 years of age participated in this cross-sectional study. All children with monocular visual acuity better than or equal to 6/6 were included. Visual perceptual skills were measured using test for visual perceptual skills (TVPS) tool. Reading speed was measured with the chosen colored overlay using Wilkins reading chart and pattern glare score was estimated using a 3cpd gratings. Visual stress was defined as change in reading speed of greater than or equal to 10% and a pattern glare score of greater than or equal to 4. Results: 252 children participated in this study and the male: female ratio of 3:2. Majority of the children preferred Magenta (28%) and Yellow (25%) colored overlay for reading. There was a significant difference between the two groups (MD=1.24±0.6) (p<0.04, 95% CI 0.01-2.43) only in the sequential memory skills. The prevalence of visual stress in this group was found to be 31% (n=78). Binary logistic regression showed that odds ratio of having poor visual perceptual skills was OR: 2.85 (95% CI 1.08-7.49) among children with visual stress. Conclusion: Children with visual stress are found to have three times poorer visual perceptual skills than children without visual stress.

Keywords: visual stress, visual perceptual skills, colored overlay, pattern glare

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3423 Meat Products Demand in Oyo West Local Government: An Application of Almost Ideal Demand System (LA/AIDS)

Authors: B. A. Adeniyi, S. A. Daud, O. Amao

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The study investigates consumer demand for meat products in Oyo West Local Government using linear approximate almost ideal demand system (LA/AIDS). Questions that were addressed by the study include: first, what is the type and quantity of meat products available to the household and their demand pattern? Second is the investigation of the factors that affect meat products demand pattern and proportion of income that is spent on them. For the above purpose cross-sectional data were collected from 156 households of the study area and analyzed to reveal the functional relationship between meat products consumption and some socio-economic variables of the household. Results indicated that per capita meat consumption increased as household income and education increased but decreased with age. It was also found that male tend to consume more meat products than their female counterparts and that increase in household size will first increased per caput meat consumption but later decreased it. Price also tends to greatly influence the demand pattern of meat products. The results of elasticity computed from the results of regression analysis revealed that own price elasticity for all meat products were negative which indicated that they were normal products while cross and expenditure elasticity were positive which further confirmed that meat products were normal and substitute products. This study therefore concludes that the relevance of these variables imposed a great challenge to the policy makers and the government, in the sense that more cost effective methods of meat production technology have to be devised in other to make consumption of meat products more affordable.

Keywords: meat products, consumption, animal production, technology

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3422 Wind Velocity Climate Zonation Based on Observation Data in Indonesia Using Cluster and Principal Component Analysis

Authors: I Dewa Gede Arya Putra

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Principal Component Analysis (PCA) is a mathematical procedure that uses orthogonal transformation techniques to change a set of data with components that may be related become components that are not related to each other. This can have an impact on clustering wind speed characteristics in Indonesia. This study uses data daily wind speed observations of the Site Meteorological Station network for 30 years. Multicollinearity tests were also performed on all of these data before doing clustering with PCA. The results show that the four main components have a total diversity of above 80% which will be used for clusters. Division of clusters using Ward's method obtained 3 types of clusters. Cluster 1 covers the central part of Sumatra Island, northern Kalimantan, northern Sulawesi, and northern Maluku with the climatological pattern of wind speed that does not have an annual cycle and a weak speed throughout the year with a low-speed ranging from 0 to 1,5 m/s². Cluster 2 covers the northern part of Sumatra Island, South Sulawesi, Bali, northern Papua with the climatological pattern conditions of wind speed that have annual cycle variations with low speeds ranging from 1 to 3 m/s². Cluster 3 covers the eastern part of Java Island, the Southeast Nusa Islands, and the southern Maluku Islands with the climatological pattern of wind speed conditions that have annual cycle variations with high speeds ranging from 1 to 4.5 m/s².

Keywords: PCA, cluster, Ward's method, wind speed

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3421 A Study of Electrowetting-Assisted Mold Filling in Nanoimprint Lithography

Authors: Wei-Hsuan Hsu, Yi-Xuan Huang

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Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.

Keywords: electrowetting, mold filling, nano-imprint, surface modification

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3420 Crop Productivity, Nutrient Uptake and Apparent Balance for Rice Based Cropping Systems under Improved Crop Varieties and Nutrient Management Practices in Previous Enclaves of Bangladesh

Authors: Md. Samim Hossain Molla, Md. Mazharul Anwar, Md. Akkas Ali, Mian Sayeed Hassan

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Being detached about 68 years from the mainland, the previous enclaves’ (Chhitmohal) farmers were engaged only in subsistence farming with low agricultural productivity and restricted access to inputs technology. To increase crop productivity for attaining food security by addressing soil status, the experiments were undertaken in 2017 and 2018 in three previous enclaves of Northern Bangladesh i.e. Dasiarchhara of Kurigram district; Dahalakhagrabari of Panchagarh district and Banskata of Lalmonirhat district under On-Farm Research Division, Bangladesh Agricultural Research Institute, Rangpur. The Mustard (var. BARI Sarisha-14)-Boro rice (var. BRRI dhan58)-T. Aman rice (var. BRRI dhan49) cropping pattern using soil test based (STB) fertilizer with cowdung (T1) or recommended fertilizer dose (T2) were tested against existing cropping pattern Fallow-Boro rice (var. BRRI dhan28)-T. Aman rice (var. Swarna) using farmers’ practices fertilizer dose (T3) in six disperse replications at each location maintaining Randomized Complete Block design. Almost all crops yields were relatively higher in T1 followed by T2. Farmers existing pattern with local varieties and imbalance fertilizer (T3) use may be decreased the crop yield. The rice equivalent yield of T1 was 109, 103 and 95% higher than T3 and the gross margin was 164, 153 and 133% higher in T1 than T3 at Dasiarchhara, Dahalakhagrabari and Banskata, respectively. The Benefit Cost Ratio for T1, T2 and T3 were 1.99, 1.78 and 1.28 in Dasiarchhara; 1.93, 1.81 and 1.27 in Dahalakhagrabari and 1.78, 1.71 and 1.25 in Banskata, respectively. There was a remarkable decrease in mineral N, P and K in the topsoil (0–15 cm) of T3 and T2 treatments at Dasiarchhara and Dahalakhagrabari, and a generally less marked decline under the same treatments at Banskata. The same practices (T1) exhibited the greatest nutrients uptake by the test crops. The apparent balance of N, P and K was negative in most cases, where it was less negative in T1 treatment. However, from the experimentation, it is revealed that balanced fertilization (STB) and inclusion of National Agricultural Research Institutes developed improved crops varieties in cropping pattern may increase the crop productivity, farm efficiency and farmer’s income in a remarkable level.

Keywords: cropping pattern, fertilizer management, nutrient balance, previous enclaves

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3419 Computational Team Dynamics and Interaction Patterns in New Product Development Teams

Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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3418 An Appraisal of Revenue Collection in Local Government: A Case Study of Boripe Local Government Iragbiji Osun State

Authors: Olanike O. Akinwale, Isiaka S. Adedoyin

Abstract:

Revenue is a fund realized by the government to meet both current and capital expenditures. The study found out the various ways through which local governments in Nigeria generate revenue or obtain funds and determined whether the people of Boripe local government are paying tax as at when due and also evaluated how the revenue generated is being used by the local government. During the course of this study, research questionnaires were drafted and distributed to respondents in the local government secretariat who supplied the information needed to carry out the research work. Data were collected by using simple random sampling technique where members of the population have been given equal chance of being picked as a member of the sample. Data were analysed using chart table; the chart analyzed the figure of the past two years revenue and expenditure of the local government. It was deduced from the result that revenue generated but this was not up to what one expected for this local government to finance the projected expenditure when the size was considered, its location as well as its natural endowment of this local government. This was due to lack of cooperation of the people and staffs within the local government in the local government jurisdiction as well as fraudulent activities the revenue collectors engaged in. Revenue generation is a fuel for development in any organization whether public or private. The ability of revenue drive of Boripe was not strong enough since the targeted revenue from taxation was not enough to meet the projected expenditure for a particular year as in 2016, the difference was carried forward to the next year.

Keywords: appraisal, expenditure, local government, questionnaire, revenue

Procedia PDF Downloads 460
3417 The Distributed Pattern of the Neurovascular Structures under Clavicle to Minimize Structural Injury in Clinical Field: Anatomical Study

Authors: Anna Jeon, Seung-Ho Han, Je-Hun Lee

Abstract:

The aim of this study was to determine the location and distribution pattern of neurovascular structures superior and inferior to the clavicle by detailed dissection. Fifteen adult non-embalmed cadavers with a mean age of 71.5 years were studied. For measurements, the most prominent point of the sternal end of the clavicle (SEC) on anterior view and the most prominent point of the acromial end of the clavicle (AEC) were identified before dissection. A line connecting the SEC and AEC was used as a reference line. The surrounding neurovascular structures were investigated. The supraclavicular nerve was densely distributed at 71.73% on the reference line. Branches of the thoracoacromial artery were located at 76.92%. Branches of subclavian vein were evenly distributed at all sections. The subclavian vein and artery and brachial plexus were located from 31.3% to 57.5%. That area needs caution because major neurovascular structures run underneath the clavicle.

Keywords: clavicle, ORIF, neurovascular structure, anatomical study

Procedia PDF Downloads 167
3416 Defect Classification of Hydrogen Fuel Pressure Vessels using Deep Learning

Authors: Dongju Kim, Youngjoo Suh, Hyojin Kim, Gyeongyeong Kim

Abstract:

Acoustic Emission Testing (AET) is widely used to test the structural integrity of an operational hydrogen storage container, and clustering algorithms are frequently used in pattern recognition methods to interpret AET results. However, the interpretation of AET results can vary from user to user as the tuning of the relevant parameters relies on the user's experience and knowledge of AET. Therefore, it is necessary to use a deep learning model to identify patterns in acoustic emission (AE) signal data that can be used to classify defects instead. In this paper, a deep learning-based model for classifying the types of defects in hydrogen storage tanks, using AE sensor waveforms, is proposed. As hydrogen storage tanks are commonly constructed using carbon fiber reinforced polymer composite (CFRP), a defect classification dataset is collected through a tensile test on a specimen of CFRP with an AE sensor attached. The performance of the classification model, using one-dimensional convolutional neural network (1-D CNN) and synthetic minority oversampling technique (SMOTE) data augmentation, achieved 91.09% accuracy for each defect. It is expected that the deep learning classification model in this paper, used with AET, will help in evaluating the operational safety of hydrogen storage containers.

Keywords: acoustic emission testing, carbon fiber reinforced polymer composite, one-dimensional convolutional neural network, smote data augmentation

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3415 Influence of the Refractory Period on Neural Networks Based on the Recognition of Neural Signatures

Authors: José Luis Carrillo-Medina, Roberto Latorre

Abstract:

Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

Procedia PDF Downloads 493
3414 Modern Detection and Description Methods for Natural Plants Recognition

Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

Abstract:

Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

Procedia PDF Downloads 278
3413 Changing Pattern of Drug Abuse: An Outpatient Department Based Study from India

Authors: Anshu Gupta, Charu Gupta

Abstract:

Background: Punjab, a border state in India has achieved notoriety world over for its drug abuse problem. People right from school kids to elderly are hooked to drugs. This pattern of substance abuse is prevalent in both cities and villages alike. Excess of younger population in India has further aggravated the situation. It is feared that the benefits of India’s economic growth may well be negated by the rising substance abuse especially in this part of the country. It is quite evident that the pattern of substance abuse tends to change over time which is an impediment in the formulation of effective strategies to tackle this issue. Aim: Purpose of the study was to ascertain the change in the pattern of drug abuse for two consecutive years in the out patient department (OPD) population. Method: The study population comprised of all the patients reporting for deaddiction to the psychiatry outpatient department over a period of twelve months for two consecutive years. All the patients were evaluated by the International Classification of Diseases; 10 criteria for substance abuse/dependence. Results: A considerably high prevalence of substance abuse was present in the Indian population. In general, there was an increase in prevalence from first to the second year, especially among the female population. Increase in prevalence of substance abuse appeared to be more prominent among the younger age group of both the sexes. A significant increase in intravenous drug abuse was observed. Peer pressure and parental imitation were the major factors fueling substance abuse. Precipitation or fear of withdrawal symptoms was the major factor preventing abstinence. Substance abuse had a significant effect on the health and interpersonal relations of these patients. Summary/Conclusion: Drug abuse and addiction are on the rise throughout India. Changing cultural values, increasing economic stress and dwindling supportive bonds appear to be leading to initiation of substance abuse. Need of the hour is to formulate a comprehensive strategy to bring about an overall reduction in the use of drugs.

Keywords: deaddiction, peer pressure, parental imitation, substance abuse/dependance

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3412 Real-Time Recognition of the Terrain Configuration to Improve Driving Stability for Unmanned Robots

Authors: Bongsoo Jeon, Jayoung Kim, Jihong Lee

Abstract:

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor (exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit (IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Keywords: inertial measurement unit, laser range finder, real-time recognition of the ground shape, proprioceptive sensor

Procedia PDF Downloads 288
3411 Degraded Document Analysis and Extraction of Original Text Document: An Approach without Optical Character Recognition

Authors: L. Hamsaveni, Navya Prakash, Suresha

Abstract:

Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

Procedia PDF Downloads 377
3410 Relationship between Right Brain and Left Brain Dominance and Intonation Learning

Authors: Mohammad Hadi Mahmoodi, Soroor Zekrati

Abstract:

The aim of this study was to investigate the relationship between hemispheric dominance and intonation learning of Iranian EFL students. In order to gain this goal, 52 female students from three levels of beginner, elementary and intermediate in Paradise Institute, and 18 male university students at Bu-Ali Sina University constituted the sample. In order to assist students learn the correct way of applying intonation to their everyday speech, the study proposed an interactive approach and provided students with visual aid through which they were able to see the intonation pattern on computer screen using 'Speech Analyzer' software. This software was also used to record subjects’ voice and compare them with the original intonation pattern. Edinburg Handedness Questionnaire (EHD), which ranges from –100 for strong left-handedness to +100 for strong right-handedness was used to indicate the hemispheric dominance of each student. The result of an independent sample t-test indicated that girls learned intonation pattern better than boys, and that right brained students significantly outperformed the left brained ones. Using one-way ANOVA, a significant difference between three proficiency levels was also found. The posthoc Scheffer test showed that the exact difference was between intermediate and elementary, and intermediate and beginner levels, but no significant difference was observed between elementary and beginner levels. The findings of the study might provide researchers with some helpful implications and useful directions for future investigation into the domain of the relationship between mind and second language learning.

Keywords: intonation, hemispheric dominance, visual aid, language learning, second language learning

Procedia PDF Downloads 519
3409 A Novel Combined Finger Counting and Finite State Machine Technique for ASL Translation Using Kinect

Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

Abstract:

This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

Procedia PDF Downloads 298
3408 Chinese Sentence Level Lip Recognition

Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

Procedia PDF Downloads 128
3407 Developing Mathematical Relationships to Evaluate the Amount of Added Ease to the Basic Pattern of Weft Knitting Fabrics and Its Fitting to the Upper Part of Egyptian Women's Bodies

Authors: Hebatullah Ali Abdel-Aleem Abdel-Hamid, Camellia Mousa Mohamed Elzean

Abstract:

Knitted garments recently became a key component in wardrobes of the Egyptian woman. Many Egyptian women depend on garments made of knitted fabrics in their outer appearance because of its specific properties including flexibility. Through observation and application, it was noticed that knitwear blocks that used for knitted fabrics somehow does not fit the figures of the Egyptian women. Moreover, the pattern makers are usually confused and unable to choose the suitable blocks for different knitting fabrics taking into consideration its physical and mechanical properties. This study seeks to develop mathematical relationships for evaluation of the amount of added- or subtracted ease to Aldrich’s basic fitting blocks for some weft knitting fabrics and its fitting to the upper part of Egyptian women's bodies. To achieve this goal, 12 samples were used to evaluate fitting of Aldrich’s Basic Fitting Block to the upper part of Egyptian women's bodies. The samples were evaluated before and after alterations, through wear trials on the standard mannequins of size 48 and 56, and judged by experienced assessors using fit evaluation scale. The data obtained were statistically analyzed to identify the efficiency of the adjustments. The Aldrich’s Basic Fitting Block was selected because his method is known internationally and easy to use.

Keywords: Aldrich basic fitting block, clothing industry, knitted fabrics, pattern construction

Procedia PDF Downloads 266
3406 Performances of Two-Segment Crash Box with Holes under Oblique Load

Authors: Moch Agus Choiron

Abstract:

Crash box design has been developed to obtain optimum energy absorption. In this study, two-segment crash box design with holes is investigated under oblique load. The deformation behavior and crash energy absorption are observed. The analysis was performed using finite element method. The crash test components were impactor, crash box, and fixed rigid base. Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. The models consist of 2 and 4 holes laid within ¼, ½ and ¾ from first segment length. 100 mm aluminum crash box and frontal crash velocity of 16 km/jam were selected. Based on simulation results, it can be concluded that 2 holes located at ¾ has the largest crash energy absorption. This behavior associated with deformation pattern, which produces higher number of folding than other models.

Keywords: crash Box, two-segments, holes configuration, oblique load, deformation pattern

Procedia PDF Downloads 361