Search results for: cosine margin face recognition

Authors: M. Khundadze, V. Varazashvili, N. Lejava, R. Jorbenadze

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Phase transitions of cerium and neodymium are investigated by using high-temperature scanning calorimeter (HT-1500 Seteram). For cerium two types of transformation are detected: at 350-372 K - hexagonal close packing (hcp) - face-centered cubic lattice (fcc) transition, and at 880-960K the face-centered cubic lattice (fcc) transformation into body-centered cubic lattice (bcc). For neodymium changing of hexagonal close packing (hcp) into the body-centered cubic lattice (bcc) is detected at 1093-1113K. The thermal characteristics of transitions – enthalpy, entropy, temperature domains – are reported.

Keywords: cerium, calorimetry, enthalpy of phase transitions, neodymium

Procedia PDF Downloads 322

Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: image compression, color image, q-coder, quantization, edge-detection

Procedia PDF Downloads 327

Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah

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Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.

Keywords: image registration, mutual information, image gradients, image transformations

Procedia PDF Downloads 245

Authors: Eno Jah Tabogo

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The aim of this research is to identify and examine current deficiencies in entrepreneurial training in improving the performance of small businesses in sub Saharan Africa economies. This research achieves this by examining the course content, training methods, and profiles of trainers and trainees of small business service providers in Sub Saharan Africa (SSA) to identify training deficiencies in improving small businesses. Data was for the analysis was collected from a sample of four entrepreneurial training providers in SSA. These four providers served an average of 1,500 trainees. Questionnaire was used to collect data via face to face and through telephone. Face validity was determined by distributing the questionnaire among a group of colleagues, followed by a group discussion to strengthen the validity of the questionnaire. Interviews were also held with managers of training programs. Content and descriptive statistics was used to analyse the data collected. The results indicated only 25% of the training content were entrepreneurial. In terms of service provided, both business, entrepreneurial, technical and after-care services were identified. It was also discovered that owners of training firms had no formal entrepreneurship background. The paper contributes by advocating for a comprehensive entrepreneurship-training program for successful small business enterprises. Recommendations that could help sustain emerging small business enterprises and direction for further research are presented.

Keywords: entrepreneurship, emerging markets, small business, training

Procedia PDF Downloads 139

Authors: Gulfam Hasan, Ijaz Ashraf, Saleem Ashraf, Muhammad Rafay Muzammil, Salman Asghar, Shafiq-Ur-Rehman Zia

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The word “climate change” has become the most popular term when anyone observes any uncertain climate variation in their respective region. Asian countries are more prone to the impact of this phenomenon, and Pakistan is the leading affected country. Last few years, governments all over the world have been trying to cater to this issue for the best entrust of their population, especially agriculture. Now the farmers in Pakistan are fully aware of the term “climate change” and are more concerned about its solutions. On the other hand, developed countries like the USA are setting a benchmark for developing countries in every sphere of life. Based on cultural and other variations, the research was carried out to identify the behavior of farmers regarding the same issue. Cross-sectional survey research was designed for an in-depth study of relevant research questions. Face-to-face interviews were conducted in Pakistan, while virtual and face-to-face interviews were conducted in the Indiana State of the USA. The results of the present study and the responses of farmers were very interesting. The common climate change mitigation strategies suggested by farmers of both countries were less use of motor vehicles (replacement with bicycles in the circle of 10 Km), less dependency on chemical fertilizers (increased use of Manure, Bio-fertilizer, Compost), and plantation of the tree. The difference of opinion was in less government interest, lack of farmers’ education, political instability (views of Pakistani farmers), awareness of local communities, self-satisfaction, and economic disparities (views of USA farmers). Based on the given evidence, it was recommended that there is a dire need to address the climate change issue all over the world without discrimination of race, color, region, or religion. Because it will affect not only agriculture but also the real effect will be on HUMANITY.

Keywords: climate change, mitigation strategies, forests, biodiversity

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Authors: O. R. Adeniyi, A. Ayandiji

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Losses are common in most vegetables because the fruit ripens rapidly and most plantain products can only be stored for a few days thereby limiting their utilization. Plantain (and banana) is highly perishable at the ambient temperature prevalent in the tropics. The specific objective of this study is to identify the socioeconomic characteristics of banana/plantain dealers and determine the perceived effect of the losses incurred in the process of marketing banana/plantain. The study was carried out in Ondo and Lagos states of south-western Nigeria. Purposive sampling technique was used to collect information from “Kolawole plantain depot”, the point of purchase in Ondo State and “Alamutu plantain market” in Mushin the point of sales in Lagos state. Preliminary study was conducted with the use of primary data collected through well-structured questionnaires administered on 60 respondents and 55 fully completed ones analysed. Budgeting, gross margin and multiple linear regression were used for analyses. Most merchants were found to be in the middle age class (30-50 years), majority of whom were female and completed their secondary school education, with eighty percent having more than 5 years’ experience of in banana/plantain marketing. The highest losses were incurred during transportation and these losses constitute about 5.62 percent of the potential total revenue. On the average, loss in gross margin is about ₦6,000.00 per merchant. The impacts of these losses are reflected in the continuously reducing level of their income. Age of the respondents played a major role in determining the level of care in the handling of the fruits. The middle age class tends to be more favoured. In conclusion, the merchants need adequate and sustainable transportation and storage facilities as a matter of utmost urgency. There is the need for government to encourage producers of the product (farmers) by giving them motivating incentives and ensuring that the environment is made conducive also for dealers by providing adequate storage facilities and ready markets locally and possibly for export.

Keywords: post-harvest, losses, plantain, banana, simple regression

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: B. S. Bamoallem, A. J. Wodehouse, G. M. Mair

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Communication takes place not only through speech, but also by means of gestures such as facial expressions, gaze, head movements, hand movements and body posture, and though there has been rapid development, communication platforms still lack this type of behavior. We believe communication platforms need to fully achieve this verbal and non-verbal behavior in order to make interactions more engaging and more efficient. In this study we decided to focus our research on the head rather than any other body part as it is a rich source of information for speech-related movement Thus we aim to investigate the value of incorporating head movements into the use of telepresence robots as communication platforms; this will be done by investigating a system that reproduces head movement manually as closely as possible.

Keywords: engagement, nonverbal behaviours, head movements, face-to-face interaction, telepresence robot

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

Procedia PDF Downloads 153

Authors: Hamza A. A. Al-Sewadi, Adnan H. M. Al-Helali, Samaa A. K. Khamis

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Ownership proofs of multimedia such as text, image, audio or video files can be achieved by the burial of watermark is them. It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications would be in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: authentication, copyright protection, information hiding, ownership, watermarking

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Authors: Aida Humaira

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Aromatic plants hold an honored place in Indonesian culture, where they are deeply intertwined with everyday customs, rituals, and ceremonies. From the fragrant herbs and spices used in cooking to the aromatic incense burned in temples and homes, aromatic plants play multifaceted roles in enhancing well-being and fostering spiritual connections. These plants are valued not only for their pleasant aromas but also for their medicinal properties and symbolic meanings. This article aims to summarize the role of aromatic plants in Indonesian traditional culture, medicine, spirituality, and how it shifted to a modern version of aromatherapy. Traditional Indonesian medicine, known as Jamu, relies heavily on aromatic plants for their therapeutic benefits. Herbalists and traditional healers use a wide array of aromatic herbs, roots, barks, and resins to treat various ailments, ranging from digestive disorders and respiratory infections to skin conditions and reproductive issues. In conclusion, aromatic plants represent a cultural treasure with multifaceted uses and significance deeply rooted in Indonesia’s tradition. From their medicinal properties to their spiritual symbolism, these plants embody the interconnection of culture, nature, and well-being. Further research and collaboration are needed to document and preserve traditional knowledge surrounding Indonesian aromatic plants and ensure their continued recognition and sustainable utilization in the face of modernization and environmental challenges.

Keywords: aromatic plants, indonesia, Jamu, traditional medicine

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Authors: Hong Im Shin

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Previous research demonstrated that self-objectification (women view themselves as objects for use) is related to system-justification. Three studies investigated whether cultural disposition as its system-justifying function could have an impact on self-objectification and dehumanization of sexualized women and men. Study 1 (N = 91) employed a survey methodology to examine the relationship between cultural disposition (collectivism vs. individualism), trait of system-justification, and self-objectification. The results showed that the higher tendency of collectivism was related to stronger system-justification and self-objectification. Study 2 (N = 60 females) introduced a single category implicit association task (SC-IAT) to assess the extent to which sexually objectified women were associated with uniquely human attributes (i.e., culture) compared to animal-related attributes (i.e., nature). According to results, female participants associated sexually objectified female targets less with human attributes compared to animal-related attributes. Study 3 (N = 46) investigated whether priming to individualism or collectivism was associated to system justification and sexual objectification of men and women with the use of a recognition task involving upright and inverted pictures of sexualized women and men. The results indicated that the female participants primed to individualism showed an inversion effect for sexualized women and men (person-like recognition), whereas there was no inversion effect for sexualized women in the priming condition of collectivism (object-like recognition). This implies that cultural disposition plays a mediating role for rationalizing the gender status, implicit dehumanization of sexualized females and self-objectification. Future research directions are discussed.

Keywords: cultural disposition, dehumanization, implicit test, self-objectification

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

Procedia PDF Downloads 279

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Fatima El Zahra Amin, Emine Efe

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This study was carried out to evaluate the effect of the education program for parents of children with Sickle Cell Anemia, on the knowledge level of parents and the reduction of pain relief by non-pharmacological methods used by parents at home. In Turkey, 54 parents and 109 from Chad agreed to participate in the survey. The data were collected by the researcher using a face-to-face interview method. Non-pharmacological treatment information form for parents, face expressions rating scale, and parent education program for non-pharmacological methods used in children with sickle cell anemia were used. It was determined that there was a statistically significant difference between the educational status, occupation, disease status, place of residence, family structure and age of parents of Chad and Turkey. According to the ratings of facial expressions scale, it was concluded that there was no significant difference between the children’s average degree of pain before and after administration of non-pharmacological methods by the groups of Chad and Turkey. It was determined that the educational programs prepared for parents of children with sickle cell anemia in both Turkey and Chad were effective in increasing the knowledge level of parents and also in reducing pain crisis with non-pharmacological methods parents used at home.

Keywords: Chad, child, non-pharmacological treatment methods, nurse, sickle cell anemia, Turkey

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Authors: Hamza A. Ali, Adnan H. M. Al-Helali

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Generally, a watermark is information that identifies the ownership of multimedia (text, image, audio or video files). It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications are done according to a secret key in a descriptive model that would be either in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: watermarking, ownership, copyright protection, steganography, information hiding, authentication

Procedia PDF Downloads 367

Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Sohni Siddiqui, Anja Schultze-Krumbholz

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Our lives now revolve more around online-related tasks, as the internet has become a necessity. One of the disturbance concerns with high internet usage is the multiplication of cyber-associated risky behaviors such as cyber aggression and/or cyberbullying. Cyber Bullying is an emerging issue that needs immediate attention from many stakeholders such as parents, doctors, school administrators, policymakers, researchers, and others, especially in the COVID-19 pandemic when online learning has been adopted as an instructional strategy, and there is a continuous rise in cyberbullying cases. The aim of the article is to review existing successful and emerging interventions designed to control bullying and cyberbullying by engaging individuals through teachers’ professional development and adopting a whole-school approach. The study identified the strengths and limitations of the programs and suggested improvements to existing interventions. Preparing interventions with a strong theoretical framework, integrating applications of emerging theories in interventions, promoting proactive and reactive strategies in combination, beginning with the baseline needs assessment surveys, reducing digital time and digital divide among parents and children, promoting the concept of lead trainer, peer trainer, and hot spots, focusing on physical activities, use of landmarks are some of the recommendations proposed by authors. In addition to face-to-face intervention, the researchers recommend updating and improving previous intervention programs with games and apps. Especially in the time of pandemic crises, when face-to-face interactions are limited and cyberbullying is triggered, the use of apps, web-based interventions, and games can be an effective way to control electronic perpetration and victimization.

Keywords: anti bullying programs, cyber bullying, individualized trainings, teachers’ professional development, whole school interventions

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Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

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Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

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Authors: Cherish Romina Prajitno, Sunisa Thaichinda

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One indicator of facial aging is wrinkles. Not only that, but wrinkles are a key indicator in our world of facial aesthetics. Wrinkles occur where fault lines develop in aging skin. Nowadays, people are more motivated to keep up their appealing and young appearance. Many individuals are seeking a fast recovery time for their aesthetic procedures and are interested in non-invasive techniques that have a proven track record for successful outcomes. The purpose of this study is to see the efficacy of 100% (pure) grapeseed oil for reducing periorbital wrinkles. This study used the split-face, double-blind method, and this treatment was administered for three months at random to fifteen patients, with the grapeseed oil at one side of the face and the other side with the placebo. The main outcome measure was determined by conducting a comparative analysis of the participants' wrinkle results during each visit using the VIsioscan® VC98. Additionally, we evaluated the skin's elasticity and barrier function using the Cutometer® MP 530 and Tewameter® TM300. Furthermore, we administered a satisfaction score questionnaire to the patients in the 12th week. The findings of the study indicate that grapeseed oil exhibited a noteworthy effect in diminishing the appearance of wrinkles in the periorbital region, enhancing the viscoelastic properties of the periorbital skin, and improving the functionality of the skin barrier in the periorbital area.

Keywords: periorbital wrinkles, pure grapeseed oil, split-face method

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Authors: A. Boonpratatong, J. Pantong, S. Kiattisaksophon, W. Senavongse

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In this study, an integrated sensing and modeling system for manual wheelchair propulsion measurement and propulsion efficiency calculation was used to indicate the level of overuse. Seven subjects participated in the measurement. On the level surface, the propulsion efficiencies were not different significantly as the riding speed increased. By contrast, the propulsion efficiencies on the 15-degree incline were restricted to around 0.5. The results are supported by previously reported wheeling resistance and propulsion torque relationships implying margin of the overuse. Upper limb musculoskeletal injuries and syndromes in manual wheelchair riders are common, chronic, and may be caused at different levels by the overuse i.e. repetitive riding on steep incline. The qualitative analysis such as the mechanical effectiveness on manual wheeling to establish the relationship between the riding difficulties, mechanical efforts and propulsion outputs is scarce, possibly due to the challenge of simultaneous measurement of those factors in conventional manual wheelchairs and everyday environments. In this study, the integrated sensing and modeling system were used to measure manual wheelchair propulsion efficiency in conventional manual wheelchairs and everyday environments. The sensing unit is comprised of the contact pressure and inertia sensors which are portable and universal. Four healthy male and three healthy female subjects participated in the measurement on level and 15-degree incline surface. Subjects were asked to perform manual wheelchair ridings with three different self-selected speeds on level surface and only preferred speed on the 15-degree incline. Five trials were performed in each condition. The kinematic data of the subject’s dominant hand and a spoke and the trunk of the wheelchair were collected through the inertia sensors. The compression force applied from the thumb of the dominant hand to the push rim was collected through the contact pressure sensors. The signals from all sensors were recorded synchronously. The subject-selected speeds for slow, preferred and fast riding on level surface and subject-preferred speed on 15-degree incline were recorded. The propulsion efficiency as a ratio between the pushing force in tangential direction to the push rim and the net force as a result of the three-dimensional riding motion were derived by inverse dynamic problem solving in the modeling unit. The intra-subject variability of the riding speed was not different significantly as the self-selected speed increased on the level surface. Since the riding speed on the 15-degree incline was difficult to regulate, the intra-subject variability was not applied. On the level surface, the propulsion efficiencies were not different significantly as the riding speed increased. However, the propulsion efficiencies on the 15-degree incline were restricted to around 0.5 for all subjects on their preferred speed. The results are supported by the previously reported relationship between the wheeling resistance and propulsion torque in which the wheelchair axle torque increased but the muscle activities were not increased when the resistance is high. This implies the margin of dynamic efforts on the relatively high resistance being similar to the margin of the overuse indicated by the restricted propulsion efficiency on the 15-degree incline.

Keywords: contact pressure sensor, inertia sensor, integrating sensing and modeling system, manual wheelchair propulsion efficiency, manual wheelchair propulsion measurement, tangential force, resultant force, three-dimensional riding motion

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Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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Authors: Ali Ulvi Uzer

Abstract:

Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

Abstract:

The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: Yi-Ju Lee

Abstract:

This study identified the hypothesised relationship between creative experience, and revisit intention of handmade oriental parasol umbrella in Kaohsiung, Taiwan. A face-to-face questionnaire survey was administered in Meinong town, Kaohsiung. The components of creative experience were found as “sense of achievement”, “unique learning” and “interaction with instructors” in creative tourism. The result also revealed significant positive relationships between creative experience and revisit intention in handmade activities. This paper provides additional suggestions for enhancing revisit intention and guidance regarding creative tourism.

Keywords: creative tourism, sense of achievement, unique learning, interaction with instructors, folk art

Procedia PDF Downloads 277

Authors: Khader S. Al-Aidmat, Venus W. Samawi

Abstract:

Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

Abstract:

Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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Authors: Min Fang, Jiaxi Yang

Abstract:

Monetary policy could be less effective at stimulating investment during periods of elevated volatility than during normal times. In this paper, we argue that elevated volatility leads to a decrease in extensive margin investment incentive so that nominal stimulus generates less aggregate investment. To do this, we first empirically document that high volatility weakens firms’ investment responses to monetary stimulus. Such effects depend on the lumpiness nature of the firm-level investment. The findings are that the channel exists for all of the physical investment, innovation investment, and organization investment.

Keywords: investment, irreversibility, volatility, uncertainty, firm heterogeneity, monetary policy

Procedia PDF Downloads 104