Search results for: weights identify

Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

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Authors: Yi-Wei Huang

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Eileen Chang is a well-known writer of modern Chinese literature. She is also a translator that publishes her self-translation The Rice Sprout Song. The purpose of the study is to identify the style of Eileen Chang’s self-translations by corpora, especially in the case of The Rice Sprout Song. The Rice Sprout Song is first written in English and then translated into Chinese by the author herself. The procedure of translation is complicated due to the bilingual transition by the same person. Therefore, the aim of the study is to identify Eileen Chang’s style on her self-translation by comparing her works The Old Man and the Sea, The Rice Sprout Song, and The Rouge of The North. The study uses computer-aided software like AntConc, Notepad++, StanfordCoreNLP, and Python to analyze the style of the works, especially focuses on reduplications and the composition of the sentences. Reduplications are commonly seen in Eileen Chang’s works, and they often appear with colors or onomatopoeia. With these criteria, the style of self-translating can be detected and analyzed.

Keywords: corpora, Eileen Chang, reduplications, self-translation

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

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The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

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Authors: Besher Gharaibeh

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This article addressed the issue of using physical exam in nursing. Nurses hold different attitudes toward using physical exam in the clinical settings. These attitudes determine to embrace physical examination in practice. So, the aim of the study was to examine registered nurses’ attitudes and practices, identify perceived barriers, and to identify the factors which influence the performance and the attitudes towards physical examinations. Results showed that even though nurses reported performing physical exam often, they had negative attitudes toward it. Stress and performing physical examinations on someone of the opposite gender (n=236; 87.4%) were the main barriers. Nurse's level of education influenced the attitude (t=-4.3; p < .01). These results indicated that RNs recognize the necessity of physical examinations, but they face many barriers and challenges which hinder the performance of the examination. Cultural factors and experience were the most influential barriers which deter performance of the physical examination.

Keywords: physical exam, nursing, barriers, practices, attitudes

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Authors: Jaejun Jong

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Fake news has recently become a serious international problem. Therefore, researchers and policymakers worldwide have sought to understand fake news and develop strategies to combat it. This study consists of two primary parts: (1) a literature review of how surveys were used to understand fake news and identify problems caused by fake news, and (2) a discussion of how surveys were used to fight back against fake news in educational settings. This second section specifically analyzes surveys used to evaluate a South Korean elementary school program designed to improve students’ metacognition and critical thinking. This section seeks to identify potential problems that may occur in the elementary school setting. The literature review shows that surveys can help people to understand fake news based on its traits rather than its definition due to the lack of agreement on the definition of fake news. The literature review also shows that people are not good at identifying fake news or evaluating their own ability to identify fake news; indeed, they are more likely to share information that aligns with their previous beliefs. In addition, the elementary school survey data shows that there may be substantial errors in the program evaluation process, likely caused by processing errors or the survey procedure, though the exact cause is not specified. Such a significant error in evaluating the effects of the educational program prevents teachers from making proper decisions and accurately evaluating the program. Therefore, identifying the source of such errors would improve the overall quality of education, which would benefit both teachers and students.

Keywords: critical thinking, elementary education, program evaluation, survey

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Authors: Azizah M. Nahari, Peter Doerner

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Phosphate (Pi) is one of the essential macronutrients in plant growth and development, and it plays a central role in metabolic processes in plants, particularly photosynthesis and respiration. Limitation of crop productivity by Pi is widespread and is likely to increase in the future. Applications of Pi fertilizers have improved soil Pi fertility and crop production; however, they have also caused environmental damage. Therefore, in order to reduce dependence on unsustainable Pi fertilizers, a better understanding of phosphate use efficiency (PUE) is required for engineering nutrient-efficient crop plants. Enhanced Pi efficiency can be achieved by improved productivity per unit Pi taken up. We aim to identify, by using association mapping, general features of the most important loci that contribute to increased PUE to allow us to delineate the physiological pathways involved in defining this trait in the model plant Arabidopsis. As PUE is in part determined by the efficiency of uptake, we designed a hydroponic system to avoid confounding effects due to differences in root system architecture leading to differences in Pi uptake. In this system, 18 parental lines and 217 lines of the MAGIC population (a Multiparent Advanced Generation Inter-Cross) grown in high and low Pi availability conditions. The results showed revealed a large variation of PUE in the parental lines, indicating that the MAGIC population was well suited to identify PUE loci and pathways. 2 of 18 parental lines had the highest PUE in low Pi while some lines responded strongly and increased PUE with increased Pi. Having examined the 217 MAGIC population, considerable variance in PUE was found. A general feature was the trend of most lines to exhibit higher PUE when grown in low Pi conditions. Association mapping is currently in progress, but initial observations indicate that a wide variety of physiological processes are involved in influencing PUE in Arabidopsis. The combination of hydroponic growth methods and genome-wide association mapping is a powerful tool to identify the physiological pathways underpinning complex quantitative traits in plants.

Keywords: hydroponic system growth, phosphate use efficiency (PUE), Genome-wide association mapping, MAGIC population

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Authors: Hanaa A. S. Oraby, Amal A. M. Hassan, Mahmoud M. Sakr, Atef A. A. Haiba

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Applying the profiling approach for the assessment of proteomic variations due to genetic modification of the Egyptian tomato cultivar "Edkawy", three complementary approaches were used. These methods are amino acids analysis, gel electrophoresis, and Gas chromatography coupled with mass spectrometry (GC/MS). The results of the present study Show evidence of proteomic variations between both modified tomato and its non-modified counterpart. Amino acids concentrations, and the protein patterns separation on the 1D SDS-PAGE were not similar in the case of transformed tomato compared to that of the non-transformed counterpart. These detected differences are most likely derived from the process of transformation. Results also revealed that the efficiency of GC/MS approach to identify a mixture of unknown proteins is limited. GC/MS analysis was only able to identify few number of protein molecules. Therefore, more advanced and specific technologies like MALDI-TOF-MS are recommended to be employed.

Keywords: GMOs, unintended effects, proteomic variations, 1D SDS-PAGE, GC/MS

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Fakhreddin El Wali Elalaoui, Maatouk Mustapha

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The problem of global climate change isbecoming more and more serious. Therefore, there is a growing interest in renewable energy sources to minimize the impact of this phenomenon. Environmental policies are changing in different countries, including Morocco, with a greater focus on the integration and development of renewable energy projects. The purpose of this paper is to evaluate the potential of solar power plants in Morocco based on two technologies: concentrated solar power (CSP) and photovoltaics (PV). In order to perform an accurate search, we must follow a certain method to select the correct criteria. Four selection criteria were retained: climate, topography, location, and water resources. AnalyticHierarchy Process (AHP) was used to calculate the weight/importance of each criterion. Once obtained, weights are applied to the map for each criterion to produce a final ranking that ranks regions according to their potential. The results show that Morocco has strong potential for both technologies, especially in the southern region. Finally, this work is the first in the field to include the whole of Morocco in the study area.

Keywords: PV, Csp, solar energy, GIS

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Authors: Z. Hamed, K. Sa'deya, E. Abdelrasheed, I. Mahamid

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The construction industry is one of the main sectors that play basic role in the urban and rural development of a society. It provides important ingredients for the development of an economy. However, many construction projects experience extensive cost overrun. This study was conducted to identify the causes of cost overrun in building construction contracts in Al Madinah, Saudi Arabia and test the importance of these causes from contractors' perspective. To achieve the study objectives, a questionnaire survey was conducted to identify and rank cost overrun causes from the perspective of contractors. The findings found that the top five cost overrun causes are: lack of experience in the line of work, lack of labor productivity, delay in payments, rework and material waste. It is hoped that the findings will guide efforts to improve the performance of construction industry in Saudi Arabia and other developing countries.

Keywords: building, contractor, cost increase, cost overrun

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Authors: Saad Alkahtani

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This study aims to identify the extent to which the faculty members who teach Arabic to speakers of other languages in Arabic language institutes at Saudi universities use computer technologies such as language laboratories, websites, software programs, and learning management system (LMS). It also seeks to identify critical difficulties that hinder the use of these technologies by faculty members. The population of the study consisted of 103 faculty members in four Arabic language institutes at Saudi universities. The results of the study showed a disparity in the use of computer technologies in teaching Arabic to non-native speakers. The means of degree of use ranged from 1.20 through 2.83. The study also identified difficulties limiting the use of computer technology in teaching Arabic. And the means of averages of difficulty of use ranged from 1.50 to 2.89. The differences were not statistically significant among the institutes (at 0.05).

Keywords: Arabic language programs, computer technology, using technology in teaching Arabic language, Arabic as a second language, computer skills

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Authors: Fety Nurlia Muzayanah, Arif Imam Suroso, Mukhamad Najib

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The market share of organic food in Indonesia just reaches 0.5-2 percents from the entire of agricultural products. The aim of this research is to analyze the relation of gender, work, age and final education toward the buying interest of organic food, to identify the factors influencing the resistance of the purchase of organic food, and to identify the market education process. The analysis result of Structural Equation Modeling (SEM) shows the factors causing the resistance of the purchase of organic food are the negative attitude toward organic food, the lack of affordable in range for organic food product and the lack of awareness toward organic food, while the subjective norms have no significant effect toward the buying interest. The market education process which can be done is the education about the use of the health of organic food, the organic certification and the economic value.

Keywords: market education, organic food, consumer behavior, structural equation modeling

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Authors: A. Kyprianou, A. Tjirkallis

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Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

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Authors: Hyo-Su Lim, Ye-Eun Song, Eun-Bi Lee, Sang-Yoon Lee, Young-Il Seo, Jin-Pyo Kim, Nam-Kyu Park

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If we analogize any physical external force given to victims in many crimes including violence, it would be possible not only to presume mutual action between victims and suspects, but to make a deduction of more various facts in cases. Therefore, the aim of this study is to identify criminal tools through secretion on clothes by using amino acid reagents such as Ninhydrin, DFO(1,8-dizafluoren-9-one), 1,2 – IND (1,2-indanedione) which are reacting to skin secretion. For more effective collecting condition, porcine skin which is physiologically similar to human was used. Although there were little differences of shape identification according to sensitivity, amino acid reagents were able to identify the fist, foot, and baseball bat. Furthermore, we conducted the experiments for developmental variations through change over time setting up 5-weeks period including first damage as variation factor, and developing materials in each action through certain reagents. Specimen level of development depending on change over time was identified. As a result, each of initial level of development was seen no changes.

Keywords: hit marks, amino acid reagents, porcine skin, criminal tool

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Authors: Arash Khorasani Esmaeili, Rosna Mat Taha, Sadegh Mohajer

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Seeds of Trifolium pratense (Red clover) were exposed in vitro for 6 weeks to six levels of lead (Pb) concentrations (0, 50, 100, 150, 200, 250 µM) to analyze the effects on growth, total chlorophyll and total protein contents of grown plants against the lead accumulation. The growth of plants was negatively affected by various levels of lead treatment. The fresh and dry weights, as well as lengths of shoots and roots of grown plants under various lead treatments, were found significantly lower in comparison with the control plants. Total chlorophyll and total soluble protein contents of grown plants under lower concentrations of lead treatment did not show significant differences when compared with the control plants, although they were affected significantly in higher levels of lead accumulation (150-250 µM).

Keywords: trifolium pratense, lead accumulation, chlorophyll content, protein content

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Authors: Chitresh Kumar, Santanu Gupta

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The research work intends to understand the process of initiation, planning and development of capital-intensive urban area level infrastructure development in East Asian Cities (specific to Indian Cities). With the onset of emphasis on sustainable urban transport, self-financed urban local bodies, it has become of utmost important to identify infrastructure and projects on a priority basis, which provide optimal utility to the urban area. Through identification of Spatial, Demographic and Socio-Economic and Political Instability Parameters and their trends for the past 60 years at the urban area and state level, the paper attempts to identify the most suitable time period when initiation of the project would become economically and demographically viable for the city.

Keywords: urban planning, regional planning, mass transit, infrastructure development, spatial planning

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Authors: Cory A. Logston

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It is imperative researchers continue to explore every transformative strategy to increase empathy and awareness of racial bias. Racism is a social and political concept that uses stereotypical ideology to highlight racial inequities. Everyone has biases they may not be aware of toward disparate out-groups. There is some form of racism in every profession; doctors, lawyers, and teachers are not immune. There have been numerous successful and unsuccessful strategies to motivate and transform an individual’s unconscious biased attitudes. One method designed to induce a transformative experience and identify implicit bias is virtual reality (VR). VR is a technology designed to transport the user to a three-dimensional environment. In a virtual reality simulation, the viewer is immersed in a realistic interactive video taking on the perspective of a Black man. The viewer as the character experiences discrimination in various life circumstances growing up as a child into adulthood. For instance, the prejudice felt in school, as an adolescent encountering the police and false accusations in the workplace. Current research suggests that an immersive VR simulation can enhance self-awareness and become a transformative learning experience. This study uses virtual reality immersion and transformative learning theory to create empathy and identify any unintentional racial bias. Participants, White teachers, will experience a VR immersion to create awareness and identify implicit biases regarding Black students. The desired outcome provides a springboard to reconceptualize their own implicit bias. Virtual reality is gaining traction in the research world and promises to be an effective tool in the transformative learning process.

Keywords: empathy, implicit bias, transformative learning, virtual reality

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Authors: M. Pramila Devi, J. Praveena

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In today’s industrial scenario, the expectations and demand of customers are reaching great heights. In order to satisfy the customer requirements the users are increasingly turning towards fourth party logistics (4PL) service providers to manage their total supply chain operations. In this present research, initially, the criteria for the selection of integrated service providers have been identified and an integrated modal based on their inter-relationship has been developed with help of shippers, with this idea of what factors to be considered and their inter-relationships while selecting integrated service provider. Later, various methods deriving the priority weights viz. Analytical Hierarchy Process (AHP) have been employed for 4PL service provider selection. The derived priorities of 4PL alternatives using methods have been critically analyzed and compared for effective selection. The use of the modal indicates that the computed quantitative evaluation can be applied to improve the precision of the selection.

Keywords: analytical hierarchy process, fourth party logistics, priority weight, criteria selection

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Authors: Kristine D. de Leon, Junifer A. Abatayo, Jose Cristina M. Pariña

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The current study is a comparative analysis of the use of shell nouns as a cohesive device (CD) in an English for Second Language (ESL) setting in order to identify their use and relationship in the quality of second language (L2) writing. As these nouns were established to anticipate the meaning within, across or outside the text, their use has fascinated writing researchers. The corpus of the study included published articles from reputable journals and graduate students’ papers in order to analyze the frequency of shell nouns using “highly prevalent” nouns in the academic community, to identify the different lexicogrammatical patterns where these nouns occur and to the functions connected with these patterns. The result of the study implies that published authors used more shell nouns in their paper than graduate students. However, the functions of the different lexicogrammatical patterns for the frequently occurring shell nouns are somewhat similar. These results could help students in enhancing the cohesion of their text and in comprehending it.

Keywords: anaphoric, cataphoric, lexico-grammatical, shell nouns

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Authors: T. Nishimura, K. Doi, H. Fujimoto, T. Wada

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We conducted perception experiments on tactile symbols to elucidate the impact of the size of these letters on the level of perceptibility. This study was based on the accessible design perspective and aimed at expanding the availability of tactile symbols for the visually impaired who are unable to read Braille characters. In particular, this study targeted people with acquired visual impairments as users of the tactile symbols. The subjects (young and elderly individuals) in this study had normal vision. They were asked to participate in the experiments to identify tactile symbols while unable to see their hand during the experiments. This study investigated the relation between the size and perceptibility of tactile symbols based on an examination using test pieces of these letters in different sizes. The results revealed that the error rates for both young and elderly subjects converged to almost 0% when 12 mm size tactile symbols were used. The findings also showed that the error rate was low and subjects could identify the symbols in 5 s when 16 mm size tactile symbols were introduced.

Keywords: accessible design, tactile sense, tactile symbols, bioinformatic

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Authors: Eva Bodi, Szilvia Veres, Farzaneh Garousi, Szilvia Varallay, Bela Kovacs

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The aim of the present study was to examine whether increasing molybdenum (Mo) concentration affects on the growth and Mo concentration of maize and sunflower (Helianthus annuus L. cv Arena PR) seedlings within laboratory conditions. In this experiment calcareous chernozem soil was used and Mo was supplemented into the soil as ammonium molybdate [(NH4)6Mo7O24.4H2O] in four different concentrations as follow: 0 (control), 30, 90 and 270 mg/kg. In this study we found that molybdenum in small amount (30 mg/kg) affects positively on growth of maize and sunflower seedlings, however, higher concentration of Mo reduces the dry weights of shoots and roots. In the case of maize the highest Mo treatment (270 mg/kg) and in sunflower 90 mg/kg treatment caused significant reduction in plant growth. In addition, we observed that molybdenum contents in the roots and shoots were very low in case of control soil but were significantly elevated with increasing concentration of Mo treatment. Only in case of sunflower the highest 270 mg/kg Mo treatment caused decrease in Mo concentration.

Keywords: dry weight, maize, molybdenum, sunflower

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Authors: Mohamed E. Harb, Enas Moustafa, Shaker Ebrahim, Moataz Soliman

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In this paper pressure detectors were synthesized and characterized using hybrid perovskite/PVDF composites as an active layer. Methylammonium lead iodide (MAPbI₃) was synthesized from methylammonium iodide (MAI) (CH₃NH₃I) and lead iodide (PbI₂). Composites of perovskite/PVDF using different weight ratio were prepared as the active material. PVDF with weights percentages of 6%, 8%, and 10% was used. All prepared materials were investigated by x-ray diffraction (XRD), Fourier transforms infrared spectrum (FTIR) and scanning electron microscopy (SEM). A Versastat 4 Potentiostat Galvanostat instrument was used to perform the current-voltage characteristics of the fabricated sensors. The pressure sensors exhibited a voltage increase with applying different forces. Also, the current-voltage characteristics (CV) showed different effects with applying forces. So, the results showed a good pressure sensing performance.

Keywords: perovskite semiconductor, hybrid perovskite, PVDF, Pressure sensing

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Authors: Faisal AlShammari, Abdulmajid Addali, Mosab Alrashed

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It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm, and such machines are important to the industry. However, the overwhelming proportion of studies have investigated the use of AE techniques for condition monitoring of higher-speed machines (typically several hundred rpm, or even higher). Few researchers have investigated the application of these techniques to low-speed machines ( < 100 rpm). This paper addressed this omission and has established which, of the available, AE techniques are suitable for the detection of incipient faults and measurement of fault growth in low-speed bearings. The first objective of this paper program was to assess the applicability of AE techniques to monitor low-speed bearings. It was found that the measured statistical parameters successfully monitored bearing conditions at low speeds (10-100 rpm). The second objective was to identify which commonly used statistical parameters derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify the onset of a fault in the out race. It was found that these parameters effectually identify the presence of a small fault seeded into the outer races. Also, it is concluded that rotational speed has a strong influence on the measured AE parameters but that they are entirely independent of the load under such load and speed conditions.

Keywords: acoustic emission, condition monitoring, NDT, statistical analysis

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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