Search results for: SURF(Speed-Up Robust Features)

Authors: Aamir Mubashar, Ibrahim Fiaz

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This research presents a three-dimensional finite element modelling strategy to simulate damage in a quasi-static three-point bending analysis of woven twill 2/2 type carbon fibre reinforced plastic (CFRP) composite on a micro-meso level using cohesive zone modelling technique. A meso scale finite element model comprised of a number of plies was developed in the commercial finite element code Abaqus/explicit. The interfaces between the plies were explicitly modelled using cohesive zone elements to allow for debonding by crack initiation and propagation. Load-deflection response of the CRFP within the quasi-static range was obtained and compared with the data existing in the literature. This provided validation of the model at the global scale. The outputs resulting from the global model were then used to develop a simulation model capturing the micro-meso scale material features. The sub-model consisted of a refined mesh representative volume element (RVE) modelled in texgen software, which was later embedded with cohesive elements in the finite element software environment. The results obtained from the developed strategy were successful in predicting the overall load-deflection response and the damage in global and sub-model at the flexure limit of the specimen. Detailed analysis of the effects of the micro-scale features was carried out.

Keywords: woven composites, multi-scale modelling, cohesive zone, finite element model

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Abderrahmane Hamdi, Julie Chalon, Benoit Dodin, Philippe Champagne

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In this report, we present a simple route to realize robust, hydrophobic, and highly transparent coatings using organic polysilazane (durazane) and zinc oxide nanoparticles (ZnO). These coatings were deposited by spraying the mixture solution on glass slides. Thus, the properties of the films were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), UV–vis-NIR spectrophotometer, and water contact angle method. This sprayable polymer mixed with ZnO nanoparticles shows high transparency for visible light > 90%, a hydrophobic character (CA > 90°), and good mechanical and chemical stability. The coating also demonstrates excellent self-cleaning properties, which makes it a promising candidate for commercial use.

Keywords: coatings, durability, hydrophobicity, organic polysilazane, self-cleaning, transparence, zinc oxide nanoparticles

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Authors: Jingjing Ye, Cijun Fan, Yan Dong

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The development of financial sector plays an important role in shaping industrial structure. However, evidence on the micro-level channels through which this relation manifest remains relatively sparse, particularly for developing countries. In this paper, we compile an industry-by-city dataset based on manufacturing firms and registered banks in 287 Chinese cities from 1998 to 2008. Based on a difference-in-difference approach, we find the highly concentrated banking sector decreases the competitiveness of firms in each manufacturing industry. There are two main reasons: i) bank accessibility successfully fosters firm expansion within each industry, however, only for sufficiently large enterprises; ii) state-owned enterprises are favored by the banking industry in China. The results are robust after considering alternative concentration and external finance dependence measures.

Keywords: bank concentration, China, difference-in-difference, industry structure

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Authors: Fiyinfoluwa Giwa, Nicholas Ngepah

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This paper investigates the relationship between the Fourth Industrial Revolution and food security in South Africa. The Ordinary Least Square was adopted from 2012 Q1 to 2021 Q4. The study used artificial intelligence investment and the food production index as the measure for the fourth industrial revolution and food security, respectively. Findings reveal a significant and positive coefficient of 0.2887, signifying a robust statistical relationship between AI adoption and the food production index. As a policy recommendation, this paper recommends the introduction of incentives for farmers and agricultural enterprises to adopt AI technologies -and the expansion of digital connectivity and access to technology in rural areas.

Keywords: Fourth Industrial Revolution, food security, artificial intelligence investment, food production index, ordinary least square

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Authors: Juliet Udoudom

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Inappropriate complement selection constitutes one of the major features of non-standard complementation in the Nigerian users of English output of sentence construction. This paper investigates complement clause choice in Written Educated Nigerian English (ENE) and offers some results. It aims at determining preferred and dispreferred patterns of complement clause selection in respect of verb heads in English by selected Nigerian users of English. The complementation data analyzed in this investigation were obtained from experimental tasks designed to elicit complement categories of Verb – Noun -, Adjective – and Prepositional – heads in English. Insights from the Government – Binding relations were employed in analyzing data, which comprised responses obtained from one hundred subjects to a picture elicitation exercise, a grammaticality judgement test, and a free composition task. The findings indicate a general tendency for clausal complements (CPs) introduced by the complementizer that to be preferred by the subjects studied. Of the 235 tokens of clausal complements which occurred in our corpus, 128 of them representing 54.46% were CPs headed by that, while whether – and if-clauses recorded 31.07% and 8.94%, respectively. The complement clause-type which recorded the lowest incidence of choice was the CP headed by the Complementiser, for with a 5.53% incident of occurrence. Further findings from the study indicate that semantic features of relevant embedding verb heads were not taken into consideration in the choice of complementisers which introduce the respective complement clauses, hence the that-clause was chosen to complement verbs like prefer. In addition, the dispreferred choice of the for-clause is explicable in terms of the fact that the respondents studied regard ‘for’ as a preposition, and not a complementiser.

Keywords: complement, complement clause complement selection, complementisers, government-binding

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Esra Yaldız, Tugba Bulbul Bahtiyar, Dicle Aydın

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Humans meet their need for shelter via housing which they structure in line with habits and necessities. In housing culture, traditional dwelling has an important role as a social and cultural transmitter. It provides concrete data by being planned in parallel with users’ life style and habits, having their own dynamics and components as well as their designs in harmony with nature, environment and the context they exist. Textures of traditional dwelling create a healthy and cozy living environment by means of adaptation to natural conditions, topography, climate, and context; utilization of construction materials found nearby and usage of traditional techniques and forms; and natural isolation of construction materials used. One of the examples of traditional settlements in Anatolia is Kilistra (Gökyurt) settlement of Konya province. Being among the important centers of Christianity in the past, besides having distinctive architecture, culture, natural features, and geographical differences (climate, geological structure, material), Kilistra can also be identified as a traditional settlement consisting of family, religious and economic structures as well as cultural interaction. The foundation of this study is the traditional residential texture of Kilistra with its unique features. The objective of this study is to assess the conformity of traditional residential texture of Kilistra with present topography, climatic data, and geographical values within the context of human scale construction, usage of green space, indigenous construction materials, construction form, building envelope, and space organization in housing.

Keywords: traditional residential architecture, Kilistra, Anatolia, Konya

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

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Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Okike Benjamin, Garba E J. D.

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Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt.

Keywords: image encryption, matrices, pixel, matrix transpose

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Authors: Faezah Shekh Abdullah, Mohd. Azizuddin Mohd. Yussof, Komathy Thiagarajan, Hasnoorina Husin, Noor Azreena Abd Aziz

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Polycystic ovary syndrome has been associated with multiple disorders such as endocrine disorder, metabolic syndrome, infertility, and endometrial cancer. Women with polycystic ovary syndrome (PCOS) are anticipated to develop three times more chances for endometrial cancer than women without PCOS. This study, therefore, was conducted to determine the association between polycystic ovary syndrome and endometrial cancer and to determine the cervical cytology features of PCOS. Patients attending the Subfertility Clinic of the National Population and Family Development Board were recruited and examined physically by medical practitioners. They were categorized into two groups; i) the PCOS group if they met Rotterdam Criteria 2004 and ii) the control group if they did not meet Rotterdam Criteria 2004. Cervical sampling was done on all patients via the Liquid-Based Cytology (LBC) method in the pre-and post-subfertility treatment. A total of 167 patients participated in the study, of which 79 belonged to the PCOS group and 88 to the control group. The findings showed no cervical and endometrial cancer cases in both groups. The Liquid-Based Cytology results in the PCOS group displayed more cases with cellular changes, i.e., benign inflammation, atrophic smear and Candida sp. infection. To conclude, no association was found between polycystic ovary syndrome and endometrial cancer. A more holistic study with a higher number of participants can further determine the association between endometrial cancer and PCOS. Furthermore, a longer duration between LBC pre- and post-subfertility treatment should be implied to observe changes in the cervical cells.

Keywords: endometrial cancer, liquid-based cytology, PCOS, polycystic ovary syndrome

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Abhimanyu Thakur, Youngjin Lee

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Glioma is a lethal brain cancer whose early diagnosis and prognosis are limited due to the dearth of a suitable technique for its early detection. Current approaches, including magnetic resonance imaging (MRI), computed tomography (CT), and invasive biopsy for the diagnosis of this lethal disease, hold several limitations, demanding an alternative method. Recently, extracellular vesicles (EVs) have been used in numerous biomarker studies, majorly exosomes and microvesicles (MVs), which are found in most of the cells and biofluids, including blood, cerebrospinal fluid (CSF), and urine. Remarkably, glioma cells (GMs) release a high number of EVs, which are found to cross the blood-brain-barrier (BBB) and impersonate the constituents of parent GMs including protein, and lncRNA; however, biophysical properties of EVs have not been explored yet as a biomarker for glioma. We isolated EVs from cell culture conditioned medium of GMs and regular primary culture, blood, and urine of wild-type (WT)- and glioma mouse models, and characterized by nano tracking analyzer, transmission electron microscopy, immunogold-EM, and differential light scanning. Next, we measured the biophysical parameters of GMs-EVs by using atomic force microscopy. Further, the functional constituents of EVs were examined by FTIR and Raman spectroscopy. Exosomes and MVs-derived from GMs, blood, and urine showed distinction biophysical parameters (roughness, adhesion force, and stiffness) and different from that of regular primary glial cells, WT-blood, and -urine, which can be attributed to the characteristic functional constituents. Therefore, biophysical features can be potential diagnostic biomarkers for glioma.

Keywords: glioma, extracellular vesicles, exosomes, microvesicles, biophysical properties

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Authors: Mostafa Vahdani, Mohsen Asadnia, Shuying Wu

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Huge amounts of e-waste are being produced by the rapidly expanding use of electronics; the majority of this material is either burned or dumped directly in landfills since recycling would either be impracticable or too expensive. Degradable and environmentally friendly materials are therefore seen as the answer to this urgent problem. Here, we create strain sensors that are biodegradable, robust, and incredibly flexible using thin films of sodium carboxymethyl cellulose (NaCMC), glycerol, and polyvinyl alcohol (PVA). Due to the creation of many inter- or intramolecular hydrogen bonds, the polymer blends (NaCMC/PVA/glycerol) exhibit a failure strain of up to 330% and negligible hysteresis when exposed to cyclic stretching-releasing. What's more intriguing is that the sensors can degrade completely in deionized water at a temperature of 95 °C in about 25 minutes. This project illustrates a novel method for developing wearable electronics that are environmentally beneficial.

Keywords: degradable, stretchable, strain sensors, wearable electronics.

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Authors: Waseem Tahir, Syed Hussain Imran Jaffery, Mohammad Azam

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In this research work, liquid nitrogen gas (LN2) is used as a cryogenic media to optimize the cutting parameters for evaluation of tool flank wear width of Tungsten Carbide Insert (CNMG 120404-WF 4215) while turning a high strength alloy steel. Robust design concept of Taguchi L9 (34) method is applied to determine the optimum conditions. The analysis is revealed that cryogenic impact is more significant in reduction of the tool flank wear. However, High Speed Machining is shown most significant as compare to cooling media on work piece surface roughness.

Keywords: turning, cryogenic cooling, liquid nitrogen, flank wear, surface finish

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Naresh Radaliyagoda, Nigel M. Jennett, Rong Lan, David Parfitt

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A series of length scale engineered multilayer material with temperature robust mechanical properties has been suggested. A range of polycrystalline copper sub-layers with the thickness varying from 1 to 25μm and buried in between two nickel layers was produced using electrodeposition dual bath technique. The structure of the multilayers was characterized using Electron Backscatter Diffraction and Scanning Electron Microscope. The interface effect on the hardness and elastic modulus was tested using Nano-indentation. Results of the grain size and layer thickness measurements, and indentation hardness have been compared. It is found that there is a combined length scale effect that improves mechanical properties in Ni/Cu multilayer structures.

Keywords: nano-indentation, size effect, multilayers, electrodeposition

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Authors: Yemane Kahsay Berhe

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The multipurpose cactus pear plant with great potential as a source of food and livestock feed faced a threat from Dactylopius spp in different countries. Specifically, D. coccus is an important pest damaging significant areas in Tigray-Ethiopia. Using pest-resistant cultivars is an important element of an integrated pest management strategy, and studying the mechanisms of resistance is vital. It can be chemical or physical, such as oxalate crystals and other cladode characteristics. Cladode features of six cultivars (three O. ficus-indica, two O. cochenillifera, and one O. robusta) were examined for resistance to D. coccus in a completely randomized design (CRD) with three replications. ‘Rojo Pelón’ (O. ficus-indica), ‘Robusta’ (O. robusta), and ‘Bioplástico’ (O. cochinillifera) are resistant cultivars; and ‘Atlixco’ and ‘Chicomostoc’ (O. ficus-indica) and ‘Nopalea’ (O. cochinillifera) are susceptible. Cultivars showed a significant difference in cladode weight in g, cladode length, cladode width, and cladode thickness in cm, where cladode thickness was higher in ‘Rojo Pelón’ followed by ‘Robusta’. Calcium oxalates number per mm was higher in ‘Bioplástico’ (20.7+2.08) followed by ‘Robusta’ (18.9+2.31) and ‘Rojo Pelón’ (15.9+0.34); and similarly, epidermis thickness found higher in ‘Bioplástico’ (0.21+0.032) and ‘Robusta’ (0.19+0.014), but similar with ‘Rojo Pelón’ (0.18+0.026). However, cuticle thickness didn’t show a difference among cultivars. Cladode thickness, calcium oxalates number, and epidermis thickness had positive correlations with resistance. These results demonstrate that calcium oxalates number and epidermis thickness might positively affect D. coccus resistance in O. ficus-indica. This feeding-barring role and the insect-plant interaction need to be studied.

Keywords: cactus pear, resiatnce, druses, epidermis thickness

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Authors: Gamal Seliem, Hassan Seliem

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Aswan area is one of the important areas in Egypt and because it encompasses the vital engineering structure of the High dam, so it has been selected for the present study. The study of the crustal deformation and gravity associated with earthquake activity in the High Dam area of great importance for the safety of the High Dam and its economic resources. This paper deals with using micro-gravity, precise leveling and GPS data for geophysical and geodetically studies. For carrying out the detailed gravity survey in the area, were established for studying the subsurface structures. To study the recent vertical movements, a profile of 10 km length joins the High Dam and Aswan old dam were established along the road connecting the two dams. This profile consists of 35 GPS/leveling stations extending along the two sides of the road and on the High Dam body. Precise leveling was carried out with GPS and repeated micro-gravity survey in the same time. GPS network consisting of nine stations was established for studying the recent crustal movements. Many campaigns from December 2001 to December 2014 were performed for collecting the gravity, leveling and GPS data. The main aim of this work is to study the structural features and the behavior of the area, as depicted from repeated micro-gravity, precise leveling and GPS measurements. The present work focuses on the analysis of the gravity, leveling and GPS data. The gravity results of the present study investigate and analyze the subsurface geologic structures and reveal to there be minor structures; features and anomalies are taking W-E and N-S directions. The geodetic results indicated lower rates of the vertical and horizontal displacements and strain values. This may be related to the stability of the area.

Keywords: repeated micro-gravity changes, precise leveling, GPS data, Aswan High Dam

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Authors: D. P. Lawrence, T. M. M. D. Ariyarathna, W. N. K. De Silva, M. D. S. C. De Silva, Lasantha Abeysiri, Pradeep Abeygunawardhna

Abstract:

Safari traveling is one of the most famous hobbies all over the world. In Sri Lanka, 'Yala' is the second-largest national park, which is a better place to go for a safari. Many number of local and foreign travelers are coming to go for a safari in 'Yala'. But 'Yala' does not have a mobile application that is made to facilitate the traveler with some important features that the traveler wants to achieve in the safari experience. To overcome these difficulties, the proposed mobile application by adding those identified features to make travelers, guiders, and administration's works easier. The proposed safari traveling guidance mobile application is called 'SMART SAFARI' for the 'Yala' National Park in Sri Lanka. There are four facilities in this mobile application that provide for travelers as well as the guiders. As the first facility, the guider and traveler can view the created map of the park, and the guider can add temporary locations of animals and special locations on the map. This is a Geographic Information System (GIS) to capture, analyze, and display geographical data. And as the second facility is to generate optimal paths according to the travelers' requirements through the park by using machine learning techniques. In the third part, the traveler can get information about animals using an animal identification system by capturing the animal. As in the other facility, the traveler will be facilitated to add reviews and a rate and view those comments under categorized sections and pre-defined score range. With those facilities, this user-friendly mobile application provides the user to get a better experience in safari traveling, and it will probably help to develop tourism culture in Sri Lanka.

Keywords: animal identification system, geographic information system, machine learning techniques, pre defined score range

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Authors: Muhammad Akhtaruzzaman

Abstract:

The impact of corporate environmental social and governance (ESG) on financial performance is often difficult to quantify despite the ESG related theories predict that ESG performance improves financial performance of a company. This research examines the link between corporate ESG performance and the financial performance of the NZX (New Zealand Stock Exchange) listed companies. For this purpose, this research utilizes mixed methods approaches to examine and understand this link. While quantitative results found no robust evidence of such a link, however, the qualitative analysis of content data suggests a strong cooccurrence exists between ESG performance and financial performance. The findings of this research have important implications for policymakers to support higher ESG-performing companies and for management practitioners to develop ESG-related strategies.

Keywords: ESG, financial performance, New Zealand firms, thematic analysis, mixed methods

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Authors: Balaji Viswanathan, Tim Oates

Abstract:

A number of pilot projects have commenced across the world to use robots for senior care. We aim to measure the likeability of these robots among seniors and help robot designers focus on the features that matter. We built a robot likability score with over 30 parameters and used this to interview 50 seniors in various locations in the United States. This paper presents the results of this field research.

Keywords: HRI, assistive robotics, social robotics, HCI, aging

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Authors: Weeam Abdulrahman, Gawaher Al-Madwary, Fatima Al-Ammari, Razan Mohammad

Abstract:

This research discusses the AI features in Replika which is a dialog with a customized characters application, interaction and communication with AI in different ways that is provided for the user. spreading a survey with questions on how the AI worked is one approach of exposing the app to others to utilize and also we made an analysis that provides us with the conclusion of our research as a result, individuals will be able to try out the app. In the methodology we explain each page that pops up in the screen while using replika and Specify each part and icon.

Keywords: Replika, AI, artificial intelligence, dialog app

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Authors: Keunhong Chae, Seokho Yoon

Abstract:

In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments.

Keywords: frequency offset estimation, maximum-likelihood, non-Gaussian noise environment, OFDM, training symbol

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Authors: Oleg Redkin, Olga Bernikova

Abstract:

It is commonly accepted that every language is both pure linguistic phenomenon as well as socially significant communicative system, which exists on the basis of certain society - its collective 'native speaker'. Therefore the language evolution and features besides its own linguistic rules and regulations are also defined by the influence of a number of extra-linguistic factors. The above mentioned statement may be illustrated by the example of the Arabic language which may be characterized by the following peculiarities: - the inner logic of the Arabic language - the 'algebraicity' of its morphological paradigms and grammar rules; - association of the Arabic language with the sacred texts of Islam, its close ties with the pre-Islamic and Islamic cultural heritage - the pre-Islamic poetry and Islamic literature and science; - territorial distribution, which in recent years went far beyond the boundaries of its traditional realm due to the development of new technologies and the spread of mass media, and what is more important, migration processes; - association of the Arabic language with the so called 'Renaissance of Islam'. These peculiarities should be remembered while considering the status of the Modern Standard Arabic (MSA) language or the Classical Arabic (CA) language as well as the Modern Arabic (MA) dialects in synchrony or from the diachronic point of view. Continuity of any system in diachrony on the one hand depends on the level of its ability to adapt itself to changing environment and by its internal ties on the other. Structural durability of language is characterized by its inner logic, hierarchy of paradigms and its grammar rules, as well as continuity of their implementation in acts of everyday communication. Since the Arabic language is both linguistic and social phenomenon the process of the Arabic language acquisition and study should not be focused only on the knowledge about linguistic features or development of communicative skills alone, but must be supplied with the information related to culture, history and religion of peoples of certain region that will expand and enrich competences of the target audience.

Keywords: Arabic, culture, Islam, language

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Authors: Ying Zhu, Ning Wu, Hai-Dong Huang, Yu-Chao Dong, Qin-Ying Sun, Wei Zhang, Qin Wang, Qiang Li

Abstract:

Background and study aims: Tracheobronchopathia osteochondroplastica (TO) is an uncommon disease of the tracheobronchial system that leads to narrowing of the airway lumen from cartilaginous and/or osseous submucosal nodules. The aim of this study is to perform a detailed review of this rare disease in a large cohort of patients with TO proven by fiberoptic bronchoscopy from China. Patients and Methods: Retrospective chart review was performed on 41,600 patients who underwent bronchoscopy in the Department of Respiratory Medicine of Changhai Hospital between January 2005 and December 2012. Cases of TO were identified based on characteristic features during bronchoscopic examination. Results: 22 cases of bronchoscopic TO were identified. Among whom one-half were male and the mean age was 47.45 ±10.91 years old. The most frequent symptoms at presentation were chronic cough (n=14) and increased sputum production (n=10). Radiographic abnormalities were observed in 3/18 patients and findings on computed tomography consistent with TO such as beaded intraluminal calcifications and/or increased luminal thickenings were observed in 18/22 patients. Patients were classified into the following categories based on the severity of bronchoscopic findings: Stage I (n=2), Stage II (n=6) and Stage III(n=14). The result that bronchoscopic improvement was observed in 2 patients administered with inhaled corticosteroids suggested that resolution of this disease is possible. Conclusions: TO is a benign disease with slow progression, which could be roughly divided into 3 stages on the basis of the characteristic endoscopic features and histopathologic findings. Chronic inflammation was thought to be more important than the other existing plausible hypotheses in the course of TO. Inhaled corticosteroids might have some impact on patients at Stage I/II.

Keywords: airway obstruction, bronchoscopy, etiology, Tracheobronchopathia osteochondroplastica (TO), treatment

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Authors: Chiara Cosentino, Carlo Pruneti, Carla Merisio, Domenico Sgromo

Abstract:

Introduction – Psychoneuroimmunology as approach clearly showed how psychological features can influence health through specific physiological pathways linked to the stress reaction. This can be true also in cancer, in its latter conceptualization seen as a chronic disease. Therefore, it is still not clear how the psychological features can combine with a physiological specific path, for a better adjustment to cancer. The aim of this study is identifying how in Italian survivors, perceived social support, body image, coping and quality of life correlate with or influence Heart Rate Variability (HRV), the physiological parameter that can mirror a condition of chronic stress or a good relaxing capability. Method - The study had an exploratory transversal design. The final sample was made of 38 ovarian cancer survivors aged from 29 to 80 (M= 56,08; SD=12,76) following a program for Ovarian Cancer at the Oncological Clinic, University Hospital of Parma, Italy. Participants were asked to fill: Multidimensional Scale of Perceived Social Support (MSPSS); Derridford Appearance Scale-59 (DAS-59); Mental Adjustment to Cancer (MAC); Quality of Life Questionnaire (EORTC). For each participant was recorded Short-Term HRV (5 minutes) using emWavePro. Results– Data showed many interesting correlations within the psychological features. EORTC scores have a significant correlation with DAS-59 (r =-.327 p <.05), MSPSS (r =.411 p<.05), and MAC scores, in particular with the strategy Fatalism (r =.364 p<.05). A good social support improves HRV (F(1,33)= 4.27 p<.05). Perceiving themselves as effective in their environment, preserving a good role functioning (EORTC), positively affects HRV (F(1,33)=9.810 p<.001). Women admitting concerns towards body image seem prone to emotive disclosure, reducing emotional distress and improving HRV (β=.453); emotional avoidance worsens HRV (β=-.391). Discussion and conclusion - Results showed a strong relationship between body image and Quality of Life. These data suggest that higher concerns on body image, in particular, the negative self-concept linked to appearance, was linked to the worst functioning in everyday life. The relation between the negative self-concept and a reduction in emotional functioning is understandable in terms of possible distress deriving from the perception of body appearance. The relationship between a high perceived social support and a better functioning in everyday life was also confirmed. In this sample fatalism, was associated with a better physical, role and emotional functioning. In these women, the presence of a good support may activate the physiological Social Engagement System improving their HRV. Perceiving themselves effective in their environment, preserving a good role functioning, also positively affects HRV, probably following the same physiological pathway. A higher presence of concerns about appearance contributes to a higher HRV. Probably women admitting more body concerns are prone to a better emotive disclosure. This could reduce emotional distress improving HRV and global health. This study reached preliminary demonstration of an ‘Integrated Model of Defense’ in these cancer survivors. In these model, psychological features interact building a better quality of life and a condition of psychological well-being that is associated and influence HRV, then the physiological condition.

Keywords: cancer survivors, heart rate variability, ovarian cancer, psychophysiological adjustment

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