Search results for: feature selection feature subset selection feature extraction/transformation

Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Bunthida Chunngam, Thanyanan Worasesthaphong

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This research had objective to develop of the website learning the local wisdom in Phra Nakhon Si Ayutthaya province and studied satisfaction of system user. This research sample was multistage sample for 100 questionnaires, analyzed data to calculated reliability value with Cronbach’s alpha coefficient method α=0.82. This system had 3 functions which were system using, system feather evaluation and system accuracy evaluation which the statistics used for data analysis was descriptive statistics to explain sample feature so these statistics were frequency, percentage, mean and standard deviation. This data analysis result found that the system using performance quality had good level satisfaction (4.44 mean), system feather function analysis had good level satisfaction (4.11 mean) and system accuracy had good level satisfaction (3.74 mean).

Keywords: website, learning, local wisdom, Phra Nakhon Si Ayutthaya province

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Authors: Nurdan Tumbek Tekeoglu

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With rising importance in all over the world, crowdfunding has become a new financing and marketing method for film industry. Crowdfunding is a new practice in film industry for funding a film project by raising monetary contributions from a large group of people. By crowdfunding an estimate fund of 20 billion USD has been raised in 2015. Through the crowdfunding platforms not only the film makers, but also the entrepreneurs and nongovernmental organizations finance and market their projects. Among the prominent crowdfunding platforms in Turkey, we can list Crowdfon, Fonlabeni, Kickstarter, Indiego, Bi Ayda, and Fongogo platforms. In 2014 the Turkish film industry celebrated its 100th anniversary and reached its peak producing around 150-200 films a year reminding the brilliant years of Yesilcam period. In general feature films apply for crowdfunding. Until April 2015 more than 190 films applied for crowdfunding platforms. Crowdfunding has a promising future in Turkey, since donation traditions has an important place in Turkish culture traditionally. This paper is exploring the marketing of the crowdfunding platforms established in Turkey in order for the films meet their target groups during the pre-production period.

Keywords: crowdfunding, marketing of films, Turkey, Turkish film industry

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Juan F. Gutierrez, Jesus M. Quintero, Diego Sandoval

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An important feature of LED technology is the fast on-off commutation, which allows data transmission. Visible Light Communication (VLC) is a wireless method to transmit data with visible light. Modulation formats such as On-Off Keying (OOK) and Color Shift Keying (CSK) are used in VLC. Since CSK is based on three color bands uses red, green, and blue monochromatic LED (RGB-LED) to define a pattern of chromaticities. This type of CSK provides poor color quality in the illuminated area. This work presents the design and implementation of a VLC system using RGB-based CSK with 16, 8, and 4 color points, mixing with a steady baseline of a phosphor white-LED, to improve the color quality of the LED-Fixture. The experimental system was assessed in terms of the Color Rendering Index (CRI) and the Symbol Error Rate (SER). Good color quality performance of the LED-Fixture was obtained with an acceptable SER. The laboratory setup used to characterize and calibrate an LED-Fixture is described.

Keywords: VLC, indoor lighting, color quality, symbol error rate, color shift keying

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Daniel Tochwin

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Continuous improvement is an essential part of effective process performance management. In order to achieve continuous quality improvement, each organization must use the appropriate selection of tools and techniques. The basic condition for success is a proper understanding of the business need faced by the company and the selection of appropriate methods to improve a given production process. The main aim of this article is to analyze the methods of conduct which are popular in practice when implementing process improvements and then to determine whether the tested methods include repetitive systematics of the approach, i.e., a similar sequence of the same or similar actions. Based on an extensive literature review, 4 methods of continuous improvement of production processes were selected: A3 report, Gemba Kaizen, PDCA cycle, and Deming cycle. The research shows that all frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re)interpretation" and the need to adapt the continuous improvement approach to the specific business process. The research shows that all the frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re) interpretation" and the need to adapt the continuous improvement approach to the specific business process.

Keywords: continuous improvement, lean methods, process improvement, PDCA

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Authors: Ljerka Kratofil Krehula, Vanja Gilja, Andrea Husak, Sniježana Šuka, Zlata Hrnjak-Murgić

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Zinc oxide (ZnO) can be used as photocatalysts for water purification. However, one particular interest is given on the integration of inorganic ZnO nanoclusters with conducting polymers because the resulting nanocomposites may possess unique properties and enhanced photocatalytic activity in comparison to pure ZnO, using UV and also visible light. It is needed to explore the appropriate structure of polypyrrole that can induce activation of ZnO photocatalyst since the synthesis of organic/inorganic hybrid materials can result in a synergistic and complementary feature, increasing ZnO photocatalytic efficiency. In this paper several different composites of polypyrrole/zinc oxide (ZnO) were studied. Composite samples were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), cyclic voltammetry (CV) and scanning electron microscopy (SEM). The photocatalytic efficiency of prepared samples was studied as a decomposition of Reactive Red 45 (RR 45) dye, which was monitored by UV-Vis spectroscopy as a change in absorbance of characteristic wavelength at 542 nm. Results show good photocatalytic efficiency of all nanocomposite samples.

Keywords: photocatalysis, polypyrrole, wastewater, zinc oxide

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

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Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

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Authors: M. Nosik, I. Rymanova, N. Adamovich, S. Sevostyanihin, K. Ryzhov, Y. Kuimova, A. Kravtchenko, N. Sergeeva, A. Sobkin

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HIV and Tuberculosis (TB) infections each speed the other's progress. HIV-infection increases the risk of TB disease. At the same time, TB infection is associated with clinical progression of HIV-infection. HIV+TB co-infected patients are also at higher risk of acquiring new opportunistic infections. An important feature of disease progression and clinical outcome is the innate and acquired immune responses. HIV and TB, however, have a spectrum of dysfunctions of the immune response. As cytokines play a crucial role in the immunopathology of both infections, it is important to study immune interactions in patients with dual infection HIV+TB. Plasma levels of proinflammatory cytokines IL-2, IFN-γ and immunoregulating cytokines IL-4, IL-10 were evaluated in 75 patients with dual infection HIV+TB, 58 patients with HIV monoinfection and 50 patients with TB monoinfection who were previously naïve for HAART. The decreased levels of IL-2, IFN-γ, IL-4 and IL-10 were observed in patients with dual infection HIV+TB in comparison with patients who had only HIV or TB which means the profound suppression of Th1 and Th2 cytokine secretion. Thus, those cytokines could possibly serve as immunological markers of progression of HIV-infection in patients with TB.

Keywords: HIV, tuberculosis (TB), HIV associated with TB, Th1/ Th2 cytokine expression

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Authors: Muzaffar Shaikh, Shoaib Shaikh, Mark Moyou, Gaby Hawat

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This paper presents the use of Analytic Hierarchy Process (AHP) in evaluating the site selection of a new plant by a corporation. Due to intense competition at a global level, multinational corporations are continuously striving to minimize production and shipping costs of their products. One key factor that plays significant role in cost minimization is where the production plant is located. In the U.S. for example, labor and land costs continue to be very high while they are much cheaper in countries such as India, China, Indonesia, etc. This is why many multinational U.S. corporations (e.g. General Electric, Caterpillar Inc., Ford, General Motors, etc.), have shifted their manufacturing plants outside. The continued expansion of the Internet and its availability along with technological advances in computer hardware and software all around the globe have facilitated U.S. corporations to expand abroad as they seek to reduce production cost. In particular, management of multinational corporations is constantly engaged in concentrating on countries at a broad level, or cities within specific countries where certain or all parts of their end products or the end products themselves can be manufactured cheaper than in the U.S. AHP is based on preference ratings of a specific decision maker who can be the Chief Operating Officer of a company or his/her designated data analytics engineer. It serves as a tool to first evaluate the plant site selection criteria and second, alternate plant sites themselves against these criteria in a systematic manner. Examples of site selection criteria are: Transportation Modes, Taxes, Energy Modes, Labor Force Availability, Labor Rates, Raw Material Availability, Political Stability, Land Costs, etc. As a necessary first step under AHP, evaluation criteria and alternate plant site countries are identified. Depending upon the fidelity of analysis, specific cities within a country can also be chosen as alternative facility locations. AHP experience in this type of analysis indicates that the initial analysis can be performed at the Country-level. Once a specific country is chosen via AHP, secondary analyses can be performed by selecting specific cities or counties within a country. AHP analysis is usually based on preferred ratings of a decision-maker (e.g., 1 to 5, 1 to 7, or 1 to 9, etc., where 1 means least preferred and a 5 means most preferred). The decision-maker assigns preferred ratings first, criterion vs. criterion and creates a Criteria Matrix. Next, he/she assigns preference ratings by alternative vs. alternative against each criterion. Once this data is collected, AHP is applied to first get the rank-ordering of criteria. Next, rank-ordering of alternatives is done against each criterion resulting in an Alternative Matrix. Finally, overall rank ordering of alternative facility locations is obtained by matrix multiplication of Alternative Matrix and Criteria Matrix. The most practical aspect of AHP is the ‘what if’ analysis that the decision-maker can conduct after the initial results to provide valuable sensitivity information of specific criteria to other criteria and alternatives.

Keywords: analytic hierarchy process, multinational corporations, plant site selection, preference ratings

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Authors: Yoftahe Nigussie Worku

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This report unveils a meticulous project focused on the design intricacies of a Fire Tube Boiler tailored for the efficient generation of saturated steam. The overarching objective is to produce 2000kg/h of saturated steam at 12-bar design pressure, achieved through the development of an advanced fire tube boiler. This design is meticulously crafted to harmonize cost-effectiveness and parameter refinement, with a keen emphasis on material selection for component parts, construction materials, and production methods throughout the analytical phases. The analytical process involves iterative calculations, utilizing pertinent formulas to optimize design parameters, including the selection of tube diameters and overall heat transfer coefficients. The boiler configuration incorporates two passes, a strategic choice influenced by tube and shell size considerations. The utilization of heavy oil fuel no. 6, with a higher heating value of 44000kJ/kg and a lower heating value of 41300kJ/kg, results in a fuel consumption of 140.37kg/hr. The boiler achieves an impressive heat output of 1610kW with an efficiency rating of 85.25%. The fluid flow pattern within the boiler adopts a cross-flow arrangement strategically chosen for inherent advantages. Internally, the welding of the tube sheet to the shell, secured by gaskets and welds, ensures structural integrity. The shell design adheres to European Standard code sections for pressure vessels, encompassing considerations for weight, supplementary accessories (lifting lugs, openings, ends, manhole), and detailed assembly drawings. This research represents a significant stride in optimizing fire tube boiler technology, balancing efficiency and safety considerations in the pursuit of enhanced saturated steam production.

Keywords: fire tube, saturated steam, material selection, efficiency

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Jhu-Wei Ji, Fa-Shian Chang, Lih-Tyng Hwang, Chih-Feng Liu, Jeng-Nan Lee, Shun-Min Wang, Kai-Yi Cho

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This paper presents a tracked robot with blade arms powered to assist movement in difficult environments. As a result, the tracked robot is able to pass a ramp or climb stairs. The main feature is a pair of blade arms on both sides of the vehicle body working in collaboration with previously validated transformable track system. When the robot encounters an obstacle in a terrain, it enlists the blade arms with power to overcome the obstacle. In disaster areas, there usually will be terrains that are full of broken and complicated slopes, broken walls, rubbles, and ditches. Thereupon, a robot, which is instructed to pass through such disaster areas, needs to have a good off-road capability for such complicated terrains. The robot with crawling-assisting blade arms would overcome the obstacles along the terrains, and possibly become to be a rescue robot. A prototype has been developed and built; experiments were carried out to validate the enhanced crawling capability of the robot.

Keywords: tracked robot, rescue robot, blade arm, crawling ability, control system

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Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

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FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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Authors: He Li

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Around the mid-1980s, Confucianism was reintroduced into China from Taiwan and Hong Kong as a result of China’s policies of reform and openness. Since then, the revival of neo-Confucianism in mainland China has accelerated and become a crucial component of the public intellectual sphere. The term xinrujia or xinruxue, loosely translated as “neo-Confucianism,” is increasingly understood as an intellectual and cultural phenomenon of the last four decades. The Confucian scholarship is in the process of restoration. This paper examines the Chinese intellectual discourse on Confucianism and democracy and places it in comparative and theoretical perspectives. With China’s rise and surge of populism in the West, particularly in the US, the leading political values of Confucianism could increasingly shape both China and the world at large. This state of affairs points to the need for more systematic efforts to assess the discourse on neo-Confucianism and its implications for China’s transformation. A number of scholars in the camp of neo-Confucianism maintain that some elements of Confucianism are not only compatible with democratic values and institutions but actually promote liberal democracy. They refer to it as Confucian democracy. By contrast, others either view Confucianism as a roadblock to democracy or envision that a convergence of democracy with Confucian values could result in a new hybrid system. The paper traces the complex interplay between Confucianism and democracy. It explores ideological differences between neo-Confucianism and liberal democracy and ascertains whether certain features of neo-Confucianism possess an affinity for the authoritarian political system. In addition to printed materials such as books and journal articles, a selection of articles from the website entitled Confucianism in China will be analyzed. The selection of this website is due to the fact that it is the leading website run by Chinese scholars focusing on neo-Confucianism. Another reason for selecting this website is its accessibility and availability. In the past few years, quite a few websites, left or right, were shut down by the authorities, but this website remains open. This paper explores the core components, dynamics, and implications of neo-Confucianism. My paper is divided into three parts. The first one discusses the origins of neo-Confucianism. The second section reviews the intellectual discourse among Chinese scholars on Confucian democracy. The third one explores the implications of the Chinese intellectual discourse on neo-Confucianism. Recently, liberal democracy has entered more conflict with official ideology. This paper, which is based on my extensive interviews in China prior to the pandemic and analysis of the primary sources in Chinese, will lay the foundation for a chapter on neo-Confucianism and democracy in my next book-length manuscript, tentatively entitled Chinese Intellectual Discourse on Democracy.

Keywords: China, confucius, confucianism, neo-confucianism, democracy

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Authors: Hemalatha Rallapalli, K. Lal Kishore

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In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

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Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

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In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

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Authors: Isil Kerti, Onur Okur, Sibel Daglilar, Recep Calin

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Particulate reinforced aluminium matrix composites have gained more importance in automotive, aeronautical and defense industries due to their specific properties like as low density, high strength and stiffness, good fatigue strength, dimensional stability at high temperature and acceptable tribological properties. In this study, 2014 Aluminium alloy used as a matrix material and B₄C and SiC were selected as reinforcements components. For production of composites materials, vacuum infiltration method was used. In the experimental studies, the reinforcement volume ratios were defined by mixing as totally 10% B₄C and SiC. Aging treatment (T6) was applied to the specimens. The effect of T6 treatment on hardness was determined by using Brinell hardness test method. The effects of the aging treatment on microstructure and chemical structure were analysed by making XRD, SEM and EDS analysis on the specimens.

Keywords: metal matrix composite, vacumm infiltration method, aluminum metal matrix, mechanical feature

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Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

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Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

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Authors: Yun-Hsuan Yu, Chi-Shung Tang, Nzar Rauf Abdullah, Vidar Gudmundsson

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Spin-orbit gap feature in energy dispersion of one-dimensional devices is revealed via strong spin-orbit interaction (SOI) effects under Zeeman field. We describe the utilization of a finger-gate or a top-gate to control the spin-dependent transport characteristics in the SOI-Zeeman influenced split-gate devices by means of a generalized spin-mixed propagation matrix method. For the finger-gate system, we find a bound state in continuum for incident electrons within the ultra-low energy regime. For the top-gate system, we observe more bound-state features in conductance associated with the formation of spin-associated hole-like or electron-like quasi-bound states around band thresholds, as well as hole bound states around the reverse point of the energy dispersion. We demonstrate that the spin-dependent transport behavior of a top-gate system is similar to that of a finger-gate system only if the top-gate length is less than the effective Fermi wavelength.

Keywords: spin-orbit, zeeman, top-gate, finger-gate, bound state

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Authors: Yoko Katsumata, Takashi Horikoshi, Noriaki Fukuzumi, Shoji Yamaguchi

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This study examined some positive sensations that caused human to experience an intense feeling or sensitivity from Venetian Masks. We surveyed 102 Japanese university students (male; 85, female; 17) about their sensitivity impressions toward Venetian Masks using sensitivity questionnaire. We used questionnaires to examine the relevance to transformation desire at Venetian masks by means of correlation analysis. The positive correlation coefficient was observed between sensitivity impressions and transformation desire.

Keywords: Venetian Masks, sensitivity impression, transformation desire, Japan

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Authors: Salim Omar Raoof

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This study was conducted in a private local sheep herd at Gabaraka village-Kirkuk-Iraq. Analysis of 77 ewes recorded and 7 Rams of local sheep presented in Gabaraka village farm plain, the age of ewes ranged between (2-4) years. The aim of this study is to investigate the genetic and non-genetic factors (type of birth, sex, and age of dam) affecting daily milk yield (DMY), birth weight (BW), weaning weight (WW) and Gain characteristics of local sheep raised under Iraq conditions, and it also aims at estimating heritability’s, BLUP. The overall mean of daily milk yield, (BW), (WW), and gain. Was 444.15gm,4.92kg,43.08kg, and 38.16kg, respectively. The results showed there was a significant effect of the type of birth and sex on (BW) and (WW). Also, the age of the dam had a significant effect on daily milk yield (BW), (WW), and gain. Generally, the estimate of heritability of DMP, BWT, WWT, and Gain tend to be 0.22, 0.17, 0.27, and 0.22, respectively. The breeding value (BLUP) for rams ranged between (-0.1684 to 0.188), (-0.205 to 0.310), and ( -0.0171 to 0.029) according to growth traits of Lambs BW, WW, and Gain, respectively. It concluded that the selection of ewes and rams at the population level in planned selection schemes is based on BLUP value and heritability.

Keywords: locally sheep, milk yield, Genetic parameters, BLUP value

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: Mais Khader, Xingjie Wei

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This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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Authors: Minhee Son, Kyung Nam Kim

Abstract:

This study explores the plan of the Korean and Japanese governments to transition into the hydrogen economy. Two motor companies, Hyundai Motor Company from Korea and Toyota from Japan, released the Hydrogen Fuel Cell Vehicle to monopolize the green energy automobile market. Although, they are the main countries which emit greenhouse gas, hydrogen energy can bring from a certain industry places, such as chemical plants and steel mills. Recent, the two countries have been focusing on the hydrogen industry including a fuel cell vehicle, a hydrogen station, a fuel cell plant, a residential fuel cell. The purpose of this paper is to find out the differences of the policies in the two countries to be hydrogen societies. We analyze the behavior of the public and private sectors in Korea and Japan about hydrogen energy and fuel cells for the transition of the hydrogen economy. Finally we show the similarities and differences of both countries in hydrogen fuel cells. And some cities have feature such as Hydrogen cities. Hydrogen energy can make impact environmental sustainability.

Keywords: fuel cell, hydrogen city, hydrogen fuel cell vehicle, hydrogen station, hydrogen energy

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Authors: Ng Mei Han, Nu'man Abdul Hadi

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Extraction of ferulic acid from palm pressed fiber using deep eutectic solvent (DES) of choline chloride-acetic acid (ChCl-AA) and choline chloride-citric acid (ChCl-CA) are reported. Influence of water content in DES on the extraction efficiency was investigated. ChCl-AA and ChCl-CA experienced a drop in viscosity from 9.678 to 1.429 and 22.658 ± 1.655 mm2/s, respectively as the water content in the DES increased from 0 to 50 wt% which contributed to higher extraction efficiency for the ferulic acid. Between 41,155 ± 940 mg/kg ferulic acid was obtained after 6 h reflux when ChCl-AA with 30 wt% water was used for the extraction compared to 30,940 ± 621 mg/kg when neat ChCl-AA was used. Although viscosity of the DES could be improved with the addition of water, there is a threshold where the DES could tolerate the presence of water without changing its solvent behavior. The optimum condition for extraction of ferulic acid from palm pressed fiber was heating for 6 h with DES containing 30 wt% water.

Keywords: deep eutectic solvent, extraction, ferulic acid, palm fibre

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Authors: Gebeyaw Molla Wondim, Damen Haile Mariam, Wubegzier Mekonnen, Catherine Arsenault

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Introduction: Maternal depression is a common psychological disorder that mostly occurs during pregnancy and after childbirth. It affects approximately one in four women worldwide. There is inconsistent evidence regarding the association between anemia and maternal depression. The objective of this systematic review was to examine the association between anemia and depression during pregnancy. Method: A comprehensive search of articles published before March 8, 2024, was conducted in seven databases such as PubMed, Scopus, Web of Science, PsycINFO, CINAHL, Cochrane Library, and Google Scholar. The Boolean operators “AND” or “OR” and “NOT” were used to connect the MeSH terms and keywords. Rayyan software was used to screen articles for final retrieval, and the PRISMA diagram was used to show the article selection process. Data extraction and risk bias assessment were done by two reviewers independently. JBI critical appraisal tool was used to assess the methodological quality of the retrieved articles. Heterogenicity was assessed through visual inspection of the extracted result, and narrative analysis was used to synthesize the result. Result: A total of 2,413 articles were obtained from seven electronic databases. Among these articles, a total of 2,398 were removed due to duplication (702 articles), by title and abstract selection criteria (1,678 articles), and by full-text review (18 articles). Finally, in this systematic review, 15 articles with a total of 628,781 pregnant women were included: seven articles were cohort studies, two were case-control, and six studies were cross-sectional. All included studies were published between 2013 and 2022. Studies conducted in the United States, South Korea, Finland, and one in South India found no significant association between anemia and maternal depression during pregnancy. On the other hand, studies conducted in Australia, Canada, Finland, Israel, Turkey, Vietnam, Ethiopia, and South India showed a significant association between anemia and depression during pregnancy. Conclusion: The overall finding of the systematic review shows the burden of anemia and antenatal depression is much higher among pregnant women in developing countries. Around three-fourths of the studies show that anemia is positively associated with antenatal depression. Almost all studies conducted in LMICs show anemia positively associated with antenatal depression.

Keywords: pregnant, women, anemia, depression

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Authors: Ibrahim Bashir, Yahaya Y. Yusuf

Abstract:

The ongoing shift towards Industry 4.0 represents a critical growth factor in the industrial enterprise, where the digital transformation of industries is increasingly seen as a crucial element for competitiveness. This transformation holds substantial potential, yet its full benefits have yet to be realized due to the fragmented approach to introducing Industry 4.0 technologies. Therefore, this pilot study aims to explore the individual and collective impact of Industry 4.0 technologies and digital transformation on organizational performance. Data were collected through a questionnaire-based survey across 51 companies in the manufacturing industry in the United Kingdom. The correlations and multiple linear regression analyses were conducted to assess the relationship and impact between the variables in the study. The results show that Industry 4.0 and digital transformation positively influence organizational performance and that Industry 4.0 technologies positively influence digital transformation. The results of this pilot study indicate that the implementation of Industry 4.0 technology is vital for increasing organizational performance; however, their roles differ largely. The differences are manifest in how the types of Industry 4.0 technologies correlate with how organizations integrate digital technologies into their operations. Hence, there is a clear indication of a strong correlation between Industry 4.0 technology, digital transformation, and organizational performance. Consequently, our study presents numerous pertinent implications that propel the theory of I4.0, digital business transformation (DBT), and organizational performance forward, as well as guide managers in the manufacturing sector.

Keywords: industry 4.0 technologies, digital transformation, digital integration, organizational performance

Procedia PDF Downloads 144