Search results for: overview of porosity classification

Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

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Authors: Mohamed Faslan

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This paper describes how caste-based differentiation functions among the Southern Muslims of Sri Lanka despite Islamic egalitarian principles. Such differences are not promoted by religious teachings, mosques, or the various Islamic religious denominations. Instead, it underpins a hereditary, hierarchical stratification in social structure. Since Islam is against social stratification and promotes egalitarianism, what are the persuasive social structures that organize the existing caste system among Southern Muslims? To answer this puzzle, this paper discusses and analyses the caste system under these five subsections: ancestry; marriage; geography; mosque ownership or trustees; and occupation. The study of caste in Sri Lanka is generally compartmentalized into separate Sinhala and Tamil systems. Most caste studies have focused on the characteristics, upward mobility, or discrimination of specific castes in relation to other castes within ethnic systems. As an operational definition, in this paper, by “southern” or the south of Sri Lanka, I refer to the Kalutara, Galle and Matara Districts. This research was conducted in these three districts, and the respondents were selected purposively. Community history interviews were used as a tool for collecting information, and grounded theory used for analysis. Caste stratification among the Southern Muslims of Sri Lanka is directly connected to whether they are descended from Arab or South Indian ancestors. Arab ancestors are considered upper caste and South Indian ancestors are considered lower caste. Endogamy is the most serious driving factor keeping caste system functioning among Muslims while the other factors—geography, mosques, and occupations—work as supporting factors.

Keywords: caste, social stratification, Sri Lanka Muslims, endogamy

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Authors: Liang Zhou, Xiaojing Zhu, Yin Lu

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Danshen can induce the angiogenesis in advanced ischemic heart disease while inhibiting the angiogenesis in cancer. Additionally, Danshen mainly contains two groups of ingredients: the hydrophilic phenolic acids (danshensu, caffeic acid and salvianolic acid B), and the lipophilic tanshinones (dihydrotanshinone I, tanshinone II A, and cryptotanshinone). The lipophilic tanshinones reduced the VEGF- and bFGF-induced proliferation of HUVECs in dose-dependent manner, but cannot perform in others. Conversely, caffeic acid and salvianolic acid B had the opposite effect. Danshensu inhibited the VEGF- and bFGF-induced migration of HUVECs, and others were not. Most of them interrupted the forming capillary-like structures of HUVECs, except the danshensu and caffeic acid. Oppositely, caffeic acid enhanced the ability of forming capillary-like structures of HUVECs. Ultimately, the lipophilic tanshinones, danshensu and salvianolic acid B inhibited the angiogenesis, whereas the caffeic acid induced the angiogenesis. These data provide useful information for the classification of ingredients of Danshen for angiogenesis.

Keywords: angiogenesis, Danshen, HUVECs, ingredients

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Authors: Yukinori Taniguchi, Kazuyoshi Kurita, Kohei Mizuta, Keigo Nishitani, Ryuichi Fukuda

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Tungsten carbide is widely used as a tool material in metal manufacturing process. Since tungsten is typical rare metal, establishment of recycle process of tungsten carbide tools and restore into cemented carbide material bring great impact to metal manufacturing industry. Recently, recycle process of tungsten carbide has been developed and established gradually. However, the demands for quality of cemented carbide tool are quite severe because hardness, toughness, anti-wear ability, heat resistance, fatigue strength and so on should be guaranteed for precision machining and tool life. Currently, it is hard to restore the recycled tungsten carbide powder entirely as raw material for new processed cemented carbide tool. In this study, to suggest positive use of recycled tungsten carbide powder, we have tried to fabricate a carbon based sintered steel which shows reinforced mechanical properties with recycled tungsten carbide powder. We have made set of newly designed sintered steels. Compression test of sintered specimen in density ratio of 0.85 (which means 15% porosity inside) has been conducted. As results, at least 1.7 times higher in nominal strength in the amount of 7.0 wt.% was shown in recycled WC powder. The strength reached to over 600 MPa for the Fe-WC-Co-Cu sintered alloy. Wear test has been conducted by using ball-on-disk type friction tester using 5 mm diameter ball with normal force of 2 N in the dry conditions. Wear amount after 1,000 m running distance shows that about 1.5 times longer life was shown in designed sintered alloy. Since results of tensile test showed that same tendency in previous testing, it is concluded that designed sintered alloy can be used for several mechanical parts with special strength and anti-wear ability in relatively low cost due to recycled tungsten carbide powder.

Keywords: tungsten carbide, recycle process, compression test, powder metallurgy, anti-wear ability

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Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Sahar S. Tabrizi, Dogan Ibrahim

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Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.

Keywords: cloud computing, cloud systems, cloud services, IaaS, PaaS, SaaS

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Authors: M. Cherki, I. Taouam, A. Amiri, F. Hmimid, T. Ould Bellahcen

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The Moroccan coasts represent an important wealth of red algae which have an economic interest. Among these algae, the Gelidium sesquipedale, which is exploited industrially for its richness in agar. The aim of this study is to establish a general overview of the macronutrient composition of Gelidium sesquipedale and to compare this composition according to three factors: the harvest site (El Jadida, Casablanca and Mohammadia), the harvest depth (coast and depth) and the drying process (open air and oven). Proteins, lipids, and carbohydrates are measured by different methods. The analysis of results show that the protein concentrations of the El Jadida and Mohammadia samples are significantly higher than that of Casablanca (0.026 ± 0.0007 µg/µg DW 0.024 ± 0.001 µg/µg DW and 0.006 ± 0.0007 µg/µg DW, p < 0.05 respectively). However, Casablanca samples are significantly richer in total sugars (0.023 ± 0.002 µg/µg DW, p < 0.05) and less rich in reducing sugars (0.0001 ± 0.00001 µg/µg DW, p < 0.05) compared to other samples. The lipid concentrations of the samples from the three harvest sites do not show any significant difference. With respect to depth, only total protein and total sugar concentrations were significantly higher in the coast versus depth samples (0.035 ± 0.004 µg/µg DW vs. 0.026 ± 0.0007 µg/µg DW and 0.035 ± 0.006 µg/µg DW vs. 0.012 ± 0.005 µg/µg DW p < 0.05 respectively). For the drying process, protein, total sugars and lipid concentrations were significantly higher in open air samples compared to oven samples (0.006 ± 0.0007 µg/µg DW). vs 0.004 ± 0.0003 µg/µg DW, 0.023 ± 0.002 µg/µg DW vs 0.007 ± 0.002 µg/µg DW and 8% vs 4% p < 0.05 respectively). Our results demonstrate that the chemical composition of Gelidium sesquipedale varies according to the harvest region. In addition, samples harvested on the coast and dried in the open air are the richest in macronutrients.

Keywords: biochemical composition, drying, depth, Gelidium sesquipedale, red algae, region

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Authors: Daniel Monsalve, Takafumi Noguchi

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Mycelium-based composites (MBC) are made by growing living mycelium on lignocellulosic fibres to create a porous composite material which can be lightweight, and biodegradable, making them suitable as a sustainable thermal insulation. Thus, they can help to reduce material extraction while improving the energy efficiency of buildings, especially when agricultural by-products are used. However, as MBC are hygroscopic materials, moisture can reduce their thermal insulation efficiency. It is known that surface growth, or “mycelium skin”, can form a natural coating due to the hydrophobic properties in the mycelium cell wall. Therefore, this research aims to biofabricate a homogeneous mycelium skin and measure its influence on the final composite material by testing material properties such as thermal conductivity, vapour permeability and water absorption by partial immersion over 24 hours. In addition, porosity, surface morphology and chemical composition were also analyzed. The white-rot fungi species Pleurotus ostreatus, Ganoderma lucidum, and Trametes versicolor were grown on 10 mm hemp fibres (Cannabis sativa), and three different biofabrication protocols were used during incubation, varying the time and surface treatment, including the addition of pre-colonised sawdust. The results indicate that density can be reduced by colonisation time, which will favourably impact thermal conductivity but will negatively affect vapour and liquid water control. Additionally, different fungi can exhibit different resistance to prolonged water absorption, and due to osmotic sensitivity, mycelium skin may also diminish moisture control. Finally, a collapse in the mycelium network after water immersion was observed through SEM, indicating how the microstructure is affected, which is also dependent on fungi species and the type of skin achieved. These results help to comprehend the differences and limitations of three of the most common species used for MBC fabrication and how precise engineering is needed to effectively control the material output.

Keywords: mycelium, thermal conductivity, vapor permeability, water absorption

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Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

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The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

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Authors: A. Al Hinai, H. Jayasuriya, H. Kotagama

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Most Gulf Cooperation Council (GCC) countries with oil-based economy like Oman are looking for other potential revenue generation options as the crude oil price is regularly fluctuating due to changing geopolitical environment. Oman has advantage of possessing world-heritage nature tourism hotspots around the country and the government is making investments and strategies to uplift the tourism industry following Oman Vision 2040 strategies. Oman’s agriculture is not significantly contributing to the economy, but possesses specific and diversified arid cropping systems. Oman has modern farms; nevertheless some of the agricultural production activities are done with cultural practices and styles that would be attractive to tourists. The aim of this paper is to investigate the potentials for promoting agritourism industry in Oman; recognize potential sites, commodities and activities, and predict potential revenue generation as a projection from that of the tourism sector. Moreover, the study enables to foresee possible auxiliary advantages of agritourism such as, empowerment of women and youth, enhancement in the value-addition industry for agricultural produce through technology transfer and capacity building, and producing export quality products. Agritourism could increase employability, empowerment of women and youth, improve value-addition industry and export-oriented agribusiness. These efforts including provision of necessary technology-transfer and capacity-building should be rendered by the collaboration of academic institutions, relevant ministries and other public and private sector stakeholders.

Keywords: agritourism, nature-based tourism, potentials, revenue generation, value addition

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

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Authors: Md. Kamrul Hassan, Ari Pappinen

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Wood energy is the single most important form of renewable energy in many parts of the world especially in the least developing countries in South Asia like Bangladesh. The last portion of the national population of this country depends on wood energy for their daily primary energy need. This paper deals with the estimation of wood fuel at the current level and identifies the challenges and strategies related to the development of this resource. Desk research, interactive research and field survey were conducted for gathering and analyzing of data for this study. The study revealed that wood fuel plays a significant role in total primary energy supply in Bangladesh, and the contribution of wood fuel in final energy consumption in 2013 was about 24%. Trees on homestead areas, secondary plantation on off forest lands, and forests are the main sources of supplying wood fuel in the country. Insufficient supply of wood fuel against high upward demand is the main cause of concern for sustainable consumption, which eventually leads deterioration and depletion of the resources. Inadequate afforestation programme, lack of initiatives towards the utilization of set-aside lands for wood energy plantations, and inefficient management of the existing resources have been identified as the major impediments to the development of wood energy in Bangladesh. The study argued that enhancement of public-private-partnership afforestation programmes, intensifying the waste and marginal lands with short-rotation tree species, and formulation of biomass-based rural energy strategies at the regional level are relevant to the promotion of sustainable wood energy in the country.

Keywords: Bangladesh, challenge, supply, wood energy

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

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The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Chinonso Jude Ugwu

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This study examines education as a global business, primarily focusing on the boom of college students worldwide. It adopts a mixed-technique approach, using primary and secondary data sources. Primary data was obtained using questionnaires and interviews focusing on international college students, academic staff, and recruitment corporations from pre-determined universities in the United States, the United Kingdom, and Australia. The secondary information was collected from relevant literature, professional reports, and databases. The study ascertained that the boom in worldwide college students is a huge trend within the training enterprise, arising primarily from the growing call for better education worldwide. The studies additionally found that different factors are responsible for the decision of international students to consider studying abroad, such as high schooling satisfaction, cultural exposure, professional opportunities, and the popularity of universities. Furthermore, the study highlights the challenges college students face worldwide, including economic difficulties, social and cultural adjustments, and visa regulations. Based on the findings, the study concludes that Education as a Global Business is a profitable enterprise with substantial potential. However, universities and governments should handle global college students’ demanding situations by creating welcoming surroundings promoting diversity and inclusivity. The study recommends that universities put money into programs and offerings that assist worldwide college students’ welfare. Governments should ease visa regulations to inspire more extraordinary worldwide college students to observe abroad.

Keywords: education, business, profitability, global students

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: P. Abtahi, B. Samali

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Façade panels of various shapes, weights, and connections usually act as a barrier between the indoor and outdoor environments. They also play a major role in enhancing the aesthetics of building structures. They are attached by different types of connections to the primary structure or inner panels in double skin façade skins. Structural buildings designed to withstand seismic shocks have been undergoing a critical appraisal in recent years, with the emphasis changing from ‘strength’ to ‘performance’. Performance based design and analysis have found their way into research, development, and practice of earthquake engineering, particularly after the 1994 Northridge and 1995 Kobe earthquakes. The design performance of facades as non-structural elements has now focused mainly on evaluating the damage sustained by façade frames with fixed connections, not movable ones. This paper will review current design standards for structural buildings, including the performance of structural and non-structural components during earthquake excitations in order to overview and evaluate the damage assessment and behaviour of various façade systems in building structures during seismic activities. The proposed solutions for each facade system will be discussed case by case to evaluate their potential for incorporation with newly designed connections. Finally, Double-Skin-Facade systems can potentially be combined with movable facade technology, although other glazing systems would require minor to major changes in their design before being integrated into the system.

Keywords: building performance, earthquake engineering, glazing system, movable façade technology

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: Debabrata Adhikari, Mikhail Matveev, Louise Brown, Jan Kočí, Andy Long

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Resin transfer molding (RTM) is increasingly used for manufacturing high-quality composite structures due to its additional advantages over prepregs of low-cost out-of-autoclave processing. However, to retain the advantages, it is critical to reduce the void content during the injection. Reinforcements commonly used in RTM, such as woven fabrics, have dual-scale porosity with mesoscale pores between the yarns and the micro-scale pores within the yarns. Due to the fabric geometry and the nature of the dual-scale flow, the flow front during injection creates a complicated fingering formation which leads to void formation. Analytical modeling of void formation for woven fabrics has been widely studied elsewhere. However, there is scope for improvement to the reduction in void formation in 3D fabrics wherein the in-plane yarn layers are confined by additional through-thickness binder yarns. In the present study, the structural morphology of the tortuous pore spaces in the 3D fabric has been studied and implemented using open-source software TexGen. An analytical model for the void and the fingering formation has been implemented based on an idealized unit cell model of the 3D fabric. Since the pore spaces between the yarns are free domains, the region is treated as flow-through connected channels, whereas intra-yarn flow has been modeled using Darcy’s law with an additional term to account for capillary pressure. Later the void fraction has been characterised using the criterion of void formation by comparing the fill time for inter and intra yarn flow. Moreover, the dual-scale two-phase flow of resin with air has been simulated in the commercial CFD solver OpenFOAM/ANSYS to predict the probable location of voids and validate the analytical model. The use of an idealised unit cell model will give the insight to optimise the mesoscale geometry of the reinforcement and injection parameters to minimise the void content during the LCM process.

Keywords: 3D fiber, void formation, RTM, process modelling

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Authors: H. J. Hong

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Sporting organizations are arguably responsible for encouraging high-performance athletes to balance their life and identity during their sporting career; sporting organizations can establish the motivational climate for high-performance athletes using athlete career development and management programs. The purpose of this article to provide an overview of career development and management programs in 20 countries and to examine the following seven features of the programs: (1) Which government-funded sporting organizations provide career development and management programs? (2) Which athletes are eligible to access the programs? (3) What are the aims and objectives of the programs? (4) What are the activities and content of the programs? (5) Who is responsible for the delivery of the programs within organizations (e.g., advisors, coordinators, service providers, counsellors, etc.)? (6) Do the sporting organizations have training and development programs for support services providers? and (7) Do the sporting organizations assess the programs in terms of the programs’ impact on high-performance athletes’ career development and management skills? Web-based data collection was conducted first. The author contacted the sporting organizations to clarify information as required by requesting further information via emails, international calls, video calls on Skype, and by visiting the sporting organizations and meeting with the practitioners (Fiji, Ireland, Korea, Scotland, Singapore, and Spain). By selecting comparable career development and management programs, the present study reviews programs across the world, identifying similarities, differences, and difficulties, so that sporting organizations and practitioners may enhance the quality of their programs. Since international comparisons of career development and management programs remain scarce, the findings deepen the knowledge of high-performance athletes’ career development, management, and transitions in the areas of organizational support programs.

Keywords: athletes' career development and management, athletes' psychological preparation, organizational support, sport career transition

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Authors: Chuluundorj Begz

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This paper presents the dynamic, psycho-cognitive approach to study of human verbal thinking on the basis of typologically different languages /as a Mongolian, English and Russian/. Topological equivalence in verbal communication serves as a basis of Universality of mental structures and therefore deep structures. Mechanism of verbal thinking consisted at the deep level of basic concepts, rules for integration and classification, neural networks of vocabulary. In neuro cognitive study of language, neural architecture and neuro psychological mechanism of verbal cognition are basis of a vector-based modeling. Verbal perception and interpretation of the infinite set of meanings and propositions in mental continuum can be modeled by applying tensor methods. Euclidean and non-Euclidean spaces are applied for a description of human semantic vocabulary and high order structures.

Keywords: Euclidean spaces, isomorphism and homomorphism, mental lexicon, mental mapping, semantic memory, verbal cognition, vector space

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Authors: Tia Kristian Tajnšek, Matjaž Mazaj, Nataša Zabukovec Logar

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Metal-organic frameworks (MOFs) with their specific properties and the possibility of tuning the structure represent excellent candidates for use in the biomedical field. Their advantage lies in large pore surfaces and volumes, as well as the possibility of using bio-friendly or bioactive constituents. So-called bioMOFs are representatives of MOFs, which are constructed from at least one biomolecule (metal, a small bioactive molecule in metal clusters and/or linker) and are intended for bio-application (usually in the field of medicine; most commonly drug delivery). When designing a bioMOF for biomedical applications, we should adhere to some guidelines for an improved toxicological profile of the material. Such as (i) choosing an endogenous/nontoxic metal, (ii) GRAS (generally recognized as safe) linker, and (iii) nontoxic solvents. Design and synthesis of bioNICS-1 (bioMOF of National Institute of Chemistry Slovenia – 1) consider all these guidelines. Zinc (Zn) was chosen as an endogenous metal with an agreeable recommended daily intake (RDI) and LD50 value, and ascorbic acid (Vitamin C) was chosen as a GRAS and active linker. With these building blocks, we have synthesized a bioNICS-1 material. The synthesis was done in ethanol using a solvothermal method. The synthesis protocol was further optimized in three separate ways. Optimization of (i) synthesis parameters to improve the yield of the synthesis, (ii) input reactant ratio and addition of specific modulators for production of larger crystals, and (iii) differing of the heating source (conventional, microwave and ultrasound) to produce nano-crystals. With optimization strategies, the synthesis yield was increased. Larger crystals were prepared for structural analysis with the use of a proper species and amount of modulator. Synthesis protocol was adjusted to different heating sources, resulting in the production of nano-crystals of bioNICS-1 material. BioNICS-1 was further activated in ethanol and structurally characterized, resolving the crystal structure of new material.

Keywords: ascorbic acid, bioMOF, MOF, optimization, synthesis, zinc ascorbate

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Authors: Othman Salim Hussein Al-Fleesy

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Background: Studies showed that sudden infant death syndrome (SIDS) has association with sleeping positions. Up-to-date no study explained how could they prevent it? Objectives: 1-To determine which sleeping position is certainly safe one to prevent SIDS. 2-To establish criteria for suggesting definition and making diagnosis for SIDS. 3-To discuss the controversy surrounding SUND, ALTE, NM, as compared to SIDS. Method: This literature review was built on a previous literature. Articles were obtained randomly according to their availability to the author. For the purpose of this work an easy approach was built by modeling an overview on SIDS topic after clarifying the misconception and misinterpretation of a number of controversial issues in regard to SIDS such as: asphyxia, sudden unexpected death among adults (Bangungut or Pokkuri), apparent life threatening event (ALTE), Nightmare, and comparing the findings with the literature review results..By this unique method we got a clue for prevention of Sudden Infant Death Syndrome. Results: The revision revealed with no doubt that no study before have studied right-side sleeping position at all. The author determined right side as the only safe position to preventing SIDS. A new definition for SIDS is suggested. The author postulated a Right side position hypothesis (Alfleesy hypothesis) which is a testable hypothesis in front of all researchers for further study . Conclusion: Our results contradict totally all previous studies and recommendations. We recommended strongly the right side position only for sleeping to prevent SIDS. New definition is suggested and a new hypothesis is postulated.

Keywords: SIDS, ALTE, nightmare, forensic sciences

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Authors: Jannika Dombrowski, Sabine Ambros, Ulrich Kulozik

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Several drying techniques are used to preserve sensitive substances such as probiotic lactic acid bacteria. With the aim to better understand differences between these processes, this work gives new insights into structural variations resulting from different preservation methods and their impact on product quality and storage stability. Industrially established methods (freeze drying, spray drying) were compared to upcoming vacuum, microwave-freeze, and microwave-vacuum drying. For freeze and microwave-freeze dried samples, survival and activity maintained 100%, whereas vacuum and microwave-vacuum dried cultures achieved 30-40% survival. Spray drying yielded in lowest viability. The results are directly related to temperature and oxygen content during drying. Interestingly, most storage stable products resulted from vacuum and microwave-vacuum drying due to denser product structures as determined by helium pycnometry and SEM images. Further, lower water adsorption velocities were responsible for lower inactivation rates. Concluding, resulting product structures as well as survival rates and storage stability mainly depend on the type of water removal instead of energy input. Microwave energy compared to conductive heating did not lead to significant differences regarding the examined factors. Correlations could be proven for three investigated microbial strains. The presentation will be completed by an overview on the energy efficiency of the presented methods.

Keywords: drying techniques, energy efficiency, lactic acid bacteria, probiotics, survival rates, structure characterization

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Authors: Nishanthi N. S., Srikanth Vedantam

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Intracellular delivery of materials has always proved to be a challenge in research and therapeutic applications. Usually, vector-based methods, such as liposomes and polymeric materials, and physical methods, such as electroporation and sonoporation have been used for introducing nucleic acids or proteins. Reliance on exogenous materials, toxicity, off-target effects was the short-comings of these methods. Microinjection was an alternative process which addressed the above drawbacks. However, its low throughput had hindered its adoption widely. Mechanical deformation of cells by squeezing them through constriction channel can cause the temporary development of pores that would facilitate non-targeted diffusion of materials. Advantages of this method include high efficiency in intracellular delivery, a wide choice of materials, improved viability and high throughput. This cell squeezing process can be studied deeper by employing simple models and efficient computational procedures. In our current work, we present a finite sized dissipative particle dynamics (FDPD) model to simulate the dynamics of the cell flowing through a constricted channel. The cell is modeled as a capsule with FDPD particles connected through a spring network to represent the membrane. The total energy of the capsule is associated with linear and radial springs in addition to constraint of the fixed area. By performing detailed simulations, we studied the strain on the membrane of the capsule for channels with varying constriction heights. The strain on the capsule membrane was found to be similar though the constriction heights vary. When strain on the membrane was correlated to the development of pores, we found higher porosity in capsule flowing in wider channel. This is due to localization of strain to a smaller region in the narrow constriction channel. But the residence time of the capsule increased as the channel constriction narrowed indicating that strain for an increased time will cause less cell viability.

Keywords: capsule, cell squeezing, dissipative particle dynamics, intracellular delivery, microfluidics, numerical simulations

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Authors: Emily Adams, Eddie Donaghy, David Henderson, Lauren Ng, Caroline Sanders, Rowena Stewart, Maria Wolters, Stewart Mercer

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Ongoing review abstract: Older People Experiencing Homelessness (OPEH) can have mental and physical indicators of aging 10–20 years earlier than the general population and experience premature mortality due to age-related chronic conditions. Emerging literature suggests digital interventions could positively impact PEH’s well-being. However, the increased reliance on digital delivery may also perpetuate digital inequalities for socially excluded groups, including PEH. The potential triple disadvantage of being older, homeless, and digitally excluded creates a uniquely problematic situation that warrants further research. This scoping review aims to investigate and synthesise the range and type of digital interventions available to OPEH and the organisations that support OPEH. The following databases were searched on 28th July 2023: Medline, Scopus, International Bibliography of the Social Sciences (IBSS)‎, Applied Social Sciences Index & Abstracts (ASSIA)‎, Association for Computing Machinery Digital Library (ACMDL) and Policy commons. A search strategy was developed in collaboration with an academic librarian. The presentation will include: An introduction to OPEH and digital exclusion Overview of the results of this review: OPEH usage of digital platforms Current digital interventions available The role of support organisations Current gaps in the evidence, future research and recommendations for policy and practice

Keywords: homeless, digital exclusion, aging, technology

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Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

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Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

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Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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Authors: Q. Ni, J. A. Serna, D. Holland, X. Wang

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The objective of this study is to develop Nuclear Magnetic Resonance (NMR) techniques to enhance bone related research applied on normal and disuse (Biglycan knockout) mice bone in vitro by using both low-field and high-field NMR simultaneously. It is known that the total amplitude of T₂ relaxation envelopes, measured by the Carr-Purcell-Meiboom-Gill NMR spin echo train (CPMG), is a representation of the liquid phase inside the pores. Therefore, the NMR CPMG magnetization amplitude can be transferred to the volume of water after calibration with the NMR signal amplitude of the known volume of the selected water. In this study, the distribution of mobile water, porosity that can be determined by using low-field (20 MHz) CPMG relaxation technique, and the pore size distributions can be determined by a computational inversion relaxation method. It is also known that the total proton intensity of magnetization from the NMR free induction decay (FID) signal is due to the water present inside the pores (mobile water), the water that has undergone hydration with the bone (bound water), and the protons in the collagen and mineral matter (solid-like protons). Therefore, the components of total mobile and bound water within bone that can be determined by low-field NMR free induction decay technique. Furthermore, the bound water in solid phase (mineral and organic constituents), especially, the dominated component of calcium hydroxyapatite (Ca₁₀(OH)₂(PO₄)₆) can be determined by using high-field (400 MHz) magic angle spinning (MAS) NMR. With MAS technique reducing NMR spectral linewidth inhomogeneous broadening and susceptibility broadening of liquid-solid mix, in particular, we can conduct further research into the ¹H and ³¹P elements and environments of bone materials to identify the locations of bound water such as OH- group within minerals and bone architecture. We hypothesize that with low-field and high-field magic angle spinning NMR can provide a more complete interpretation of water distribution, particularly, in bound water, and these data are important to access bone quality and predict the mechanical behavior of bone.

Keywords: bone, mice bone, NMR, water in bone

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