Search results for: market crash prediction

Authors: Marwa Brahim, Nicolas Brosse, Nadia Boussetta, Nabil Grimi, Eugene Vorobiev

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Rapeseed plant is an established product in France which is mainly dedicated to oil production. However, the economic potential of residues from this industry (rapeseed hulls, rapeseed cake, rapeseed straw etc.), has not been fully exploited. Currently, only low-grade applications are found in the market. As a consequence, it was deemed of interest to develop a technological platform aiming to convert rapeseed residues into value- added products. Specifically, a focus is given on the conversion of rapeseed straw into valuable molecules (e.g. lignin, glucose). Existing pretreatment technologies have many drawbacks mainly the production of sugar degradation products that limit the effectiveness of saccharification and fermentation steps in the overall scheme of the lignocellulosic biorefinery. In addition, the viability of fractionation strategies is a challenge in an environmental context increasingly standardized. Hence, the need to find cleaner alternatives with comparable efficiency by implementing physical phenomena that could destabilize the structural integrity of biomass without necessarily using chemical solvents. To meet environmental standards increasingly stringent, the present work aims to study the new pretreatment strategies involving lower consumption of chemicals with an attenuation of the severity of the treatment. These strategies consist on coupling physical treatments either high voltage electrical discharges or ultrasounds to conventional chemical pretreatments (soda and organosolv). Ultrasounds treatment is based on the cavitation phenomenon, and high voltage electrical discharges cause an electrical breakdown accompanied by many secondary phenomena. The choice of process was based on a technological feasibility study taking into account the economic profitability of the whole chain after products valorization. Priority was given to sugars valorization into bioethanol and lignin sale.

Keywords: high voltage electrical discharges, organosolv, pretreatment strategies, rapeseed straw, soda, ultrasounds

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Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Patrice Conner

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Nanotechnologies have enormous potential to contribute to human flourishing in responsible and sustainable ways. They are rapidly developing field of science, technology and innovation. As enabling technologies, their full scope of applications is potentially very wide. Major implications are expected in many areas, e.g. healthcare, information and communication technologies, energy production and storage, materials science/chemical engineering, manufacturing, environmental protection, consumer products, etc. However, nanotechnologies are unlikely to realize their full potential unless their associated societal and ethical issues are adequately attended. Namely nanotechnologies and nanoparticles may expose humans and the environment to new health risks, possibly involving quite different mechanisms of interference with the physiology of human and environmental species. One of the building blocks of the ‘safe, integrated and responsible’ approach is standardization. Both the Economic and Social Committee and the European Parliament have highlighted the importance to be attached to standardization as a means to accompany the introduction on the market of nanotechnologies and nanomaterials, and a means to facilitate the implementation of regulation. ISO and CEN have respectively started in 2005 and 2006 to deal with selected topics related to this emerging and enabling technology. In the beginning of 2010, EC DG ‘Enterprise and Industry’ addressed the mandate M/461 to CEN, CENELEC and ETSI for standardization activities regarding nanotechnologies and nanomaterials. Thus CEN/TC 352 ‘Nanotechnologies’ has been asked to take the leadership for the coordination in the execution of M/461 (46 topics to be standardized) and to contact relevant European and International Technical committees and interested stakeholders as appropriate (56 structures have been identified). Prior requests from M/461 deal with characterization and exposure of nanomaterials and any matters related to Health, Safety and Environment. Answers will be given to: - What are the structures and how they work? - Where are we right now and how work is going from now onwards? - How CEN’s work and targets deal with and interact with global matters in this field?

Keywords: characterization, environmental protection, exposure, health risks, nanotechnologies, responsible and sustainable ways, safety

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Authors: Liana Melissa E. de la Rosa, Jayson P. Ada

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This exploratory study was conducted to determine the sociology of the Facebook. Specifically, it aimed to know the socio-demographic profile of the respondents in terms of age, sex, year level and monthly allowance; find out the common usage of Facebook to the respondents; identify the features of Facebook that are commonly used by the respondents; understand the benefits and risks of using the Facebook; determine how frequent the respondents use the Facebook; and find out if there is a significant relationship between socio-demographic profile of the respondents and their Facebook usage. This study used the exploratory research design and correlational design employing research survey questionnaire as its main data gathering instrument. Students of the University of Eastern Philippines were selected as the respondents of this study through quota sampling. Ten (10) students were randomly selected from each college of the university. Based on the findings of this study, the following conclusion were drawn: The majority of the respondents are aged 18 and 21 old, female, are third year students, and have monthly allowance of P 2,000 above. On the respondents’ usage of Facebook, the majority of use the Facebook on a daily basis for one to two (1-2) hours everyday. And most users used Facebook by renting a computer in an internet cafe. On the use of Facebook, most users have created their profiles mainly to connect with people and gain new friends. The most commonly used features of Facebook, are: photos application, like button, wall, notification, friend, chat, network, groups and “like” pages status updates, messages and inbox and events. While the other Facebook features that are seldom used by the respondents are games, news feed, user name, video sharing and notes. And the least used Facebook features are questions, poke feature, credits and the market place. The respondents stated that the major benefit that the Facebook has given to its users is its ability to keep in touch with family members or friends while the main risk identified is that the users can become addicted to the Internet. On the tests of relationships between the respondents’ use of Facebook and the four (4) socio-demographic profile variables: age, sex, year level, and month allowance, were found to be not significantly related to the respondents’ use of the Facebook. While the variable found to be significantly related was gender.

Keywords: Facebook, sociology, social networking, exploratory study

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Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Henry Kelly, Helena Shaw

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This paper will seek how innovative methods from Health Economics and, to a lesser extent, wellbeing analysis can be applied in the Cost-Benefit Analysis (CBA) of transport infrastructure and policy interventions. The context for this will focus on the framework articulated by the UK Treasury (finance department) and the English Department for Transport. Both have well-established methods for undertaking CBA, but there is increased policy interest, particularly at a regional level of exploring broader strategic goals beyond those traditionally associated with transport user benefits, productivity gains, and labour market access. Links to different CBA approaches internationally, such as New Zealand, France, and Wales will be referenced. By exploring a complementary method of accessing the impacts of policies through the quantification of health impacts is a fruitful line to explore. In a previous piece of work, 14 impact pathways were identified, mapping the relationship between transport and health. These are wide-ranging, from improved employment prospects, the stress of unreliable journey times, and air quality to isolation and loneliness. Importantly, we will consider these different measures of health from an intersectional point of view to ensure that the basis that remains in the health industry does not get translated across to this work. The objective is to explore how a CBA based on these pathways may, through quantifying forecast impacts in terms of Quality-Adjusted Life Years may, produce different findings than a standard approach. Of particular interest is how a health-based approach may have different distributional impacts on socio-economic groups and may favour distinct types of interventions. Consideration will be given to the degree this approach may double-count impacts or if it is possible to identify additional benefits to the established CBA approach. The investigation will explore a range of schemes, from a high-speed rail link, highway improvements, rural mobility hubs, and coach services to cycle lanes. The conclusions should aid the progression of methods concerning the assessment of publicly funded infrastructure projects.

Keywords: cost-benefit analysis, health, QALYs transport

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Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

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Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

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Authors: Sanjeev Prasher, T. Sai Vijay, Chandan Parsad, Abhishek Banerjee, Sahakari Nikhil Krishna, Subham Chatterjee

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With rapid rise in internet retailing, the industry is set for a major implosion. Due to the little difference among competitors, companies find it difficult to segment and target the right shoppers. The objective of the study is to segment Indian online shoppers on the basis of the factors – website characteristics and shopping values. Together, these cover extrinsic and intrinsic factors that affect shoppers as they visit web retailers. Data were collected using questionnaire from 319 Indian online shoppers, and factor analysis was used to confirm the factors influencing the shoppers in their selection of web portals. Thereafter, cluster analysis was applied, and different segments of shoppers were identified. The relationship between income groups and online shoppers’ segments was tracked using correspondence analysis. Significant findings from the study include that web entertainment and informativeness together contribute more than fifty percent of the total influence on the web shoppers. Contrary to general perception that shoppers seek utilitarian leverages, the present study highlights the preference for fun, excitement, and entertainment during browsing of the website. Four segments namely Information Seekers, Utility Seekers, Value Seekers and Core Shoppers were identified and profiled. Value seekers emerged to be the most dominant segment with two-fifth of the respondents falling for hedonic as well as utilitarian shopping values. With overlap among the segments, utilitarian shopping value garnered prominence with more than fifty-eight percent of the total respondents. Moreover, a strong relation has been established between the income levels and the segments of Indian online shoppers. Web shoppers show different motives from being utility seekers to information seekers, core shoppers and finally value seekers as income levels increase. Companies can strategically use this information for target marketing and align their web portals accordingly. This study can further be used to develop models revolving around satisfaction, trust and customer loyalty.

Keywords: online shopping, shopping values, effectiveness of information content, web informativeness, web entertainment, information seekers, utility seekers, value seekers, core shoppers

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Patricia Sumod

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There is a unique movement of fashion that features a trend around secondhand clothing. This is especially observed in the lifestyles of the millennials, where the concept of reusing apparel and accessories is noticeable and, therefore, slowly diminishing the high consumption of fast fashion and generating environmental awareness. This paper will focus on how this clothing trend influences and engages consumers in buying secondhand clothing and creating fashionable looks simultaneously. To further examine the millennials’ motivation towards consumption and using secondhand fashion, a concept as a trendsetter, this paper will take a closer look at their idea of concern for the environment. Considering second-hand clothing is a sustainable consumption practice, it will investigate the role of social influencers, trendsetters, and millennials in overall fashion consumption in this context. This study aims to understand how secondhand clothing and millennials differ from other consumers regarding the perception of fast-depleting natural resources, price sensitivity, vintage attachments, and psychographics. Secondly, the paper will also present the connection of emotion between millennials and secondhand clothing that may not be necessarily purchased but received. This study will reflect on the already identified influences in increased purchase behavior and an uncharted positive relationship between the consumer and the products. This behavior will further formulate into a habit by consumer segments, creating an expanded market for secondhand clothing. There is no definite indication that fast fashion will cease to exist, but slowing its rapid movement is an attempt to work toward a sustainable future. The conclusion will present possibilities for consumers to engage in C2C online interaction, thereby reinforcing a notable change in consumer behavior and attitude in contradiction to today’s extreme consumerism and willingness to be adaptable to a minimalist way of life. Fashion brands will then begin a new forecast to actively accommodate the new millennial concept of fashion that will advertise more concern than insatiability. The research will be with literature from various authors, insights provided by researchers on this new wave of consumers, and a qualitative approach with face-to-face interviews with a sample group who are in the practice of secondhand clothing consumption.

Keywords: second-hand clothing, millennials, sustainability, consumption practice, fashion environment.

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Authors: Rachel Gough

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In 2014, Skellig Michael, an island off Ireland’s western seaboard and UNESCO world heritage site became a major setting in Disney’s Star Wars franchise. The subsequent influx of tourists to the site has proven to be a point of contention nationally. The increased visitor numbers have uplifted certain areas of the local economy, the mainland, but have caused irreparable damage to historic monuments and to endangered bird populations who breed on the island. Recent research carried out by a state body suggests far-reaching and longterm negative impacts on the island’s culture and environment, should the association with the Star Wars franchise persist. In spite of this, the film has been widely endorsed by the Irish government as providing a vital economic boost to historically marginalised rural areas through film tourism. This paper argues quite plainly that what is taking place on Skellig is neocolonialism. Skellig Michael’s unique resources, its aesthetic qualities, its ecosystem, and its cultural currency have been sold by the state to a multinational corporation, who profit from their use. Meanwhile, locals are left to do their best to turn a market trend into sustainable business at the expense of culture ecology and community. This paper intends to be the first dedicated study into the psychogeographic and cultural impact of Skellig Michael’s deterioration as a result of film tourism. It will discuss the projected impact of this incident on Irish culture more broadly and finally will attempt to lay out a roadmap for more collaborative filmmaking and touristic approach, which allows local cultures and ecosystem’s to thrive without drastically inhibiting cultural production. This paper will ultimately find that the consequences of this representation call for a requirement to read tourism as a split concept — namely into what we might loosely call “eco-tourism” and more capital-based “profit-bottom-line tourism.”

Keywords: ecology, film tourism, neocolonialism, sustainability

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Authors: Mindaye Teshome, Evaldo Muñoz Braz, Carlos M. M. Eleto Torres, Patricia Mattos

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Sustainable forest management planning requires up-to-date information on the structure, standing volume, biomass, and growth rate of trees from a given forest. This kind of information is lacking in many forests in Ethiopia. The objective of this study was to quantify the population structure, diameter growth rate, and standing volume of wood from Juniperus procera trees in the Chilimo forest. A total of 163 sample plots were set up in the forest to collect the relevant vegetation data. Growth ring measurements were conducted on stem disc samples collected from 12 J. procera trees. Diameter and height measurements were recorded from a total of 1399 individual trees with dbh ≥ 2 cm. The growth rate, maximum current and mean annual increments, minimum logging diameter, and cutting cycle were estimated, and alternative cutting cycles were established. Using these data, the harvestable volume of wood was projected by alternating four minimum logging diameters and five cutting cycles following the stand table projection method. The results show that J. procera trees have an average density of 183 stems ha⁻¹, a total basal area of 12.1 m² ha⁻¹, and a standing volume of 98.9 m³ ha⁻¹. The mean annual diameter growth ranges between 0.50 and 0.65 cm year⁻¹ with an overall mean of 0.59 cm year⁻¹. The population of J. procera tree followed a reverse J-shape diameter distribution pattern. The maximum current annual increment in volume (CAI) occurred at around 49 years when trees reached 30 cm in diameter. Trees showed the maximum mean annual increment in volume (MAI) around 91 years, with a diameter size of 50 cm. The simulation analysis revealed that 40 cm MLD and a 15-year cutting cycle are the best minimum logging diameter and cutting cycle. This combination showed the largest harvestable volume of wood potential, volume increments, and a 35% recovery of the initially harvested volume. It is concluded that the forest is well stocked and has a large amount of harvestable volume of wood from J. procera trees. This will enable the country to partly meet the national wood demand through domestic wood production. The use of the current population structure and diameter growth data from tree ring analysis enables the exact prediction of the harvestable volume of wood. The developed model supplied an idea about the productivity of the J. procera tree population and enables policymakers to develop specific management criteria for wood harvesting.

Keywords: logging, growth model, cutting cycle, minimum logging diameter

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Authors: Lahcen Daoudi, Fatima Zahra Omdi, Abldelali Gourfi

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In Morocco, as in most Mediterranean countries, water scarcity is a common situation because of low and unevenly distributed rainfall. The expansions of irrigated lands, as well as the growth of urban and industrial areas and tourist resorts, contribute to an increase of water demand. Therefore in the 1960s Morocco embarked on an ambitious program to increase the number of dams to boost water retention capacity. However, the decrease in the capacity of these reservoirs caused by sedimentation is a major problem; it is estimated at 75 million m3/year. Dams and reservoirs became unusable for their intended purposes due to sedimentation in large rivers that result from soil erosion. Soil erosion presents an important driving force in the process affecting the landscape. It has become one of the most serious environmental problems that raised much interest throughout the world. Monitoring soil erosion risk is an important part of soil conservation practices. The estimation of soil loss risk is the first step for a successful control of water erosion. The aim of this study is to estimate the soil loss risk and its spatial distribution in the different fields of Morocco and to prioritize areas for soil conservation interventions. The approach followed is the Revised Universal Soil Loss Equation (RUSLE) using remote sensing and GIS, which is the most popular empirically based model used globally for erosion prediction and control. This model has been tested in many agricultural watersheds in the world, particularly for large-scale basins due to the simplicity of the model formulation and easy availability of the dataset. The spatial distribution of the annual soil loss was elaborated by the combination of several factors: rainfall erosivity, soil erodability, topography, and land cover. The average annual soil loss estimated in several basins watershed of Morocco varies from 0 to 50t/ha/year. Watersheds characterized by high-erosion-vulnerability are located in the North (Rif Mountains) and more particularly in the Central part of Morocco (High Atlas Mountains). This variation of vulnerability is highly correlated to slope variation which indicates that the topography factor is the main agent of soil erosion within these basin catchments. These results could be helpful for the planning of natural resources management and for implementing sustainable long-term management strategies which are necessary for soil conservation and for increasing over the projected economic life of the dam implemented.

Keywords: soil loss, RUSLE, GIS-remote sensing, watershed, Morocco

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Sukhila Krishnan, Smita Mohanty, Sanjay K. Nayak

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Polylactide (PLA) and thermoplastic starch (TPS) are the most promising bio-based materials presently available on the market. Polylactic acid is one of the versatile biodegradable polyester showing wide range of applications in various fields and starch is a biopolymer which is renewable, cheap as well as extensively available. The usual increase in the cost of petroleum-based commodities in the next decades opens bright future for these materials. Their biodegradability and compostability was an added advantage in applications that are difficult to recycle. Currently, thermoplastic starch (TPS) has been used as a substitute for synthetic plastic in several commercial products. But, TPS shows some limitations mainly due to its brittle and hydrophilic nature, which has to be resolved to widen its application.The objective of the work we report here was to initiate chemical modifications on TPS and to build up a process to control its chemical structure using a solution process which can reduce its water sensitive properties and then blended it with PLA to improve compatibility between PLA and TPS. The method involves in cleavage of starch amylose and amylopectin chain backbone to plasticize with glycerol and water in batch mixer and then the prepared TPS was reacted in solution with diisocyanates i.e, 4,4'-Methylenediphenyl Diisocyanate (MDI).This diisocyanate was used before with great success for the chemical modification of TPS surface. The method utilized here will form an urethane-linkages between reactive isocyanate groups (–NCO) and hydroxyl groups (-OH) of starch as well as of glycerol. New polymer synthesised shows a reduced crystallinity, less hydrophilic and enhanced compatibility with other polymers. The TPS was prepared by Haake Rheomix 600 batch mixer with roller rotors operating at 50 rpm. The produced material is then refluxed for 5hrs with MDI in toluene with constant stirring. Finally, the modified TPS was melt blended with PLA in different compositions. Blends obtained shows an improved mechanical properties. These materials produced are characterized by Fourier Transform Infrared Spectra (FTIR), DSC, X-Ray diffraction and mechanical tests.

Keywords: polylactic acid, thermoplastic starch, Methylenediphenyl Diisocyanate, Polylactide (PLA)

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Authors: Napasri Suwanajote

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The purposes of this research were to analyse and evaluate successful factors in OTOP production process for the developing of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, marketing management

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Nazli Kazanoglu

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Reconciliation of work and family life has been an area of interest within the academic as well as in the political debate for more than three decades. With the dramatic changes in the extent to which women and men contribute to unpaid domestic work and paid employment, the reconciliation of work and family life issues have become more prominent than ever before. And they have begun to enjoy an increased attention of policy makers both at the EU and national levels. Over the last three decades the EU has initiated numerous equality programs and strategies and roadmaps regarding reconciliation of work and family life, though particularly because of the crisis and increasing willingness of achieving the EUs target of seventy five per cent of men and women in employment by 2020, those programs, strategies and roadmaps emphasized on eradicating womens familial burdens while entering labor market and providing them as equal opportunities as their male counterparts have. Reconciliation of work and family life policies thus bit by bit moved away from the objectives with a strong commitment to ensuring gender equality towards employment objectives. This paper is thus an endeavor to look at the nature of EU reconciliation of work and family life policies from the angle of gender equality. More precisely relying on the feminist literature, this paper rests on the assumption that reconciliation of work and family policies should provide the sufficient measures indeed with a more emphasis on endorsing gender equality rather than economic concerns and prioritizes two inter-related aspects while evaluating the gender equality of reconciliation of work and family life policies. First providing free choice to women in terms of their family and work lives and second challenge the unequal division of labor at home. In that sense, it investigates the nature of the changing uses and meanings of gender equality in reconciliation of work and family life policies in different stages of the EU social policy development particularly after the introduction of European Employment Strategy which gave a tremendous importance to reconciliation of work and family life during their collaborations with other issues on the EU agenda as well as the major rationale behind their development and implementation and locates them in terms of two inter-related parameters mentioned above.

Keywords: European Union, division of unpaid work, gender equality, rhetoric of free choice

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Authors: Joanna Peksa, Faith Dillon-Lee

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Current developments in the Western economies have turned some universities into corporate institutions driven by practices of production and commodity. Academia is increasingly becoming integrated into national economies as a result of students paying fees and is consequently using business practices in student retention and engagement. With these changes, pedagogy status as a priority within the institution has been changing in light of these new demands. New strategies have blurred the boundaries that separate a student from a client. This led to a change of the dynamic, disrupting the traditional idea of the knowledge market, and emphasizing the corporate aspect of universities. In some cases, where students are seen primarily as a customer, the purpose of academia is no longer to educate but sell a commodity and retain fee-paying students. This paper considers opposing viewpoints on the commodification of higher education, reflecting on the reality of maintaining a pedagogic grounding in an increasingly commercialized sector. By analysing a case study of the Student Success Festival, an event that involved academic and marketing teams, the differences are considered between the respective visions of the pedagogic arm of the university and the corporate. This study argues that the initial concept of the event, based on the principles of gamification, independent learning, and cognitive criticality, was more clearly linked to a grounded pedagogic approach. However, when liaising with the marketing team in a crucial step in the creative process, it became apparent that these principles were not considered a priority in terms of their remit. While the study acknowledges in the power of pedagogy, the findings show that a pact of concord is necessary between different stakeholders in order for students to benefit fully from their learning experience. Nevertheless, while issues of power prevail and whenever power is unevenly distributed, reaching a consensus becomes increasingly challenging and further research should closely monitor the developments in pedagogy in the UK higher education.

Keywords: economic pressure, commodification, pedagogy, gamification, public service, marketization

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Authors: Bougema Theodore Ntenkeh, Chi-bikom Barbara Kyien

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The reduction of poverty and hunger sits at the heart of the United Nations 2030 Agenda for Sustainable Development, and are the first two of the Sustainable Development Goals. The World Food Day celebrated on the 16th of October every year, highlights the need for people to have physical and economic access at all times to enough nutritious and safe food to live a healthy and active life; while the world poverty day celebrated on the 17th of October is an opportunity to acknowledge the struggle of people living in poverty, a chance for them to make their concerns heard, and for the community to recognize and support poor people in their fight against poverty. The association between household food security and poverty reduction is not only sparse in Cameroon but mostly qualitative. The paper therefore investigates the effect of household food security on poverty reduction in Cameroon quantitatively using data from the Cameroon Household Consumption Survey collected by the Government Statistics Office. The methodology employed five indicators of household food security using the Multiple Correspondence Analysis and poverty is captured as a dummy variable. Using a control function technique, with pre and post estimation test for robustness, the study postulates that household food security has a positive and significant effect on poverty reduction in Cameroon. A unit increase in the food security score reduces the probability of the household being poor by 31.8%, and this effect is statistically significant at 1%. The result further illustrates that the age of the household head and household size increases household poverty while households residing in urban areas are significantly less poor. The paper therefore recommends that households should diversify their food intake to enhance an effective supply of labour in the job market as a strategy to reduce household poverty. Furthermore, family planning methods should be encouraged as a strategy to reduce birth rate for an equitable distribution of household resources including food while the government of Cameroon should also develop the rural areas given that trend in urbanization are associated with the concentration of productive economic activities, leading to increase household income, increased household food security and poverty reduction.

Keywords: food security, poverty reduction, SDGs, Cameroon

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: Eleni C. Mazarakioti, Anastasios Zotos, Anna-Akrivi Thomatou, Efthimios Kokkotos, Achilleas Kontogeorgos, Athanasios Ladavos, Angelos Patakas

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“Gigantes Elefantes” is a particularly dynamic crop of giant beans cultivated in western Macedonia (Greece). This variety of large beans growing in this area and specifically in the regions of Prespes and Kastoria is a protected designation of origin (PDO) species with high nutritional quality. Mislabeling of geographical origin and blending with unidentified samples are common fraudulent practices in Greek food market with financial and possible health consequences. In the last decades, multi-elemental composition analysis has been used in identifying the geographical origin of foods and agricultural products. In an attempt to discriminate the authenticity of Greek beans, multi-elemental analysis (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Ge, K, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, Se, Sr, Ta, Ti, Tl, U, V, W, Zn, Zr) was performed by inductively coupled plasma mass spectrometry (ICP-MS) on 320 samples of beans, originated from Greece (Prespes and Kastoria), China and Poland. All samples were collected during the autumn of 2021. The obtained data were analysed by principal component analysis (PCA), an unsupervised statistical method, which allows for to reduce of the dimensionality of the enormous datasets. Statistical analysis revealed a clear separation of beans that had been cultivated in Greece compared with those from China and Poland. An adequate discrimination of geographical origin between bean samples originating from the two Greece regions, Prespes and Kastoria, was also evident. Our results suggest that multi-elemental analysis combined with the appropriate multivariate statistical method could be a useful tool for bean’s geographical authentication. Acknowledgment: This research has been financed by the Public Investment Programme/General Secretariat for Research and Innovation, under the call “YPOERGO 3, code 2018SE01300000: project title: ‘Elaboration and implementation of methodology for authenticity and geographical origin assessment of agricultural products.

Keywords: geographical origin, authenticity, multi-elemental analysis, beans, ICP-MS, PCA

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Authors: Corinna Zeli, Silvia Calati, Marco Simeoni, Chiara Comastri

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Developmental stuttering affects about 10% of preschool children; although the high percentage of natural recovery, a quarter of them will become an adult who stutters. An effective early intervention should help those children with high persistence risk for the future. The Psicodizione method for early stuttering is an Italian behavior indirect treatment for preschool children who stutter in which method parents act as good guides for communication, modeling their own fluency. In this study, we give a preliminary measure to evaluate the long-term effectiveness of Psicodizione method on stuttering preschool children with a high persistence risk. Among all Italian children treated with the Psicodizione method between 2018 and 2019, we selected 8 kids with at least 3 high risk persistence factors from the Illinois Prediction Criteria proposed by Yairi and Seery. The factors chosen for the selection were: one parent who stutters (1pt mother; 1.5pt father), male gender, ≥ 4 years old at onset; ≥ 12 months from onset of symptoms before treatment. For this study, the families were contacted after an average period of time of 14,7 months (range 3 - 26 months). Parental reports were gathered with a standard online questionnaire in order to obtain data reflecting fluency from a wide range of the children’s life situations. The minimum worthwhile outcome was set at "mild evidence" in a 5 point Likert scale (1 mild evidence- 5 high severity evidence). A second group of 6 children, among those treated with the Piscodizione method, was selected as high potential for spontaneous remission (low persistence risk). The children in this group had to fulfill all the following criteria: female gender, symptoms for less than 12 months (before treatment), age of onset <4 years old, none of the parents with persistent stuttering. At the time of this follow-up, the children were aged 6–9 years, with a mean of 15 months post-treatment. Among the children in the high persistence risk group, 2 (25%) hadn’t had stutter anymore, and 3 (37,5%) had mild stutter based on parental reports. In the low persistency risk group, the children were aged 4–6 years, with a mean of 14 months post-treatment, and 5 (84%) hadn’t had stutter anymore (for the past 16 months on average).62,5% of children at high risk of persistence after Psicodizione treatment showed mild evidence of stutter at most. 75% of parents confirmed a better fluency than before the treatment. The low persistence risk group seemed to be representative of spontaneous recovery. This study’s design could help to better evaluate the success of the proposed interventions for stuttering preschool children and provides a preliminary measure of the effectiveness of the Psicodizione method on high persistence risk children.

Keywords: early treatment, fluency, preschool children, stuttering

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Authors: Fangliang Chen, Yihe Huang, Tejav Deganyar, Anselm Boehm, Hamid Batoul

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With growing population density and further urbanization, the average noise level in cities is increasing. Excessive noise is not only annoying but also leads to a negative impact on human health. To deal with the increasing city noise, environmental regulations bring up higher standards on acoustic comfort in buildings by mitigating the noise transmission from building envelope exterior to interior. Framed window, door and façade systems are the leading choice for modern fenestration construction, which provides demonstrated quality of weathering reliability, environmental efficiency, and installation ease. The overall sound insulation of such systems depends both on glasses and frames, where glass usually covers the majority of the exposed surfaces, thus it is the main source of sound energy transmission. While frames in modern façade systems become slimmer for aesthetic appearance, which contribute to a minimal percentage of exposed surfaces. Nevertheless, frames might provide substantial transmission paths for sound travels through because of much less mass crossing the path, thus becoming more critical in limiting the acoustic performance of the whole system. There are various methodologies and numerical programs that can accurately predict the acoustic performance of either glasses or frames. However, due to the vast variance of size and dimension between frame and glass in the same system, there is no satisfactory theoretical approach or affordable simulation tool in current practice to access the over acoustic performance of a whole façade system. For this reason, laboratory test turns out to be the only reliable source. However, laboratory test is very time consuming and high costly, moreover different lab might provide slightly different test results because of varieties of test chambers, sample mounting, and test operations, which significantly constrains the early phase design of framed façade systems. To address this dilemma, this study provides an effective analytical methodology to predict the acoustic performance of framed façade systems, based on vast amount of acoustic test results on glass, frame and the whole façade system consist of both. Further test results validate the current model is able to accurately predict the overall sound transmission loss of a framed system as long as the acoustic behavior of the frame is available. Though the presented methodology is mainly developed from façade systems with aluminum frames, it can be easily extended to systems with frames of other materials such as steel, PVC or wood.

Keywords: city noise, building facades, sound mitigation, sound transmission loss, framed façade system

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Authors: Chukwumeka Daniel Ezeliora

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The Nigerian manufacturing sector plays a pivotal role in the country's economic growth and development. However, it faces numerous challenges, including operational inefficiencies and inherent risks that hinder its sustainable growth. This research aims to address these challenges by exploring the integration of Lean and Six Sigma methodologies into the manufacturing processes, ultimately enhancing operational effectiveness and risk mitigation. The core of this research involves the development of a sustainable Lean Six Sigma framework tailored to the specific needs and challenges of Nigeria's manufacturing environment. This framework aims to streamline processes, reduce waste, improve product quality, and enhance overall operational efficiency. It incorporates principles of sustainability to ensure that the proposed methodologies align with environmental and social responsibility goals. To validate the effectiveness of the integrated Lean Six Sigma approach, case studies and real-world applications within select manufacturing companies in Nigeria will be conducted. Data were collected to measure the impact of the integration on key performance indicators, such as production efficiency, defect reduction, and risk mitigation. The findings from this research provide valuable insights and practical recommendations for selected manufacturing companies in South East Nigeria. By adopting sustainable Lean Six Sigma methodologies, these organizations can optimize their operations, reduce operational risks, improve product quality, and enhance their competitiveness in the global market. In conclusion, this research aims to bridge the gap between theory and practice by developing a comprehensive framework for the integration of Lean and Six Sigma methodologies in Nigeria's manufacturing sector. This integration is envisioned to contribute significantly to the sector's sustainable growth, improved operational efficiency, and effective risk mitigation strategies, ultimately benefiting the Nigerian economy as a whole.

Keywords: lean six sigma, manufacturing, risk mitigation, sustainability, operational efficiency

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Authors: Alexander Buhr, Klaus Ehrenfried

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Trackside induced airflow velocities, also known as slipstream velocities, are an important criterion for the design of high-speed trains. The maximum permitted values are given by the Technical Specifications for Interoperability (TSI) and have to be checked in the approval process. For train manufactures it is of great interest to know in advance, how new train geometries would perform in TSI tests. The Reynolds number in moving model experiments is lower compared to full-scale. Especially the limited model length leads to a thinner boundary layer at the rear end. The hypothesis is that the boundary layer rolls up to characteristic flow structures in the train wake, in which the maximum flow velocities can be observed. The idea is to enlarge the boundary layer using roughness elements at the train model head so that the ratio between the boundary layer thickness and the car width at the rear end is comparable to a full-scale train. This may lead to similar flow structures in the wake and better prediction accuracy for TSI tests. In this case, the design of the roughness elements is limited by the moving model rig. Small rectangular roughness shapes are used to get a sufficient effect on the boundary layer, while the elements are robust enough to withstand the high accelerating and decelerating forces during the test runs. For this investigation, High-Speed Particle Image Velocimetry (HS-PIV) measurements on an ICE3 train model have been realized in the moving model rig of the DLR in Göttingen, the so called tunnel simulation facility Göttingen (TSG). The flow velocities within the boundary layer are analysed in a plain parallel to the ground. The height of the plane corresponds to a test position in the EN standard (TSI). Three different shapes of roughness elements are tested. The boundary layer thickness and displacement thickness as well as the momentum thickness and the form factor are calculated along the train model. Conditional sampling is used to analyse the size and dynamics of the flow structures at the time of maximum velocity in the train wake behind the train. As expected, larger roughness elements increase the boundary layer thickness and lead to larger flow velocities in the boundary layer and in the wake flow structures. The boundary layer thickness, displacement thickness and momentum thickness are increased by using larger roughness especially when applied in the height close to the measuring plane. The roughness elements also cause high fluctuations in the form factors of the boundary layer. Behind the roughness elements, the form factors rapidly are approaching toward constant values. This indicates that the boundary layer, while growing slowly along the second half of the train model, has reached a state of equilibrium.

Keywords: boundary layer, high-speed PIV, ICE3, moving train model, roughness elements

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Authors: Kaleb Shiferaw, Berhanu Geberemedhin

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Ethiopian farmers have a long tradition of beekeeping and the country has huge potential for honey production. However traditional mode of production still dominates the sub sector which negatively affect the total production and productivity. A number of studies have been conducted to better understand the working honey production, however, none of them systematically investigate the extent of technical efficiency of the sub-sector. This paper uses Stochastic Frontier production model to quantifying the extent of technical efficiency and identify exogenous determinant of inefficiency. The result showed that consistent with other studies traditional practice dominate small scale honey production in Ethiopia. The finding also revealed that use of purchased inputs such as bee forage and other supplement is very limited among honey producers indicating that natural bee forage is the primary source of bee forage. The immediate consequence of all these is low production and productivity. The number of hives the household owns, whether the household used improved apiculture technologies, availability of natural forest which is the primary sources of nectar for bees and amount of land owned by the households were found to have a significant influence on the amount of honey produced by beekeeper. Our result further showed that the mean technical efficiency of honey producers is 0.79 implying that, on average honey producer produce 80 percent of the maximum output. The implication is that 20 percent of the potential output is lost due to technical inefficiency. Number of hives owned by a honey produces, distance to district town-a proxy to market access, household wealth, and whether the household head has a leadership role in the PA affect the technical efficiency of honey producers. The finding suggest that policies that aim to expand the use of improved hives is expected to increase the honey production at household level. The result also suggest that investment on rural infrastructure would be instrumental in improving technical efficiency of honey producer.

Keywords: small-scale honey producer, Ethiopia, technical efficiency in apiculture, stochastic frontier analysis

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Authors: Mansur Hamma-Adama, Tahar Kouider

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Construction Industry has been evolving since the development of Building Information Modelling (BIM). This technological process is unstoppable; it is out to the market with remarkable case studies of solving the long industry’s history of fragmentation. This industry has been changing over time; United States has recorded the most significant development in construction digitalization, Australia, United Kingdom and some other developed nations are also amongst promoters of BIM process and its development. Recently, a developing country like China and Malaysia are keying into the industry’s digital shift, while very little move is seen in South Africa whose development is considered higher and perhaps leader in the digital transition amongst the African countries. To authors’ best knowledge, Nigerian construction industry has never engaged in BIM discussions hence has no attention at national level. Consequently, Nigeria has no “Noteworthy BIM publications.” Decision makers and key stakeholders need to be informed on the current trend of the industry’s development (BIM in specific) and the opportunities of adopting this digitalization trend in relation to the identified challenges. BIM concept can be traced mostly in Architectural practices than engineering practices in Nigeria. A superficial BIM practice is found to be at organisational level only and operating a model based - “BIM stage 1.” Research to adopting this innovation has received very little attention. This piece of work is literature review based, aimed at exploring BIM in Nigeria and its prospects. The exploration reveals limitations in the literature availability as to extensive research in the development of BIM in the country. Numerous challenges were noticed including building collapse, inefficiencies, cost overrun and late project delivery. BIM has potentials to overcome the above challenges and even beyond. Low level of BIM adoption with reasonable level of awareness is noticed. However, lack of policy and guideline as well as serious lack of experts in the field are amongst the major barriers to BIM adoption. The industry needs to embrace BIM to possibly compete with its global counterpart.

Keywords: adoption, BIM, CAD, construction industry, Nigeria, opportunities

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Authors: Tanvi P. Medshinge, Prasad Vaidya, Monisha E. Royan

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In India, cooling loads in residential sector is a major contributor to its total energy consumption. Due to the increasing cooling need, the market penetration of air-conditioners is further expected to rise. Natural Ventilation (NV), however, possesses great potential to save significant energy consumption especially for residential buildings in moderate climates. As multifamily residential apartment buildings are designed by repetitive use of prototype designs, deriving individual NV based design prototype solutions for a combination of different wind incidence angles and orientations would provide significant opportunity to address the rise in cooling loads by residential sector. This paper presents the results of NV performance of a selected prototype apartment design with a cluster of four units in Pune, India, and an attempt to improve the NV performance through design modifications. The water table apparatus, a physical modelling tool, is used to study the flow patterns and simulate wind-induced NV performance. Quantification of NV performance is done by post processing images captured from video recordings in terms of percentage of area with good and poor access to ventilation. NV performance of the existing design for eight wind incidence angles showed that of the cluster of four units, the windward units showed good access to ventilation for all rooms, and the leeward units had lower access to ventilation with the bedrooms in the leeward units having the least access. The results showed improved performance in all the units for all wind incidence angles to more than 80% good access to ventilation. Some units showed an additional improvement to more than 90% good access to ventilation. This process of design and performance evaluation improved some individual units from 0% to 100% for good access to ventilation. The results demonstrate the ease of use and the power of the water table apparatus for performance-based design to simulate wind induced NV.  

Keywords: fluid dynamics, prototype design, natural ventilation, simulations, water table apparatus, wind incidence angles

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