Search results for: Interacting water level process

Authors: Omid F. Valilai, Mahmoud Houshmand

Abstract:

Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Keywords: CAx, Collaboration management, STEP applicationmodules, STEP standard, XML data structures

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Authors: Sayem Zafar, Mahmood Rahi

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Rigorous international maritime regulations are in place to limit boat and ship hydrocarbon emissions. The global sustainability goals are reducing the fuel consumption and minimizing the emissions from the ships and boats. These maritime sustainability goals have attracted a lot of research interest. Energy harvesting and storage system is designed in this study based on hybrid renewable and conventional energy systems. This energy harvesting and storage system is designed for marine applications, such as, boats and small ships. These systems can be utilized for mobile use or off-grid remote electrification. This study analyzed the use of micro power generation for boats and small ships. The energy harvesting and storage system has two distinct systems i.e. dockside shore-based system and on-board system. The shore-based system consists of a small wind turbine, photovoltaic (PV) panels, small gas turbine, hydrogen generator and high-pressure hydrogen storage tank. This dockside system is to provide easy access to the boats and small ships for supply of hydrogen. The on-board system consists of hydrogen storage tanks and fuel cells. The wind turbine and PV panels generate electricity to operate electrolyzer. A small gas turbine is used as a supplementary power system to contribute in case the hybrid renewable energy system does not provide the required energy. The electrolyzer performs the electrolysis on distilled water to produce hydrogen. The hydrogen is stored in high-pressure tanks. The hydrogen from the high-pressure tank is filled in the low-pressure tanks on-board seagoing vessels to operate the fuel cell. The boats and small ships use the hydrogen fuel cell to provide power to electric propulsion motors and for on-board auxiliary use. For shore-based system, a small wind turbine with the total length of 4.5 m and the disk diameter of 1.8 m is used. The small wind turbine dimensions make it big enough to be used to charge batteries yet small enough to be installed on the rooftops of dockside facility. The small dimensions also make the wind turbine easily transportable. In this paper, PV, sizing and solar flux are studied parametrically. System performance is evaluated under different operating and environmental conditions. The parametric study is conducted to evaluate the energy output and storage capacity of energy storage system. Results are generated for a wide range of conditions to analyze the usability of hybrid energy harvesting and storage system. This energy harvesting method significantly improves the usability and output of the renewable energy sources. It also shows that small hybrid energy systems have promising practical applications.

Keywords: Energy harvesting, fuel cell, hybrid energy system, hydrogen, wind turbine.

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Authors: Tomas Makaras, Gintaras Svecevičius

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Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Keywords: Fish behavior biomarker, landfill leachate, locomotor activity, rainbow trout juveniles, sublethal effects.

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Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: Lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS.

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias

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Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.

Keywords: automatic clustering, bioinformatics tool, gene ontology, protein sequence annotation, semantic similarity search

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Authors: Saman Keshavarzi

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The process of planning, designing and building neighborhoods is a complex and multidimensional part of urban planning. Understanding the elements that give a neighborhood a sense of identity can lead to successful city planning and result in a cohesive and functional community where people feel a sense of belonging. These factors are important in ensuring that the needs of the urban population are met to live in a safe, pleasant and healthy society. This research paper aims to identify the elements of the identity of traditional neighborhoods in Isfahan and analyzes ways of using these elements in the design of modern neighborhoods to increase social interaction between communities and cultural reunification of people. The neighborhood of Jolfa in Isfahan has a unique socio-cultural identity as it dates back to the Safavid Dynasty of the 16^th century, and most of its inhabitants are Christian Armenians of a religious minority. The elements of the identity of Jolfa were analyzed through the following research methods: field observations, distribution of questionnaires and qualitative analysis. The basic methodology that was used to further understand the Jolfa neighborhood and deconstruct the identity image that residents associate with their respective neighborhoods was a qualitative research method. This was done through utilizing questionnaires that respondents had to fill out in response to a series of research questions. From collecting these qualitative data, the major finding was that traditional neighborhoods that have elements of identity embedded in them are seen to have closer-knit communities whose residents have strong societal ties. This area of study in urban planning is vital to ensuring that new neighborhoods are built with concepts of social cohesion, community and inclusion in mind as they are what lead to strong, connected, and prosperous societies.

Keywords: Development, housing, identity, neighborhood, policy, urbanization.

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Authors: G. Disciglio, G. Gatta, F. Lops, A. Libutti, A. Tarantino, E. Tarantino

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The experimental trial was carried out in open field at Foggia district (Apulia Region, Southern Italy), during the spring-summer season 2014, in order to evaluate the effect of four biostimulant products (RadiconÒ, Viormon plusÒ, LysodinÒ and SiaptonÒ 10L), compared with a control (no biostimulant), on the infestation of processing tomato crop (cv Dres) by the chlorophyll-lacking root parasite Phelipanche ramosa. Biostimulants consist in different categories of products (microbial inoculants, humic and fulvic acids, hydrolyzed proteins and aminoacids, seaweed extracts) which play various roles in plant growing, including the improvement of crop resistance and quali-quantitative characteristics of yield. The experimental trial was arranged according to a complete randomized block design with five treatments, each of one replicated three times. The processing tomato seedlings were transplanted on 5 May 2014. Throughout the crop cycle, P. ramosa infestation was assessed according to the number of emerged shoots (branched plants) counted in each plot, at 66, 78 and 92 day after transplanting. The tomato fruits were harvested at full-stage of maturity on 8 August 2014. From each plot, the marketable yield was measured and the quali-quantitative yield parameters (mean weight, dry matter content, colour coordinate, colour index and soluble solids content of the fruits) were determined. The whole dataset was tested according to the basic assumptions for the analysis of variance (ANOVA) and the differences between the means were determined using Tukey’s tests at the 5% probability level. The results of the study showed that none of the applied biostimulants provided a whole control of Phelipanche, although some positive effects were obtained from their application. To this respect, the RadiconÒ appeared to be the most effective in reducing the infestation of this root-parasite in tomato crop. This treatment also gave the higher tomato yield.

Keywords: Biostimulants, control methods, Phelipanche ramosa, processing tomato crop.

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: Customer value, Huff's Gravity Model, POS, retailer.

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Authors: Fawzi Irshaid, Kamal Mansi

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Thyroid dysfunction is one of the most frequently reported complications of chronic blood transfusion therapy in patients with beta-thalassemia major (BTM). However, the occurrence of thyroid dysfunction and its possible association with iron overload in BTM patients is still under debate. Therefore, this study aimed to investigate the status of thyroid functions and iron overload in adolescent and young adult patients with BTM in Jordan population. Thirty six BTM patients aged 12-28 years and matched controls were included in this study. All patients have been receiving frequent blood transfusion to maintain pretransfusion hemoglobin concentration above 10 g dl-1 and deferoxamine at a dose of 45 mg kg-1 day-1 (8 h, 5-7 days/week) by subcutaneous infusion. Blood samples were drawn from patients and controls. The status of thyroid functions and iron overload was evaluated by measurements of serum free thyroxine (FT4), triiodothyronine (FT3), thyrotropin (TSH) and serum ferritin level. A number of some hematological and biochemical parameters were also measured. It was found that hematocrit, serum ferritin, hemoglobin, FT3 and zinc, copper mean values were significantly higher in the patients than in the controls (P< 0.05). On other hand, leukocyte, FT4 and TSH mean values were similar to that of the controls. In addition, our data also indicated that all of the above examined parameters were not significantly affected by the patient-s age and gender. Deferoxamine approach for removing excess iron from our BTM patient did not normalize the values of serum ferritin, copper and zinc, suggesting poor compliance with deferoxamine chelation therapy. Thus, we recommend the use of a combination of deferoxamine and deferiprone to reduce the risk of excess of iron in our patients. Furthermore, thyroid dysfunction appears to be a rare complication, because our patients showed normal mean levels for serum TSH and FT4. However, high mean levels of serum ferritin, zinc, copper might be seen as potential risk factors for initiation and development of thyroid dysfunctions and other diseases. Therefore, further studies must be carried out at yearly intervals with large sample number, to detect subclinical thyroid dysfunction cases.

Keywords: beta-thalassemia major, deferoxamine, iron overload, triiodothyronine, zinc.

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Authors: V. Barot, S. McLeod, R. Harrison, A. A. West

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Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Keywords: Broadcaster, circular buffer, Component-based, distributed manufacturing, remote data propagation.

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Authors: Berceste Gülçin Özdemir

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The representation of women characters in cinema has been discussed for centuries. In cinema where dominant narrative codes prevail and scopophilic views exist over women characters, passive stereotypes of women are observed in the representation of women characters. In films shot from a woman’s point of view in Turkish Cinema and even in the films outside the main stream in which the stories of women characters are told, the fact that women characters are discussed on the basis of feminist film theories triggers the question: ‘Are feminist films produced in Turkish Cinema?’ The spaces that are used in the representation of women characters are observed to be used as spaces that convert characters into passive subjects on the basis of the space factor in the narrative. The representation of women characters in the possible surveillance spaces integrates the characters and compresses them in these spaces. In this study, narrative analysis was used to investigate women characters representation in the surveillance spaces. For the study framework, firstly a case study films are selected, and in the second level, women characters representations in surveillance spaces are argued by narrative analysis using feminist film theories. Two questions are argued with feminist film theories: ‘Why do especially women directors represent their female characters to viewers by representing them in surveillance spaces?’ and ‘Can this type of presentation contribute to the feminist film practice and become important with regard to feminist film theories?’ The representation of women characters in a passive and observed way in surveillance spaces of the narrative reveals the questioning of also the discourses of films outside of the main stream. As films that produce alternative discourses and reveal different cinematic languages, those outside the main stream are expected to bring other points of view also to the representation of women characters in spaces. These questionings are selected as the baseline and Turkish films such as Watch Tower and Mustang, directed by women, were examined. This examination paves the way for discussions regarding the women characters in surveillance spaces. Outcomes can be argued from the viewpoint of representation in the genre by feminist film theories. In the context of feminist film theories and feminist film practice, alternatives should be found that can corporally reveal the existence of women in both the representation of women characters in spaces and in the usage of the space factor.

Keywords: Feminist film theory, representation, space, women filmmaker, women characters.

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Authors: Y. Z. Wu, Z. Dong, S. K. You

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Global approximation using metamodel for complex mathematical function or computer model over a large variable domain is often needed in sensibility analysis, computer simulation, optimal control, and global design optimization of complex, multiphysics systems. To overcome the limitations of the existing response surface (RS), surrogate or metamodel modeling methods for complex models over large variable domain, a new adaptive and regressive RS modeling method using quadratic functions and local area model improvement schemes is introduced. The method applies an iterative and Latin hypercube sampling based RS update process, divides the entire domain of design variables into multiple cells, identifies rougher cells with large modeling error, and further divides these cells along the roughest dimension direction. A small number of additional sampling points from the original, expensive model are added over the small and isolated rough cells to improve the RS model locally until the model accuracy criteria are satisfied. The method then combines local RS cells to regenerate the global RS model with satisfactory accuracy. An effective RS cells sorting algorithm is also introduced to improve the efficiency of model evaluation. Benchmark tests are presented and use of the new metamodeling method to replace complex hybrid electrical vehicle powertrain performance model in vehicle design optimization and optimal control are discussed.

Keywords: Global approximation, polynomial response surface, domain decomposition, domain combination, multiphysics modeling, hybrid powertrain optimization

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Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: Active learning, blended learning, maker movement, new product development, open innovation laboratory.

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Authors: Ahmad B. Habieb, Gabriele Milani, Tavio Tavio, Federico Milani

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Housings in developing countries have often inadequate seismic protection, particularly for masonry. People choose this type of structure since the cost and application are relatively cheap. Seismic protection of masonry remains an interesting issue among researchers. In this study, we develop a low-cost seismic isolation system for masonry using fiber reinforced elastomeric isolators. The elastomer proposed consists of few layers of rubber pads and fiber lamina, making it lower in cost comparing to the conventional isolators. We present a finite element (FE) analysis to predict the behavior of the low cost rubber isolators undergoing moderate deformations. The FE model of the elastomer involves a hyperelastic material property for the rubber pad. We adopt a Yeoh hyperelasticity model and estimate its coefficients through the available experimental data. Having the shear behavior of the elastomers, we apply that isolation system onto small masonry housing. To attach the isolators on the building, we model the shear behavior of the isolation system by means of a damped nonlinear spring model. By this attempt, the FE analysis becomes computationally inexpensive. Several ground motion data are applied to observe its sensitivity. Roof acceleration and tensile damage of walls become the parameters to evaluate the performance of the isolators. In this study, a concrete damage plasticity model is used to model masonry in the nonlinear range. This tool is available in the standard package of Abaqus FE software. Finally, the results show that the low-cost isolators proposed are capable of reducing roof acceleration and damage level of masonry housing. Through this study, we are also capable of monitoring the shear deformation of isolators during seismic motion. It is useful to determine whether the isolator is applicable. According to the results, the deformations of isolators on the benchmark one story building are relatively small.

Keywords: Masonry, low cost elastomeric isolator, finite element analysis, hyperelasticity, damped non-linear spring, concrete damage plasticity.

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

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The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

Abstract:

The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Marshal D. Kafle, Jun H. Kim, Hyun W. Been, Kyoung M. Min, Sung H. Kim

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Fluid viscous damping systems are well suited for many air vehicles subjected to shock and vibration. These damping system work with the principle of viscous fluid throttling through the orifice to create huge pressure difference between compression and rebound chamber and obtain the required damping force. One application of such systems is its use in aircraft door system to counteract the door’s velocity and safely stop it. In exigency situations like crash or emergency landing where the door doesn’t open easily, possibly due to unusually tilting of fuselage or some obstacles or intrusion of debris obstruction to move the parts of the door, such system can be combined with other systems to provide needed force to forcefully open the door and also securely stop it simultaneously within the required time i.e. less than 8 seconds. In the present study, a hydraulic system called snubber along with other systems like actuator, gas bottle assembly which together known as emergency power assist system (EPAS) is designed, built and experimentally studied to check the magnitude of angular velocity, damping force and time required to effectively open the door. Whenever needed, the gas pressure from the bottle is released to actuate the actuator and at the same time pull the snubber’s piston to operate the emergency opening of the door. Such EPAS installed in the suspension arm of the aircraft door is studied explicitly changing parameters like orifice size, oil level, oil viscosity and bypass valve gap and its spring of the snubber at varying temperature to generate the optimum design case. Comparative analysis of the EPAS at several cases is done and conclusions are made. It is found that during emergency condition, the system opening time and angular velocity, when snubber with 0.3mm piston and shaft orifice and bypass valve gap of 0.5 mm with its original spring is used, shows significant improvement over the old ones.

Keywords: Aircraft Door Damper, Bypass Valve, Emergency Power Assist System, Hydraulic Damper, Oil viscosity.

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Authors: Katie Emerson, Sara Perez-Ojalvo, Jim Komorowski, Danielle Greenberg

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The purpose of this study was to evaluate arginase activity levels in response to combinations of an inositol-stabilized arginine silicate (ASI; Nitrosigine®), L-arginine, and Inositol. Arginine acts as a vasodilator that promotes increased blood flow resulting in enhanced delivery of oxygen and nutrients to the brain and other tissues. Arginase, found in human serum, catalyzes the conversion of arginine to ornithine and urea, completing the last step in the urea cycle. Decreasing arginase levels maintains arginine and results in increased nitric oxide production. This study aimed to determine the most effective combination of ASI, L-arginine and inositol for minimizing arginase levels and therefore maximize ASI’s effect on cognition. Serum was taken from untreated healthy donors by separation from clotted factors. Arginase activity of serum in the presence or absence of test products was determined (QuantiChrom™, DARG-100, Bioassay Systems, Hayward CA). The remaining ultra-filtrated serum units were harvested and used as the source for the arginase enzyme. ASI alone or combined with varied levels of Inositol were tested as follows: ASI + inositol at 0.25 g, 0.5 g, 0.75 g, or 1.00 g. L-arginine was also tested as a positive control. All tests elicited changes in arginase activity demonstrating the efficacy of the method used. Adding L-arginine to serum from untreated subjects, with or without inositol only had a mild effect. Adding inositol at all levels reduced arginase activity. Adding 0.5 g to the standardized amount of ASI led to the lowest amount of arginase activity as compared to the 0.25 g, 0.75 g or 1.00g doses of inositol or to L-arginine alone. The outcome of this study demonstrates an interaction of the pairing of inositol with ASI on the activity of the enzyme arginase. We found that neither the maximum nor minimum amount of inositol tested in this study led to maximal arginase inhibition. Since the inhibition of arginase activity is desirable for product formulations looking to maintain arginine levels, the most effective amount of inositol was deemed preferred. Subsequent studies suggest this moderate level of inositol in combination with ASI leads to cognitive improvements including reaction time, executive function, and concentration.

Keywords: Arginine, blood flow, colorimetry, urea cycle.

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Authors: M. T. Yazdani Sabouni, Rasaratnam Logendran

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We consider a typical problem in the assembly of printed circuit boards (PCBs) in a two-machine flow shop system to simultaneously minimize the weighted sum of weighted tardiness and weighted flow time. The investigated problem is a group scheduling problem in which PCBs are assembled in groups and the interest is to find the best sequence of groups as well as the boards within each group to minimize the objective function value. The type of setup operation between any two board groups is characterized as carryover sequence-dependent setup time, which exactly matches with the real application of this problem. As a technical constraint, all of the boards must be kitted before the assembly operation starts (kitting operation) and by kitting staff. The main idea developed in this paper is to completely eliminate the role of kitting staff by assigning the task of kitting to the machine operator during the time he is idle which is referred to as integration of internal (machine) and external (kitting) setup times. Performing the kitting operation, which is a preparation process of the next set of boards while the other boards are currently being assembled, results in the boards to continuously enter the system or have dynamic arrival times. Consequently, a dynamic PCB assembly system is introduced for the first time in the assembly of PCBs, which also has characteristics similar to that of just-in-time manufacturing. The problem investigated is computationally very complex, meaning that finding the optimal solutions especially when the problem size gets larger is impossible. Thus, a heuristic based on Genetic Algorithm (GA) is employed. An example problem on the application of the GA developed is demonstrated and also numerical results of applying the GA on solving several instances are provided.

Keywords: Genetic algorithm, Dynamic PCB assembly, Carryover sequence-dependent setup times, Multi-objective.

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Authors: Malathi Balakrishnan, Cheng Lee Ooi, Chander Vengadasalam

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The purpose of this study is to explore a case study of trainee teachers’ learning experience on innovating traditional games during the traditional game carnival. It explores issues arising from multiple case studies of trainee teachers learning experiences in innovating traditional games. A qualitative methodology was adopted through observations, semi-structured interviews and reflective journals’ content analysis of trainee teachers’ learning experiences creating and implementing innovative traditional games. Twelve groups of 36 trainee teachers who registered for Sports and Physical Education Management Course were the participants for this research during the traditional game carnival. Semi structured interviews were administrated after the trainee teachers learning experiences in creating innovative traditional games. Reflective journals were collected after carnival day and the content analyzed. Inductive data analysis was used to evaluate various data sources. All the collected data were then evaluated through the Nvivo data analysis process. Inductive reasoning was interpreted based on the Self Determination Theory (SDT). The findings showed that the trainee teachers had positive game participation experiences, game knowledge about traditional games and positive motivation to innovate the game. The data also revealed the influence of themes like cultural significance and creativity. It can be concluded from the findings that the organized game carnival, as a requirement of course work by the Institute of Teacher Training Malaysia, was able to enhance teacher trainers’ innovative thinking skills. The SDT, as a multidimensional approach to motivation, was utilized. Therefore, teacher trainers may have more learning experiences using the SDT.

Keywords: Learning experiences, innovation, traditional games, trainee teachers.

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: Human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence.

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Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

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In the modern manufacturing systems, the use of thermal cutting techniques using oxyfuel, plasma and laser have become indispensable for the shape forming of high quality complex components; however, the conventional chip removal production techniques still have its widespread space in the manufacturing industry. Both these types of machining operations require the positioning of end effector tool at the edge where the cutting process commences. This repositioning of the cutting tool in every machining operation is repeated several times and is termed as non-productive time or airtime motion. Minimization of this non-productive machining time plays an important role in mass production with high speed machining. As, the tool moves from one region to the other by rapid movement and visits a meticulous region once in the whole operation, hence the non-productive time can be minimized by synchronizing the tool movements. In this work, this problem is being formulated as a general travelling salesman problem (TSP) and a genetic algorithm approach has been applied to solve the same. For improving the efficiency of the algorithm, the GA has been hybridized with a noble special heuristic and simulating annealing (SA). In the present work a novel heuristic in the combination of GA has been developed for synchronization of toolpath movements during repositioning of the tool. A comparative analysis of new Meta heuristic techniques with simple genetic algorithm has been performed. The proposed metaheuristic approach shows better performance than simple genetic algorithm for minimization of nonproductive toolpath length. Also, the results obtained with the help of hybrid simulated annealing genetic algorithm (HSAGA) are also found better than the results using simple genetic algorithm only.

Keywords: Non-productive time, Airtime, 2.5 D milling, Laser cutting, Metaheuristic, Genetic Algorithm, Simulated Annealing.

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Authors: К. R. Aida–Zade, C. Ardil, S. S. Rustamov

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Statement of the automatic speech recognition problem, the assignment of speech recognition and the application fields are shown in the paper. At the same time as Azerbaijan speech, the establishment principles of speech recognition system and the problems arising in the system are investigated. The computing algorithms of speech features, being the main part of speech recognition system, are analyzed. From this point of view, the determination algorithms of Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) coefficients expressing the basic speech features are developed. Combined use of cepstrals of MFCC and LPC in speech recognition system is suggested to improve the reliability of speech recognition system. To this end, the recognition system is divided into MFCC and LPC-based recognition subsystems. The training and recognition processes are realized in both subsystems separately, and recognition system gets the decision being the same results of each subsystems. This results in decrease of error rate during recognition. The training and recognition processes are realized by artificial neural networks in the automatic speech recognition system. The neural networks are trained by the conjugate gradient method. In the paper the problems observed by the number of speech features at training the neural networks of MFCC and LPC-based speech recognition subsystems are investigated. The variety of results of neural networks trained from different initial points in training process is analyzed. Methodology of combined use of neural networks trained from different initial points in speech recognition system is suggested to improve the reliability of recognition system and increase the recognition quality, and obtained practical results are shown.

Keywords: Speech recognition, cepstral analysis, Voice activation detection algorithm, Mel Frequency Cepstral Coefficients, features of speech, Cepstral Mean Subtraction, neural networks, Linear Predictive Coding.

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Authors: U. K. Sahin, N. Erdumlu, C. Saricam, I. Gocek, M. H. Arslan, H. Acikgoz-Tufan, B. Kalav

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Finishing is an important part of fabric processing with which a wide range of features are imparted to greige or colored fabrics for various end-uses. Especially, by the addition or impartation of nano-scaled particles to the fabric structure composite fabrics, a kind of composite materials can be acquired. Composite materials, generally shortened as composites or in other words composition materials, are engineered or naturally occurring materials made from two or more component materials with significantly different physical, mechanical or chemical characteristics remaining separate and distinctive at the macroscopic or microscopic scale within the end product structure. Therefore, the technique finishing which is one of the fundamental methods to be applied on fabrics for obtainment of composite fabrics with many functionalities was used in the current study with the same purpose. However, regardless of the finishing materials applied, the efficient life of finished product on offering desired feature is low, since the durability of finishes on the material is limited. Any increase in durability of these finishes on textiles would enhance the life of use for textiles, which will result in happier users. Therefore, in this study, since higher durability was desired for the finishing materials fixed on the fabrics, nano-scaled hollow structured cyclodextrins were chemically imparted by grafting to the structure of conventional cotton fabrics by the help of finishing technique in order to be fixed permanently. By this way, a processed and functionalized base fabric having potential to be treated in the subsequent processes with many different finishing agents and nanomaterials could be obtained. Henceforth, this fabric can be used as a multi-functional fabric due to the encapturing ability of cyclodextrins to molecules/particles via physical/chemical means. In this study, scoured and rinsed woven bleached plain weave 100% cotton fabrics were utilized because textiles made of cotton are the most demanded textile products in the textile market by the textile consumers in daily life. Cotton fabric samples were immersed in treating baths containing β-cyclodextrin and 1,2,3,4-butanetetracarboxylic acid and to reduce the curing temperature the catalyst sodium hypophosphite monohydrate was used. All impregnated fabric samples were pre-dried. The reaction of grafting was performed in dry state. The treated and cured fabric samples were rinsed with warm distilled water and dried. The samples were dried for 4 h and weighed before and after finishing and rinsing. Stability and durability of β-cyclodextrins on fabric surface against external factors such as washing as well as strength of functionalized fabric in terms of tensile and tear strength were tested. Presence and homogeneity of distribution of β-cyclodextrins on fabric surface were characterized.

Keywords: Cotton fabric, cyclodextrin, improved durability, multifunctional composite textile.

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Authors: Abeer Aljohani

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The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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Authors: Isaac Kofi Mensah

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Governments around the world are adopting Information and Communication Technologies (ICTs) because of the important opportunities it provides through E-government (EG) to modernize government public administration processes and delivery of quality and efficient public services. Almost every country in the world is adopting ICT in its public sector administration (EG) to modernize and change the traditional process of government, increase citizen engagement and participation in governance, as well as the provision of timely information to citizens. This paper, therefore, seeks to present the adoption, development and implementation of EG in regions globally, as well as the ICT indicators around the world, which are making EG initiatives successful. Europe leads the world in its EG adoption and development index, followed by the Americas, Asia, Oceania and Africa. There is a gradual growth in ICT indicators in terms of the increase in Internet access and usage, increase in broadband penetration, an increase of individuals using the Internet at home and a decline in fixed telephone use, while the mobile cellular phone has been on the increase year-on-year. Though the lack of ICT infrastructure is a major challenge to EG adoption and implementation around the world, in Africa it is very pervasive, hampering the expansion of Internet access and provision of broadband, and hence is a barrier to the successful adoption, development, and implementation of EG initiatives in countries on the continent. But with the general improvement and increase in ICT indicators around the world, it provides countries in Europe, Americas, Asia, Arab States, Oceania and Africa with the huge opportunity to enhance public service delivery through the adoption of EG. Countries within these regions cannot fail their citizens who desire to enjoy an enhanced and efficient public service delivery from government and its many state institutions.

Keywords: E-government development index, e-government, indicators, information and communication technologies.

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Authors: Fruzsina Pataki-Bittó, Edit Németh

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On the one hand, new technologies and communication tools improve employee productivity and accelerate information and knowledge transfer, while on the other hand, information overload and continuous interruptions make it even harder to concentrate at work. It is a great challenge for companies to find the right balance, while there is also an ongoing demand to recruit and retain the talented employees who are able to adopt the modern work style and effectively use modern communication tools. For this reason, this research does not focus on the objective measures of office interruptions, but aims to find those disruption factors which influence the comfort and job satisfaction of employees, and the way how they feel generally at work. The focus of this research is on how employees feel about the different types of interruptions, which are those they themselves identify as hindering factors, and those they feel as stress factors. By identifying and then reducing these destructive factors, job satisfaction can reach a higher level and employee turnover can be reduced. During the research, we collected information from depth interviews and questionnaires asking about work environment, communication channels used in the workplace, individual communication preferences, factors considered as disruptions, and individual steps taken to avoid interruptions. The questionnaire was completed by 141 office workers from several types of workplaces based in Hungary. Even though 66 respondents are working at Hungarian offices of multinational companies, the research is about the characteristics of the Hungarian labor force. The most important result of the research shows that while more than one third of the respondents consider office noise as a disturbing factor, personal inquiries are welcome and considered useful, even if in such cases the work environment will not be convenient to solve tasks requiring concentration. Analyzing the sizes of the offices, in an open-space environment, the rate of those who consider office noise as a disturbing factor is surprisingly lower than in smaller office rooms. Opinions are more diverse regarding information communication technologies. In addition to the interruption factors affecting the employees' job satisfaction, the research also focuses on the role of the offices in the 21^st century.

Keywords: Information overload, interruption, job satisfaction, office environment, work efficiency.

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Authors: Mpofu Vongai, Vhurumuku Elaosi

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Many African countries, such as Zimbabwe and South Africa, have curricula reform agendas that include incorporation of Indigenous Knowledge and Nature of Science (NOS) into school Science, Technology, Engineering and Mathematics (STEM) education. It is argued that at high school level, STEM learning, which incorporates understandings of indigenization science and NOS, has the potential to provide a strong foundation for a culturally embedded scientific knowledge essential for their advancement in Science and Technology. Globally, investment in STEM education is recognized as essential for economic development. For this reason, developing countries such as Zimbabwe and South Africa have been investing into training specialized teachers in natural sciences and technology. However, in many cases this training has been detached from the cultural realities and contexts of indigenous learners. For this reason, the STEM curricula reform has provided implementation challenges to teachers. An issue of major concern is the teachers’ pedagogical content knowledge (PCK), which is essential for effective implementation of these STEM curricula. Well-developed Teacher PCK include an understanding of both the nature of indigenous knowledge (NOIK) and of NOS. This paper reports the results of a study that investigated the development of 3 South African and 3 Zimbabwean in-service teachers’ abilities to integrate NOS and NOIK as part of their PCK. A participatory action research design was utilized. The main focus was on capturing, determining and developing teachers STEM knowledge for integrating NOIK and NOS in science classrooms. Their use of indigenous games was used to determine how their subject knowledge for STEM and pedagogical abilities could be developed. Qualitative data were gathered through the use dialogues between the researchers and the in-service teachers, as well as interviewing the participating teachers. Analysis of the data provides a methodological window through which in-service teachers’ PCK can be STEMITIZED and their abilities to integrate NOS and NOIK developed. Implications are raised for developing teachers’ STEM education in universities and teacher training colleges.

Keywords: Indigenous knowledge, nature of science, pedagogical content knowledge, STEM education.

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Authors: Emanuel Teixeira, Anderson Ramos, Marisa Lourenço, Fernando J. Velez, Jon M. Peha

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This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Keywords: 5G, millimetre wavebands, super high-frequency band, SINR, signal-to-interference-plus-noise ratio, cost benefit analysis.

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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