Search results for: controls engineering

Authors: Sujesh F. Sujan, Steve W. Jones, Arto Kiviniemi

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The use of Building Information Modelling (BIM) in the Architectural-Engineering-Construction (AEC) industry is a form of systemic innovation. Unlike incremental innovation, (such as the technological development of CAD from hand based drawings to 2D electronically printed drawings) any form of systemic innovation in Project-Based Inter-Organisational Networks requires complete collaboration and results in numerous benefits if adopted and utilised properly. Proper use of BIM involves people collaborating with the use of interoperable BIM compliant tools. The AEC industry globally has been known for its adversarial and fragmented nature where firms take advantage of one another to increase their own profitability. Due to the industry’s nature, getting people to collaborate by unifying their goals is critical to successful BIM adoption. However, this form of innovation is often being forced artificially in the old ways of working which do not suit collaboration. This may be one of the reasons for its low global use even though the technology was developed more than 20 years ago. Therefore, there is a need to develop a metric/method to support and allow industry players to gain confidence in their investment into BIM software and workflow methods. This paper departs from defining systemic risk as a risk that affects all the project participants at a given stage of a project and defines categories of systemic risks. The need to generalise is to allow method applicability to any industry where the category will be the same, but the example of the risk will depend on the industry the study is done in. The method proposed seeks to use individual perception of an example of systemic risk as a key parameter. The significance of this study lies in relating the variance of individual perception of systemic risk to how much the team is collaborating. The method bases its notions on the claim that a more unified range of individual perceptions would mean a higher probability that the team is collaborating better. Since contracts and procurement devise how a project team operates, the method could also break the methodological barrier of highly subjective findings that case studies inflict, which has limited the possibility of generalising between global industries. Since human nature applies in all industries, the authors’ intuition is that perception can be a valuable parameter to study collaboration which is essential especially in projects that utilise systemic innovation such as BIM.

Keywords: building information modelling, perception of risk, systemic innovation, team collaboration

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Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

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The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

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Authors: Azmanirah Ab Rahman, Jamil Ahmad, Ruhizan Muhammad Yasin

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Rubric is a very important tool for teachers and students for a variety of purposes. Teachers use the rubric for evaluating student work while students use rubrics for self-assessment. Therefore, this paper was emphasized scoring rubric as a scoring tool for teachers in an environment of Competency Based Education and Training (CBET) in Malaysia Vocational College. A total of three teachers in the fields of electrical and electronics engineering were interviewed to identify how the use of rubrics practiced since vocational transformation implemented in 2012. Overall holistic rubric used to determine the performance of students in the skills area.

Keywords: rubric, vocational education, teachers, CBET

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Authors: Fazal-e-Amin, Abdullah S. Alghamdi, Iftikhar Ahmad

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Software ecosystems’ concept is an inspiration from the natural ecosystem. Software ecosystems refer to large systems developed on top of a platform composed of different components developed by different entities of that ecosystem. Ecosystems improve information access, dissemination and coordination considerably. The ability to evolve and accommodate new subsystems gives a boost to the software ecosystems. In this paper, Saudi education software ecosystem is discussed and its need and potential benefits are highlighted. This work will provide a basis for further research in this area and foundation in development of Saudi education ecosystem.

Keywords: software ecosystem, education software, framework, software engineering

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Lizeth Fuentes-Mera, Vanessa Perez-Silos, Nidia K. Moncada-Saucedo, Alejandro Garcia-Ruiz, Alberto Camacho, Jorge Lara-Arias, Ivan Marino-Martinez, Victor Romero-Diaz, Adolfo Soto-Dominguez, Humberto Rodriguez-Rocha, Hang Lin, Victor Pena-Martinez

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Biphasic scaffolds in cartilage tissue engineering have been designed to influence not only the recapitulation of the osteochondral architecture but also to take advantage of the healing ability of bone to promote the implant integration with the surrounding tissue and then bone restoration and cartilage regeneration. This study reports the development and characterization of a biphasic scaffold based on the assembly of a cartilage phase constituted by fibroin biofunctionalized with bovine cartilage matrix; cellularized with differentiated pre-chondrocytes from adipose tissue stem cells (autologous) and well attached to a bone phase (bone bovine decellularized) to mimic the structure of the nature of native tissue and to promote the cartilage regeneration in a model of joint damage in pigs. Biphasic scaffolds were assembled by fibroin crystallization with methanol. The histological and ultrastructural architectures were evaluated by optical and scanning electron microscopy respectively. Mechanical tests were conducted to evaluate Young's modulus of the implant. For the biological evaluation, pre-chondrocytes were loaded onto the scaffolds and cellular adhesion, proliferation, and gene expression analysis of cartilage extracellular matrix components was performed. The scaffolds that were cellularized and matured for 10 days were implanted into critical 3 mm in diameter and 9-mm in depth osteochondral defects in a porcine model (n=4). Three treatments were applied per knee: Group 1: monophasic cellular scaffold (MS) (single chondral phase), group 2: biphasic scaffold, cellularized only in the chondral phase (BS1), group 3: BS cellularized in both bone and chondral phases (BS2). Simultaneously, a control without treatment was evaluated. After 4 weeks of surgery, integration and regeneration tissues were analyzed by x-rays, histology and immunohistochemistry evaluation. The mechanical assessment showed that the acellular biphasic composites exhibited Young's modulus of 805.01 kPa similar to native cartilage (400-800 kPa). In vitro biological studies revealed the chondroinductive ability of the biphasic implant, evidenced by an increase in sulfated glycosaminoglycan (GAGs) and type II collagen, both secreted by the chondrocytes cultured on the scaffold during 28 days. No evidence of adverse or inflammatory reactions was observed in the in vivo trial; however, In group 1, the defects were not reconstructed. In group 2 and 3 a good integration of the implant with the surrounding tissue was observed. Defects in group 2 were fulfilled by hyaline cartilage and normal bone. Group 3 defects showed fibrous repair tissue. In conclusion; our findings demonstrated the efficacy of biphasic and bioactive scaffold based on silk fibroin, which entwined chondroinductive features and biomechanical capability with appropriate integration with the surrounding tissue, representing a promising alternative for osteochondral tissue-engineering applications.

Keywords: biphasic scaffold, extracellular cartilage matrix, silk fibroin, osteochondral tissue engineering

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Authors: Maria Tsouroufli, Andrea Mondokova, Subashini Suresh

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Background: The under-representation of women and consequent failure to fulfil their potential contribution to Science, Technology, Engineering, Maths, and Medicine (STEMM) subjects in the UK is an issue that the Higher Education sector is being encouraged to address. Focus: The aim of this research is to investigate the barriers, facilitators, and incentives that influence diverse groups of women who have embarked upon a related career in STEMM subjects. The project will address a number of interconnected research questions: 1. How do participants perceive the barriers, facilitators and incentives for women in terms of research, teaching and management/leadership at each stage of their development towards forging a career in STEMM? 2. How might gender intersect with ethnicity, pregnancy/maternity and academic grade in the career experiences of women in STEMM? 3. How do participants perceive the example of female role models in emulating them as a career model? 4. How do successful females in STEMM see themselves as role models and what strategies do they employ to promote their careers? 5. How does institutional culture manifest itself as a barrier or facilitator for women in STEMM subjects in the institution? Methodology and Theoretical framework: A mixed-methodology will be employed in a case study of one university. The study will draw on extant quantitative data for context and involve conducting a qualitative inquiry to discover the perceptions of staff and students around the key concepts under study (career progression, sense of belonging and tenure, role-models, personal satisfaction, perceived gender in/equality, institutional culture). The analysis will be informed by an intersectionality framework, feminist and gender theory, and organisational psychology and human resource management perspectives. Implications: Preliminary findings will be collected in 2017. Conclusions will be drawn and used to inform recruitment and retention, and the development and implementation of initiatives to enhance the experiences and outcomes of women working and studying in STEMM subjects in Higher Education.

Keywords: under-representation, women, STEMM subjects, intersectionality

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Authors: Adama Sow, Abdoulaye Guiss´e, Oumar Niang

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To assist medical diagnosis, we propose a federation of several existing and open medical ontologies and terminologies. The goal is to merge the strengths of all these resources to provide clinicians the access to a variety of shared knowledges that can facilitate identification and association of human diseases and all of their available characteristic signs such as symptoms and clinical signs. This work results to an integration model loaded from target known ontologies of the bioportal platform such as DOID, MESH, and SNOMED for diseases selection, SYMP, and CSSO for all existing signs.

Keywords: medical decision, medical ontologies, ontologies integration, linked data, knowledge engineering, e-health system

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Authors: Farahnaz Sadat Golestan Hashemi, Mohd Razi Ismail, Mohd Y. Rafii

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A huge revolution has emerged in genome engineering by the discovery of CRISPR (clustered regularly interspaced palindromic repeats) and CRISPR-associated system genes (Cas) in bacteria. The function of type II Streptococcus pyogenes (Sp) CRISPR/Cas9 system has been confirmed in various species. Other S. thermophilus (St) CRISPR-Cas systems, CRISPR1-Cas and CRISPR3-Cas, have been also reported for preventing phage infection. The CRISPR1-Cas system interferes by cleaving foreign dsDNA entering the cell in a length-specific and orientation-dependant manner. The S. thermophilus CRISPR3-Cas system also acts by cleaving phage dsDNA genomes at the same specific position inside the targeted protospacer as observed in the CRISPR1-Cas system. It is worth mentioning, for the effective DNA cleavage activity, RNA-guided Cas9 orthologs require their own specific PAM (protospacer adjacent motif) sequences. Activity levels are based on the sequence of the protospacer and specific combinations of favorable PAM bases. Therefore, based on the specific length and sequence of PAM followed by a constant length of target site for the three orthogonals of Cas9 protein, a well-organized procedure will be required for high-throughput and accurate mining of possible target sites in a large genomic dataset. Consequently, we created a reliable procedure to explore potential gRNA sequences for type I (Streptococcus thermophiles), II (Streptococcus pyogenes), and III (Streptococcus thermophiles) CRISPR/Cas systems. To mine CRISPR target sites, four different searching modes of sgRNA binding to target DNA strand were applied. These searching modes are as follows: i) coding strand searching, ii) anti-coding strand searching, iii) both strand searching, and iv) paired-gRNA searching. The output of such procedure highlights the power of comparative genome mining for different CRISPR/Cas systems. This could yield a repertoire of Cas9 variants with expanded capabilities of gRNA design, and will pave the way for further advance genome and epigenome engineering.

Keywords: CRISPR/Cas systems, gRNA mining, Streptococcus pyogenes, Streptococcus thermophiles

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Authors: Irtaza M. Syed, Kaameran Raahemifar

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This paper presents comparative analysis of photovoltaic systems (PVS) and proposes practical techniques to improve operational efficiency of the PVS. The best engineering and construction practices for PVS are identified and field oriented recommendation are made. Comparative analysis of central and string inverter based, as well as 600 and 1000 VDC PVS are performed. In addition, direct current (DC) and alternating current (AC) photovoltaic (PV) module based systems are compared. Comparison shows that 1000 V DC String Inverters based PVS is the best choice.

Keywords: photovoltaic module, photovoltaic systems, operational efficiency improvement, comparative analysis

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Authors: Danying Gu, Xiaoyan Li, Yuanlei He

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As a knowledge-intensive industry, nuclear industry highly values the importance of safety and quality. The life cycle of a NPP (Nuclear Power Plant) can last 100 years from the initial research and design to its decommissioning. How to implement the high-quality knowledge management and how to contribute to a more safe, advanced and economic NPP (Nuclear Power Plant) is the most important issue and responsibility for knowledge management. As the lead of nuclear industry, nuclear research and design institute has competitive advantages of its advanced technology, knowledge and information, DKM (Design Knowledge Management) of nuclear research and design institute is the core of the knowledge management in the whole nuclear industry. In this paper, the study and practice on DKM and knowledge transfer across the life cycle of a new-built NPP in China is introduced. For this digital intelligent NPP, the whole design process is based on a digital design platform which includes NPP engineering and design dynamic analyzer, visualization engineering verification platform, digital operation maintenance support platform and digital equipment design, manufacture integrated collaborative platform. In order to make all the design data and information transfer across design, construction, commissioning and operation, the overall architecture of new-built digital NPP should become a modern knowledge management system. So a digital information transfer model across the NPP life cycle is proposed in this paper. The challenges related to design knowledge transfer is also discussed, such as digital information handover, data center and data sorting, unified data coding system. On the other hand, effective delivery of design information during the construction and operation phase will contribute to the comprehensive understanding of design ideas and components and systems for the construction contractor and operation unit, largely increasing the safety, quality and economic benefits during the life cycle. The operation and maintenance records generated from the NPP operation process have great significance for maintaining the operating state of NPP, especially the comprehensiveness, validity and traceability of the records. So the requirements of an online monitoring and smart diagnosis system of NPP is also proposed, to help utility-owners to improve the safety and efficiency.

Keywords: design knowledge management, digital nuclear power plant, knowledge transfer, life cycle

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Authors: Pieter De Vries, Renate Klaassen, Maria Ioannides

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This paper is about an explorative research into the use of emerging technologies for teaching and learning in higher engineering education. The assumption is that these technologies and applications, which are not yet widely adopted, will help to improve education and as such actively work on the ability to better deal with the mismatch of skills bothering our industries. Technologies such as 3D printing, the Internet of Things, Virtual Reality, and others, are in a dynamic state of development which makes it difficult to grasp the value for education. Also, the instruments in current educational research seem not appropriate to assess the value of such technologies. This explorative research aims to foster an approach to better deal with this new complexity. The need to find out is urgent, because these technologies will be dominantly present in the near future in all aspects of life, including education. The methodology used in this research comprised an inventory of emerging technologies and tools that potentially give way to innovation and are used or about to be used in technical universities. The inventory was based on both a literature review and a review of reports and web resources like blogs and others and included a series of interviews with stakeholders in engineering education and at representative industries. In addition, a number of small experiments were executed with the aim to analyze the requirements for the use of in this case Virtual Reality and the Internet of Things to better understanding the opportunities and limitations in the day-today learning environment. The major findings indicate that it is rather difficult to decide about the value of these technologies for education due to the dynamic state of change and therefor unpredictability and the lack of a coherent policy at the institutions. Most decisions are being made by teachers on an individual basis, who in their micro-environment are not equipped to select, test and ultimately decide about the use of these technologies. Most experiences are being made in the industry knowing that the skills to handle these technologies are in high demand. The industry though is worried about the inclination and the capability of education to help bridge the skills gap related to the emergence of new technologies. Due to the complexity, the diversity, the speed of development and the decay, education is challenged to develop an approach that can make these technologies work in an integrated fashion. For education to fully profit from the opportunities, these technologies offer it is eminent to develop a pro-active strategy and a sustainable approach to frame the emerging technologies development.

Keywords: emerging technologies, internet of things, pro-active strategy, virtual reality

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Nalinee B. Suryawanshi, Vinay M. Bhandari, Laxmi Gayatri Sorokhaibam, Vivek V. Ranade

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Deep desulphurization of transportation fuels is a major environmental concern all over the world and recently prescribed norms for the sulphur content require below 10 ppm sulphur concentrations in fuels such as diesel and gasoline. The existing technologies largely based on catalytic processes such as hydrodesulphurization, oxidation require newer catalysts and demand high cost of deep desulphurization whereas adsorption based processes have limitations due to lower capacity of sulphur removal. The present work is an attempt to provide alternatives for the existing methodologies using a newer non-catalytic process based on hydrodynamic cavitation. The developed process requires appropriate combining of organic and aqueous phases under ambient conditions and passing through a cavitating device such as orifice, venturi or vortex diode. The implosion of vapour cavities formed in the cavitating device generates (in-situ) oxidizing species which react with the sulphur moiety resulting in the removal of sulphur from the organic phase. In this work, orifice was used as a cavitating device and deep desulphurization was demonstrated for removal of thiophene as a model sulphur compound from synthetic fuel of n-octane, toluene and n-octanol. The effect of concentration of sulphur (up to 300 ppm), nature of organic phase and effect of pressure drop (0.5 to 10 bar) was discussed. A very high removal of sulphur content of more than 90% was demonstrated. The process is easy to operate, essentially works at ambient conditions and the ratio of aqueous to organic phase can be easily adjusted to maximise sulphur removal. Experimental studies were also carried out using commercial diesel as a solvent and the results substantiate similar high sulphur removal. A comparison of the two cavitating devices- one with a linear flow and one using vortex flow for effecting pressure drop and cavitation indicates similar trends in terms of sulphur removal behaviour. The developed process is expected to provide an attractive environmental engineering alternative for deep desulphurization of transportation fuels.

Keywords: cavitation, petroleum, separation, sulphur removal

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Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

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Software architecture plays a key role in software development but absence of formal description of software architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for software architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate software architectural design information.

Keywords: semantic-based software architecture, software architecture, ontology, software engineering

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Authors: Mikaela Kutrolli, Noah S. Pereira, Vanessa Scanlon, Mohamadmahdi Samandari, Ali Tamayol

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Bone tissue engineering has drawn significant attention and various biomaterials have been tested. Polymers such as polycaprolactone (PCL) offer excellent biocompatibility, reasonable mechanical properties, and biodegradability. However, PCL scaffolds suffer a critical drawback: a lack of micro/mesoporosity, affecting cell attachment, tissue integration, and mineralization. It also results in a slow degradation rate. While 3D-printing has addressed the issue of macroporosity through CAD-guided fabrication, PCL scaffolds still exhibit poor smaller-scale porosity. To overcome this, we generated composites of PCL, hydroxyapatite (HA), and powdered sucrose (PS). The latter serves as a sacrificial material to generate porous particles after sucrose dissolution. Additionally, we have incorporated dexamethasone (DEX) to boost the PCL osteogenic properties. The resulting scaffolds maintain controlled macroporosity from the lattice print structure but also develop micro/mesoporosity within PCL fibers when exposed to aqueous environments. The study involved mixing PS into solvent-dissolved PCL in different weight ratios of PS to PCL (70:30, 50:50, and 30:70 wt%). The resulting composite was used for 3D printing of scaffolds at room temperature. Printability was optimized by adjusting pressure, speed, and layer height through filament collapse and fusion test. Enzymatic degradation, porogen leaching, and DEX release profiles were characterized. Physical properties were assessed using wettability, SEM, and micro-CT to quantify the porosity (percentage, pore size, and interconnectivity). Raman spectroscopy was used to verify the absence of sugar after leaching. Mechanical characteristics were evaluated via compression testing before and after porogen leaching. Bone marrow stromal cells (BMSCs) behavior in the printed scaffolds was studied by assessing viability, metabolic activity, osteo-differentiation, and mineralization. The scaffolds with a 70% sugar concentration exhibited superior printability and reached the highest porosity of 80%, but performed poorly during mechanical testing. A 50% PS concentration demonstrated a 70% porosity, with an average pore size of 25 µm, favoring cell attachment. No trace of sucrose was found in Raman after leaching the sugar for 8 hours. Water contact angle results show improved hydrophilicity as the sugar concentration increased, making the scaffolds more conductive to cell adhesion. The behavior of bone marrow stromal cells (BMSCs) showed positive viability and proliferation results with an increasing trend of mineralization and osteo-differentiation as the sucrose concentration increased. The addition of HA and DEX also promoted mineralization and osteo-differentiation in the cultures. The integration of PS as porogen at a concentration of 50%wt within PCL scaffolds presents a promising approach to address the poor cell attachment and tissue integration issues of PCL in bone tissue engineering. The method allows for the fabrication of scaffolds with tunable porosity and mechanical properties, suitable for various applications. The addition of HA and DEX further enhanced the scaffolds. Future studies will apply the scaffolds in an in-vivo model to thoroughly investigate their performance.

Keywords: bone, PCL, 3D printing, tissue engineering

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Authors: Naveen Porika, Snigdho Majumdar, Niraj Sethi

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Water, food and energy securities are emerging as increasingly important and vital issues for India and the world. Hyderabad urban agglomeration (HUA), the capital city of Andhra Pradesh State in India, is the sixth largest city has a population of about 8.2 million. The Musi River, which is a tributary of Krishna river flows from west to east right through the heart of Hyderabad, about 80% of the water used by people is released back as sewage, which flows back into Musi every day with detrimental effects on the environment and people downstream of the city. The average daily sewage generated in Hyderabad city is 950 MLD, however, treatment capacity exists only for 541 Million Liters per Day (MLD) but only 407 MLD of sewage is treated. As a result, 543 MLD of sewage daily flows into Musi river. Hyderabad’s current estimated water demand stands at 320 Million Gallons per Day (MGD). However, its installed capacity is merely 270 MGD; by 2020 estimated demand will grow to 400 MGD. There is huge gap between current supply and demand, and this is likely to widen by 2021. Developing new fresh water sources is a challenge for Hyderabad, as the fresh water sources are few and far from the City (about 150-200 km) and requires excessive pumping. The constraints presented above make the conventional alternatives for supply augmentation unsustainable and unattractive .One such dependable and captive source of easily available water is the treated sewage. With proper treatment, water of desired quality can be recovered from the waste water (sewage) for recycle and reuse. Hyderabad Amberpet sewage treatment of capacity 339 MLD is Asia’s largest sewage treatment plant. Tertiary sewage treatment Standard basic engineering modules of 30 MLD,60 MLD, 120MLD & 180 MLD for sewage treatment plants has been developed which are utilized for developing Sewage Reclamation & Reuse model in Asia’s largest sewage treatment plant. This paper will focus on Hyderabad Water Supply & Demand, Sewage Generation & Treatment, Technical aspects of Tertiary Sewage Treatment and Utilization of developed standard modules for reclamation & reuse of treated sewage to overcome the deficit of 130 MGD as projected by 2021.

Keywords: water reclamation, reuse, Andhra Pradesh, hyderabad, musi river, sewage, demand and supply, recycle, Amberpet, 339 MLD, engineering modules, tertiary treatment

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Authors: Kostandinos Katsamangas, Fawad Inam

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Graphene was dispersed using a tip sonicator and the effect of surfactants were analysed. Sodium Dodecyl Sulphate (SDS) and Polyvinyl Alcohol (PVA) were compared to observe whether or not they had any effect on any de-wrinkling, and secondly whether they aided to achieve better dispersions. There is a huge demand for wrinkle free graphene as this will greatly increase its usefulness in various engineering applications. A comprehensive literature on de-wrinkling graphene has been discussed. Low magnification Scanning Electronic Microscopy (SEM) was conducted to assess the quality of graphene de-wrinkling. The utilization of the PVA has a significant effect on de-wrinkling whereas SDS had minimal effect on the de-wrinkling of graphene.

Keywords: Graphene, de-wrinkling, dispersion, surfactants, scanning electronic microscopy

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Authors: Lu-Chen Yeh‚ Jui-Ming Yeh

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In this manuscript, we produced neat electrospun poly(o-methoxyaniline) (POMA) fibers and utilized it for applying the growth of neural stem cells. The transparency and morphology of as-prepared POMA fibers were characterized by UV-visible spectroscopy and scanning electron microscopy, respectively. It was found to have no adverse effects on the long-term proliferation of the neural stem cells (NSCs), retained the ability to self-renew, and exhibit multi-potentiality. Results of immunofluorescence staining studies confirmed that POMA electrospun fibers could provide a great environment for NSCs and enhance its differentiation.

Keywords: electrospun, polyaniline, neural stem cell, differentiation

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Authors: M. A. Yazdi, J. Yang, L. Yihui, H. Su

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The application of recycle waste tires into civil engineering practices, namely asphalt paving mixtures and cementbased materials has been gaining ground across the world. This review summarizes and compares the recent achievements in the area of plain rubberized concrete (PRC), in details. Different treatment methods have been discussed to improve the performance of rubberized Portland cement concrete. The review also includes the effects of size and amount of tire rubbers on mechanical and durability properties of PRC. The microstructure behaviour of the rubberized concrete was detailed.

Keywords: waste rubber aggregates, microstructure, treatment methods, size and content effects

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Authors: Massoud Farag Abouklaish

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The main aim of the present study is to investigate and classify the particle size distribution of sandy soils in Libya. More than fifty soil samples collected from many regions in North, West and South of Libya. Laboratory sieve analysis tests performed on disturbed soil samples to determine grain size distribution. As well as to provide an indicator of general engineering behavior and good understanding, test results are presented and analysed. In addition, conclusions, recommendations are made.

Keywords: Libya, grain size, sandy soils, sieve analysis tests

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Authors: M. Marchewka

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The article is devoted to the possible optical transitions in double quantum wells system based on HgTe/HgCd(Mn)Te heterostructures. Such structures can find applications as detectors and sources of radiation in the terahertz range. The Double Quantum Wells (DQW) systems consist of two QWs separated by the transparent for electrons barrier. Such systems look promising from the point of view of the additional degrees of freedom. In the case of the topological insulator in about 6.4nm wide HgTe QW or strained 3D HgTe films at the interfaces, the topologically protected surface states appear at the interfaces/surfaces. Electrons in those edge states move along the interfaces/surfaces without backscattering due to time-reversal symmetry. Combination of the topological properties, which was already verified by the experimental way, together with the very well know properties of the DQWs, can be very interesting from the applications point of view, especially in the THz area. It is important that at the present stage, the technology makes it possible to create high-quality structures of this type, and intensive experimental and theoretical studies of their properties are already underway. The idea presented in this paper is based on the eight-band KP model, including the additional terms related to the structural inversion asymmetry, interfaces inversion asymmetry, the influence of the magnetically content, and the uniaxial strain describe the full pictures of the possible real structure. All of this term, together with the external electric field, can be sources of breaking symmetry in investigated materials. Using the 8 band KP model, we investigated the electronic shape structure with and without magnetic field from the application point of view as a THz detector in a small magnetic field (below 2T). We believe that such structures are the way to get the tunable topological insulators and the multilayer topological insulator. Using the one-dimensional electrons at the topologically protected interface states as fast and collision-free signal carriers as charge and signal carriers, the detection of the optical signal should be fast, which is very important in the high-resolution detection of signals in the THz range. The proposed engineering of the investigated structures is now one of the important steps on the way to get the proper structures with predicted properties.

Keywords: topological insulator, THz spectroscopy, KP model, II-VI compounds

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Authors: Fatima Benchikh-Amiraa, Hocine Laouerb, Smain Amiraa, Guido Flaminic

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The essential oils of the aerial parts of Lavandula multifida and L. stoechas were extracted at the full bloom stage by hydrodistillation and theirs chemical compositions were estimated by means of gas chromatography–mass spectrometry (GC–MS). A total of 46 and 67 constituents were identified representing 95.5% and 98.2% of the total oils, respectively. The main components of L. multifida oil were carvacrol (63.8%), beta-bisabolene (8.7%), spathulenol (6.2%), caryophyllene oxide (3.6%) and linalool (2.9%). The oil of L. stoechas was dominated by fenchone (63.9%), camphor (7.8%), 1,8-cineole (5.3%) and myrtenyl acetate (4.2).

Keywords: essential oils, Lavandula multifida, Lavandula stoechas, chemical and molecular engineering

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Authors: B. Kekezoglu, C. Kocatepe, O. Arikan, Y. Hacialiefendioglu, G. Ucar

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One of the significant problems of energy systems is to supply economic and efficient energy to consumers. Therefore studies has been continued to reduce technical losses in the network. In this paper, the technical losses analyzed for a portion of European side of Istanbul MV distribution network for different compensation scenarios by considering real system and load data and results are presented. Investigated system is modeled with CYME Power Engineering Software and optimal capacity placement has been proposed to minimize losses.

Keywords: distribution system, optimal capacitor placement, reactive power compensation, technical losses

Procedia PDF Downloads 674

Authors: Rina Arum Prastyanti

Abstract:

Information technology has changed the ways of transacting and enabling new opportunities in business transactions. Problems to be faced by consumers M Commerce, among others, the consumer will have difficulty accessing the full information about the products on offer and the forms of transactions given the small screen and limited storage capacity, the need to protect children from various forms of excess supply and usage as well as errors in access and disseminate personal data, not to mention the more complex problems as well as problems agreements, dispute resolution that can protect consumers and assurance of security of personal data. It is no less important is the risk of payment and personal information of payment dal am also an important issue that should be on the swatch solution. The purpose of this study is 1) to describe the phenomenon of the use of Mobile Commerce in Indonesia. 2) To determine the form of legal protection for the consumer use of Mobile Commerce. 3) To get the right type of law so as to provide legal protection for consumers Mobile Commerce users. This research is a descriptive qualitative research. Primary and secondary data sources. This research is a normative law. Engineering conducted engineering research library collection or library research. The analysis technique used is deductive analysis techniques. Growing mobile technology and more affordable prices as well as low rates of provider competition also affects the increasing number of mobile users, Indonesia is placed into 4 HP users in the world, the number of mobile phones in Indonesia is estimated at around 250.1 million telephones with a population of 237 556. 363. Indonesian form of legal protection in the use of mobile commerce still a part of the Law No. 11 of 2008 on Information and Electronic Transactions and until now there is no rule of law that specifically regulates mobile commerce. Legal protection model that can be applied to protect consumers of mobile commerce users ensuring that consumers get information about potential security and privacy challenges they may face in m commerce and measures that can be used to limit the risk. Encourage the development of security measures and built security features. To encourage mobile operators to implement data security policies and measures to prevent unauthorized transactions. Provide appropriate methods both time and effectiveness of redress when consumers suffer financial loss.

Keywords: mobile commerce, legal protection, consumer, effectiveness

Procedia PDF Downloads 364

Authors: Suyeb Ahmed Khan, Mahmood Mian

Abstract:

Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

Procedia PDF Downloads 592

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 61

Authors: S. Al-Sowayan

Abstract:

Rogowski coils are increasingly used for measurement of AC and transient electric currents. Mostly used Rogowski coils now are with circular or rectangular cores. In order to increase the sensitivity of the measurement of Rogowski coil and perform smooth wire winding, this paper studies the effect of increasing the mutual inductance in order to increase the coil sensitivity by presenting the calculation and simulation of a Rogowski coil with equilateral hexagonal shaped core and comparing the resulted mutual inductance with commonly used core shapes.

Keywords: Rogowski coil, mutual inductance, magnetic flux density, communication engineering

Procedia PDF Downloads 370

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 134

Authors: Asaf Toker

Abstract:

Matricelf developed a technology that enables the production of autologous engineered tissue composed of matrix and cells derived from patients Omentum biopsy. The platform showed remarkable pre-clinical results for several medical conditions. The company recently licensed the technology that enabled scientist at Tel Aviv university that 3D printed a human heart from human cells and matrix for the first time in human history. The company plans to conduct its first human clinical trial for Acute Spinal Cord Injury (SCI) early in 2023.

Keywords: tissue engineering, regenerative medicine, spinal Cord Injury, autologous implants, iPSC

Procedia PDF Downloads 126