Search results for: fully automated

Authors: Ammar Asfari, Faizah Finur Fithriah, Shighia Ajeng Savitri

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Jakarta as the capital city of Indonesia held an important role for the country, that is being the city where central government is located. But its topographic character which categorized as lowland area is causing an ultimate trouble. With average height of 7 meters above the sea level, flood keeps occurring in this city. On the other hand, water exploitation that caused land subsidence and sea-levels increasing by global warming make it even worse. Giant Sea Wall Development is a project created by Jakarta’s government to overcome flood, which is inspired by Saemangeum Dam in South Korea. For further planning, Giant Sea Wall is planned to be water reservoir for Jakarta’s inhabitants. This research’s aim is to fully understand the knowledge and opinion of people living in North Jakarta (Jakarta’s Coastal Area) on Giant Sea Wall development planning using qualitative method analysis with descriptive approach. The result of this research will be one of the determining factors in Giant Sea Wall Jakarta development planning continuance.

Keywords: descriptive approach, Giant Sea Wall Jakarta, qualitative method analysis, society perception

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Authors: Costrie Ganes Widayanti

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Learning Disabilities (LDs) are less understood by the Indonesia’s educational practitioners. As a result, students with LDs are at risk of being outcast from the learning process that requires participation, which potentially disconnects them academically and socially. Its objective is to raise the voice of students with LDs regarding their engagement in the classroom. This research is conducted in two urban regular public primary schools in Indonesia. The study uses an ethnographic case study research design, which explores the views and experiences of four (4) students with LDs. The data were collected using participant observations and interviews. The preliminary findings highlighted two areas: 1) the stigmatization about LDs; and 2) perceived membership. Having LDs was a barrier to fully engage in the academic and social life. Interestingly, they were more likely dependent on each other for support as limited assistance was offered by teachers and peers. Their peers did not take a keen interest in helping them when they found difficulties with the assignments. Furthermore, due to their low academic performance, they were not in favor of being nominated as a group member. In a situation that required them to do a group assignment, they were not expected to give a contribution, positioning themselves as incompatible. These findings indicated that such practices legitimate the hegemony of the superior over those who are powerless and left behind.

Keywords: engagement, experiences, learning disability, qualitative design

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Hamilton V. Niculescu

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Following a three year study conducted on eighteen Irish people that are involved in growing vegetables in various community gardens around Dublin, Republic of Ireland, it was revealed that addition of some automated features aimed at improving agricultural practices represented a process which was regarded as potentially beneficial, and as a great tool to closely monitor climate conditions inside the greenhouses. The participants were provided with a free custom-built mobile app through which they could remotely monitor and control features such as irrigation, air ventilation, and windows to ensure optimal growing conditions for vegetables growing inside purpose-built greenhouses. While the initial interest was generally high, within weeks, the participants' level of interaction with the enclosures slowly declined. By employing a constructivist grounded theory methodology, following focus group discussions, in-depth semi-structured interviews, and observations, it was revealed that participants' trust in newer technologies, and renewables, in particular, was low. There are various reasons for this, but because the participants in this study consist of mainly working-class people, it can be argued that lack of education and knowledge are the main barriers acting against the adoption of innovations. Consequently, it was revealed that most participants eventually decided to "set and forget" the systems in automatic working mode, indicating that the immediate effect of introducing people to assisting technologies also introduced some unintended consequences into their lifestyle. It is argued that this occurrence also indicates the fact that people initially "read" newer technologies and only adopt those features that they find useful and less intrusive in regards to their current lifestyle.

Keywords: automation, communication, greenhouse, sustainable

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Authors: Wael M Albadri, Hassnen M Jafer, Ehab H Sfoog

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Relationship between undrained shear strength (Su) and over consolidation ratio (OCR) of clay soil (marine clay) is very important in the field of geotechnical engineering to estimate the settlement behaviour of clay and to prepare a small scale physical modelling test. In this study, a relationship between shear strength and OCR parameters was determined using the laboratory vane shear apparatus and the fully automatic consolidated apparatus. The main objective was to establish non-linear correlation formula between shear strength and OCR and comparing it with previous studies. Therefore, in order to achieve this objective, three points were chosen to obtain 18 undisturbed samples which were collected with an increasing depth of 1.0 m to 3.5 m each 0.5 m. Clay samples were prepared under undrained condition for both tests. It was found that the OCR and shear strength are inversely proportional at similar depth and at same undrained conditions. However, a good correlation was obtained from the relationships where the R2 values were very close to 1.0 using polynomial equations. The comparison between the experimental result and previous equation from other researchers produced a non-linear correlation which has a similar pattern with this study.

Keywords: shear strength, over-consolidation ratio, vane shear test, clayey soil

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Authors: Siavash Salamatpoor, Hossein Motaghedi, Jr., Mehrdad Nategh

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In this study, undrained triaxial tests under anisotropic consolidation were conducted on the reconstituted samples of Ramsar sand, which underlies a densely populated, seismic region of the southern coast of Caspian Sea in Mazandaran province, Iran. Ramsar costal city is regularly visited by many tourists. Accordingly, many tall building and heavy structures are going to be constructed over this coastal area. This region is overlaid by poorly graded clean sand and because of high water level, is susceptible to liquefaction. The specimens were consolidated anisotropically to simulate initial shear stress which is mobilized due to surface constructions. Different states of soil behavior were obtained by applying different levels of initial relative density, shear stress, and effective stress. It is shown that Ramsar clean sand can experience the whole possible states of liquefiable soils i.e. fully liquefaction, limited liquefaction, and dilation behaviors. It would be shown that by increasing the shear parameter in high confine pressure, the liquefaction susceptibility has increased while for low confine pressure it would be vice versa.

Keywords: anisotropic, triaxial test, shear parameter, static liquefaction

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Claudio D'Alonzo

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According to recent tendencies, progress on resource efficiency is possible and it will lead to economic, environmental, and social benefits. The passage to a circular economy system, in which all the materials and energy will maintain their value for as long as possible, waste is reduced and only a few resources are used, is one of the most relevant parts of the European Union's environmental policy to develop a sustainable, competitive and low-carbon economy. A definition of circular economy can be found in Decision 1386/2013/EU of the European Parliament and of the Council on a General Union Environment Action Programme to 2020 named “Living well, within the limits of our planet”. The purpose of renewing waste management systems in the UE and making the European model one of the most effective in the world, a revised waste legislative framework entered into force in July 2018. Regarding the Italian legislation, the laws to be modified are the Legislative Decree 3 April 2006, n. 152 and the laws ruling waste management, end-of-waste, by-products and, the regulatory principles regarding circular economy. European rules on end-of-waste are not fully harmonised and so there are legal challenges. The target to be achieved is full consistency between the laws implementing waste and chemicals policies. Only in this way, materials will be safe, fit-for-purpose and designed for durability; additionally, they will have a low environmental impact.

Keywords: circular economy, end-of-waste, legislation, secondary raw materials

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Authors: Kwame Kodua-Ntim

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The study explored the authors self-archiving to create awareness of open-access institutional repositories in universities. The qualitative approach of the study was informed by the interpretive paradigm as well as the case research design. The target population for the study was all twelve (12) open-access institutional repositories managers and administrators purposively selected from the five (5) universities in Ghana. The universities were chosen since they were the only ones listed in the Directory of Open Access Repositories. Interviews were conducted using a semi-structured interview guide and data were analyzed using thematic analysis. The study revealed that academics had some information about self-archiving in open-access institutional repositories and university libraries with open-access institutional repositories were using DSpace software. Managers and administrators of open-access institutional repositories mediated content uploaded and believed that author self-archiving could improve awareness of open-access institutional repositories. The study recommended that universities should fully implement the author’s self-archiving protocol, and academics should be trained to be able to upload research works onto open-access institutional repositories. Furthermore, the university and university library should provide rigorous policies on author self-archiving and incentives for author self-archiving in the open access institutional repositories.

Keywords: author, awareness, institutional repositories, open access, open archive, self-archiving

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Authors: Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considered about the consumption of fossil fuels and also Reduction of consumption civil energy in megacities that play a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials and the adaptation with the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article we investigates the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

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Authors: H. Ahmed, A. Schlenkhoff

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Recently, permeable breakwaters have been suggested to overcome the disadvantages of fully protection breakwaters. These protection structures have minor impacts on the coastal environment and neighboring beaches where they provide a more economical protection from waves and currents. For regular waves, a numerical model is used (FLOW-3D, VOF) to investigate the hydraulic performance of a permeable breakwater. The model of permeable breakwater consists of a pair of identical vertical slotted walls with an impermeable upper and lower part, where the draft is a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at distant of 0.5 and 1.5 of the water depth from the first one. The numerical model is validated by comparisons with previous laboratory data and semi-analytical results of the same model. A good agreement between the numerical results and both laboratory data and semi-analytical results has been shown and the results indicate the applicability of the numerical model to reproduce most of the important features of the interaction. Through the numerical investigation, the friction factor of the model is carefully discussed.

Keywords: coastal structures, permeable breakwater, slotted wall, numerical model, energy dissipation coefficient

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Authors: Ismail Halijah, Abdullah Rusli

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Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

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Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its microstructure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

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Authors: Won Jung, Azianti Ismail

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Functional safety is about electrical, electronics, and programmable electronic safety-related system focuses on the potential risk of malfunction which may have a significant impact on the safety of humans and/or the environment based on IEC 61508. In November 2011, the automotive industry has been introduced to automotive functional safety ISO 26262 which addresses the complete safety installation from sensor to actuator with its technical as well as management issues. Nowadays, most of the modern automobiles are equipped with embedded electronic systems which include many Electronic Controller Units (ECUs), electronic sensors, signals, bus systems and coding. Due to upcoming more sophisticated systems installed in automobiles, the need to carry out detailed safety is very crucial. Assimilation of existing practices with this new standard is a major challenge for the automotive industry in reducing redundancy, time and resources. Therefore, this paper will analyze the research trends on pre and post introduction of ISO 26262 through publications as well as to take a glimpse in the activities for implementing this standard by the automotive manufacturers around the world. It is going to highlight issues and challenges which have been discussed among the experts in this field. Even though it will take some time for this standard to be fully implemented, the benefits from this implementation will raise the competitiveness in the global automotive market.

Keywords: ISO 26262, automotive, functional safety, implementation, standard, challenges

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Renata Hrecska

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This research aims to present today's corporate law reforms in the micro, small and medium-sized enterprise sector. The UN Commission on International Trade Law (UNCITRAL) currently deals with emerging issues in the sector in its Working Group I that has specifically focused on possible company law simplifications, including the creation of a fully unique company, the UNCITRAL Limited Liability Organization. However, beyond the work at the UN, the different states has also been focusing on simplification efforts and demands in the sphere of commercial law. We can observe that e.g. Slovakia, Serbia, Poland, Croatia, Hungary, Romania and France are undergoing legal reforms aimed at restructuring the sector through simplification of registration or operation. An important objective of the research is to examine where the boundary is for the legal entity to be more transparent and accountable, while the legislator wants to bring the possibility of establishing a company closer to the citizen. The research material presents the advantages and disadvantages of different initiatives with comparative legal instruments and draws conclusions on the possible future vision. The researcher herself attended some of the meetings of the relevant UNCITRAL working group as a national delegated expert, giving her a personal insight into the UNLLO discourse.

Keywords: commercial law, company formation, MSME, UNCITRAL

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Sehrish Iftikhar, Ahmad Ali Shahid, Kiran Nawaz, Waheed Anwar

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Discovery and development of new compounds require intense studies in chemistry, biochemistry. Numerous experiments under laboratory-, greenhouse- and field conditions can be performed to select suitable candidates and to understand their full potential. Novel fungicides are fundamental to combat plant diseases. Fusarium solani is important plant pathogen. New broad spectrum foliar fungicides against complex II were designed in this study. Complex II, namely succinate dehydrogenase (SDH), or succinate quinone oxidoreductase (SQR) is a multi-subunit enzyme at the crossroads of TCA and ETC at the inner mitochondrial membrane. The need for new and innovative fungicides is driven by resistance management, regulatory hurdles and increasing customer expectations amongst others. Fungicidal activity was assessed for the effect on mycelial growth and spore germination of the fungi using fungicide amended media assay. In mycelial growth assay compounds C10 and C6 were highly active against all the isolates. The compounds C1 and C10 were found most potent in spore germination test. It fully proved that the SDHIs designed in this paper displayed as good inhibitory effects against Fusarium solani.

Keywords: Wilt, Fusarium, SDH, antifungal

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Serin Darwish, Hakim Saibi, Amir Gabr

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The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

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Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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Authors: Michael Shulman, Paige North, Benedikt Ahrens, Dmitris Tsementzis

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The Univalence Principle is the statement that equivalent mathematical structures are indistinguishable. We prove a general version of this principle that applies to all set-based, categorical, and higher-categorical structures defined in a non-algebraic and space-based style, as well as models of higher-order theories such as topological spaces. In particular, we formulate a general definition of indiscernibility for objects of any such structure, and a corresponding univalence condition that generalizes Rezk’s completeness condition for Segal spaces and ensures that all equivalences of structures are levelwise equivalences. Our work builds on Makkai’s First-Order Logic with Dependent Sorts, but is expressed in Voevodsky’s Univalent Foundations (UF), extending previous work on the Structure Identity Principle and univalent categories in UF. This enables indistinguishability to be expressed simply as identification, and yields a formal theory that is interpretable in classical homotopy theory, but also in other higher topos models. It follows that Univalent Foundations is a fully equivalence-invariant foundation for higher-categorical mathematics, as intended by Voevodsky.

Keywords: category theory, higher structures, inverse category, univalence

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Authors: Ming Wei

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Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

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Authors: Daniel Mueller, Melanie Breitbach, Stefan Cornelius, Sarah Pakulla-Dickel, Margaretha Koenig, Anke Prochnow, Mario Scherer

Abstract:

The European STR standard set (ESS) of loci as well as the new expanded CODIS core loci set as recommended by the CODIS Core Loci Working Group, has led to a higher standardization and harmonization in STR analysis across borders. Various multiplex PCRs assays have since been developed for the analysis of these 17 ESS or 23 CODIS expansion STR markers that all meet high technical demands. However, forensic analysts are often faced with difficult STR results and the questions thereupon. What is the reason that no peaks are visible in the electropherogram? Did the PCR fail? Was the DNA concentration too low? QIAGEN’s newest Investigator STR kits contain a novel Quality Sensor (QS) that acts as internal performance control and gives useful information for evaluating the amplification efficiency of the PCR. QS indicates if the reaction has worked in general and furthermore allows discriminating between the presence of inhibitors or DNA degradation as a cause for the typical ski slope effect observed in STR profiles of such challenging samples. This information can be used to choose the most appropriate rework strategy.Based on the latest PCR chemistry called FRM 2.0, QIAGEN now provides the next technological generation for STR analysis, the Investigator ESSplex SE QS and Investigator 24plex QS Kits. The new PCR chemistry ensures robust and fast PCR amplification with improved inhibitor resistance and easy handling for a manual or automated setup. The short cycling time of 60 min reduces the duration of the total PCR analysis to make a whole workflow analysis in one day more likely. To facilitate the interpretation of STR results a smart primer design was applied for best possible marker distribution, highest concordance rates and a robust gender typing.

Keywords: PCR, QIAGEN, quality sensor, STR

Procedia PDF Downloads 477

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

Abstract:

Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Konstantinos G. Dassios, Guillaume Bonnefont, Gilbert Fantozzi, Theodore E. Matikas, Costas Galiotis

Abstract:

We report herein the development and preliminary mechanical characterization of fully-dense multi-wall carbon nanotube (MWCNT)-reinforced ceramics and glasses based on a completely new methodology termed High Shear Compaction (HSC). The tubes are introduced and bound to the matrix grains by aid of polymeric binders to form flexible green bodies which are sintered and densified by spark plasma sintering to unprecedentedly high densities of 100% of the pure-matrix value. The strategy was validated across a PyrexTM glass / MWCNT composite while no identifiable factors limit application to other types of matrices. Non-destructive evaluation, based on ultrasonics, of the dynamic mechanical properties of the materials including elastic, shear and bulk modulus as well as Poisson’s ratio showed optimum property improvement at 0.5 %wt tube loading while evidence of nanoscale-specific energy dissipative characteristics acting complementary to nanotube bridging and pull-out indicate a high potential in a wide range of reinforcing and multifunctional applications.

Keywords: ceramic matrix composites, carbon nanotubes, toughening, ultrasonics

Procedia PDF Downloads 357

Authors: Manuela Nayantara Jeyaraj

Abstract:

Information Technology (IT) is considered to be the prime contributor towards most of the energy releases and hence recursively impacting on the environmental Carbon Footprint on a major scale. The hostile effects brought about due to this massive carbon release such as global warming and ecosystem wipe-outs are currently being realized in Sri Lanka due to the rapid development and merging of computer based technologies. Sri Lanka, being a nature-rich island, has the undying need to preserve its natural environment hence resolving to better ‘Green IT’ practices in all possible spheres. Green IT implies the IT related practices for environmental sustainability. But the industrial divisions in Sri Lanka are still hesitant to fully realize the benefits of applying better “Green IT” principles due to considerations related to costs and other issues. In order to bring about a positive awareness of Green IT, the use of Smart Grids, which is yet a conceptualized principle within the Sri Lankan context, can be considered as a feasible proof in hand. This paper tends to analyze the feasibility of utilizing Smart Grids to ensure minimized cost and effects in preserving the environment hence ensuring Sustainable Green IT practices in an economically and technologically viable manner in Sri Lanka.

Keywords: green IT, industry, smart grid, Sri Lanka, sustainability

Procedia PDF Downloads 314

Authors: Hanife Genç

Abstract:

This study was conducted to determine sex differentiation of laboratory reared Elm nymphalid (Nymphalis polychloros Linnaeus, 1758) by examining the morphological structure of pupal stage. Laboratory colony of elm nymphalid, reared on pear leaves, were used to set up experiments. It was performed with 5 replications having 8 pupae for each replication. Dorsal, ventral and lateral parts of external morphological structures of pupae were examined by Olympus SZX9 microscope and photographed. When fully grown, mature larvae wander the highest part of the rearing cage and pupae were formed hanging by cremaster. After completing prepupa stage about 1.5±0.3 days, they all pupated. Pupal stage was completed at 25±1°C about 4.38±1.20 days. Pupal weights were 0.483±0.05 g in females and 0.392±0.08 g (n=40) in males respectively. Pupal emergence rate was 95%, with 22 females and 16 males. Examinations of ventral parts of 8th, 9th, and 10th abdominal segments revealed that anal opening were found at 10th abdominal segment in both sexes, 3 lumbs were determined at 9th abdominal segments then the specific opening structure at 8th segment was only found on female pupae.

Keywords: sex differentiation, Nymphalis polychloros, pupa, Linnaeus

Procedia PDF Downloads 219