Search results for: smart scaffolds

Authors: Peter Sabev, Katalina Grigorova

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Test automation allows performing difficult and time consuming manual software testing tasks efficiently, quickly and repeatedly. However, development and maintenance of automated tests is expensive, so it needs a proper prioritization what to automate first. This paper describes a simple yet efficient approach for such prioritization of test cases based on the effort needed for both manual execution and software test automation. The suggested approach is very flexible because it allows working with a variety of assessment methods, and adding or removing new candidates at any time. The theoretical ideas presented in this article have been successfully applied in real world situations in several software companies by the authors and their colleagues including testing of real estate websites, cryptographic and authentication solutions, OSGi-based middleware framework that has been applied in various systems for smart homes, connected cars, production plants, sensors, home appliances, car head units and engine control units (ECU), vending machines, medical devices, industry equipment and other devices that either contain or are connected to an embedded service gateway.

Keywords: automated testing, manual testing, test automation, software testing, test prioritization

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Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

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This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: fuzzy logic, intelligent system, precision agriculture, renewable energy

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Authors: Jeet Chakraborty, Sanjay Dutta

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Antibiotic resistance by bacteria has proved to be a severe threat to mankind in recent times, and this fortifies an urgency to design and develop potent antibacterial small molecules/compounds with nonconventional mechanisms than the conventional ones. DNA carries the genetic signature of any organism, and bacteria maintain their genomic DNA inside the cell in a well-regulated compact form with the help of various nucleoid associated proteins like HU, HNS, etc. These proteins control various fundamental processes like gene expression, replication, etc., inside the cell. Alteration of the native DNA structure of bacteria can lead to severe consequences in cellular processes inside the bacterial cell that ultimately result in the death of the organism. The change in the global DNA structure by small molecules initiates a plethora of cellular responses that have not been very well investigated. Echinomycin and Triostin-A are biologically active Quinoxaline small molecules that typically consist of a quinoxaline chromophore attached with an octadepsipeptide ring. They bind to double-stranded DNA in a sequence-specific way and have high activity against a wide variety of bacteria, mainly against Gram-positive ones. To date, few synthetic quinoxaline scaffolds were synthesized, displaying antibacterial potential against a broad scale of pathogenic bacteria. QNOs (Quinoxaline N-oxides) are known to target DNA and instigate reactive oxygen species (ROS) production in bacteria, thereby exhibiting antibacterial properties. The divergent role of Quinoxaline small molecules in medicinal research qualifies them for the evaluation of their antimicrobial properties as a potential candidate. The previous study from our lab has given new insights on a 6-nitroquinoxaline derivative 1d as an intercalator of DNA, which induces conformational changes in DNA upon binding.7 The binding event observed was dependent on the presence of a crucial benzyl substituent on the quinoxaline moiety. This was associated with a large induced CD (ICD) appearing in a sigmoidal pattern upon the interaction of 1d with dsDNA. The induction of DNA superstructures by 1d at high Drug:DNA ratios was observed that ultimately led to DNA condensation. Eviction of invitro-assembled nucleosome upon treatment with a high dose of 1d was also observed. In this work, monoquinoxaline derivatives of 1d were synthesized by various modifications of the 1d scaffold. The set of synthesized 6-nitroquinoxaline derivatives along with 1d were all subjected to antibacterial evaluation across five different bacteria species. Among the compound set, 3a displayed potent antibacterial activity against Staphylococcus aureus bacteria. 3a was further subjected to various biophysical studies to check whether the DNA structural alteration potential was still intact. The biological response of S. aureus cells upon treatment with 3a was studied using various cell biology processes, which led to the conclusion that 3d can initiate DNA damage in the S. aureus cells. Finally, the potential of 3a in disrupting preformed S.aureus and S.epidermidis biofilms was also studied.

Keywords: DNA structural change, antibacterial, intercalator, DNA superstructures, biofilms

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Pontsho E. Tseke, Phatu W. Mashela

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Climate-smart agriculture dictates that underusilised indigenous plant, which served as food for local marginalized communities, be assessed for introduction into mainstream agriculture. Most of the underutilised indigenous plants had survived adverse conditions in the wild; with limited information on how the interact with most abiotic and biotic factors. Cucumis myriocarpus leafy vegetable has nutritional, pharmacological and industrial applications, with limited information on how it interacts with effective microorganisms. The objective of this study was to determine the effects vesicular arbuscular mycorrhiza (VAM) on the growth of C. myriocarpus indigenous leafy vegetable under greenhouse conditions. Four-weeks-old seedlings of C. myriocarpus were transplanted into 20-cm-diameter plastic pots. Two weeks after transplanting, VAM was applied at 0, 10, 20, 30, 40, 50, 60 and 70 g Biocult-VAM plant. At 56 days after treatments, plant growth variables of C. myriocarpus with increase Biocult-VAM levels exhibited positive quadratic relations. Plant variables and increasing concentrations of salinity exhibited positive quadric relations, with 95 to 99% associations. Inclusion, Biocult-VAM can be used in sustainable production of C. myriocarpus for functional food security.

Keywords: abiotic, biotic, rhizasphere, sustainable agriculture

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Authors: J. Gochermann

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German energy market is under historical change. Turning-off the nuclear power plants and intensive subsidization of the renewable energies causes a paradigm change from big central energy production and distribution to more local structures, bringing the energy production near to the consumption. The formerly big energy market with only a few big energy plants and grid operating companies is changing into a disperse market with growing numbers of small and medium size companies (SME) generating new value-added products and services. This change in then energy market, in Germany called the “Energiewende”, inverts also the previous innovation system. Big power plants and large grids required also big operating companies. Innovations in the energy market focused mainly on big projects and complex energy technologies. Innovation in the new energy market structure is much more dispersed. Increasing number of SME is now able to develop energy production and storage technologies, smart technologies to control the grids, and numerous new energy related services. Innovation is now regional distributed, which is a remarkable problem for the old big energy companies. The paper will explain the change in the German energy market and the paradigm change as well as the consequences for the innovation structure in the German energy market. It will show examples how SME participate from this change and how innovation systems, as well for the big companies and for SME, can be adapted.

Keywords: changing energy markets, disperse innovation, new value-added products and services, SME

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Authors: Lisbeth Amhag

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The aim of the study is to describe and analyze the design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-to-face interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.

Keywords: computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning

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Authors: Sai Shruthi Sridhar, A. Madhumidha, Kreethika Guru, Priyanka Sekar, Ananthi Malayappan

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Numerous changes in technology and its recent development are structuring long withstanding effect to our world, one among them is the emergence of “Internet of Things” (IoT). Similar to Technology world, one industry stands out in everyday life–healthcare. Attention to “quality of health care” is an increasingly important issue in a global economy and for every individual. As per WHO (World Health Organization) it is estimated to be less than 50% adhere to the medication provided and only about 20% get their medicine on time. Medication adherence is one of the top problems in healthcare which is fixable by use of technology. In recent past, there were minor provisions for elderly and specially-skilled to get motivated and to adhere medicines prescribed. This paper proposes a novel solution that uses IOT based RFID Medication Reminder Solution to provide personal health care services. This employs real time tracking which offer quick counter measures. The proposed solution builds on the recent digital advances in sensor technologies, smart phones and cloud services. This novel solution is easily adoptable and can benefit millions of people with a direct impact on the nation’s health care expenditure with innovative scenarios and pervasive connectivity.

Keywords: cloud services, IoT, RFID, sensors

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Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

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The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

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Authors: Saman Momeni, Abolghassem Zabihollah, Mehdi Behzad

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Non-uniform laminated composite structures are being used in many engineering applications where the structures are subjected to unpredicted vibration. To mitigate the vibration response of these structures, recently, magnetorheological fluid (MR), is added to non-uniform (tapered) thickness laminated composite structures to achieve a new generation of the smart composite as MR tapered beam. However, due to the nature of MR fluid, especially the low stiffness, MR tapered beam exhibit lower stiffness and in turn, lower natural frequencies. To achieve the basic design requirements of the structure without MR fluid, one may need to apply a predefined magnetic energy to the structures, requiring a constant source of energy. In the present work, a passive initial stiffness control of MR tapered beam has been studied. The effects of adding nanoparticles on the dynamic response of MR tapered beam has been investigated. It is observed that adding nanoparticles up to 3% may significantly modify the natural frequencies of the structures and achieve dynamic behavior of the structures before addition of MR fluid. Two Models of tapered structures have been taken into consideration. It is observed that adding only 3% of nanoparticles backs the structures to its initial dynamic behavior.

Keywords: non uniform laminated structures, MR fluid, nanoparticles, vibration, stiffness

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Authors: Rawan Ashraf, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Three-dimensional (3D) bio-printing has become a versatile and powerful method for generating a variety of biological constructs, including bone or extracellular matrix scaffolds endo- or epithelial, muscle tissue, as well as organoids. Aim of the study: Fabricate a low cost DIY 3D bio-printer to produce 3D bio-printed products such as anti-microbial packaging or multi-organs on chips. We demonstrate the alignment between two types of 3D printer technology (3D Bio-printer and DLP) on Multi-organ-on-a-chip (multi-OoC) devices fabrication. Methods: First, Design and Fabrication of the Syringe Unit for Modification of an Off-the-Shelf 3D Printer, then Preparation of Hydrogel based on natural polymers Sodium Alginate and Gelatin, followed by acquisition of the cell suspension, then modeling the desired 3D structure. Preparation for 3D printing, then Cell-free and cell-laden hydrogels went through the printing process at room temperature under sterile conditions and finally post printing curing process and studying the printed structure regards physical and chemical characteristics. The hard scaffold of the Organ on chip devices was designed and fabricated using the DLP-3D printer, following similar approaches as the Microfluidics system fabrication. Results: The fabricated Bio-Ink was based onHydrogel polymer mix of sodium alginate and gelatin 15% to 0.5%, respectively. Later the 3D printing process was conducted using a higher percentage of alginate-based hydrogels because of it viscosity and the controllable crosslinking, unlike the thermal crosslinking of Gelatin. The hydrogels were colored to simulate the representation of two types of cells. The adaption of the hard scaffold, whether for the Microfluidics system or the hard-tissues, has been acquired by the DLP 3D printers with fabricated natural bioactive essential oils that contain antimicrobial activity, followed by printing in Situ three complex layers of soft-hydrogel as a cell-free Bio-Ink to simulate the real-life tissue engineering process. The final product was a proof of concept for a rapid 3D cell culturing approaches that uses an engineered hard scaffold along with soft-tissues, thus, several applications were offered as products of the current prototype, including the Organ-On-Chip as a successful integration between DLP and 3D bioprinter. Conclusion: Multiple designs for the organ-on-a-chip (multi-OoC) devices have been acquired in our study with main focus on the low cost fabrication of such technology and the potential to revolutionize human health research and development. We describe circumstances in which multi-organ models are useful after briefly examining the requirement for full multi-organ models with a systemic component. Following that, we took a look at the current multi-OoC platforms, such as integrated body-on-a-chip devices and modular techniques that use linked organ-specific modules.

Keywords: 3d bio-printer, hydrogel, multi-organ on chip, bio-inks

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Authors: Ebrahim Sabermaash Eshghi, Donna Sandsmark

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In changing modern economic conditions of the world, one the most important issues facing managers of firms, is increasing the sales and profitability through sales of newly developed products. This is while purpose of decreasing unnecessary costs is one of the most essential programs of smart managers for more implementation with new conditions in current business. In modern life, condition of misgiving is dominant in all of the industries. Accordingly, in this research, influence of different aspects of presenting products to the market is investigated. This study is done through a Quantitative-Qualitative (Interviews and Questionnaire) approach. In sum, 103 of informed managers and experts of Pars-Khazar Company have been examined through census. Validity of measurement tools was approved through judgments of experts. Reliability of tools was gained through Cronbach's alpha coefficient in size of 0.930 and in sum, validity and reliability of tools were approved generally. Results of regression test revealed that the influence of all aspects of product introduction supported the performance of product, positively and significantly. In addition that influence of two new factors raised from the interview, namely Human Resource Management and Management of product’s pre-test on performance of products was approved.

Keywords: introducing products, performance, home appliances, price, advertisement, production

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: T. Qasim, M. Obeidat, S. Al-Sharairi

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The objective of this study is to investigate the effect of the excessive use of smartphones. Smartphones have enormous effects on the human body in that some musculoskeletal disorders (MSDs) and health problems might evolve. These days, there is a wide use of the smartphones among all age groups of society, thus, the focus on smartphone effects on human behavior and health, especially on the young and elderly people, becomes a crucial issue. This study was conducted in Jordan on smartphone users for different genders and ages, by conducting a survey to collect data related to the symptoms and MSDs that are resulted from the excessive use of smartphones. A total of 357 responses were used in the analysis. The main related symptoms were numbness, fingers pain, and pain in arm, all linked to age and gender for comparative reasons. A statistical analysis was performed to find the effects of extensive usage of a smartphone for long periods of time on the human body. Results show that the significant variables were the vision problems and the time spent when using the smartphone that cause vision problems. Other variables including age of user and ear problems due to the use of the headsets were found to be a border line significant.

Keywords: smart phone, age group, musculoskeletal disorders (MSDs), health problems

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Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: V. Schmidt, L. Janovák, N. Wiegand, B. Patczai, K. Turzó

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Large bone defects are not able to heal spontaneously. Bioactive glasses seem to be appropriate (bio)materials for bone reconstruction. Bioactive glasses are osteoconductive and osteoinductive, therefore, play a useful role in bony regeneration and repair. Because of their not optimal mechanical properties (e.g., brittleness, low bending strength, and fracture toughness), their applications are limited. Bioactive glass can be used as a coating material applied on metal surfaces. In this way -when using them as implants- the excellent mechanical properties of metals and the biocompatibility and bioactivity of glasses will be utilized. Furthermore, ion release effects of bioactive glasses regarding osteogenic and angiogenic responses have been shown. Silicate bioactive glasses (45S5 Bioglass) induce the release and exchange of soluble Si, Ca, P, and Na ions on the material surface. This will lead to special cellular responses inducing bone formation, which is favorable in the biointegration of the orthopedic prosthesis. The incorporation of other additional elements in the silicate network such as fluorine, magnesium, iron, silver, potassium, or zinc has been shown, as the local delivery of these ions is able to enhance specific cell functions. Although hip and knee prostheses present a high success rate, bacterial infections -mainly implant associated- are serious and frequent complications. Infection can also develop after implantation of hip prostheses, the elimination of which means more surgeries for the patient and additional costs for the clinic. Prosthesis-related infection is a severe complication of orthopedic surgery, which often causes prolonged illness, pain, and functional loss. While international efforts are made to reduce the risk of these infections, orthopedic surgical infections (SSIs) continue to occur in high numbers. It is currently estimated that up to 2.5% of primary hip and knee surgeries and up to 20% of revision arthroplasties are complicated by periprosthetic joint infection (PJIs). According to some authors, these numbers are underestimated, and they are also increasing. Staphylococcus aureus is the leading cause of both SSIs and PJIs, and the prevalence of methicillin-resistant S. aureus (MRSA) is on the rise, particularly in the United States. These deep infections lead to implant removal and consequently increase morbidity and mortality. The study targets this clinical problem using our experience so far with the Ag-doped polymer coatings on Titanium implants. Non-modified or modified (e.g., doped with antibacterial agents, like Ag) bioactive glasses could play a role in the prevention of infections or the therapy of infected tissues. Bioactive glasses have excellent biocompatibility, proved by in vitro cell culture studies of human osteoblast-like MG-63 cells. Ag-doped bioactive glass-scaffold has a good antibacterial ability against Escherichia coli and other bacteria. It may be concluded that these scaffolds have great potential in the prevention and therapy of implant-associated bone infection.

Keywords: antibacterial agents, bioactive glass, hip and knee prosthesis, medical implants

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Authors: Archana Sharma, Vijayashree Nayak, Ashok Kumar

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Three-dimensional matrices were fabricated from blend of natural-natural polymers like carrageenan-gelatin and synthetic -natural polymers such as PEG- gelatin (PEG of different molecular weights (2,000 and 6,000) using two different crosslinkers; glutaraldehyde and EDC-NHS by cryogelation technique. Blends represented a feasible approach to design 3-D scaffolds with controllable mechanical, physical and biochemical properties without compromising biocompatibility and biodegradability. These matrices possessed interconnected porous structure, good mechanical strength, biodegradable nature, constant swelling kinetics, ability to withstand high temperature and visco-elastic behavior. Hemocompatibility of cryogel matrices was determined by coagulation assays and hemolytic activity assay which demonstrated that these cryogels have negligible effects on coagulation time and have excellent blood compatibility. In vitro biocompatibility (cell-matrix interaction) inferred good cell adhesion, proliferation, and secretion of ECM on matrices. These matrices provide a microenvironment for the growth, proliferation, differentiation and secretion of ECM of different cell types such as IMR-32, C2C12, Cos-7, rat bone marrow derived MSCs and human bone marrow MSCs. Hoechst 33342 and PI staining also confirmed that the cells were uniformly distributed, adhered and proliferated properly on the cryogel matrix. An ideal scaffold used for tissue engineering application should allow the cells to adhere, proliferate and maintain their functionality. Neurotransmitter analysis has been done which indicated that IMR-32 cells adhered, proliferated and secreted neurotransmitters when they interacted with these matrices which showed restoration of their functionality. The cell-matrix interaction up to molecular level was also evaluated so to check genotoxicity and protein expression profile which indicated that these cryogel matrices are non-genotoxic and maintained biofunctionality of cells growing on these matrices. All these cryogels, when implanted subcutaneously in balb/c mice, showed no adverse systemic or local toxicity effects at implantation site. There was no significant increase in inflammatory cell count has otherwise been observed after scaffold implantation. These cryogels are supermacroporous and this porous structure allows cell infiltration and proliferation of host cells. This showed the integration and presence of infiltrated cells into the cryogel implants. Histological analysis confirmed that the implanted cryogels do not have any adverse effect in spite of host immune system recognition at the site of implantation, on its surrounding tissues and other vital host organs. In vivo biocompatibility study after in vitro biocompatibility analysis has also concluded that these synthesized cryogels act as important biological substitutes, more adaptable and appropriate for transplantation. Thus, these cryogels showed their potential for soft tissue engineering applications.

Keywords: cryogelation, hemocompatibility, in vitro biocompatibility, in vivo biocompatibility, soft tissue engineering applications

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Rushva Parihar, Anushka Barua

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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.

Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

Procedia PDF Downloads 234

Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

Abstract:

Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

Procedia PDF Downloads 867

Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

Procedia PDF Downloads 233

Authors: Jude A. Mbanasor, Chigozirim N. Onwusiribe

Abstract:

The enigma climate change is no longer an illusion but a reality. In the recent years, the Nigeria climate has changed and the changes are shown by the changing patterns of rainfall, the sunshine, increasing level carbon and nitrous emission as well as deforestation. This study analyzed the behavioural response of bee keepers to variations in the climate and the adaptation techniques developed in response to the climate variation. Beekeeping is a viable economic activity for the alleviation of poverty as the products include honey, wax, pollen, propolis, royal jelly, venom, queens, bees and their larvae and are all marketable. The study adopted the multistage sampling technique to select 120 beekeepers from the five states of Southeast Nigeria. Well-structured questionnaires and focus group discussions were adopted to collect the required data. Statistical tools like the Principal component analysis, data envelopment models, graphs, and charts were used for the data analysis. Changing patterns of rainfall and sunshine with the increasing rate of deforestation had a negative effect on the habitat of the bees. The bee keepers have adopted the Kenya Top bar and Langstroth hives and they establish the bee hives on fallow farmland close to the cultivated communal farms with more flowering crops.

Keywords: climate, farmer, response, smart

Procedia PDF Downloads 133

Authors: Raluca Ionela Maxim

Abstract:

Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models

Procedia PDF Downloads 135

Authors: Minh Nguyen

Abstract:

Today, QR or Quick Response Codes are prevalent, and mobile/smart devices can efficiently read and understand them. Therefore, we can see their appearance in many areas, such as storing web pages/websites, business phone numbers, redirecting to an app download, business location, social media. The popularity of the QR Code is mainly because of its many advantages, such as it can hold a good amount of information, is small, easy to scan and read by a general RGB camera, and it can still work with some damages on its surface. However, there are still some issues. For instance, some areas needed to be kept untouched for its successful decode (e.g., the “Finder Patterns,” the “Quiet Zone,” etc.), the capability of built-in auto-correction is not robust enough, and it is not flexible enough for many application such as Augment Reality (AR). We proposed a new Colour Quick Response Code that has several advantages over the original ones: (1) there is no untouchable area, (2) it allows up to 40% of the entire code area to be damaged, (3) it is more beneficial for Augmented Reality applications, and (4) it is back-compatible and readable by available QR Code scanners such as Pyzbar. From our experience, our Colour Quick Response Code is significantly more flexible on damage compared to the original QR Code. Our code is believed to be suitable in situations where standard 2D Barcodes fail to work, such as curved and shiny surfaces, for instance, medical blood test sample tubes and syringes.

Keywords: QR code, computer vision, image processing, 2D barcode

Procedia PDF Downloads 118

Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

Abstract:

The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 111