Search results for: CBSD (component based software development)

Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Pierre-Andre Mudry, Jean Decaix, Jeremy Schmid, Cesar Papilloud, Cecile Munch-Alligne

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In most of the Swiss Alpine regions, the availability of water resources is usually adequate even in times of drought, as evidenced by the 2003 and 2018 summers. Indeed, important natural stocks are for the moment available in the form of snow and ice, but the situation is likely to change in the future due to global and regional climate change. In addition, alpine mountain regions are areas where climate change will be felt very rapidly and with high intensity. For instance, the ice regime of these regions has already been affected in recent years with a modification of the monthly availability and extreme events of precipitations. The current research, focusing on the municipality of Val de Bagnes, located in the canton of Valais, Switzerland, is part of a project led by the Altis company and achieved in collaboration with WSL, BlueArk Entremont, and HES-SO Valais-Wallis. In this region, water occupies a key position notably for winter and summer tourism. Thus, multiple actors want to apprehend the future needs and availabilities of water, on both the 2050 and 2100 horizons, in order to plan the modifications to the water supply and distribution networks. For those changes to be salient and efficient, a good knowledge of the current water distribution networks is of most importance. In the current case, the water drinking network is well documented, but this is not the case for the irrigation one. Since the water consumption for irrigation is ten times higher than for drinking water, data acquisition on the irrigation network is a major point to determine future scenarios. This paper first presents the instrumentation and simulation of the irrigation network using custom-designed IoT devices, which are coupled with a digital clone simulated to reduce the number of measuring locations. The developed IoT ad-hoc devices are energy-autonomous and can measure flows and pressures using industrial sensors such as calorimetric water flow meters. Measurements are periodically transmitted using the LoRaWAN protocol over a dedicated infrastructure deployed in the municipality. The gathered values can then be visualized in real-time on a dashboard, which also provides historical data for analysis. In a second phase, a digital clone of the irrigation network was modeled using EPANET, a software for water distribution systems that performs extended-period simulations of flows and pressures in pressurized networks composed of reservoirs, pipes, junctions, and sinks. As a preliminary work, only a part of the irrigation network was modelled and validated by comparisons with the measurements. The simulations are carried out by imposing the consumption of water at several locations. The validation is performed by comparing the simulated pressures are different nodes with the measured ones. An accuracy of +/- 15% is observed on most of the nodes, which is acceptable for the operator of the network and demonstrates the validity of the approach. Future steps will focus on the deployment of the measurement devices on the whole network and the complete modelling of the network. Then, scenarios of future consumption will be investigated. Acknowledgment— The authors would like to thank the Swiss Federal Office for Environment (FOEN), the Swiss Federal Office for Agriculture (OFAG) for their financial supports, and ALTIS for the technical support, this project being part of the Swiss Pilot program 'Adaptation aux changements climatiques'.

Keywords: hydraulic digital clone, IoT water monitoring, LoRaWAN water measurements, EPANET, irrigation network

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Authors: James Freeman, Andry Rakotonirainy

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Train pedestrian collisions are common and are the most likely to result in severe injuries and fatalities when compared to other types of rail crossing accidents. However, there is limited research that has focused on understanding the reasons why some pedestrians’ break level crossings rules, which limits the development of effective countermeasures. As a result, this study undertook a deeper exploration into the origins of risky pedestrian behaviour through structured interviews. A total of 40 pedestrians who admitted to either intentionally breaking crossing rules or making crossing errors participated in an in-depth telephone interview. Qualitative analysis was undertaken via thematic analysis that revealed participants were more likely to report deliberately breaking rules (rather than make errors), particular after the train had passed the crossing as compared to before it arrives. Predominant reasons for such behaviours were identified to be: calculated risk taking, impatience, poor knowledge of rules and low likelihood of detection. The findings have direct implications for the development of effective countermeasures to improve crossing safety (and managing risk) such as increasing surveillance and transit officer presence, as well as installing appropriate barriers that either deter or incapacitate pedestrians from violating crossing rules. This paper will further outline the study findings in regards to the development of countermeasures as well as provide direction for future research efforts in this area.

Keywords: crossings, mistakes, risk, violations

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Authors: Nazihe Sedighi, Mohsen Nokhbatolphoghaei

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Bisphenol A (BPA) is a monomer used in the manufacture of polycarbonate plastics. Due to having properties such as transparency, heat and impact resistance, it is used widely in medicine, sorts, electronic components, and food containers. It is also used in the production of resins which is applied for lining cans. BPA releases from resins and polycarbonate when it is heated or continuously used the containers from which BPA can enter the body. There are several reports indicating the presence of BPA in the placenta, amniotic fluid, and the embryo itself. While researchers investigated the teratogenic effect of BPA on embryos, very limited work has been done on the effects of BPA when applied from early stages of development. In this study, The teratogenic effect of BPA was investigated at earliest preimplantation (day zero) through day 15.5 of the development of Balb/C mouse embryos. After ensuring the pregnancy via observing vaginal plug, Pregnant mice were divided into five groups. For the three experimental groups, the amount of 500, 750, and 1000 mg/kg/d Bisphenol A was given orally according to body weight. The sham group that was treated with sesame oil, which was used as vehicle and control group remained intact. On day 18.5 of gestation, embryos were removed from the uterus. Randomly half of the embryo were fixed in Bouin for tissue analysis. The other half were prepared for skeletal system staining using Alizarin Red and alcian blue dies. The results showed that the embryonic weight and the crown-rump length of embryos decreased significantly (P < 0.05) in all experimental groups compared to the control group and the sham. In this study, skeletal abnormalities such as delay in ossification of skull and limbs as well as the deviation in the backbone were seen. This research suggests that pregnant mothers need to be aware of possible teratogenic effects of BPA at any stage of pregnancy especially from early to mid stages. In this case, pregnant mothers may need to stop using any manufacture of polycarbonate plastics, as a container for food or drinking.

Keywords: bisphenol A, development, polycarbonate plastic, skeletal system, teratogenicity

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Authors: Manana Lobzhanidze

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Reforming the pension system is urgent in Georgia due to socio-economic problems. Replacing the current pension system with a new one requires, on the one hand, an assessment of the challenges in this field and, on the other hand, a study of the best practices of foreign experience. Objectives: The aim of the research is to identify challenges in the pension reform process in Georgia, to study international experience, and to develop recommendations for the implementation of an effective pension system. Methodologies: A desk study was conducted, and methods of analysis, comparison, grouping, matrix charts, and scenario analysis were used. Findings: The advantages of accumulative pension compared to the current pension system are identified. The main challenge is the non-targeting of the pension contributions and the ineffective investment policy; the public's attitude towards the cumulative pension system is determined.

Keywords: pension reform, challenges, international practice, opportunity for development

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Zainab Zendana Shafii

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Lullabies have been broadly defined as songs that are sung to calm and soothe children. While this is true, this paper intends to show that lullabies exceed these functions. The paper, in exploring Nupe lullabies, examines the various functions that lullabies perform in terms of language development, cultural enrichment and also the retelling of history as it relates to the culture of the Nupe people of northern Nigeria. The theoretical framework used is the functionalist theory. This theory postulates that all cultural or social phenomena have a positive function and that all are indispensable. The functionalist theory is based on the premise that all aspects of a society—institutions, roles, norms, etc.—serve a purpose and that all are indispensable for the long-term survival of the society. To this end, this paper dissects the various lullabies in Nupeland with a view to exploring the meaning that these songs generate and why they are even sung at all. The qualitative research methodology has been used to gather materials.

Keywords: Nupe, lullabies, Nigeria, northern

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Authors: Leonardo Coloma

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The world changes constantly, every second its properties vary due either natural factors or human intervention. As the most intelligent creatures on the planet, human beings have transformed the environment and paradoxically –have allowed ‘mother nature’ to lose species, accelerate the processes of climate change, the deterioration of the ozone layer, among others. The rapid population growth, the procurement, administration and distribution of resources, waste management, and technological advances are some of the factors that boost urban sprawl whose gray stain extends over the territory, facing challenges such as pollution, overpopulation and scarcity of resources. In Ecuador, these problems are added to the social, cultural, economic and political anomalies that have historically affected it. This fact can represent a greater delay when trying to solve global problems, without having paid attention to local inconveniences –smaller ones, but ones that could be the key to project smart solutions on bigger ones. This research aims to highlight the main characteristics of the development models adopted by two Amazonian cities, and analyze the impact of such urban growth on society; to finally define the parameters that would allow the development of an intelligent city in Ecuador, prepared for the challenges of the XXI Century. Contrasts in the climate, temperature, and landscape of Ecuadorian cities are fused with the cultural diversity of its people, generating a multiplicity of nuances of an indecipherable wealth. However, we strive to apply development models that do not recognize that wealth, not understanding them and ignoring that their proposals will vary according to where they are applied. Urban plans seem to take a bit of each of the new theories and proposals of development, which, in the encounter with the informal growth of cities, with those excluded and ‘isolated’ societies, generate absurd morphologies - where the uncertain becomes tangible. The desire to project smart cities is ever growing, but it is important to consider that this concept does not only have to do with the use of information and communication technologies. Its success is achieved when advances in science and technology allow the establishment of a better relationship between people and their context (natural and built). As a research methodology, urban analysis through mappings, diagrams and geographical studies, as well as the identification of sensorial elements when living the city, will make evident the shortcomings of the urban models adopted by certain populations of the Ecuadorian Amazon. Following the vision of previous investigations started since 2014 as part of ‘Centro de Acciones Urbanas,’ the results of this study will encourage the dialogue between the city (as a physical fact) and those who ‘make the city’ (people as its main actors). This research will allow the development of workshops and meetings with different professionals, organizations and individuals in general.

Keywords: Latin American cities, smart cities, urban development, urban morphology, urban sprawl

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Shiming Li, Qingwang Liu, Honggan Wu, Jianbing Zhang

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Plantation forests are useful for timber production, recreation, environmental protection and social development. Stands height is an important parameter for the estimation of forest volume and carbon stocks. Although lidar is suitable technology for the vertical parameters extraction of forests, but high costs make it not suitable for operational inventory. With the development of computer vision and photogrammetry, aerial photos from unmanned aerial system can be used as an alternative solution for height mapping. Structure-from-motion (SfM) photogrammetry technique can be used to extract DSM and DEM information. Canopy height model (CHM) can be achieved by subtraction DEM from DSM. Our result shows that overlapping aerial photos is a potential solution for plantation forests height mapping.

Keywords: forest height mapping, plantation forests, structure-from-motion photogrammetry, UAS

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Authors: Lin Dong, Fei Shi

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Based on the railway network and the principles of space syntax, the study attempts to reconstruct the spatial relationship of the passenger network connections from space and time perspective. According to the travel time data of main stations in the Yangtze River Delta urban agglomeration obtained by the Internet, the topological drawing of railway network under different time sections is constructed. With the comprehensive index composed of connection and integration, the accessibility and network operation efficiency of the railway network in different time periods is calculated, while the fairness of the network is analyzed by the fairness indicators constructed with the integration and location entropy from the perspective of horizontal and vertical fairness respectively. From the analysis of the efficiency and fairness of the railway passenger transport network, the study finds: (1) There is a strong regularity in regional system accessibility change; (2) The problems of efficiency and fairness are different in different time periods; (3) The improvement of efficiency will lead to the decline of horizontal fairness to a certain extent, while from the perspective of vertical fairness, the supply-demand situation has changed smoothly with time; (4) The network connection efficiency of Shanghai, Jiangsu and Zhejiang regions is higher than that of the western regions such as Anqing and Chizhou; (5) The marginalization of Nantong, Yancheng, Yangzhou, Taizhou is obvious. The study explores the application of spatial syntactic theory in regional traffic analysis, in order to provide a reference for the development of urban agglomeration transportation network.

Keywords: spatial syntax, the Yangtze River Delta, railway passenger time, efficiency and fairness

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Authors: Yong Pan, Li Wang, Xue Qiong Su, Dong Wen Gao

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To date, nanomaterials have received extensive attention over the years because of their wide application. Various nanomaterials such as nanoparticles, nanowire, nanoring, nanostars and other nanostructures have begun to be systematically studied. The preparation of these materials by chemical methods is not only costly, but also has a long cycle and high toxicity. At the same time, preparation of nanoparticles of multi-doped composites has been limited due to the special structure of the materials. In order to prepare multi-doped composites with the same structure as macro-materials and simplify the preparation method, the Ga_xCo_1-xZnSe_0.4 (x = 0.1, 0.3, 0.5) nanoparticles are prepared by Pulse Laser Ablation (PLA) method. The particle component and structure are systematically investigated by X-ray diffraction (XRD) and Raman spectra, which show that the success of our preparation and the same concentration between nanoparticles (NPs) and target. Morphology of the NPs characterized by Transmission Electron Microscopy (TEM) indicates the circular-shaped particles in preparation. Fluorescence properties are reflected by PL spectra, which demonstrate the best performance in concentration of Ga_0.3Co_0.3ZnSe_0.4. Therefore, all the results suggest that PLA is promising to prepare the multi-NPs since it can modulate performance of NPs.

Keywords: PLA, physics, nanoparticles, multi-doped

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Authors: Joshua Buli, David Pietrowski, Samuel Britton

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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

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Authors: Maritsa Kurashvili, George Adamia, Tamar Ananiashvili, Lia Amiranasvili, Tamar Varazi, Marina Pruidze, Marlen Gordeziani, Gia Khatisashvili

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The goal of presented work is the development phytoremediation method targeted to cleaning environment polluted with organochlorine pesticides, based on joint application of plants and microorganisms. For this aim the selection of plants and microorganisms with corresponding capabilities towards three organochlorine pesticides (Lindane, DDT and PCP) has been carried out. The tolerance of plants to tested pesticides and induction degree of plant detoxification enzymes by these compounds have been used as main criteria for estimating the applicability of plants in proposed technology. Obtained results show that alfalfa, maize and soybean among tested six plant species have highest tolerance to pesticides. As a result of screening, more than 30 strains from genera Pseudomonas have been selected. As a result of GC analysis of incubation area, 11 active cultures for investigated pesticides are carefully chosen.

Keywords: DDT, Lindane, organochlorine pesticides, PCP, phytoremediation

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Authors: Irtaza M. Syed, Kaameran Raahemifar

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

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

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Authors: Dawit Hoyiso, Abinet Arega, Terefe Markos

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Background: - In spite of all the various programs and strategies to promote the use of research finding there is still gap between theory and practice. Difference in outcomes, health inequalities, and poorly performing health service continue to present a challenge to all nurses. A number of studies from various countries have reported that nurses’ experience of evidence-based practice is low. In Ethiopia there is an information gap on the extent of evidence based nursing practice and its associated factors. Objective: - the study aims to assess the implementation of evidence based nursing practice and associated factors among nurses in Jimma zone public hospitals. Method: - Institution based cross-sectional study was conducted from March 1-30/2015. A total of 333 sampled nurses for quantitative and 8 in-depth interview of key informants were involved in the study. Semi-structured questionnaire was adapted from funk’s BARRIER scale and Friedman’s test. Multivariable Linear regression was used to determine significance of association between dependent and independent variables. Pretest was done on 17 nurses of Bedele hospital. Ethical issue was secured. Result:-Of 333 distributed questionnaires 302 were completed, giving 90.6% response rate. Of 302 participants 245 were involved in EBP activities to different level (from seldom to often). About forty five(18.4%) of the respondents had implemented evidence based practice to low level (sometimes), one hundred three (42 %) of respondents had implemented evidence based practice to medium level and ninety seven (39.6 %) of respondents had implemented evidence based practice to high level(often). The first greatest perceived barrier was setting characteristic (mean score=26.60±7.08). Knowledge about research evidence was positively associated with implementation of evidence based nursing practice (β=0.76, P=0.008). Similarly, Place where the respondent graduated was positively associated with implementation of evidence based nursing practice (β=2.270, P=0.047). Also availability of information resources was positively associated with implementation of evidence based practice (β=0.67, P= 0.006). Conclusion: -Even though larger portion of nurses in this study were involved in evidence-based practice whereas small number of participants had implemented frequently. Evidence-based nursing practice was positively associated with knowledge of research, place where respondents graduated, and the availability of information resources. Organizational factors were found to be the greatest perceived barrier. Intervention programs on awareness creation, training, resource provision, and curriculum issues to improve implementation of evidence based nursing practice by stakeholders are recommended.

Keywords: evidence based practice, nursing practice, research utilization, Ethiopia

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Authors: Soroor Ghaziof, Wei Gao

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Zn alloy and composite coatings are widely used in buildings and structures, automobile and fasteners industries to protect steel component from corrosion. In this paper, Zn-Ni-Al2O3 nano-composite coatings were electrodeposited on mild steel using a novel sol enhanced electroplating method. In this method, transparent Al2O3 sol was added into the acidic Zn-Ni bath to produced Zn-Ni-Al2O3 nano-composite coatings. The effect of alumina sol on the electrodeposition process, and coating properties was investigated using cyclic voltammetry, XRD, ESEM and Tafel test. Results from XRD tests showed that the structure of all coatings was single γ-Ni5Zn21 phase. Cyclic voltammetry results showed that the electrodeposition overpotential was lower in the presence of alumina sol in the bath, and caused the reduction potential of Zn-Ni to shift to more positive values. Zn-Ni-Al2O3 nano composite coatings produced more uniform and compact deposits, with fine grained microstructure when compared to Zn-Ni coatings. The corrosion resistance of Zn-Ni coatings was improved significantly by incorporation of alumina nano particles into the coatings.

Keywords: Zn-Ni-Al2O3 composite coatings, steel, sol-enhanced electroplating, corrosion resistance

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Authors: Sohail Ahmed, Ke Xing

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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). This research proposed an analytical framework for ETICS, its concepts, and theory by integrating CAS methodology into the management of the technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution, and realization of the technological innovation capabilities in complex dynamic environments. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS, and summarizes the sources of technological innovation, the elements of each subject, and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions, and government agencies with the leading enterprises in industrial settings. The study was exploratory and based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of the enterprise's technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on the enterprise’s research and development personnel, investments in technological processes, and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise technological innovation capability system, research institutions, multi-agents

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Authors: Andrew Randles, Ilker Ocak, Cheam Daw Don, Navab Singh, Alex Gu

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Nine Degrees of Freedom (9 DOF) systems are already in development in many areas. In this paper, an integrated pressure sensor is proposed that will make use of an already existing monolithic 9 DOF inertial MEMS platform. Capacitive pressure sensors can suffer from limited sensitivity for a given size of membrane. This novel pressure sensor design increases the sensitivity by over 5 times compared to a traditional array of square diaphragms while still fitting within a 2 mm x 2 mm chip and maintaining a fixed static capacitance. The improved design uses one large diaphragm supported by pillars with fixed electrodes placed above the areas of maximum deflection. The design optimization increases the sensitivity from 0.22 fF/kPa to 1.16 fF/kPa. Temperature sensitivity was also examined through simulation.

Keywords: capacitive pressure sensor, 9 DOF, 10 DOF, sensor, capacitive, inertial measurement unit, IMU, inertial navigation system, INS

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

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Authors: Joseph Ippolito, David Megenhardt

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In the United States, displaced workers, the unemployed and those seeking to build additional work skills are provided employment training and job placement services through a system of One-Stop Career Centers that are sponsored by the country’s 593 local Workforce Boards. During the period 2010-2015, these centers served roughly 8 million individuals each year. The quality of services provided at these centers rests upon professional employment specialists who work closely with clients to identify their job interests, to connect them to appropriate training opportunities, to match them with needed supportive social services and to guide them to eventual employment. Despite the crucial role these Employment Specialists play, currently there are no broadly accepted standards that establish what these individuals are expected to do in the workplace, nor are there indicators to assess how well an individual performs these responsibilities. Education Development Center (EDC) and the United Labor Agency (ULA) have partnered to create a foundation upon which curriculum can be developed that addresses the skills, knowledge and behaviors that Employment Specialists must master in order to serve their clients effectively. EDC is a non-profit, education research and development organization that designs, implements, and evaluates programs to improve education, health and economic opportunity worldwide. ULA is the social action arm of organized labor in Greater Cleveland, Ohio. ULA currently operates One-Stop Career Centers in both Cleveland and Pittsburgh, Pennsylvania. This case study outlines efforts taken to create standards that define the work of Employment Specialists and to establish indicators that can guide assessment of work performance. The methodology involved in the study has engaged a panel of expert Employment Specialists in rigorous, structured dialogues that analyze and identify the characteristics that enable them to be effective in their jobs. It has also drawn upon and integrated reviews of the panel’s work by more than 100 other Employment Specialists across the country. The results of this process are two documents that provide resources for developing training curriculum for future Employment Specialists, namely: an occupational profile of an Employment Specialist that offers a detailed articulation of the skills, knowledge and behaviors that enable individuals to be successful at this job, and; a collection of performance based indicators, aligned to the profile, which illustrate what the work responsibilities of an Employment Specialist 'look like' a four levels of effectiveness ranging from novice to expert. The method of occupational analysis used by the study has application across a broad number of fields.

Keywords: assessment, employability, job standards, workforce development

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Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

Procedia PDF Downloads 94

Authors: Sumei Cai, Hong Li

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Either during water or gas injection into reservoir, in order to understand the areal flow pressure distribution underground, associated bounding deformation is prevalently monitored by ground or downhole tiltmeters. In this paper, an inverse solution to elastic response of far field displacements induced by reservoir pressure change due to flow injection was studied. Furthermore, the fundamental theory on inverse solution to elastic problem as well as its spatial smoothing approach is presented. Taking advantage of source code development based on Boundary Element Method, numerical analysis on the monitoring data of ground surface displacements to further understand the behavior of reservoir process was developed. Numerical examples were also conducted to verify the effectiveness.

Keywords: remote displacement, inverse problem, boundary element method, BEM, reservoir process

Procedia PDF Downloads 105

Authors: L. M. H. Mustonen, S. A. Heikkilä

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The focus of the paper is to describe team teaching as a HAMK’s pedagogical method, and its impacts to the teachers work. Background: Traditionally it is thought that teaching is a job where one mostly works alone. More and more teachers feel that their work is getting more stressful. Solutions to these problems have been sought in Häme University of Applied sciences’ (From now on referred to as HAMK). HAMK has made a strategic change to move to the group oriented working of teachers. Instead of isolated study courses, there are now larger 15 credits study modules. Implementation: As examples of the method, two cases are presented: technical project module and summer studies module, which was integrated into the EU development project called Energy Efficiency with Precise Control. In autumn 2017, technical project will be implemented third time. There are at least three teachers involved in it and it is the first module of the new students. Main focus is to learn the basic skills of project working. From communicational viewpoint, they learn the basics of written and oral reporting and the basics of video reporting skills. According to our quality control system, the need for the development is evaluated in the end of the module. There are always some differences in each implementation but the basics are the same. The other case summer studies 2017 is new and part of a larger EU project. For the first time, we took a larger group of first to third year students from different study programmes to the summer studies. The students learned professional skills and also skills from different fields of study, international cooperation, and communication skills. Benefits and challenges: After three years, it is possible to consider what the changes mean in the everyday work of the teachers - and of course – what it means to students and the learning process. The perspective is HAMK’s electrical and automation study programme: At first, the change always means more work. The routines born after many years and the course material used for years may not be valid anymore. Teachers are teaching in modules simultaneously and often with some subjects overlapping. Finding the time to plan the modules together is often difficult. The essential benefit is that the learning outcomes have improved. This can be seen in the feedback given by both the teachers and the students. Conclusions: A new type of working environment is being born. A team of teachers designs a module that matches the objectives and ponders the answers to such questions as what are the knowledge-based targets of the module? Which pedagogical solutions will achieve the desired results? At what point do multiple teachers instruct the class together? How is the module evaluated? How can the module be developed further for the next execution? The team discusses openly and finds the solutions. Collegiate responsibility and support are always present. These are strengthening factors of the new communal university teaching culture. They are also strong sources of pleasure of work.

Keywords: pedagogical development, summer studies, team teaching, well-being at work

Procedia PDF Downloads 93

Authors: Z. Zerdoumi, D. Benatia, , D. Chicouche

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This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP-DFE) trained with the back propagation algorithm. The capacity of the MLP-DFE to deal with nonlinear channels is evaluated. From simulation results it can be noted that the MLP based DFE improves significantly the restored signal quality, the steady state mean square error (MSE), and minimum Bit Error Rate (BER), when comparing with its conventional counterpart.

Keywords: Artificial Neural Network, signal restoration, Nonlinear Channel equalization, equalization

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Authors: Rahul Arora, S. S. Dhami

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This paper implements the design structure of industrial robot along with the different transmission components like gear assembly and analysis of complete industrial robot. In this paper, it gives the overview on the most efficient types of modeling and different analysis results that can be obtained for an industrial robot. The investigation is executed in regards to two classifications i.e. the deformation and the stress tests. SolidWorks is utilized to design and review the 3D drawing plan while ANSYS Workbench is utilized to execute the FEA on an industrial robot and the designed component. The CAD evaluation was conducted on a disentangled model of an industrial robot. The study includes design and drafting its transmission system. In CAE study static, modal and dynamic analysis are presented. Every one of the outcomes is divided in regard with the impact of the static and dynamic analysis on the situating exactness of the robot. It gives critical data with respect to parts of the industrial robot that are inclined to harm under higher high force applications. Therefore, the mechanical structure under different operating conditions can help in optimizing the manipulator geometry and in selecting the right material for the same. The FEA analysis is conducted for four different materials on the same industrial robot and gear assembly.

Keywords: CAD, CAE, FEA, robot, static, dynamic, modal, gear assembly

Procedia PDF Downloads 364

Authors: Hamida Y. Mostafa, Ghada E. Khedr, Dina M. Abd El-Aty

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Sulfur compound removal from petroleum fractions is a critical component of environmental protection demands. Solvent extraction, oxidative desulfurization, or hydro-treatment techniques have traditionally been used as the removal processes. While all methods were capable of eliminating sulfur compounds at moderate rates, they had some limitations. A major problem with these routes is their high running expenses, which are caused by their prolonged operation times and high energy consumption. Therefore, new methods for removing sulfur are still necessary. In the current study, a simple assisted desulfurization system for gas oil fraction has been successfully developed using acetonitrile and methanol as a solvent under microwave irradiation. The key variables affecting sulfur removal have been studied, including microwave power, irradiation time, and solvent to gas oil volume ratio. At the conclusion of the research that is being presented, promising results have been found. The results show that a microwave-assisted extractive desulfurization method had remove sulfur with a high degree of efficiency under the suitable conditions.

Keywords: extractive desulfurization, microwave assisted extraction, petroleum fractions, acetonitrile and methanol

Procedia PDF Downloads 84

Authors: Ahmed Tarek, Ahmed Alveed

Abstract:

Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

Procedia PDF Downloads 133