Search results for: evidence based practice

Authors: Yichin Chen

Abstract:

Taiwan is an island characterized by an active tectonics and high erosion rates. Monitoring the dynamic landscape of Taiwan is an important issue for disaster mitigation, geomorphological research, and watershed management. Long-term and high spatiotemporal landform data is essential for quantifying and simulating the geomorphological processes and developing warning systems. Recently, the advances in unmanned aerial vehicle (UAV) and computational photogrammetry technology have provided an effective way to rebuild and monitor the topography changes in high spatio-temporal resolutions. This study rebuilds the 30-years landform change in the Aiyuzi watershed in 1986-2017 by using the aerial photogrammetry-based techniques. The Aiyuzi watershed, located in central Taiwan and has an area of 3.99 Km², is famous for its frequent landslide and debris flow disasters. This study took the aerial photos by using UAV and collected multi-temporal historical, stereo photographs, taken by the Aerial Survey Office of Taiwan’s Forestry Bureau. To rebuild the orthoimages and digital surface models (DSMs), Pix4DMapper, a photogrammetry software, was used. Furthermore, to control model accuracy, a set of ground control points was surveyed by using eGPS. The results show that the generated DSMs have the ground sampling distance (GSD) of ~10 cm and ~0.3 cm from the UAV’s and historical photographs, respectively, and vertical error of ~1 m. By comparing the DSMs, there are many deep-seated landslides (with depth over 20 m) occurred on the upstream in the Aiyuzi watershed. Even though a large amount of sediment is delivered from the landslides, the steep main channel has sufficient capacity to transport sediment from the channel and to erode the river bed to ~20 m in depth. Most sediments are transported to the outlet of watershed and deposits on the downstream channel. This case study shows that UAV and photogrammetry technology are useful for topography change monitoring effectively.

Keywords: aerial photogrammetry, landslide, landform change, Taiwan

Procedia PDF Downloads 144

Authors: Shima Taheri, Simon Clark

Abstract:

Concrete is an essential building material used in the majority of structures. Degradation of concrete over time increases the life-cycle cost of an asset with an estimated annual cost of billions of dollars to national economies. Most of the concrete failure occurs due to cracks, which propagate through a structure and cause weakening leading to failure. Stopping crack propagation is thus the key to protecting concrete structures from failure and is the best way to prevent inconveniences and catastrophes. Furthermore, the majority of cracks occur deep within the concrete in inaccessible areas and are invisible to normal inspection. Few materials intrinsically possess self-healing ability, but one that does is concrete. However, self-healing in concrete is limited to small dormant cracks in a moist environment and is difficult to control. In this project, we developed a method for self-healing of nascent fractures in concrete components through the automatic release of self-curing healing agents encapsulated in breakable nano- and micro-structures. The Poly(methyl methacrylate) (PMMA) based two-part adhesive is encapsulated in core-shell structures with brittle/weak inert shell, synthesized via miniemulsion/solvent evaporation polymerization. Stress fields associated with propagating cracks can break these capsules releasing the healing agents at the point where they are needed. The shell thickness is playing an important role in preserving the content until the final setting of concrete. The capsules can also be surface functionalized with carboxyl groups to overcome the homogenous mixing issues. Currently, this formulated self-healing system can replace up to 1% of cement in a concrete formulation. Increasing this amount to 5-7% in the concrete formulation without compromising compression strength and shrinkage properties, is still under investigation. This self-healing system will not only increase the durability of structures by stopping crack propagation but also allow the use of less cement in concrete construction, thereby adding to the global effort for CO2 emission reduction.

Keywords: self-healing concrete, concrete crack, concrete deterioration, durability

Procedia PDF Downloads 102

Authors: Aidan Ryan, Nahima Miah, Sahaj Kaur, Imogen Sutherland, Mohamed Saleh

Abstract:

Pulmonary symptoms are a common presentation to the emergency department. Due to a lack of understanding of the underlying pathophysiology, chronic liver disease is not often considered a cause of dyspnea. We present three patients who were admitted with significant respiratory distress secondary to hepatopulmonary syndrome, portopulmonary hypertension, and hepatic hydrothorax. The first is a 27-year-old male with a 6-month history of progressive dyspnea. The patient developed a severe type 1 respiratory failure with a PaO₂ of 6.3kPa and was escalated to critical care, where he was managed with non-invasive ventilation to maintain oxygen saturation. He had an agitated saline contrast echocardiogram, which showed the presence of a possible shunt. A CT angiogram revealed significant liver cirrhosis, portal hypertension, and large para esophageal varices. Ultrasound of the abdomen showed coarse liver echo patter and enlarged spleen. Along with these imaging findings, his biochemistry demonstrated impaired synthetic liver function with an elevated international normalized ratio (INR) of 1.4 and hypoalbuminaemia of 28g/L. The patient was then transferred to a tertiary center for further management. Further investigations confirmed a shunt of 56%, and liver biopsy confirmed cirrhosis suggestive of alpha-1-antitripsyin deficiency. The findings were consistent with a diagnosis of hepatopulmonary syndrome, and the patient is awaiting a liver transplant. The second patient is a 56-year-old male with a 12-month history of worsening dyspnoea, jaundice, confusion. His medical history included liver cirrhosis, portal hypertension, and grade 1 oesophageal varices secondary to significant alcohol excess. On admission, he developed a type 1 respiratory failure with PaO₂ of 6.8kPa requiring 10L of oxygen. CT pulmonary angiogram was negative for pulmonary embolism but showed evidence of chronic pulmonary hypertension, liver cirrhosis, and portal hypertension. An echocardiogram revealed a grossly dilated right heart with reduced function, pulmonary and tricuspid regurgitation, and pulmonary artery pressures estimated at 78mmHg. His biochemical markers showed impaired synthetic liver function with an INR of 3.2, albumin of 29g/L, along with raised bilirubin of 148mg/dL. During his long admission, he was managed with diuretics with little improvement. After three weeks, he was diagnosed with portopulmonary hypertension and was commenced on terlipressin. This resulted in successfully weaning off oxygen, and he was discharged home. The third patient is a 61-year-old male who presented to the local ambulatory care unit for therapeutic paracentesis on a background of decompensated liver cirrhosis. On presenting, he complained of a 2-day history of worsening dyspnoea and a productive cough. Chest x-ray showed a large pleural effusion, increasing in size over the previous eight months, and his abdomen was visibly distended with ascitic fluid. Unfortunately, the patient deteriorated, developing a larger effusion along with an increase in oxygen demand, and passed away. Without underlying cardiorespiratory disease, in the presence of a persistent pleural effusion with underlying decompensated cirrhosis, he was diagnosed with hepatic hydrothorax. While each presented with dyspnoea, the cause and underlying pathophysiology differ significantly from case to case. By describing these complications, we hope to improve awareness and aid prompt and accurate diagnosis, vital for improving outcomes.

Keywords: dyspnea, hepatic hydrothorax, hepatopulmonary syndrome, portopulmonary syndrome

Procedia PDF Downloads 109

Authors: Morten Brøgger, Kim Wittchen

Abstract:

Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.

Keywords: building stock energy modelling, energy-savings, archetype

Procedia PDF Downloads 143

Authors: Dchieche Amina, Aboulaich Rajae

Abstract:

Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

Procedia PDF Downloads 314

Authors: Uchenna Cosmas Ugwu, Osmond Chukwuemeka Ene

Abstract:

Globally, older adults are considered the most vulnerable groups to age-related diseases including diabetes mellitus, obesity, cardiovascular diseases, cancer and osteoporosis. With improved access to quality healthcare services, these complications can be prevented and the incidence rates reduced to the least occurrence. The aim of this study is to validate appropriate measures for improving quality healthcare services utilization among elderly persons in Nigeria and also to determine the significant association within demographic variables. A cross-sectional survey research design was adopted. Using a convenient sampling technique, a total of 400 experts (150 registered nurses and 250 public health professionals) with minimum of doctoral degree qualification were sampled and studied. A structured instrument titled “Expert-Based Healthcare Services Utilization Questionnaire (EBHSUQ) with .83 reliability index was used for data collection. All the statistical data analysis was completed using frequency counts, percentage scores and chi-square statistics. The results were significant at p≤0.05. It was found that quality healthcare services utilization by elderly persons in Nigeria would be improved if the services are: available (83%), affordable (82%), accessible (79%), suitable (77%), acceptable (77%), continuous (75%) and stress-free (75%). Statistically, significant association existed on quality healthcare services utilization with gender (p=.03<.05) and age (p=.01<.05) while none was observed on work experience (p=.23>.05), marital status (p=.11>.05) and employment category (p=.09>.05). To improve quality healthcare services utilization for elderly persons in Nigeria, the adoption of appropriate measures by Nigerian government and professionals in healthcare sectors are paramount. Therefore, there is need for collaborative efforts by the Nigerian government and healthcare professionals geared towards educating the general public through mass sensitization, awareness campaign, conferences, seminars and workshops for the importance of accessing healthcare services.

Keywords: elderly persons, healthcare services, cross-sectional survey research design, utilization.

Procedia PDF Downloads 43

Authors: Sanket S. Jugade, Swapneel U. Naphade, Satyabodh M. Kulkarni

Abstract:

Microscale energy harvesters can be used to convert ambient mechanical vibrations to electrical energy. Such devices have great applications in low powered electronics in remote environments like powering wireless sensor nodes of Internet of Things, lightings on highways or in ships, etc. In this paper, a Microelectromechanical systems (MEMS) based energy harvester has been modeled using Analytical and Finite Element Method (FEM). The device consists of a microcantilever with a proof mass attached to its free end and a Polyvinylidene Fluoride (PVDF) piezoelectric thin film deposited on the surface of microcantilever in a unimorph or bimorph configuration. For the analytical method, the energy harvester was modeled as an equivalent electrical system in SIMULINK. The Finite element model was developed and analyzed using the commercial package COMSOL Multiphysics. The modal analysis was performed first to find the fundamental natural frequency and its variation with geometrical parameters of the system. Then the harmonic analysis was performed to find the input mechanical power, output electrical voltage, and power for a range of excitation frequencies and base acceleration values. The variation of output power with load resistance, PVDF film thickness, and damping values was also found out. The results from FEM were then validated with that of the analytical model. Finally, the performance of the device was optimized with respect to various electro-mechanical parameters. For a unimorph configuration consisting of single crystal silicon microcantilever of dimensions 8mm×2mm×80µm and proof mass of 9.32 mg with optimal values of the thickness of PVDF film and load resistance as 225 µm and 20 MΩ respectively, the maximum electrical power generated for base excitation of 0.2g at 630 Hz is 0.9 µW.

Keywords: bimorph, energy harvester, FEM, harmonic analysis, MEMS, PVDF, unimorph

Procedia PDF Downloads 175

Authors: Dmitrii Glushkov, Aleksandr G. Nigay, Olga S. Yashutina

Abstract:

In recent years, due to the intensive development of the Arctic and Antarctic areas, the actual task is to develop technology for the effective utilization of solid and liquid combustible wastes in an environment with low temperatures. Firstly, such technology will help to prevent the dumping of waste into the World Ocean and reduce the risks of causing environmental damage to the Far North areas. Secondly, promising actions will help to prepare fuel compositions from the waste in the places of their production. Such kind of fuels can be used as energy resources. It will reduce waste utilization costs when transporting them to the mainland. In the present study, we suggest a solution to the problem of waste utilization by the preparation of gel fuels based on solid and liquid combustible components with the addition of the thickener. Such kind of fuels is characterized by ease of preparation, storage, transportation and use (as energy resources). The main regularities and characteristics of physical and chemical processes are established with varying parameters of gel fuels and heating sources in wide ranges. The obtained results let us conclude about the prospects of gel fuels practical application for combustible wastes utilization. Appropriate technology will be characterized by positive environmental, operational and economic effects. The composition of the gel fuels can vary in a wide range. The fuels preparation based on one type of a combustible liquid or a several liquids mixture with the finely dispersed components addition makes it possible to obtain compositions with predicted rheological, energy or environmental characteristics. Besides, gel fuels have a lower level of the fire hazard compared to common solid and liquid fuels. This makes them convenient for storage and transportation. In such conditions, it is not necessary to transport combustible wastes from the territory of the Arctic and the Antarctic to the mainland for processing, which is now quite an expensive procedure. The research was funded by the Russian Science Foundation (project No. 18-13-00031).

Keywords: combustible liquid waste, gel fuel, ignition and combustion, utilization

Procedia PDF Downloads 103

Authors: Ghodsieh Isapour Toutizad, Aiyong Wang, Joonsoo Han, Derek Creaser, Louise Olsson, Magnus Skoglundh, Hanna HaRelind

Abstract:

Nitrous oxide (N2O), which is generally formed as a byproduct of industrial chemical processes and fossil fuel combustion, has attracted considerable attention due to its destructive role in global warming and ozone layer depletion. From various developed technologies used for lean NOx reduction, the selective catalytic reduction (SCR) of NOx with ammonia is presently the most applied method. Therefore, the development of catalysts for efficient lean NOx reduction without forming N2O in the process, or only forming it to a very small extent from the exhaust gases is of crucial significance. One type of catalysts that nowadays are used for this aim are zeolite-based catalysts. It is owing to their remarkable catalytic performance under practical reaction conditions such as high thermal stability and high N2 selectivity. Among all zeolites, copper ion-exchanged zeolites, with CHA, MFI, and BEA framework structure (like SSZ-13, ZSM-5 and Beta, respectively), represent higher hydrothermal stability, high activity and N2 selectivity. This work aims at investigating the effect of the zeolite framework structure on the formation of N2O during NH3-SCR reaction conditions over three Cu-based zeolites ranging from small-pore to large-pore framework structure. In the zeolite framework, Cu exists in two cationic forms, that can catalyze the SCR reaction by activating NO to form NO+ and/or surface nitrate species. The nitrate species can thereafter react with NH3 to form another intermediate, ammonium nitrate, which seems to be one source for N2O formation at low temperatures. The results from in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) indicate that during the NO oxidation step, mainly NO+ and nitrate species are formed on the surface of the catalysts. The intensity of the absorption peak attributed to NO+ species is higher for the Cu-CHA sample compared to the other two samples, indicating a higher stability of this species in small cages. Furthermore, upon the addition of NH3, through the standard SCR reaction conditions, absorption peaks assigned to N-H stretching and bending vibrations are building up. At the same time, negative peaks are evolving in the O-H stretching region, indicating blocking/replacement of surface OH-groups by NH3 and NH4+. By removing NH3 and adding NO2 to the inlet gas composition, the peaks in the N-H stretching and bending vibration regions show a decreasing trend in intensity, with the decrease being more pronounced for increasing pore size. It can probably be owing to the higher accumulation of ammonia species in the small-pore size zeolite compared to the other two samples. Furthermore, it is worth noting that the ammonia surface species are strongly bonded to the CHA zeolite structure, which makes it more difficult to react with NO2. To conclude, the framework structure of the zeolite seems to play an important role in the formation and reactivity of surface species relevant for the SCR process. Here we intend to discuss the connection between the zeolite structure, the surface species, and the formation of N2O during ammonia-SCR.

Keywords: fast SCR, nitrous oxide, NOx, standard SCR, zeolites

Procedia PDF Downloads 217

Authors: Upasana G. Singh, Meera Gungea

Abstract:

Learning is no more confined to the traditional classroom, teacher, and student interaction. Many universities offer courses through the Open and Distance Learning (ODL) mode, attracting a diversity of learners in terms of age, gender, and profession to name a few. The ODL mode has surfaced as one of the famous sought-after modes of learning, allowing learners to invest in their educational growth without hampering their personal and professional commitments. This mode of learning, however, requires that those who ultimately choose to adopt it must be prepared to undertake studies through such medium. The purpose of this research is to assess whether students who join universities offering courses through the ODL mode are ready to embark and study within such a framework. This study will be helpful to unveil the challenges students face in such an environment and thus contribute to developing a framework to ease adoption and integration into the ODL environment. Prior to the implementation of e-learning, a readiness assessment is essential for any institution that wants to adopt any form of e-learning. Various e-learning readiness assessment models have been developed over the years. However, this study is based on a conceptual model for e-Learning Readiness Assessment which is a ‘hybrid model’. This hybrid model consists of 4 main parameters: 1) Technological readiness, 2) Culture readiness, 3) Content readiness, and 4) Demographics factors, with 4 sub-areas, namely, technology, innovation, people and self-development. The model also includes the attitudes of users towards the adoption of e-learning as an important aspect of assessing e-learning readiness. For this study, some factors and sub-factors of the hybrid model have been considered and adapted, together with the ‘Attitude’ component. A questionnaire was designed based on the models and students where the target population were students enrolled at the Open University of Mauritius, in undergraduate and postgraduate courses. Preliminary findings indicate that most (68%) learners have an average knowledge about ODL form of learning, despite not many (72%) having previous experience with ODL. Despite learning through ODL 74% of learners preferred hard copy learning material and 48% found difficulty in reading learning material on electronic devices.

Keywords: open learning, distance learning, student readiness, a hybrid model

Procedia PDF Downloads 96

Authors: P. Abachi, S. Karami, K. Purazrang

Abstract:

The amorphous reinforcements (metallic glasses) can be considered as promising options for reinforcing light-weight aluminum and its alloys. By using the proper type of reinforcement, one can overcome to drawbacks such as interfacial de-cohesion and undesirable reactions which can be created at ceramic particle and metallic matrix interface. In this work, the Zr-based amorphous phase was produced via mechanical milling of elemental powders. Based on Miedema semi-empirical Model and diagrams for formation enthalpies and/or Gibbs free energies of Zr-Cu amorphous phase in comparison with the crystalline phase, the glass formability range was predicted. The composite was produced using the powder mixture of the aluminum and metallic glass and spark plasma sintering (SPS) at the temperature slightly above the glass transition Tg of the metallic glass particles. The selected temperature and rapid sintering route were suitable for consolidation of an aluminum matrix without crystallization of amorphous phase. To characterize amorphous phase formation, X-ray diffraction (XRD) phase analyses were performed on powder mixture after specified intervals of milling. The microstructure of the composite was studied by optical and scanning electron microscope (SEM). Uniaxial compression tests were carried out on composite specimens with the dimension of 4 mm long and a cross-section of 2 ˟ 2mm2. The micrographs indicated an appropriate reinforcement distribution in the metallic matrix. The comparison of stress–strain curves of the consolidated composite and the non-reinforced Al matrix alloy in compression showed that the enhancement of yield strength and mechanical strength are combined with an appreciable plastic strain at fracture. It can be concluded that metallic glasses (amorphous phases) are alternative reinforcement material for lightweight metal matrix composites capable of producing high strength and adequate ductility. However, this is in the expense of minor density increase.

Keywords: aluminum matrix composite, amorphous phase, mechanical alloying, spark plasma sintering

Procedia PDF Downloads 346

Authors: Yongrong Li, Ralf Domroes

Abstract:

Due to significant energy savings, enablement of higher machining speed as well as environmentally friendly features, Minimum Quantity Lubrication (MQL) has been used for many machining processes efficiently. However, in the deep hole drilling field (small tool diameter D < 5 mm) and long tool (length L > 25xD) it is always a bottle neck for a single channel MQL system. The single channel MQL, based on the Venturi principle, faces a lack of enough oil quantity caused by dropped pressure difference during the deep hole drilling process. In this paper, a system concept based on a bypass design has explored its possibility to dynamically reach the required pressure difference between the air inlet and the inside of aerosol generator, so that the deep hole drilling demanded volume of oil can be generated and delivered to tool tips. The system concept has been investigated in static and dynamic laboratory testing. In the static test, the oil volume with and without bypass control were measured. This shows an oil quantity increasing potential up to 1000%. A spray pattern test has demonstrated the differences of aerosol particle size, aerosol distribution and reaction time between single channel and bypass controlled single channel MQL systems. A dynamic trial machining test of deep hole drilling (drill tool D=4.5mm, L= 40xD) has been carried out with the proposed system on a difficult machining material AlSi7Mg. The tool wear along a 100 meter drilling was tracked and analyzed. The result shows that the single channel MQL with a bypass control can overcome the limitation and enhance deep hole drilling with a small tool. The optimized combination of inlet air pressure and bypass control results in a high quality oil delivery to tool tips with a uniform and continuous aerosol flow.

Keywords: deep hole drilling, green production, Minimum Quantity Lubrication (MQL), near dry machining

Procedia PDF Downloads 191

Authors: Young-Kwan Choi, Han-Sang Jeong

Abstract:

Floating photovoltaic system is a technology that combines photovoltaic power generation with floating structure. However, since floating technology has not been utilized in photovoltaic generation, there are no standardized criteria. It is separately developed and used by different installation bodies. This paper aims to discuss the change of floating photovoltaic system technology based on examples of floating photovoltaic systems installed in Korea.

Keywords: floating photovoltaic system, floating PV installation, ocean floating photovoltaic system, tracking type floating photovoltaic system

Procedia PDF Downloads 547

Authors: Kefi Rahmadio, Filipus Armando Ginting, Richard Nainggolan

Abstract:

This research shows the formation of the West Buru Basin and the potential utilization of this West Buru Basin as a geothermal potential. The research area is West Buru Island which is part of the West Buru Basin. The island is located in Maluku Province, with its capital city named Namlea. The island is divided into 10 districts, namely District Kepalamadan, Airbuaya District, Wapelau District, Namlea District, Waeapo District, Batabual District, Namrole District, Waesama District, Leksula District, and Ambalau District. The formation in this basin is Permian-Quarter. They start from the Formation Ghegan, Dalan Formation, Mefa Formation, Kuma Formation, Waeken Formation, Wakatin Formation, Ftau Formation and Leko Formation. These formations are composing this West Buru Basin. Determination of prospect area in the geothermal area with preliminary investigation stage through observation of manifestation, topographic shape and structure are found around prospect area. This is done because there is no data of earth that support the determination of prospect area more accurately. In Waepo area, electric power generated based on field observation and structural analysis, geothermal area of ​Waeapo was approximately 6 km², with reference to the SNI 'Classification of Geothermal Potential' (No.03-5012-1999), an area of ​​1 km² is assumed to be 12.5 MWe. The speculative potential of this area is (Q) = 6 x 12.5 MWe = 75 MWe. In the Bata Bual area, the geothermal prospect projected 4 km², the speculative potential of the Bata Bual area is worth (Q) = 4 x 12.5 MWe = 50 MWe. In Kepala Madan area, based on the estimation of manifestation area, there is a wide area of ​​prospect in Kepala Madan area about 4 km². The geothermal energy potential of the speculative level in Kepala Madan district is (Q) = 4 x 12.5 MWe = 50 MWe. These three areas are the largest geothermal potential on the island of West Buru. From the above research, it can be concluded that there is potential in West Buru Island. Further exploration is needed to find greater potential. Therefore, researchers want to explain the geothermal potential contained in the West Buru Basin, within the scope of West Buru Island. This potential can be utilized for the community of West Buru Island.

Keywords: West Buru basin, West Buru island, potential, Waepo, Bata Bual, Kepala Madan

Procedia PDF Downloads 213

Authors: Shankaran Sitarama

Abstract:

New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

Procedia PDF Downloads 54

Authors: Darius Jakimavicius

Abstract:

Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

Procedia PDF Downloads 27

Authors: P. Susheela, Mary Rosaline, R. Radha

Abstract:

This research was designed to determine the bioactive compounds present in the nest samples of the mud dauber wasp, Sceliophron caementarium. Insects and insect-based products have been used for the treatment of various ailments from a very long time. It has been found that all over the world including the western societies and the indigenous populations, the usage of insect-based medicine plays an important role in various healing practices and magic rituals. Studies on the therapeutic usage of insects are negligible when compared to plants, the. In the present scenario, it is important to explore bioactive compounds from natural sources rather than depending on synthetic drugs that have adverse effects on human body. Keeping this in view, an attempt was made to analyze and identify bioactive components from the nest sample of the mud dauber wasp, Sceliophron caementarium. The nests of the mud dauber wasp, Sceliophron caementarium were collected from Coimbatore, Tamil Nadu, India. The nest sample was extracted with ethanol for 6-8 hours using Soxhlet apparatus. The final residue was obtained by filtering the extract through Whatman filter paper No.41. The GCMS analysis of the nest sample was performed using Perkin Elmer Elite - 5 capillary column. The resultant compounds were compared with the database of National Institute Standard and Technology (NIST), WILEY8, FAME. The GC-MS analysis of the concentrated ethanol extract revealed the presence of eight constituents like Methylene chloride, Eicosanoic acid, 1, 1’:3’, 1’’-Terphenyl, 5'-Phenyl, Di-N-Decylsulfone, 1, 2-Bis (Trimethylsilyl) Benzene, Androstane-11, 17-Dione, 3-[(Trimethylsilyl) Oxy]-, 17-[O-(Phenylmethyl) O. Most of the identified compounds were reported as having biological activities viz. anti-inflammatory, antibacterial and antifungal properties that can be of pharmaceutical importance and further study of these isolated compounds may prove their medicinal importance in future.

Keywords: Sceliophron caementarium, Gas chromatography-mass spectrometry, ethanol extract, bioactive compounds

Procedia PDF Downloads 277

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

Abstract:

Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

Procedia PDF Downloads 71

Authors: Khairil I. Othman, Mahfuzah Mahayaddin, Zarina Bibi Ibrahim

Abstract:

We develop and demonstrate a computationally efficient numerical technique to solve first order stiff differential equations. This technique is based on block method whereby three approximate points are calculated. The Cholistani of varied step sizes are presented in divided difference form. Stability regions of the formulae are briefly discussed in this paper. Numerical results show that this block method perform very well compared to existing methods.

Keywords: block method, divided difference, stiff, computational

Procedia PDF Downloads 412

Authors: Prakash, Vikash Kumar, Vinay Bansal, L. N. Das

Abstract:

Dual biometrics is a subpart of multimodal biometrics, which refers to the use of a variety of modalities to identify and authenticate persons rather than just one. We limit the risks of mistakes by mixing several modals, and hackers have a tiny possibility of collecting information. Our goal is to collect the precise characteristics of iris and palmprint, produce a fusion of both methodologies, and ensure that authentication is only successful when the biometrics match a particular user. After combining different modalities, we created an effective strategy with a mean DI and EER of 2.41 and 5.21, respectively. A biometric system has been proposed.

Keywords: multimodal, fusion, palmprint, Iris, EER, DI

Procedia PDF Downloads 138

Authors: Qi Liu, Jiqin Yao, Xiaohu Zhou, Bo Zheng

Abstract:

The first artificial cell was produced by Thomas Chang in the 1950s when he was trying to make a mimic of red blood cells. Since then, many different types of artificial cells have been constructed from one of the two approaches: a so-called bottom-up approach, which aims to create a cell from scratch, and a top-down approach, in which genes are sequentially knocked out from organisms until only the minimal genome required for sustaining life remains. In this project, bottom-up approach was used to build a new cell-free expression system which mimics artificial cell that capable of protein expression and communicate with each other. The artificial cells constructed from the bottom-up approach are usually lipid vesicles, polymersomes, hydrogels or aqueous droplets containing the nucleic acids and transcription-translation machinery. However, lipid vesicles based artificial cells capable of communication present several issues in the cell communication research: (1) The lipid vesicles normally lose the important functions such as protein expression within a few hours. (2) The lipid membrane allows the permeation of only small molecules and limits the types of molecules that can be sensed and released to the surrounding environment for chemical communication; (3) The lipid vesicles are prone to rupture due to the imbalance of the osmotic pressure. To address these issues, the hydrogel-based artificial cells were constructed in this work. To construct the artificial cell, polyacrylamide hydrogel was functionalized with Acrylate PEG Succinimidyl Carboxymethyl Ester (ACLT-PEG2000-SCM) moiety on the polymer backbone. The proteinaceous factors can then be immobilized on the polymer backbone by the reaction between primary amines of proteins and N-hydroxysuccinimide esters (NHS esters) of ACLT-PEG2000-SCM, the plasmid template and ribosome were encapsulated inside the hydrogel particles. Because the artificial cell could continuously express protein with the supply of nutrients and energy, the artificial cell-artificial cell communication and artificial cell-natural cell communication could be achieved by combining the artificial cell vector with designed plasmids. The plasmids were designed referring to the quorum sensing (QS) system of bacteria, which largely relied on cognate acyl-homoserine lactone (AHL) / transcription pairs. In one communication pair, “sender” is the artificial cell or natural cell that can produce AHL signal molecule by synthesizing the corresponding signal synthase that catalyzed the conversion of S-adenosyl-L-methionine (SAM) into AHL, while the “receiver” is the artificial cell or natural cell that can sense the quorum sensing signaling molecule form “sender” and in turn express the gene of interest. In the experiment, GFP was first immobilized inside the hydrogel particle to prove that the functionalized hydrogel particles could be used for protein binding. After that, the successful communication between artificial cell-artificial cell and artificial cell-natural cell was demonstrated, the successful signal between artificial cell-artificial cell or artificial cell-natural cell could be observed by recording the fluorescence signal increase. The hydrogel-based artificial cell designed in this work can help to study the complex communication system in bacteria, it can also be further developed for therapeutic applications.

Keywords: artificial cell, cell-free system, gene circuit, synthetic biology

Procedia PDF Downloads 131

Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

Abstract:

Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

Procedia PDF Downloads 122

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha, Kamila Drzozga

Abstract:

Catecholamines are the principal neurotransmitters that mediate a variety of the central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, fluorescent techniques for detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid modified biosensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in the manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence sensing strategy for catecholamines detection based on FRET (fluorescence resonance energy transfer) phenomena observed for, i.e., complexes of Fe²⁺ and epinephrine. The biosensor was constructed using low temperature co-fired ceramics technology (LTCC). This sensing system used the catalytical oxidation of catecholamines and quench of the strong luminescence of obtained complexes due to FRET. The detection process was based on the oxidation of substrate in the presence of the enzyme–laccase/tyrosinase.

Keywords: biosensor, conducting polymer, enzyme, FRET, LTCC

Procedia PDF Downloads 247

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

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

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

Procedia PDF Downloads 121

Authors: Nuno Biga

Abstract:

Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

Procedia PDF Downloads 89

Authors: P. Weerkamp Bartholomeus

Abstract:

Autism treatment evaluation is crucial for monitoring the development of an intervention at an early stage. ‘ReAttach’ is a new intervention based on the principles of attachment and social cognitive training. Practical research suggests promising results on a variety of developmental areas. Five years after the first ReAttach sessions these findings can be extended with qualitative research by means of follow-up interviews. The potential impact of this treatment on daily life functioning and well-being of autistic persons becomes clear.

Keywords: autism, innovation, treatment, social cognitive training

Procedia PDF Downloads 273

Authors: April Love Palad, Charita B. Lasala

Abstract:

Mastery on English language is one of the important goals of all English language teachers. This goal can be seen based from the students’ actual performance using the target language which is English. Learning the English language includes hard work where efforts need to be exerted and this can be attained gradually over a long period of time. It is extremely important for all English language teachers to know the effects of incorporating games in teaching. Whether this strategy can have positive or negative effects in students learning, teachers should always consider what is best for their learners. Games may help and provide confidents language learners. These games help teachers to create context in which the language is suitable and significant. Focusing in accuracy and fluency is the heart of this study and this will be obtain in either teaching English using the traditional method or teaching English using language games. It is very important for all English teachers to know which strategy is effective in teaching English to be able to cope with students’ underachievement in this subject. This study made use of the comparative-experimental method. It made use of the pre-post test design with the aim to explore the effectiveness of the language games as strategy used in language teaching for high school students. There were two groups of students being observed, the controlled and the experimental, employing the two strategies in teaching English –traditional and with the use of language games. The scores obtained by two samples were compared to know the effectiveness of the two strategies in teaching English. In this study, it found out that language games help improve students’ fluency and accuracy in the use of target language and this is very evident in the results obtained in the pre-test and post –test result as well the mean gain scores by the two groups of students. In addition, this study also gives us a clear view on the positive effects on the use of language games in teaching which also supported by the related studies based from this research. The findings of the study served as the bases for the creation of the proposed learning plan that integrated language games that teachers may use in their own teaching. This study further concluded that language games are effective in developing students’ fluency in using the English language. This justifies that games help encourage students to learn and be entertained at the same time. Aside from that, games also promote developing language competency. This study will be very useful to teachers who are in doubt in the use of this strategy in their teaching.

Keywords: language games, experimental, comparative, strategy, language teaching, methodology

Procedia PDF Downloads 402

Authors: Ichiro Takahashi

Abstract:

One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

Procedia PDF Downloads 151

Authors: Yasin Polat, Yılmaz Dağdemir, Mehmet Arı

Abstract:

Samarium (III) oxide and Ytterbium (III) oxide doped Bismuth trioxide solid solutions, the nano ceramic (Bi2O3)1-x-y(Sm2O3)x(Yb2O3)y ternary system were obtained with x=5, 20 mol %, and y=5, 20 mol % dopant concentrations have been synthesized in air atmosphere with solid state reaction. Temperature dependent electrical conductivity of the samples have been investigated by 4-point probe technique by heating and cooling process. Doped-Bi2O3 materials of solid electrolyte systems are good oxygen anions O2-conductors which have collected much attention as potential solid ceramic electrolytes for solid oxide fuel cells (SOFCs) because of their relatively high oxygen ionic conductivity at lower temperatures.(Bi2O3)-based electrolytes have also wide other technological applications in devices with high economical interest such as oxygen sensors, ceramic membranes for oxygen separation, oxygen pumps, catalyzing of some heterogeneous reactions, partial oxidation of the hydrocarbons, and additive material in paints. In recent years, many experimental researches have mostly focused on improving of the Bi-based electrolytes which have high oxide ionic conductivity at low temperatures and better performance as alternatives to traditional stabilized zirconia has taken place. Generally, these systems are much better solid electrolytes than well-known stabilized zirconia, because some of the bismuth trioxide phases exhibit higher ion conductivity than other oxide ionic conductors. Crystal structure of the Nano ceramic (Bi2O3)1-x-y(Sm2O3)x(Yb2O3)y has been determined by X-Ray powder diffractions (XRD) measurements before and after electrical conductivity measurements of the samples. Surface and grain structure properties of the samples were determined by SEM analysis. The samples which synthesized in this study can be used in industrial applications such as electrolytes of the solid oxide fuel cells (SOFC).

Keywords: 4-point probe technique, bismuth trioxide, solid state reaction, solid oxide fuel cell

Procedia PDF Downloads 281

Authors: Thiago Brito Bezerra

Abstract:

This paper presents a novel approach to reduce power consumption of digital filters based on dynamic bypassing of partial products in their multipliers. The bypassing elements incorporated into the multiplier hardware eliminate redundant signal transitions, which appear within the carry-save adders when the partial product is zero. This technique reduces the power consumption by around 20%. The circuit implementation was made using the AMS 0.18 um technology. The bypassing technique applied to the circuits is outlined.

Keywords: digital filter, low-power, bypassing technique, low-pass filter

Procedia PDF Downloads 363