Search results for: Support Vector Machines (SVMs)

Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 164

Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

Procedia PDF Downloads 416

Authors: Setareh Shayanfar

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Given the increasing importance of peer relationships during adolescence, the present study aimed to examine peer interactions that facilitate or hinder adolescents’ regulation of negative emotions. Using the Enhanced Critical Incident Technique, 1-hour semi-structured interviews were conducted with 16 junior high school adolescents. Participants were asked to recall situations when they experienced strong negative emotions during the past school year, indicate the peer interactions that helped or hindered their emotion regulation, and identify prospective interactions with the potential to help regulate their emotions. Data analysis extracted 182 critical incidents, including 109 helping incidents, 45 hindering incidents, and 28 wish list items, which generated 10 categories nested within four overarching themes: Positive Personal Support included (a) supportive presence, (b) expressing concern, (c) empathizing, and (d) encouraging and cheering up; while Strategy Transmission included (e) sharing perspective, and (f) giving advice; Activated Support included (g) taking action, and (h) distracting; while Negative Personal Interactions included (i) withdrawing and (j) punishing. Implications for mental health and service providers, as well as recommendations for future research, are presented.

Keywords: adolescence, emotion regulation, enhanced critical incident technique, peers

Procedia PDF Downloads 127

Authors: Isao Tomita

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Electrical conduction in a quasi-one-dimensional polycrystalline metallic ring with a long electron phase coherence length realized at low temperature is investigated. In this situation, the wave nature of electrons is important in the ring, where the electrical current I can be induced by a vector potential that arises from a static magnetic field applied perpendicularly to the ring’s area. It is shown that if the average grain size of the polycrystalline ring becomes large (or comparable to the Fermi wavelength), the electrical current I increases to ~I0, where I0 is a current in a disorder-free ring. The cause of this increasing effect is examined, and this takes place if the electron localization length in the polycrystalline potential increases with increasing grain size, which gives rise to coherent connection of tails of a localized electron wave function in the ring and thus provides highly coherent electrical conduction.

Keywords: electrical conduction, electron phase coherence, polycrystalline metal, magnetic field

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

Procedia PDF Downloads 345

Authors: M. Al-Farttoosi, M. Y. Rafiq, J. Summerscales, C. Williams

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Structures can be subjected to impact loading from various sources like earthquake, tsunami, missiles and explosions. The impact loading can cause different degrees of damage to concrete structures. The demand for strengthening and rehabilitation of damaged structures is increasing. In recent years, Car0bon Fibre Reinforced Polymer (CFRP) matrix composites has gain more attention for strengthening and repairing these structures. To study the impact behaviour of the reinforced concrete (RC) beams strengthened or repaired using CFRP, a heavy impact test machine was designed and manufactured .The machine included a newly designed support system for beams together with various instrumentation. This paper describes the support design configuration of the impact test machine, instrumentation and dynamic analysis of the concrete beams. To evaluate the efficiency of the new impact test machine, experimental impact tests were conducted on simple supported reinforced concrete beam. Different methods were used to determine the impact force and impact response of the RC beams in terms of inertia force, maximum deflection, reaction force and fracture energy. The manufactured impact test machine was successfully used in testing RC beams under impact loading and used successfully to test the reinforced concrete beams strengthened or repaired using CFRP under impact loading.

Keywords: beam, concrete, impact, machine

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Authors: A. Alseiari, P. Farrell

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Maintenance has evolved into an imperative function, and contributes significantly to efficient and effective equipment performance. Total Productive Maintenance (TPM) is an ideal approach to support the development and implementation of operation performance improvement. It systematically aims to understand the function of equipment, the service quality relationship with equipment and the probable critical equipment failure conditions. Implementation of TPM programmes need strategic planning and there has been little research applied in this area within Middle-East power plants. In the power sector of Abu Dhabi, technologically and strategically, the power industry is extremely important, and it thus needs effective and efficient equipment management support. The aim of this paper is to investigate barriers to successful TPM implementation in the Abu Dhabi power industry. The study has been conducted in the context of a leading power company in the UAE. Semi-structured interviews were conducted with 16 employees, including maintenance and operation staff, and senior managers. The findings of this research identified seven key barriers, thus: managerial; organisational; cultural; financial; educational; communications; and auditing. With respect to the understanding of these barriers and obstacles in TPM implementation, the findings can contribute towards improved equipment operations and maintenance in power organisations.

Keywords: Abu Dhabi Power Industry, TPM implementation, key barriers, organisational culture, critical success factors

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Authors: Grace Baptie, Jackie Andrade, Alison Bacon, Alyson Norman

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Background: Many women experience their childbirth as traumatic, and 4-6% of mothers present with postnatal posttraumatic stress disorder (PTSD) as a result of their birth. Aims: To measure the relationship between obstetric and subjective experience of childbirth on mothers’ experience of postnatal trauma and identify salient aspects of the birth experience considered traumatic. Methods: Women who had given birth within the last year completed an online mixed-methods survey reporting on their subjective and obstetric birth experience as well as symptoms of postnatal trauma, depression and anxiety. Findings: 29% of mothers experienced their labour as traumatic and 15% met full or partial criteria for PTSD. Feeling supported and in control mediated the relationship between obstetric intervention and postnatal trauma symptoms. Five key themes were identified from the qualitative data regarding aspects of the birth considered traumatic including: obstetric complications; lack of control; concern for baby; psychological trauma and lack of support. Conclusion: Subjective birth experience is a significantly stronger predictor of postnatal trauma than level of medical intervention, the psychological consequences of which can be buffered by an increased level of support and control.

Keywords: birth trauma, perinatal mental health, postnatal PTSD, subjective experience

Procedia PDF Downloads 134

Authors: P. Aarumugam, N. Krishnamoorthy, K. Gunasekaran

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The mosquitoes with loss of minimum three legs especially the hind legs have the negative impact on the survival hood of mosquitoes. Three days old unfed adult female laboratory strain was selected in each generation against sublethal dosages (0.004%, 0.005%, 0.007% and 0.01%) of deltamethrin upto 40 generations. Impregnated papers with acetone were used for control. Every fourth generation, survived mosquitoes were observed for functional mortality. Hind legs lost were significantly (P< 0.05) higher in treated than the controls up to generation 24, thereafter no significant lost. In contrary, no significant forelegs lost among exposed mosquitoes. Middle legs lost were also not significant in the exposed mosquitoes except first generation (F1). The field strain (Chennai) did not show any significant loss of legs (fore or mid or hind) compared to the control. The selection pressure on mosquito population influences strong natural selection to develop various adaptive mechanisms.

Keywords: Anopheles stephensi, deltamethrin, functional mortality, synthetic pyrethroids

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Authors: Wei Quan, Liu Chao, Mohammed N. Afsar

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The dielectric properties and ionic conductivity of novel "ceramic state" polymer electrolytes for high capacity lithium battery are characterized by radio-frequency and Microwave methods in two broad frequency ranges from 50 Hz to 20 KHz and 4 GHz to 40 GHz. This innovative solid polymer electrolyte which is highly ionic conductive (10-3 S/cm at room temperature) from -40 oC to +150 oC and can be used in any battery application. Such polymer exhibits properties more like a ceramic rather than polymer. The various applied measurement methods produced accurate dielectric results for comprehensive analysis of electrochemical properties and ion transportation mechanism of this newly invented polymer electrolyte. Two techniques and instruments employing air gap measurement by capacitance bridge and inwave guide measurement by vector network analyzer are applied to measure the complex dielectric spectra. The complex dielectric spectra are used to determine the complex alternating current electrical conductivity and thus the ionic conductivity.

Keywords: polymer electrolyte, dielectric permittivity, lithium battery, ionic relaxation, microwave measurement

Procedia PDF Downloads 462

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Farhia Hassan Mohamed

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This study examined the macroeconomic factors that affect the inflation Rate in Somalia using quarterly time series data from 1991q1 to 2017q4 retired from World Development Indicators and SESRIC. It employed the vector error correction model (VECM) and Granger Causality method to measure the long-run and short-run causality of the GDP, inflation exchange rate, and unemployment. The study confirmed that there is one cointegration equation between GDP, exchange rate, inflation, and unemployment in Somalia. However, the VECM model's result indicates a long-run relationship among variables. The VEC Granger causality/Block Exogeneity Wald test result confirmed that all covariates are statistically significant at 5% and are Granger's cause of inflation in the short term. Finally, the impulse response result showed that inflation responds negatively to the shocks from the exchange rate and unemployment rate and positively to GDP and itself. Drawing from the empirical findings, the study makes several policy recommendations for both the monetary and Government sides.

Keywords: CPI, OP, exchange rate, inflation ADF, Johansen, PP, VECM, impulse, ECT

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Authors: Serge Provost, Yishan Zang

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Copulas are currently utilized in finance, reliability theory, machine learning, signal processing, geodesy, hydrology and biostatistics, among several other fields of scientific investigation. It follows from Sklar's theorem that the joint distribution function of a multidimensional random vector can be expressed in terms of its associated copula and marginals. Since marginal distributions can easily be determined by making use of a variety of techniques, we address the problem of securing the distribution of the copula. This will be done by using several approaches. For example, we will obtain bivariate least-squares approximations of the empirical copulas, modify the kernel density estimation technique and propose a criterion for selecting appropriate bandwidths, differentiate linearized empirical copulas, secure Bernstein polynomial approximations of suitable degrees, and apply a corollary to Sklar's result. Illustrative examples involving actual observations will be presented. The proposed methodologies will as well be applied to a sample generated from a known copula distribution in order to validate their effectiveness.

Keywords: copulas, Bernstein polynomial approximation, least-squares polynomial approximation, kernel density estimation, density approximation

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Authors: Samira Ghizellaoui, Manel Boumagoura

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Calcium carbonate precipitation is a widespread problem, especially in hard water systems. The main water supply that supplies the city of Constantine with drinking water is underground water called Hamma water. This water has a very high hardness of around 590 mg/L CaCO₃. This leads to the formation of scale, consisting mainly of calcium carbonate, which can be responsible for the clogging of valves and the deterioration of equipment (water heaters, washing machines and encrustations in the pipes). Plant extracts used as scale inhibitors have attracted the attention of several researchers. In recent years, green inhibitors have attracted great interest because they are biodegradable, non-toxic and do not affect the environment. The aim of our work is to evaluate the effectiveness of a chemical antiscale treatment in the presence of three green inhibitors: gallicacid; quercetin; alginate, and three mixtures: (gallic acid-quercetin); (quercetin-alginate); (gallic acid-alginate). The results show that the inhibitory effect is manifested from an addition of 1mg/L of gallic acid, 10 mg/L of quercetin, 0.2 mg/L of alginate, 0.4mg/L of (gallic acid-quercetin), 2mg/L of (quercetin-alginate) and 0.4 mg/L of (gallic acid-alginate). On the other hand, 100 mg/L (Drinking water standard) of Ca2+is reached for partial softening at 4 mg/L of gallic acid, 40 mg/L of quercetin, 0.6mg/L of alginate, 4mg/L of (gallic acid-quercetin), 10mg/L of (quercetin-alginate) and 1.6 mg/L of (gallic acid-alginate).

Keywords: water, scaling, calcium carbonate, green inhibitor

Procedia PDF Downloads 54

Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

Procedia PDF Downloads 293

Authors: S. Belakry, D. Fasquelle, A. Rolle, E. Capoen, R. N. Vannier, J. C. Carru

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Solid oxide fuel cells (SOFCs) are promising devices for energy conversion due to their high electrical efficiency and eco-friendly behavior. Their performance is not only influenced by the microstructural and electrical properties of the electrodes and electrolyte but also depends on the interactions at the interfaces. Nowadays, commercial SOFCs are electrically efficient at high operating temperatures, typically between 800 and 1000 °C, which restricts their real-life applications. The present work deals with the objectives to reduce the operating temperature and to develop cost-effective intermediate-temperature solid oxide fuel cells (IT-SOFCs). This work focuses on the development of metal-supported solid oxide fuel cells (MS-IT-SOFCs) that would provide cheaper SOFC cells with increased lifetime and reduced operating temperature. In the framework, the local company TIBTECH brings its skills for the manufacturing of porous metal supports. This part of the work focuses on the physical, chemical, and electrical characterizations of porous metallic supports (stainless steel 316 L and FeCrAl alloy) under different exposure conditions of temperature and atmosphere by studying oxidation, mechanical resistance, and electrical conductivity of the materials. Within the target operating temperature (i.e., 500 to 700 ° C), the stainless steel 316 L and FeCrAl alloy slightly oxidize in the air and H2, but don’t deform; whereas under Ar atmosphere, they oxidize more than with previously mentioned atmospheres. Above 700 °C under air and Ar, the two metallic supports undergo high oxidation. From 500 to 700 °C, the resistivity of FeCrAl increases by 55%. But nevertheless, the FeCrAl resistivity increases more slowly than the stainless steel 316L resistivity. This study allows us to verify the compatibility of electrodes and electrolyte materials with metallic support at the operating requirements of the IT-SOFC cell. The characterizations made in this context will also allow us to choose the most suitable fabrication process for all functional layers in order to limit the oxidation of the metallic supports.

Keywords: stainless steel 316L, FeCrAl alloy, solid oxide fuel cells, porous metallic support

Procedia PDF Downloads 79

Authors: Y. O’Connor, C. Heavin, S. O’ Connor, J. Gallagher, J. Wu, J. O’Donoghue

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Background: To improve the delivery of paediatric healthcare in resource-poor settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (poor adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (Low cost Intervention For disEase control) as an exemplar. Results: A service blueprint is developed which illustrates how the eCCM solution can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users.

Keywords: adherence, community health workers, developing countries, mobile clinical decision support systems, CDSS, service blueprint

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Authors: Jenq-Shyong Chen, Ben-Fong Yu

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CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: E. M. Mhlongo, E. Lutge

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In 2010, South Africa’s National Department of Health (NDoH) launched national primary health care (PHC) initiative to strengthen health promotion, disease prevention, and early disease detection. The strategy, called Re-engineering Primary Health Care (rPHC), aims to support a preventive and health-promoting community-based PHC model by using community-based outreach teams (known in South Africa as Ward-based Primary Health Care Outreach teams or WBPHCOTs). These teams provide health education, promote healthy behaviors, assess community health needs, manage minor health problems, and support linkages to health services and health facilities. Ward based primary health care outreach teams are supervised by a professional nurse who is the outreach team leader. In South Africa, the WBPHCOTs have been established, registered, and are reporting their activities in the District Health Information System (DHIS). This study explored and described the challenges faced by outreach team leaders in supporting and supervising the WBPHCOTs. Qualitative data were obtained through interviews conducted with the outreach team leaders at a sub-district level. Thematic analysis of data was done. Findings revealed some challenges faced by team leaders in day to day execution of their duties. Issues such as staff shortages, inadequate resources to carry out health promotion activities, and lack of co-operation from team members may undermine the capacity of team leaders to support and supervise the WBPHCOTs. Many community members are under the impression that the outreach team is responsible for bringing the clinic to the community while the outreach teams do not carry any medication/treatment with them when doing home visits. The study further highlights issues around the challenges of WBPHCOTs at a household level. In conclusion, the WBPHCOTs are an important component of National Health Insurance (NHI), and in order for NHI to be optimally implemented, the issues raised in this research should be addressed with some urgency.

Keywords: community health worker, national health insurance, primary health care, ward-based primary health care outreach teams

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Authors: Magdalena Orth, Gunnar Gotz

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Background: Domestic accountability, budget transparency and public financial management (PFM) are considered vital components of good governance in developing countries. The aid modality budget support (BS) promotes these governance functions in developing countries. BS engages in political decision-making and provides financial and technical support to poverty reduction strategies of the partner countries. Nevertheless, many donors have withdrawn their support from this modality due to cases of corruption, fraud or human rights violations. This exit from BS is leaving a finance and governance vacuum in the countries. The evaluation team analyzed the consequences of terminating the use of this modality and found particularly negative effects for good governance outcomes. Methodology: The evaluation uses a qualitative (theory-based) approach consisting of a comparative case study design, which is complemented by a process-tracing approach. For the case studies, the team conducted over 100 semi-structured interviews in Malawi, Uganda, Rwanda and Zambia and used four country-specific, tailor-made budget analysis. In combination with a previous DEval evaluation synthesis on the effects of BS, the team was able to create a before-and-after comparison that yields causal effects. Main Findings: In all four countries domestic accountability and budget transparency declined if other forms of pressure are not replacing BS´s mutual accountability mechanisms. In Malawi a fraud scandal created pressure from the society and from donors so that accountability was improved. In the other countries, these pressure mechanisms were absent so that domestic accountability declined. BS enables donors to actively participate in political processes of the partner country as donors transfer funds into the treasury of the partner country and conduct a high-level political dialogue. The results confirm that the exit from BS created a governance vacuum that, if not compensated through external/internal pressure, leads to a deterioration of good governance. For example, in the case of highly aid dependent Malawi did the possibility of a relaunch of BS provide sufficient incentives to push for governance reforms. Overall the results show that the three good governance areas are negatively affected by the exit from BS. This stands in contrast to positive effects found before the exit. The team concludes that the relationship is causal, because the before-and-after comparison coherently shows that the presence of BS correlates with positive effects and the absence with negative effects. Conclusion: These findings strongly suggest that BS is an effective modality to promote governance and its abolishment is likely to cause governance disruptions. Donors and partner governments should find ways to re-engage in closely coordinated policy-based aid modalities. In addition, a coordinated and carefully managed exit-strategy should be in place before an exit from similar modalities is considered. Particularly a continued framework of mutual accountability and a high-level political dialogue should be aspired to maintain pressure and oversight that is required to achieve good governance.

Keywords: budget support, domestic accountability, public financial management and budget transparency, Sub-Sahara Africa

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Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, REVIVE team

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The environment of the mosquitoes complex Culex pipiens sl. in Portugal mainland is evaluated based in its abundance, using a data set georeferenced, collected during seven years (2006-2012) from May to October. The suitability of the different regions can be delineated using the relative abundance areas; the suitablility index is directly proportional to disease transmission risk and allows focusing mitigation measures in order to avoid outbreaks of vector-borne diseases. The interest in the Culex pipiens complex is justified by its medical importance: the females bite all warm-blooded vertebrates and are involved in the circulation of several arbovirus of concern to human health, like West Nile virus, iridoviruses, rheoviruses and parvoviruses. The abundance of Culex pipiens mosquitoes were documented systematically all over the territory by the local health services, in a long duration program running since 2006. The environmental factors used to characterize the vector habitat are land use/land cover, distance to cartographed water bodies, altitude and latitude. Focus will be on the mosquito females, which gonotrophic cycle mate-bloodmeal-oviposition is responsible for the virus transmission; its abundance is the key for the planning of non-aggressive prophylactic countermeasures that may eradicate the transmission risk and simultaneously avoid chemical ambient degradation. Meteorological parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures) and daily total rainfall were gathered from the weather stations network for the same dates and crossed with the standardized females’ abundance in a geographic information system (GIS). Mean capture and percentage of above average captures related to each variable are used as criteria to compute a threshold for each meteorological parameter; the difference of the mean capture above/below the threshold was statistically assessed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the meaningful thresholds for each parameter. The intersection of the maps of all the parameters obtained for each month show the evolution of the suitable meteorological conditions through the mosquito season, considered as May to October, although the first and last month are less relevant. In parallel, mean and above average captures were related to the physiographic parameters – the land use/land cover classes most relevant in each month, the altitudes preferred and the most frequent distance to water bodies, a factor closely related with the mosquito biology. The maps produced with these results were crossed with the meteorological maps previously segmented, in order to get an index of suitability for the complex Culex pipiens evaluated all over the country, and its evolution from the beginning to the end of the mosquitoes season.

Keywords: suitability index, Culex pipiens, habitat evolution, GIS model

Procedia PDF Downloads 566

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

Procedia PDF Downloads 221

Authors: Aram Yakoby, Yossef H. Hatzor, Shmulik Pinkert

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This work presents an applied engineering method for evaluating the stability of underground openings under conditions of uncertainty. The developed method is demonstrated by a comprehensive parametric study on a case of large-diameter vertical borehole stability analysis, with uncertainties regarding the in-situ stress distribution. To this aim, a safety factor analysis is performed for the stability of both supported and unsupported boreholes. In the analysis, we used analytic geomechanical calculations and advanced numerical modeling to evaluate the estimated stress field. In addition, the work presents the development of a boundary condition for the numerical model that fits the nature of the problem and yields excellent accuracy. The borehole stability analysis is studied in terms of (1) the stress ratio in the vertical and horizontal directions, (2) the mechanical properties and geometry of the support system, and (3) the parametric sensitivity. The method's results are studied in light of a real case study of an underground waste disposal site. The conclusions of this study focus on the developed method for capturing the parametric uncertainty, the definition of critical geological depths, the criteria for implementing structural support, and the effectiveness of further in-situ investigations.

Keywords: borehole stability, in-situ stress, parametric study, factor of safety

Procedia PDF Downloads 47

Authors: Rahul Saraswat

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More recently, a focus is given on replacing machined stainless steel metal flow-fields with inexpensive wiremesh current collectors. The flow-fields are based on simple woven wiremesh screens of various stainless steels, which are sandwiched between a thin metal plate of the same material to create a bipolar plate/flow-field configuration for use in a stack. Major advantages of using stainless steel wire screens include the elimination of expensive raw materials as well as machining and/or other special fabrication costs. Objective of the project is to improve the performance of the passive direct methanol fuel cell without increasing the cost of the cell and to make it as compact and light as possible. From the literature survey, it was found that very little is done in this direction & the following methodology was used. 1.) The passive DMFC cell can be made more compact, lighter and less costly by changing the material used in its construction. 2.) Controlling the fuel diffusion rate through the cell improves the performance of the cell. A passive liquid feed direct methanol fuel cell ( DMFC ) was fabricated using given MEA( Membrane Electrode Assembly ) and tested for different current collector structure. Mesh current collectors of different mesh densities, along with different support structures, were used, and the performance was found to be better. Methanol concentration was also varied. Optimisation of mesh size, support structure and fuel concentration was achieved. Cost analysis was also performed hereby. From the performance analysis study of DMFC, we can conclude with the following points : Area specific resistance (ASR) of wiremesh current collectors is lower than ASR of stainless steel current collectors. Also, the power produced by wiremesh current collectors is always more than that produced by stainless steel current collectors. Low or moderate methanol concentrations should be used for better and stable DMFC performance. Wiremesh is a good substitute of stainless steel for current collector plates of passive DMFC because of lower cost( by about 27 %), flexibility and light in weight characteristics of wiremesh.

Keywords: direct methanol fuel cell, membrane electrode assembly, mesh, mesh size, methanol concentration and support structure

Procedia PDF Downloads 57

Authors: Chathurika Sewwandi Kannangara, Jerome Carson

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The objective of this research is to identify strengths among the individuals with dyslexia and design a positive psychology intervention to support such individuals. Dyslexia is a combination of abilities and difficulties that affect the learning process in areas as such reading, spelling and writing. It is a persistent condition. The research aims to adapt positive psychology techniques to support individuals with dyslexia. Population of the research will be undergraduate and college level students with dyslexia. First phase of the study will be conducted on a sample of undergraduate and college level students with dyslexia in Bolton, UK. The concept of treatment in positive psychology is not only to fix the component just what is wrong, instead it is also to develop and construct on what is right in the individual. The first phase of the research aims to identify the signature strengths among the individuals with dyslexia using Interviews, Descriptions on personal experiences on ‘My life with Dyslexia’, and Values in Action (VIA) strength survey. In order to conduct the survey for individuals with dyslexia, the VIA survey has been hosted in a website which is solely developed in the form of dyslexia friendly context. Dyslexia friendly website for surveys had designed and developed following the British Dyslexia Association guidelines. The findings of the first phase would be utilized for the second phase of the research to develop the positive psychology intervention.

Keywords: dyslexia, signature strengths, positive psychology, qualitative study, learning difficulties

Procedia PDF Downloads 425

Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

Abstract:

Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

Procedia PDF Downloads 88

Authors: Emma Garcia-Meca, Jennifer Martinez-Ferrero, Camino Ramon Llorens

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This paper provides insights into how narcissistic Chief Executive Officers (CEOs) influence the presence of women in top management teams (TMT). We also study whether a CEO's power and gender and the gender diversity of the firm's board moderate the relationship between CEO narcissism and TMT gender diversity. Our results reveal that narcissistic CEOs are less likely to support women in TMTs, confirming that CEO personality traits influence team structure. Further results suggest that this aversion increases as the CEO's power grows when female representation on boards decreases and when the CEO is a woman. This paper integrates theories that use the social psychology and upper echelon theories, offering a greater understanding of how CEO personality traits influence the structure of firms. We also contribute to the knowledge about how different governance characteristics can moderate the influence of narcissistic CEOs on women in TMTs, highlighting the relevance of governance traits that increase the effect of narcissism. The results demonstrate different female behavior toward promoting TMT gender equality depending on the specific position of women in the firm's hierarchy and their psychological attributes. We find that women directors support social identity values, and narcissistic female CEOs act like queen bees.

Keywords: gender diversity, board, corporate governance, female CEO, management

Procedia PDF Downloads 106

Authors: Nweke Kingsley

Abstract:

From the times of ancient Greece to modern times, democratic elections have been associated with a higher number of participants. Sequel to this, politicians globally and incumbent governments appear concerned with understanding the personality traits that may assure them of unflinching support by electorates. The study examined how openness to experience predicted electoral behaviour among senior non-teaching employees of Nnamdi Azikiwe University Awka. One hundred and thirty-three non-teaching employees who volunteered were randomly selected for the study. Two instruments were used for data collection: The Electoral Behaviour Scale, and the Openness to Experience dimension of the Personality Trait Inventory. A correlational design was adopted for the study, and the data generated were statistically analyzed using Pearson Product Moment and linear regression statistics. Results revealed that Openness to Experience positively and significantly predicted Electoral Behaviour among senior non-teaching employees of Nnamdi Azikiwe University, Awka. It was recommended that politicians and stakeholders hold town hall meetings and seminars to increase awareness of the electoral perception of electorates with the Openness to Experience trait as this will increase their support and yield successive results during elections.

Keywords: electoral-behaviour, employees, non-teaching, openness-to-experience

Procedia PDF Downloads 36

Authors: J. K. Chawla, S. K. Jain, M. K. Mishra

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Ion-acoustic double layers have been studied in magnetized plasma. The modified Korteweg-de Vries (m-KdV) equation using reductive perturbation method is derived. It is found that for the selected set of parameters, the system supports rarefactive double layers depending upon the value of nonthermal parameters. It is also found that the magnetization affects only the width of the double layer. For a given set of parameter values, increases in the magnetization and the obliqueness angle (θ) between wave vector and magnetic field, affect the width of the double layers, however the amplitude of the double layers have no effect. An increase in the values of nonthermal parameter decreases the amplitude of the rarefactive double layer. The effect of the ion temperature ratio on the amplitude and width of the double layers are also discussed in detail.

Keywords: ion-acoustic double layers, magnetized electronegative plasma, reductive perturbation method, the modified Korteweg-de Vries (KdV) equation

Procedia PDF Downloads 594