Search results for: Noise Barriers

Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

Procedia PDF Downloads 148

Authors: Sibongiseni Peacock, Denver Naidoo, Sikhalazo Dube

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The study investigates the impact of the National Red Meat Development Programme on household food security in rural areas of uMzimkhulu. Self-administered questionnaires were employed to gather data from 77 smallholder beef farmers participating in the St. Paul feedlot project. Data analysis utilized the Household Food Insecurity Access Scale (HFIAS) developed by USAID to assess the household food security status of St. Paul feedlot beneficiaries, with descriptive statistics employed for result analysis. Findings indicate that the majority (80.50%) of beneficiaries experienced food insecurity, while (19.50%) were classified as food secure, with most participants falling within the category of moderate food insecurity. Food insecurity predominantly stemmed from challenges faced by farmers unable to sell their cattle or whose cattle were not market-ready due to bureaucratic obstacles hindering the programme. Farmers identified feed shortages as the primary constraint, resulting in missed income opportunities. These findings underscore the critical need to address feed challenges and bureaucratic barriers to enhance the efficacy of the National Red Meat Development Programme in promoting household food security in rural areas.

Keywords: National Red Meat Development, household food security, St. Paul feedlot, livestock, HFIAS

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Authors: Marc Gärtner, Monika Huesmann, Katharina Schiederig

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While workplace flexibility provides opportunities to better balance work and family care, careers in management are still predominantly based on physical presence, blurred boundaries and a culture of availability at the workplace. Thus, carers (mostly women) still experience disadvantages and stalled careers. In a multi-case study, funded by the German Federal Ministry of Education and Research, success factors and barriers of flexible work arrangements in five big organizations, including three of the largest German companies, have been identified. Using qualitative interview methods, the working models of 10 female and male users of flexible work arrangements like part time, home office and job sharing have been studied. The study group applied a 360-degree approach with focus groups, covering the users’ themselves, their superiors, colleagues and staff as well as in-house human resource managers. The group interviews reveal that success of flexible models is mainly built on three factors: (a) the inclusiveness of the organizational culture, (b) the commitment of leaders and especially the supervisors, and (c) the fitting of the model and the user(s). Flexibilization of time and space can indeed contribute to a better work-life balance. This is, however, not a necessary outcome, as the interviews suggest, but depends on the right implementation of the right model in the particular work environment. Beyond the actual study results, the presentation will also assess the methodological approach.

Keywords: flexible work, leadership, organizational culture, work-life balance

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Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

Procedia PDF Downloads 155

Authors: Wenwen Lei, David R. Mckenzie

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Recent findings of anomalously high gas flow rates in carbon nanotubes show smooth hydrophobic walls can increase specular reflection of molecules and reduce the tangential momentum accommodation coefficient (TMAC). Here we report the first measurements of water vapor flows in microtubes over a wide humidity range and show that for hydrophobic silica there is a range of humidity over which an adsorbed water layer reduces TMAC and accelerates flow. Our results show that this association between hydrophobicity and accelerated moisture flow occurs in readily available materials. We develop a hierarchical theory that unifies Maxwell’s ideas on TMAC with Langmuir’s ideas on adsorption. We fit the TMAC data as a function of humidity with the hierarchical theory based on two stages of Langmuir adsorption and derive total adsorption isotherms for water on hydrophobic silica that agree with direct observations. We propose structures for each stage of the water adsorption, the first reducing TMAC by a passivation of adsorptive patches and a smoothing of the surface, the second resembling bulk water with large TMAC. We find that leak testing of moisture barriers with an ideal gas such as helium may not be accurate enough for critical applications and that direct measurements of the water leak rate should be made.

Keywords: water vapor flows, silica microtubes, TMAC, enhanced flow rates

Procedia PDF Downloads 252

Authors: Przewodowski Włodzimierz, Przewodowska Agnieszka, Sekrecka Danuta, Michałowska Dorota

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Colloidal metal nanoparticles are widely applied in various areas and have great potential in different biotechnological applications. Their particular properties associated with both the antiseptic, antioxidant and anti aging properties as well as ability to penetrate most of the biological barriers, synergy in the absorption of nutrients and nontoxic to plants. The properties make them potentially useful in the fast and safe production of healthy, certified starting material in the production of plants exposed to many pathogenic microorganisms causing serious diseases, significantly affecting yield and causing the economic losses. In this case it is crucial to provide appropriate conditions for the production, storage and distribution of the plant material. Therefore, the aim of the proposed research was to develop and identify the influence of four colloidal metal nanoparticles on growth and proliferation of in vitro cultures of potato (Solanum tuberosum) - one of the most economically important strategic crops in the world. The research on different varieties of potato was performed by placing the explants of the in vitro cultures on sterile Murashige and Skoog (MS) type medium. The influence of the nanocolloids was evaluated using the MS medium impregnated with the examinated nanoparticles. The vigour of growth and the rate of proliferation was examinated for 6-8 weeks with both night/day-length and temperature over the ranges 8/16 h and 20–22 °C respectively. The results of our preliminary work confirmed high usefulness of the nanocolloids in the safe production of the examinated in vitro cultures.

Keywords: colloidal metal nanoparticles, in vitro cultures, potato, propagation

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Authors: Vrajesh Chokshi

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In last three decades, the global economy is substantially changed. Today, we are living in highly inter-connected world. The global markets are more open and consumers are well informed about products and services. The information technology revolution has broken all barriers in global business. The E-commerce has given opportunities of global trades to corporate. The IT is extensively used in almost all industries. After liberalization in 1992, the Indian economy is also significantly changed. The IT (information technology) and ITES (IT enable services) are extensively used in supply chain management. In India, previously car rental service business was dominated by local organization and operated through local contact. This industry is very lucrative and to catch this opportunity, many new corporate have ventured into e-commerce car rental service business in India. As the market is very competitive, branding is also very important part of marketing strategy. Now, the E-commerce portals those are in car rental business in India have realized the importance of the same and have started usage of all types of communication channel to promote their brand in different Indian markets. At consumer side, the awareness is also being considerably increased due to marketing communication campaign run by these companies. This paper aims to understand effectiveness of branding strategies in car rental business in India and also tries to identify unique promotional strategies to consolidate brand image of this business in different Indian markets.

Keywords: branding strategies, car rental business, CRM (customer relationship management), ITES (information technology enabled services)

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Authors: Arka Roy, Chandra Prakash Dubey

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Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

Procedia PDF Downloads 193

Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Stephanie Giordano, Eric Lam, Rosa Plasencia

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An important piece of active aging is ensuring people have the right support to meet individual needs. Using NCI-AD data, we will look at measures of satisfaction with community access and needed services among people with physical disabilities receiving LTSS in the US. National Core Indicators—Aging and Disabilities (NCI-AD) is a voluntary effort by State Medicaid, aging, and disability agencies across the US to measure and track their own performance. NCI-AD uses a standardized survey – the Adult Consumer Survey (ACS), to hear directly from people receiving services about the quality of services and supports they receive. Data from the 2018-19 ACS found that compared to people without a physical disability, those with a physical disability were more likely to make choices about the services they receive, including when and how often they receive those services. Yet people with a physical disability were less likely to report they get enough assistance with everyday activities (e.g., shopping, housework, and taking medications) and self-care (e.g., dressing or bathing) and more likely to report that services and supports do not fully meet their needs and goals. A further breakdown by age shows that people 40-65 years old with a physical disability experienced even greater barriers to being as active in the community as they would like to be, indicating a need to better support people as they age with or into a disability. We will explore how these and other outcomes were affected by COVID-19, take a closer look at outcomes by demographics (e.g., race/ethnicity, gender, and mental health diagnoses) and discuss implications on the future needs of service systems.

Keywords: quality-of-life, long-term services and supports, person-centered, community

Procedia PDF Downloads 90

Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

Procedia PDF Downloads 159

Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: E. Kharaishvili, G. Erkomaishvili, M. Chavleishvili

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The paper evaluates the natural and resource potential of agriculture, a traditional sector for Georgia. It is concluded that despite favorable conditions the rate of development of the sector is lower compared to other sectors of the economy, self-sufficiency rate for locally produced agricultural products is low; on average, import of food is 4 times higher compared to export, and the country faces considerable challenges in this regard. Tendencies of self-sufficiency rates are studied, and it is concluded that the indicators of export and import of agro-food products increase in accordance with the tendency of increasing production in agricultural sector. The paper substantiates stimulating impact of international trade on agricultural development. Two alternative strategies are assessed in this respect: 1) export stimulation, and 2) import replacement strategies. It is concluded that significant tendencies are observed in agro-food sector of Georgia; in particular, productivity is low; import volume significantly exceeds the export volume. It is considered that the growth of export will allow Georgia to overcome limited opportunities of local market and encourage increasing competitiveness. Various tools of economic policy are suggested for achieving these goals; in particular to subsidize export, optimize trade barriers, manage exchange rates effectively, offer special financial services, provide insurance for export, etc.

Keywords: agro-food sector, trend of production, export stimulation, economic policy

Procedia PDF Downloads 184

Authors: B. Van Kessel, P. T. Kockelkorn, T. R. Speelman, T. C. Wierikx, C. Mai Van, T. A. Bogaard

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Saltwater intrusion is a common problem in estuaries around the world, as it could hinder the freshwater supply of coastal zones. This problem is likely to grow due to climate change and sea-level rise. The influence of these factors on the saltwater intrusion was investigated for the Cai River in the Khanh Hoa province in Vietnam. In addition, the Cai River has high seasonal fluctuations in discharge, leading to increased saltwater intrusion during the dry season. Sea level rise, river discharge changes, river mouth widening and a proposed saltwater intrusion prevention dam can have influences on the saltwater intrusion but have not been quantified for the Cai River estuary. This research used both an analytical and numerical model to investigate the effect of the aforementioned factors. The analytical model was based on a model proposed by Savenije and was calibrated using limited in situ data. The numerical model was a 3D hydrodynamic model made using the Delft3D4 software. The analytical model and numerical model agreed with in situ data, mostly for tidally average data. Both models indicated a roughly similar dependence on discharge, also agreeing that this parameter had the most severe influence on the modeled saltwater intrusion. Especially for discharges below 10 m/s3, the saltwater was predicted to reach further than 10 km. In the models, both sea-level rise and river widening mainly resulted in salinity increments up to 3 kg/m3 in the middle part of the river. The predicted sea-level rise in 2070 was simulated to lead to an increase of 0.5 km in saltwater intrusion length. Furthermore, the effect of the saltwater intrusion dam seemed significant in the model used, but only for the highest position of the gate.

Keywords: Cai River, hydraulic models, river discharge, saltwater intrusion, tidal barriers

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Authors: Kawser Ahmed, K. Bousson, Milca F. Coelho

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4D flight trajectory optimization is one of the key ingredients to improve flight efficiency and to enhance the air traffic capacity in the current air traffic management (ATM). The present paper explores the iterative dynamic programming (IDP) as a potential numerical optimization method for 4D flight trajectory optimization. IDP is an iterative version of the Dynamic programming (DP) method. Due to the numerical framework, DP is very suitable to deal with nonlinear discrete dynamic systems. The 4D waypoint representation of the flight trajectory is similar to the discretization by a grid system; thus DP is a natural method to deal with the 4D flight trajectory optimization. However, the computational time and space complexity demanded by the DP is enormous due to the immense number of grid points required to find the optimum, which prevents the use of the DP in many practical high dimension problems. On the other hand, the IDP has shown potentials to deal successfully with high dimension optimal control problems even with a few numbers of grid points at each stage, which reduces the computational effort over the traditional DP approach. Although the IDP has been applied successfully in chemical engineering problems, IDP is yet to be validated in 4D flight trajectory optimization problems. In this paper, the IDP has been successfully used to generate minimum length 4D optimal trajectory avoiding any obstacle in its path, such as a no-fly zone or residential areas when flying in low altitude to reduce noise pollution.

Keywords: 4D waypoint navigation, iterative dynamic programming, obstacle avoidance, trajectory optimization

Procedia PDF Downloads 142

Authors: Dina Zakeri, Ali Aminzad

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Multimedia-assisted teaching results in eliminating traditional training barriers, facilitating the cognition process and upgrading learning outcomes. This study attempted to examine the effects of implementing multimedia on teaching technical translation model and on the technical text translation ability of Iranian students of translation. To fulfill the purpose of the study, a total of forty-six learners were selected out of fifty-seven participants in a higher education center in Tehran based on their scores in Preliminary English Test (PET) and were divided randomly into the experimental and control groups. Prior to the treatment, a technical text translation questionnaire was devised and then approved and validated by three assistant professors of technical fields and three assistant professors of Teaching English as a Foreign Language (TEFL) at the university. This questionnaire was administered as a pretest to both groups. Control and experimental groups were trained for five successive weeks using identical course books but with a different lesson plan that allowed employing multimedia for the experimental group only. The devised and approved questionnaire was administered as a posttest to both groups at the end of the instruction. A multivariate ANOVA was run to compare the two groups’ means on the PET, pretest and posttest. The results showed the rejection of all null hypotheses of the study and revealed that multimedia significantly improved technical text translation ability of the learners.

Keywords: multimedia, multimedia-mediated teaching, technical translation model, technical text, translation ability

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Authors: Hamid Sharif, Nazish Saleem Abbas, Muhammad Haris Jamil

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An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal. Because of the complexity of the optimization algorithms, most adaptive filters are digital filters. Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications, including adaptive noise cancellation and echo cancellation. Acoustic echo cancellation is a common occurrence in today’s telecommunication systems. The signal interference caused by acoustic echo is distracting to both users and causes a reduction in the quality of the communication. In this paper, we review different techniques of adaptive filtering to reduce this unwanted echo. In this paper, we see the behavior of techniques and algorithms of adaptive filtering like Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Variable Step-Size Least Mean Square (VSLMS), Variable Step-Size Normalized Least Mean Square (VSNLMS), New Varying Step Size LMS Algorithm (NVSSLMS) and Recursive Least Square (RLS) algorithms to reduce this unwanted echo, to increase communication quality.

Keywords: adaptive acoustic, echo cancellation, LMS algorithm, adaptive filter, normalized least mean square (NLMS), variable step-size least mean square (VSLMS)

Procedia PDF Downloads 64

Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: M. Solairaju, Nithin J. Thomas, S. Ganesan

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Each and every rotating part of a machine element consists of bearings within its structure. In particular, the rolling element bearings such as cylindrical roller bearing and deep groove ball bearings are frequently used. Improper handling, excessive loading, improper lubrication and sealing cause bearing damage. Hence health monitoring of bearings is an important aspect for radiation pattern of bearing vibration is computed using the dipole model. Sound pressure level for defect-free and race defect the prolonged life of machinery and auto motives. This paper presents modeling and analysis of Acoustic response of deep groove ball bearing with localized race defects. Most of the ball bearings, especially in machine tool spindles and high-speed applications are pre-loaded along an axial direction. The present study is carried out with axial preload. Based on the vibration response, the orbit motion of the inner race is studied, and it was found that the oscillation takes place predominantly in the axial direction. Simplified acoustic is estimated. Acoustic response shows a better indication in identifying the defective bearing. The computed sound signal is visualized in diagrammatic representation using Symmetrised Dot Pattern (SDP). SDP gives better visual distinction between the defective and defect-free bearing

Keywords: bearing, dipole, noise, sound

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Authors: Bishwa Nath Oli

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Nepal is highly impacted by climate change and adaptation has been a major focus. This paper investigates the gaps and coherence in national policies across water, forestry, local development and agriculture sectors, identifies their links to climate change adaptation and national development plans and analyzes the effectiveness of climate change policy on adaptation. The study was based on a content analysis of relevant policy documents on the level of attention given to adaptation and key informant interviews. Findings show that sectoral policies have differing degrees of cross thematic coherence, often with mismatched priorities and differing the paths towards achieving climate change goal. They are somewhat coherent in addressing immediate disaster management issues rather than in climate adaptation. In some cases, they are too broad and complicated and the implementation suffers from barriers and limits due to lack of capacity, investment, research and knowledge needed for evidence-based policy process. They do not adequately provide operational guidance in supporting communities in adapting to climate change. The study recommends to a) embrace longer-term cross-sectoral planning within government structures to foster greater policy coherence and integrated adaptation planning, b) increase awareness and flow of information on the potential role of communities in climate change, c) review the existing development sectors from the climate change perspectives, and d) formulate a comprehensive climate change legislation based on the need to implement the new Constitution.

Keywords: agriculture, climate change adaptation, forestry, policies

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Authors: Iyabo Aremu

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The role of the teacher in stirring a qualitative and distinctive knowledge-driven and value-laden environment with modern teaching practices cannot be over accentuated. In spite of the myriad advantages the use of Information and Communication Technology (ICT) promises, many teachers are still at the rear of this archetypical transition. These teachers; notable forces needed to elicit positive academic performances of students of higher learning are ill-equipped for the task. In view of this, the research work sought to assess how teachers have been able to effectively apply ICT tools to improve students’ academic performance in the higher institution and to evaluate the challenges faced by teachers in using these tools. Thus, the research adopted descriptive survey research design and involved a sample of 25 lecturers from five schools in the study area: Adeniran Ogunsanya College of Education (AOCOED). The barrier to Teachers’ Use of ICT Questionnaire (BTUICTQ) was used to gather data from these respondents. The data gathered was tested with chi-square at 0.05 level of significance. The results revealed that the perception and attitude of teachers towards the use of ICT is not favourable. It was also discovered that teachers suffer from gaps in ICT knowledge and skills. Finally, the research showed that lack of training and inadequate support is a major challenge teacher contend with. The study recommended that teachers should be given adequate training and support and that teachers’ unrestricted access to ICT gadgets should be ensured by schools.

Keywords: ICT, teachers, AOCOED, academic performance

Procedia PDF Downloads 142

Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Samuel Matylewicz, K. W. Goossen

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The deployment of white or cool (high albedo) roofing is a common energy savings recommendation for a variety of buildings all over the world. Here, the effect of a white roof on the energy savings of an ice rink facility in the northeastern US is determined by measuring the effect of solar irradiance on the consumption of the rink's ice refrigeration system. The consumption of the refrigeration system was logged over a year, along with multiple weather vectors, and a statistical model was applied. The experimental model indicates that the expected savings of replacing the existing grey roof with a white roof on the consumption of the refrigeration system is only 4.7 %. This overall result of the statistical model is confirmed with isolated instances of otherwise similar weather days, but cloudy vs. sunny, where there was no measurable difference in refrigeration consumption up to the noise in the local data, which was a few percent. This compares with a simple theoretical calculation that indicates 30% savings. The difference is attributed to a lack of convective cooling of the roof in the theoretical model. The best experimental model shows a relative effect of the weather vectors dry bulb temperature, solar irradiance, wind speed, and relative humidity on refrigeration consumption of 1, 0.026, 0.163, and -0.056, respectively. This result can have an impact on decisions to apply white roofing to refrigerated buildings in general.

Keywords: cool roofs, solar cooling load, refrigerated buildings, energy-efficient building envelopes

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Caroline Hoorn

Abstract:

Post-matriculants in disadvantaged communities such as Douglas encounter a number of career challenges. The transition to the democratic dispensation in 1994, coupled with the rapid changes in the information domain that are characteristic of post-industrial life, complicate the career development trajectories of disadvantaged youth. The career development stories and experiences of disadvantaged youth in provinces such as the Northern Cape have not been told, leading to their marginalisation. It is against this background that the study explored the gendered dimensions of career development narratives, experiences, and choices of post-matriculants in the Douglas community in the Northern Cape. Using a qualitative, narrative approach, the researcher elicited career development stories from 23 participants in Douglas using semi-structured interviews. Two main themes were highlighted through the narratives; (1) willingness to challenge the traditional male dominated career script (2) breaking gender barriers. The study showed that gender did not have any influence on the career choices of the post-matriculants. The perceptions around career choices and gender were being challenged partly by the urge to affirm equality and the constant reminder of the poverty-stricken conditions prevalent in the households. A preferred gender is not required to be attached to the fulfilment of outcomes in a knowledge-based economy. Thus, it is not an issue of gender or masculinity but knowledge and skills. Furthermore, the study revealed that the career choices being considered are still the traditionally stereotypical careers like nursing, teaching, and social work, which demonstrates a lack of information to a broader pool of career options to select from.

Keywords: career development, gender, narratives, post-matriculants

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Authors: Joseph C. Chen, Joshua Cox

Abstract:

This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L₁₈ Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi Parameter Design, surface roughness, Wire EDM, dimensional accuracy

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Authors: Mai Yen Nhi Doan, Viet Le, Chamindika Weerakoon

Abstract:

Social enterprises have emerged as sustainable organisations that deliver social achievement along with long-term financial advancement. However, recorded financial barriers have urged social enterprises to divert to other financing methods due to the misaligned ideology with traditional financing capitalists, in which crowdfunding can be a promising alternative. Previous studies in crowdfunding have inadequately addressed crowdfunding for social enterprises, with conflicting results due to the unsuitable analysis of signals in isolation rather than in combinations, using the data from platforms that do not support social enterprises. Extending the signalling theory, this study suggests that crowdfunding success results from the collaboration between costly and costless signals. The proposed conceptual framework enlightens the interaction between costly signals as “organisational information”, “social entrepreneur’s credibility,” and “third-party endorsement” and costless signals as various sub-signals under the “campaign preparedness” signal to achieve crowdfunding success. Using Qualitative Comparative Analysis, this study examined 45 crowdfunding campaigns run by Australian social enterprises on StartSomeGood and Chuffed. The analysis found that different combinations of costly and costless signals can lead to crowdfunding success, allowing social enterprises to adopt suitable combinations of signals to their context. Costless signal – campaign preparedness is fundamental for success, though different costless sub-signals under campaign preparedness can interact with different costly signals for the desired outcome. Third-party endorsement signal was found to be the necessary signal for crowdfunding success for Australian social enterprises.

Keywords: crowdfunding, qualitative comparative analysis (QCA), signalling theory, social enterprises

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Authors: Kazuma Mizukoshi

Abstract:

Are electoral politics in contemporary Brazil still local in organization and focus? The importance of this question lies in its paradoxical trajectories. First, often coupled with institutional and sociological ‘barriers’ (e.g. the selection and election of candidates relatively loyal to the local party leadership, the predominance of territorialized electoral campaigns, and the resilience of political clientelism), the regionalization of electoral politics has been a viable and practical solution especially for pragmatic politicians in some Latin American countries. On the other hand, some leftist parties that once served as minor opposition forces at the time of foundational or initial elections have certainly expanded vote shares. Some were eventually capable of holding most (if not a majority) legislative seats since the 1990s. Though not yet rigorously demonstrated, theoretically implicit in the rise of leftist parties in legislative elections is the gradual (if not complete) nationalization of electoral support—meaning the growing equality of a party’s vote share across electoral districts and its change over time. This study will develop four hypotheses to explain the dynamics of party nationalization in contemporary Brazil: district magnitude, ethnic and class fractionalization of each district, voting intentions in federal and state executive elections, and finally the left-right stances of electorates. The study will demonstrate these hypotheses by closely working with the Brazilian Electoral Study (2002-2014).

Keywords: party nationalization, presidential coattails, Left, Brazil

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Authors: Benjamin Ankomah-Asare, Richard Adade

Abstract:

Sea level rise (SLR) poses a significant threat to coastal communities globally. Ghana has over the years implemented protective measures such as the construction of groynes and revetment to serve as barriers to sea waves in major cities and towns to prevent sea erosion and flooding. For vulnerable rural coastal communities, the planned retreat is often proposed; however, relocation costs are often underestimated as losses of future social and cultural value are not always adequately taken into account. Through a mixed-methods approach combining qualitative interviews, surveys, and spatial analysis, the study examined the experiences of coastal rural communities in Ghana and assess the effectiveness of relocation strategies in addressing the socio-economic and environmental challenges posed by sea level rise. The study revealed the devastating consequences of sea level rise on these communities, including increased flooding, erosion, and saltwater intrusion into freshwater sources. Moreover, it highlights the adaptive capacities within these communities and how factors such as infrastructure, economic activities, cultural heritage, and governance structures shape their resilience in the face of environmental change. While relocation can be an effective strategy in reducing the risks associated with sea level rise, the study recommends that proper implementation of this adaptation strategy can be achieved when coupled with community-led planning, participatory decision-making, and targeted support for vulnerable groups.

Keywords: sea level rise, relocation, socio-ecological impacts, rural communities

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