Search results for: data reduction

Authors: Iman Shabanzadeh

Abstract:

Earthquake is known as one of the most frequent natural hazards in Iran. Therefore, policy making to improve the strengthening of structures is one of the requirements of the approach to prevent and reduce the risk of the destructive effects of earthquakes. In order to choose the optimal policy in the face of earthquakes, this article tries to examine the cost of financial damages caused by earthquakes in the building sector and compare it with the costs of retrofitting. In this study, the results of adopting the scenario of "action after the earthquake" and the policy scenario of "strengthening structures before the earthquake" have been collected, calculated and finally analyzed by putting them together. Methodologically, data received from governorates and building retrofitting engineering companies have been used. The scope of the study is earthquakes occurred in the geographical area of Iran, and among them, eight earthquakes have been specifically studied: Miane, Ahar and Haris, Qator, Momor, Khorasan, Damghan and Shahroud, Gohran, Hormozgan and Ezgole. The main basis of the calculations is the data obtained from retrofitting companies regarding the cost per square meter of building retrofitting and the data of the governorate regarding the power of earthquake destruction, the realized costs for the reconstruction and construction of residential units. The estimated costs have been converted to the value of 2021 using the time value of money method to enable comparison and aggregation. The cost-benefit comparison of the two policies of action after the earthquake and retrofitting before the earthquake in the eight earthquakes investigated shows that the country has suffered five thousand billion Tomans of losses due to the lack of retrofitting of buildings against earthquakes. Based on the data of the Budget Law's of Iran, this figure was approximately twice the budget of the Ministry of Roads and Urban Development and five times the budget of the Islamic Revolution Housing Foundation in 2021. The results show that the policy of retrofitting structures before an earthquake is significantly more optimal than the competing scenario. The comparison of the two policy scenarios examined in this study shows that the policy of retrofitting buildings before an earthquake, on the one hand, prevents huge losses, and on the other hand, by increasing the number of earthquake-resistant houses, it reduces the amount of earthquake destruction. In addition to other positive effects of retrofitting, such as the reduction of mortality due to earthquake resistance of buildings and the reduction of other economic and social effects caused by earthquakes. These are things that can prove the cost-effectiveness of the policy scenario of "strengthening structures before earthquakes" in Iran.

Keywords: disaster economy, earthquake economy, cost-benefit analysis, resilience

Procedia PDF Downloads 53

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

Abstract:

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

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

Procedia PDF Downloads 441

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

Procedia PDF Downloads 371

Authors: Chol Min Yu, Sok Chol Ri

Abstract:

The optimization of formation and growth of metallic nuggets during self-reduction of coal composite briquette (CCB here) is essential to increase the yield of valuable metals. The formation of metallic nuggets was investigated theoretically and experimentally during the reduction of coal composite briquette made from stainless steel dust and coal. The formation of metallic nuggets is influenced by slag viscosity and interfacial tension between the liquid metal and the slag in the reduced product. Surface tensions of liquid metal and slag are rather strong, respectively, due to the high basicity of its slag. Strong surface tensions of them lead to increase of interfacial tension between the liquid metal and the slag to be favorable to the growth of metallic nuggets. The viscosity of slag and interfacial tension between the liquid metal and the slag depends on the temperature and composition of the slag. The formation and the growth of metallic nuggets depend on carbon to oxygen ratio FC/O and temperature.

Keywords: stainless steel dust, coal-composite briquette, temperature, high basicity, interfacial tension

Procedia PDF Downloads 77

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

Procedia PDF Downloads 157

Authors: Hilal Kivrak, Aykut ÇağLar, Nahit Aktaş, Ali Osman Solak

Abstract:

At present, Cd/TiO₂ and CdTe/TiO₂ catalysts are prepared via sodium borohydride (NaBH4) reduction method. These catalysts are characterized by fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). These Cd/TiO₂ and CdTe/TiO₂ are employed as catalysts for the photocatalytic oxidation of glucose. Cyclic voltammetry (CV), chronoamperometry (CA), and electrochemical impedance spectroscopy (EIS) measurements are used to investigate their glucose electrooxidation activities of catalysts at long and under UV illumination (ʎ=354 nm). CdTe/TiO₂ catalyst is showed the best photocatalytic glucose electrooxidation activity compared to Cd/TiO₂ catalyst.

Keywords: cadmium, NaBH4 reduction method, photocatalytic glucose electrooxidation, Tellerium, TiO2

Procedia PDF Downloads 266

Authors: Salvatore Luongo, Carlo Luongo

Abstract:

This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

Procedia PDF Downloads 277

Authors: P. Acosta-Santamaría, A. Ibatá-Soto, A. López-Vásquez

Abstract:

Organic compounds in wastewaters coming from textile and pharmaceutical industry generated multiple harmful effects on the environment and the human health. One of them is the methyl orange (MeO), an azoic dye considered to be a recalcitrant compound. The heterogeneous photocatalysis emerges as an alternative for treating this type of hazardous compounds, through the generation of OH radicals using radiation and a semiconductor oxide. According to the author’s knowledge, catalysts such as TiO₂ doped with metals show high efficiency in degrading MeO; however, this presents economic limitations on industrial scale. Black sand can be considered as a naturally doped catalyst because in its structure is common to find compounds such as titanium, iron and aluminum oxides, also elements such as zircon, cadmium, manganese, etc. This study reports the photocatalytic activity of the mineral black sand used as semiconductor in the discoloration of MeO by oxidation and reduction photocatalytic techniques. For this, magnetic composites from the mineral were prepared (RM, M1, M2 and NM) and their activity were tested through MeO discoloration while TiO₂ was used as reference. For the fractions, chemical, morphological and structural characterizations were performed using Scanning Electron Microscopy with Energy Dispersive X-Ray (SEM-EDX), X-Ray Diffraction (XRD) and X-Ray Fluorescence (XRF) analysis. M2 fraction showed higher MeO discoloration (93%) in oxidation conditions at pH 2 and it could be due to the presence of ferric oxides. However, the best result to reduction process was using M1 fraction (20%) at pH 2, which contains a higher titanium percentage. In the first process, hydrogen peroxide (H₂O₂) was used as electron donor agent. According to the results, black sand mineral can be used as natural semiconductor in photocatalytic process. It could be considered as a photocatalyst precursor in such processes, due to its low cost and easy access.

Keywords: black sand mineral, methyl orange, oxidation, photocatalysis, reduction

Procedia PDF Downloads 379

Authors: Ekele T. Ochedi, Ahmad H. Taki, Birgit Painter

Abstract:

The effect of the sun and its path on thermal comfort and energy consumption in residential buildings in tropical climates constitute a serious concern for designers, building owners, and users. Passive design approaches based on the sun and its path have been identified as a means of reducing energy consumption as well as enhancing thermal comfort in buildings worldwide. Hence, a thorough understanding regarding the sun path is key to achieving this. This is necessary due to energy need, poor energy supply, and distribution, energy poverty, and over-dependence on electric generators for power supply in Nigeria. These challenges call for a change in the approach to energy-related issues, especially in terms of buildings. The aim of this study is to explore the influence of building orientation, glazing and the use of shading devices on residential buildings in Nigeria. This is intended to provide data that will guide designers in the design of energy-efficient residential buildings. The paper used EnergyPlus to analyze a typical semi-detached residential building in Lokoja, Nigeria using hourly weather data for a period of 10 years. Building performance was studied as well as possible improvement regarding different orientations, glazing types and shading devices. The simulation results show some reductions in energy consumption in response to changes in building orientation, types of glazing and the use of shading devices. The results indicate 29.45% reduction in solar gains and 1.90% in annual operative temperature using natural ventilation only. This shows a huge potential to reduce energy consumption and improve people’s well-being through the use of proper building orientation, glazing and appropriate shading devices on building envelope. The study concludes that for a significant reduction in total energy consumption by residential buildings, the design should focus on multiple design options rather than concentrating on one or few building elements. Moreover, the investigation confirms that energy performance modeling can be used by building designers to take advantage of the sun and to evaluate various design options.

Keywords: energy consumption, energy-efficient buildings, glazing, thermal comfort, shading devices, solar gains

Procedia PDF Downloads 206

Authors: Gabi N. Nehme

Abstract:

The reduction of phosphorus and sulfur in engine oil are the main topics of this paper. Very reproducible boundary lubrication tests were conducted as part of Design of Experiment software (DOE) to study the behavior of fluorinated catalyst iron fluoride (FeF3), and polutetrafluoroethylene or Teflon (PTFE) in developing environmentally friendly (reduced P and S) anti-wear additives for future engine oil formulations. Multi-component Chevron fully formulated oil (GF3) and Chevron plain oil were used with the addition of PTFE and catalyst to characterize and analyze their performance. Lower phosphorus blends were the goal of the model solution. Experiments indicated that new sub-micron FeF3 catalyst played an important role in preventing breakdown of the tribofilm.

Keywords: wear, SEM, EDS, friction, lubricants

Procedia PDF Downloads 282

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 223

Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Abstract:

Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

Procedia PDF Downloads 222

Authors: Andrew Terhemen Tyowua, Zhibing Zhang, Michael J. Adams

Abstract:

Water vapor sorption data at a range of temperatures (25–70 °C) have been obtained for starch (corn and wheat) and non-starch (carrageenan and xanthan gum) hydrocolloid particles in the form of a thin slab. The results reveal that the data may be more accurately described by an existing sigmoidal rather than a Fickian model. The sigmoidal model accounts for the initial surface sorption before the onset of bulk diffusion. At relatively small water activities (≤ 0.3), the absorption of the moisture caused the particles to be plasticized, but at greater activity values (> 0.3), anti-plasticization was induced. However, it was found that for the whole range of water activities and temperatures studied, the data could be characterized by a single non-dimensional number, which was termed the non-Fickian diffusion number where τ is the characteristic time of surface sorption, D is the bulk diffusion coefficient and L is the thickness of the layer of particles. The activation energy suggested that the anti-plasticization mechanism was the result of a reduction in the molecular free volume or an increase in crystallinity.

Keywords: anti-plasticization, arrhenius behavior, diffusion coefficient, hygroscopic polymers, moisture migration, non-fickian sigmoidal model

Procedia PDF Downloads 28

Authors: Fatemeh Yazdanmehr, Iulian Nistor

Abstract:

The scope of the current study is the evaluation of the electric field effect on electrostatic desalting mathematical modeling with laboratory data. This research study was focused on developing a model for an existing operation desalting unit of one of the Iranian heavy oil field with a 75 MBPD production capacity. The high temperature of inlet oil to dehydration unit reduces the oil recovery, so the mathematical modeling of desalter operation parameters is very significant. The existing production unit operating data has been used for the accuracy of the mathematical desalting plant model. The inlet oil temperature to desalter was decreased from 110 to 80°C, and the desalted electrical field was increased from 0.75 to 2.5 Kv/cm. The model result shows that the desalter parameter changes meet the water-oil specification and also the oil production and consequently annual income is increased. In addition to that, changing desalter operation conditions reduces environmental footprint because of flare gas reduction. Following to specify the accuracy of selected electrostatic desalter electrical field, laboratory data has been used. Experimental data are used to ensure the effect of electrical field change on desalter. Therefore, the lab test is done on a crude oil sample. The results include the dehydration efficiency in the presence of a demulsifier and under electrical field (0.75 Kv) conditions at various temperatures. Comparing lab experimental and electrostatic desalter mathematical model results shows 1-3 percent acceptable error which confirms the validity of desalter specification and operation conditions changes.

Keywords: desalter, electrical field, demulsification, mathematical modeling, water-oil separation

Procedia PDF Downloads 131

Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

With the gravity load reduction in the structural and non-structural components, the lightweight construction will be achieved as well as the improvement of efficiency and functional specifications. The advantages of lightweight construction can be examined in two levels. The first is the mass reduction of load bearing structure which results in increasing internal useful space and the other one is the mass reduction of building which decreases the effects of seismic load as a result. In order to achieve this goal, the essential building materials specifications and also optimum load bearing geometry of structural systems and elements have to be considered, so lightweight materials selection particularly with lightweight aggregate for building components will be the first step of lightweight construction. In the next step, in addition to selecting the prominent samples of Iran's traditional architecture, the process of these works improvement is analyzed through the viewpoints of structural efficiency and lightweighting and also the practical methods of lightweight construction have been extracted. The optimum design of load bearing geometry of structural system has to be considered not only in the structural system elements, but also in their composition and the selection of dimensions, proportions, forms and optimum orientations, can lead to get a maximum materials efficiency for loads and stresses bearing.

Keywords: gravity load, light-weighting structural system, load bearing geometry, seismic behavior

Procedia PDF Downloads 539

Authors: N. Chahmana, I. Zerroual

Abstract:

The aim of our work is the contribution to the improvement of the performances of the positive plate of the lead acid battery. For that, we synthesized two varieties of PbO2 used in industry, alpha and beta PbO2 by electrochemical way starting from the not formed industrial plates. We studied the kinetics of reduction of the alpha varieties and PbO2 beta on electrode with microcavity in sulphuric medium. The electrochemical study of the powders of α and β-PbO2 was made by cyclic voltamperometry with sweeping of potential by using a traditional assembly with three electrodes. Values of the coefficient of diffusion of the proton in α and β-PbO2 are respectively equal to 0.498*10-8cm2 /s and 0.793*10-8 cm2 /s. During the cycling of the two varieties of PbO2, we obtain a clear increase in the capacity.

Keywords: lead accumulator, α and β - PbO2, synthesis, kinetics, cyclic voltametry, coefficient of diffusion

Procedia PDF Downloads 574

Authors: Jongbae Lee, Seongsoo Lee

Abstract:

Modern sensors often embed small-size digital controller for sensor control, value calibration, and signal processing. These sensors require digital data communication with host microprocessors, but conventional digital communication protocols are too heavy for price reduction. SAE J2716 SENT (single edge nibble transmission) protocol transmits direct digital waveforms instead of complicated analog modulated signals. In this paper, a SENT interface is designed in Verilog HDL (hardware description language) and implemented in FPGA (field-programmable gate array) evaluation board. The designed SENT interface consists of frame encoder/decoder, configuration register, tick period generator, CRC (cyclic redundancy code) generator/checker, and TX/RX (transmission/reception) buffer. Frame encoder/decoder is implemented as a finite state machine, and it controls whole SENT interface. Configuration register contains various parameters such as operation mode, tick length, CRC option, pause pulse option, and number of nibble data. Tick period generator generates tick signals from input clock. CRC generator/checker generates or checks CRC in the SENT data frame. TX/RX buffer stores transmission/received data. The designed SENT interface can send or receives digital data in 25~65 kbps at 3 us tick. Synthesized in 0.18 um fabrication technologies, it is implemented about 2,500 gates.

Keywords: digital sensor interface, SAE J2716, SENT, verilog HDL

Procedia PDF Downloads 293

Authors: Thachamon Sinsoongsud, Noppawan Piaseu

Abstract:

This predictive study was aimed to 1) describe self efficacy for risk reduction and preventive behavior for osteoporosis, and 2) examine factors predicting preventive behavior for osteoporosis in nursing students. Through purposive sampling, the sample included 746 nursing students in a public university in Bangkok, Thailand. Data were collected by a self-reported questionnaire on self efficacy and preventive behavior for osteoporosis. Data were analyzed using descriptive statistics and multiple regression analysis with stepwise method. Results revealed that majority of the students were female (98.3%) with mean age of 19.86 + 1.26 years. The students had self efficacy and preventive behavior for osteoporosis at moderate level. Self efficacy and level of education could together predicted 35.2% variance of preventive behavior for osteoporosis (p< .001). Results suggest approaches for promoting preventive behavior for osteoporosis through enhancing self efficacy among nursing students in a public university in Bangkok, Thailand.

Keywords: osteoporosis, self-efficacy, preventive behavior, nursing students

Procedia PDF Downloads 375

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

Procedia PDF Downloads 224

Authors: Anli Du Preez, James Bekker

Abstract:

Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

Procedia PDF Downloads 165

Authors: Bahia Braktia, S. Anna Marcela Montenegro, Imene Abdessemed

Abstract:

Adult education is still considered a crucial area of education. In a developing framework, it is regarded as a practical approach for social inclusion and poverty reduction. They are also perceived as a way to serve adults who did not have the chance to education in their early ages by providing them knowledge, skills and values. Non-formal adult education and trainings are critical means in a society to break poverty and unemployment, and to decrease the social inequality. This paper investigates the perception of women trainees about a series of workshops in natural beauty products, held in Algeria and Costa Rica and organized by a non-profit educational organization, to improve their socio-economic status. This research seeks to explore ways of empowering women by assessing their needs and providing them with skills to start their own business. A questionnaire is administered before the workshops and focus groups are held at the end. A qualitative research method is employed to analyze the data. Preliminary results show that the trainees aspire to create their businesses with the objectives of poverty reduction and social inclusion. The findings also reveal the need for small business funding programs and entrepreneurial training programs.

Keywords: adult education, non-formal education, socio-economic status, women empowerment

Procedia PDF Downloads 205

Authors: Shuwen Wu, Zhi LI

Abstract:

Atomically dispersed Fe‒N₄ catalysts are proven as promising alternatives to commercial Pt/C for the oxygen reduction reaction. Most reported Fe‒N₄ catalysts suffer from inferior O‒O bond-breaking capability due to superoxo-like O₂ adsorption, though the isolated dual-atomic metal sites strategy is extensively adopted. Atomic Fe clusters hold greater promise for promoting O‒O bond cleavage by forming peroxo-like O₂ adsorption. However, the excessively strong binding strength between Fe clusters and oxygenated intermediates sacrifices the activity. Here, we first report a Fex/Cu‒N@CF catalyst with atomic Fe clusters functionalized by adjacent single Cu‒N₄ sites anchoring on a porous carbon nanofiber membrane. The theoretical calculation indicates that the single Cu‒N₄ sites can modulate the electronic configuration of Fe clusters to reduce O₂* protonation reaction free energy, which ultimately enhances the electrocatalytic performance. Particularly, the Cu‒N₄ sites can increase the overlaps between the d orbitals of Fe and p orbitals of O to accelerate O‒O cleavage in OOH*. As a result, this unique atomic catalyst exhibits a half potential (E1/2) of 0.944 V in an alkaline medium exceeding that of commercial Pt/C, whereas acidic performance E1/2 = 0.815 V is comparable to Pt/C. This work shows the great potential of single atoms for improvements in atomic cluster catalysts.

Keywords: Hierarchical porous fibers, atomic Fe clusters, Cu single atoms, oxygen reduction reaction; O-O bond cleavage

Procedia PDF Downloads 111

Authors: Ali Hojati Najafabadi, Mohamad Hosein Rahmati, Seyed Ali Madanizadeh

Abstract:

Governments execute energy subsidy reforms by either increasing energy prices or reducing energy price dispersion. These policies make less use of energy per plant (intensive margin), vary the total number of firms (extensive margin), promote technological progress (technology channel), and make additional resources to redistribute (resource channel). We estimate a structural dynamic firm model with endogenous technology adaptation using data from the manufacturing firms in Iran and a country ranked the second-largest energy subsidy plan by the IMF. The findings show significant dynamics and distributional effects due to an energy reform plan. The price elasticity of energy consumption in the industrial sector is about -2.34, while it is -3.98 for large firms. The dispersion elasticity, defined as the amounts of changes in energy consumption by a one-percent reduction in the standard error of energy price distribution, is about 1.43, suggesting significant room for a distributional policy. We show that the intensive margin is the main driver of energy price elasticity, whereas the other channels mostly offset it. In contrast, the labor response is mainly through the extensive margin. Total factor productivity slightly improves in light of the reduction in energy consumption if, at the same time, the redistribution policy boosts the aggregate demands.

Keywords: energy reform, firm dynamics, structural estimation, subsidy policy

Procedia PDF Downloads 87

Authors: Muhammad Dawood Idrees, Maria Hafeez, Arsalan Ansari

Abstract:

Toll tax collection is the earliest method of tax collection and revenue generation. This revenue is utilized for the development of roads networks, maintenance, and connecting to roads and highways across the country. Pakistan is one of the biggest countries, covers a wide area of land, roads networks, and motorways are important source of connecting cities. Every day millions of people use motorways, and they have to stop at toll plazas to pay toll tax as majority of toll plazas are manually collecting toll tax. The purpose of this study is to calculate the waiting time of vehicles at Karachi Hyderabad (M-9) motorway. As Karachi is the biggest city of Pakistan and hundreds of thousands of people use this route to approach other cities. Currently, toll tax collection is manual system which is a major cause for long time waiting at toll plaza. This study calculates the waiting time of vehicles, fuel consumed in waiting time, manpower employed at toll plaza as all process is manual, and it also leads to mental and physical fatigue of driver. All wastages of sources are also calculated, and a most feasible automatic toll tax collection system is proposed which is not only beneficial to reduce waiting time but also beneficial in reduction of fuel, reduction of manpower employed, and reduction in physical and mental fatigue. A cost comparison in terms of wastages is also shown between manual and automatic toll tax collection system (E-Z Pass). Results of this study reveal that, if automatic tool collection system is implemented at Karachi to Hyderabad motorway (M-9), there will be a significance reduction in waiting time of vehicles, which leads to reduction of fuel consumption, environmental pollution, mental and physical fatigue of driver. All these reductions are also calculated in terms of money (Pakistani rupees) and it is obtained that millions of rupees can be saved by using automatic tool collection system which will lead to improve the economy of country.

Keywords: toll tax collection, waiting time, wastages, driver fatigue

Procedia PDF Downloads 145

Authors: Ossai Paulinus Edwin

Abstract:

Cash Management is a broad area having to do with the collection, concentration, and disbursement of cash including measuring the level of liquidity and managing the cash balance and short-Term Investments. Cash Management involves the efficient collection and disbursement of cash and cash equivalents. It also includes management of marketable securities because, in modern Terminology, money comprises marketable securities and actual cash in hand or in a bank. This cash management is concerned with management of cash inflow and cash outflow of a business especially as it concerns a developing nation like Nigeria. The paper throws light on the impact of cashless policy in Nigeria as it was introduced by the Central Bank of Nigeria (CBN) in December 2011 and was kick-started in Lagos in January 2012. Survey research was adopted with the questionnaires as data collection instrument. Responses show that cashless policy if adopted generally shall increase employment opportunities, reduce cash related robbery thereby reducing risk of carrying cash; it shall also reduce cash related corruption and attract more foreign investors to the country. It is expected that the introduction of cashless policy in Nigeria is a step in the right direction as it shall bring about modernization of Nigeria payment system, reduction in the cost of banking services, reduction in high security and safety risk and also curb banking related corruptions.

Keywords: cashless economy, cash management, cashless policy, e-banking, Nigeria

Procedia PDF Downloads 536

Authors: Maria Kralova, Michal Palecek

Abstract:

We have detected factors leading to recidivism (the Czech Republic data). The employment during imprisonment turned out to be the most significant predictor with a positive effect on reduction of a rate of recidivism. Accordingly, we mainly focus on this predictor and its economic consequences. Smart public policy can cut government costs dramatically as more than a half of prisoners in the Czech Republic are recidivists. The operating cost cut of the Czech prison service could be CZK 127,680,000 (USD 5,889,623) in 2013 if a public policy had been set smarter.

Keywords: cost-cut, effective, optimal, public policy, reducing recidivism

Procedia PDF Downloads 526

Authors: Li Mengmeng, Kang Jian

Abstract:

With the rapid development of the city, the noise pollution becomes more and more serious. Noise has seriously affected people's normal life, study and work. In addition, noise has seriously affected the city's ecological environment and the migration of birds. Therefore, it is urgent to control the noise. As one of natural noise-reducing materials, plants have been paid more and more attention. In urban landscape design, it is very important to choose plant species with good noise reduction effect to the sustainable development of urban ecology. The aim of this paper is to find out the characteristics of the plant with good noise reduction effect and apply it in urban landscape design. This study investigated the vibration of leaves of six plant species in a sound field using a Keyence (IG-1000/CCD) Laser Micrometer. The results of the experiments showed that the vibration speed of plant leaves increased obviously after being stimulated by sound source, about 5-10 times. In addition, when driven by the same sound, the speed of all leaves varied with the difference of leaf thickness, leaf size and leaf mass. The speed of all leaves would increase with the increase of leaf size and leaf mass, while those would decrease with the increase of leaf thickness.

Keywords: landscape design, leaf vibration , noise attenuation, plants configuration

Procedia PDF Downloads 223

Authors: John M. Ikome, Martha E. Ikome, Therese Van Wyk

Abstract:

Productivity optimization of a company can significantly increase the company’s output and productivity which can be in the form of corrective actions of ineffective activities, process simplification, and reduction of variations, responsiveness, and reduction of set-up-time which are all under the classification of waste within the manufacturing environment. Deriving a means to eliminate a number of these issues has a key importance for manufacturing organization. This paper focused on a number of industrial engineering techniques which include a cause and effect diagram, to identify and optimize the method or systems being used. Based on our results, it shows that there are a number of variations within the production processes that can significantly disrupt the expected output.

Keywords: optimization, fishbone, diagram, productivity

Procedia PDF Downloads 309

Authors: Matheus Madureira Matos, Alexandre Rodrigues Farias

Abstract:

Magnetic Resonance Imaging (MRI) is a vital imaging technique used in both clinical and pre-clinical areas to obtain detailed anatomical and functional information. However, MRI scans can be expensive, time-consuming, and often require the use of anesthetics to keep animals still during the imaging process. Anesthetics are commonly administered to animals undergoing MRI scans to ensure they remain still during the imaging process. However, prolonged or repeated exposure to anesthetics can have adverse effects on animals, including physiological alterations and potential toxicity. Minimizing the duration and frequency of anesthesia is, therefore, crucial for the well-being of research animals. In recent years, various sampling trajectories have been investigated to reduce the number of MRI measurements leading to shorter scanning time and minimizing the duration of animal exposure to the effects of anesthetics. Compressed sensing (CS) and sampling trajectories, such as cartesian, spiral, and radial, have emerged as powerful tools to reduce MRI data while preserving diagnostic quality. This work aims to apply CS and cartesian, spiral, and radial sampling trajectories for the reconstruction of MRI of the abdomen of mice sub-sampled at levels below that defined by the Nyquist theorem. The methodology of this work consists of using a fully sampled reference MRI of a female model C57B1/6 mouse acquired experimentally in a 4.7 Tesla MRI scanner for small animals using Spin Echo pulse sequences. The image is down-sampled by cartesian, radial, and spiral sampling paths and then reconstructed by CS. The quality of the reconstructed images is objectively assessed by three quality assessment techniques RMSE (Root mean square error), PSNR (Peak to Signal Noise Ratio), and SSIM (Structural similarity index measure). The utilization of optimized sampling trajectories and CS technique has demonstrated the potential for a significant reduction of up to 70% of image data acquisition. This result translates into shorter scan times, minimizing the duration and frequency of anesthesia administration and reducing the potential risks associated with it.

Keywords: compressed sensing, magnetic resonance, sampling trajectories, small animals

Procedia PDF Downloads 69

Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

Procedia PDF Downloads 187