Search results for: open source data
25277 Photovoltaic Solar Energy in Public Buildings: A Showcase for Society
Authors: Eliane Ferreira da Silva
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This paper aims to mobilize and sensitize public administration leaders to good practices and encourage investment in the PV system in Brazil. It presents a case study methodology for dimensioning the PV system in the roofs of the public buildings of the Esplanade of the Ministries, Brasilia, capital of the country, with predefined resources, starting with the Sustainable Esplanade Project (SEP), of the exponential growth of photovoltaic solar energy in the world and making a comparison with the solar power plant of the Ministry of Mines and Energy (MME), active since: 6/10/2016. In order to do so, it was necessary to evaluate the energy efficiency of the buildings in the period from January 2016 to April 2017, (16 months) identifying the opportunities to reduce electric energy expenses, through the adjustment of contracted demand, the tariff framework and correction of existing active energy. The instrument used to collect data on electric bills was the e-SIC citizen information system. The study considered in addition to the technical and operational aspects, the historical, cultural, architectural and climatic aspects, involved by several actors. Identifying the reductions of expenses, the study directed to the following aspects: Case 1) economic feasibility for exchanges of common lamps, for LED lamps, and, Case 2) economic feasibility for the implementation of photovoltaic solar system connected to the grid. For the case 2, PV*SOL Premium Software was used to simulate several possibilities of photovoltaic panels, analyzing the best performance, according to local characteristics, such as solar orientation, latitude, annual average solar radiation. A simulation of an ideal photovoltaic solar system was made, with due calculations of its yield, to provide a compensation of the energy expenditure of the building - or part of it - through the use of the alternative source in question. The study develops a methodology for public administration, as a major consumer of electricity, to act in a responsible, fiscalizing and incentive way in reducing energy waste, and consequently reducing greenhouse gases.Keywords: energy efficiency, esplanade of ministries, photovoltaic solar energy, public buildings, sustainable building
Procedia PDF Downloads 13225276 End-to-End Control and Management of Multi-AS Virtual Service Networks Using SDN and Autonomic Computing Architecture
Authors: Yong Xue, Daniel A. Menascé
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Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain
Procedia PDF Downloads 53125275 Detection of Change Points in Earthquakes Data: A Bayesian Approach
Authors: F. A. Al-Awadhi, D. Al-Hulail
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In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode
Procedia PDF Downloads 45625274 Adopting a New Policy in Maritime Law for Protecting Ship Mortgagees Against Maritime Liens
Authors: Mojtaba Eshraghi Arani
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Ship financing is the vital element in the development of shipping industry because while the ship constitutes the owners’ main asset, she is considered a reliable security in the financiers’ viewpoint as well. However, it is most probable that a financier who has accepted a ship as security will face many creditors who are privileged and rank before him for collecting, out of the ship, the money that they are owed. In fact, according to the current rule of maritime law, which was established by “Convention Internationale pour l’Unification de Certaines Règles Relatives aux Privilèges et Hypothèques Maritimes, Brussels, 10 April 1926”, the mortgages, hypotheques, and other charges on vessels rank after several secured claims referred to as “maritime liens”. Such maritime liens are an exhaustive list of claims including but not limited to “expenses incurred in the common interest of the creditors to preserve the vessel or to procure its sale and the distribution of the proceeds of sale”, “tonnage dues, light or harbour dues, and other public taxes and charges of the same character”, “claims arising out of the contract of engagement of the master, crew and other persons hired on board”, “remuneration for assistance and salvage”, “the contribution of the vessel in general average”, “indemnities for collision or other damage caused to works forming part of harbours, docks, etc,” “indemnities for personal injury to passengers or crew or for loss of or damage to cargo”, “claims resulting form contracts entered into or acts done by the master”. The same rule survived with only some minor change in the categories of maritime liens in the substitute conventions 1967 and 1993. The status que in maritime law have always been considered as a major obstacle to the development of shipping market and has inevitably led to increase in the interest rates and other related costs of ship financing. It seems that the national and international policy makers have yet to change their mind being worried about the deviation from the old marine traditions. However, it is crystal clear that the continuation of status que will harm, to a great extent, the shipowners and, consequently, the international merchants as a whole. It is argued in this article that the raison d'être for many categories of maritime liens cease to exist anymore, in view of which, the international community has to recognize only a minimum category of maritime liens which are created in the common interests of all creditors; to this effect, only two category of “compensation due for the salvage of ship” and “extraordinary expenses indispensable for the preservation of the ship” can be declared as taking priority over the mortgagee rights, in anology with the Geneva Convention on the International Recognition of Rights in Aircrafts (1948). A qualitative method with the concept of interpretation of data collection has been used in this manuscript. The source of the data is the analysis of international conventions and domestic laws.Keywords: ship finance, mortgage, maritime liens, brussels convenion, geneva convention 1948
Procedia PDF Downloads 7225273 Delineating Floodplain along the Nasia River in Northern Ghana Using HAND Contour
Authors: Benjamin K. Ghansah, Richard K. Appoh, Iliya Nababa, Eric K. Forkuo
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The Nasia River is an important source of water for domestic and agricultural purposes to the inhabitants of its catchment. Major farming activities takes place within the floodplain of the river and its network of tributaries. The actual inundation extent of the river system is; however, unknown. Reasons for this lack of information include financial constraints and inadequate human resources as flood modelling is becoming increasingly complex by the day. Knowledge of the inundation extent will help in the assessment of risk posed by the annual flooding of the river, and help in the planning of flood recession agricultural activities. This study used a simple terrain based algorithm, Height Above Nearest Drainage (HAND), to delineate the floodplain of the Nasia River and its tributaries. The HAND model is a drainage normalized digital elevation model, which has its height reference based on the local drainage systems rather than the average mean sea level (AMSL). The underlying principle guiding the development of the HAND model is that hillslope flow paths behave differently when the reference gradient is to the local drainage network as compared to the seaward gradient. The new terrain model of the catchment was created using the NASA’s SRTM Digital Elevation Model (DEM) 30m as the only data input. Contours (HAND Contour) were then generated from the normalized DEM. Based on field flood inundation survey, historical information of flooding of the area as well as satellite images, a HAND Contour of 2m was found to best correlates with the flood inundation extent of the river and its tributaries. A percentage accuracy of 75% was obtained when the surface area created by the 2m contour was compared with surface area of the floodplain computed from a satellite image captured during the peak flooding season in September 2016. It was estimated that the flooding of the Nasia River and its tributaries created a floodplain area of 1011 km².Keywords: digital elevation model, floodplain, HAND contour, inundation extent, Nasia River
Procedia PDF Downloads 45725272 Development of Educational Institutions in Afghanistan and Especially in the Region of “Herat” Opportunities and Challenges
Authors: Sayed Jamal Ud Din Heravi
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The development of educational institutions has an important role in the progress and advancement of the state, in the stability and security of the state and its exposure, in the flourishing of minds, in devoting the role of science, developing society, and meeting people’s desires and needs. Afghanistan is a Muslim country located in Central Asia on the borders of Pakistan, Iran, Tajikistan, and Uzbekistan, and it also borders China's Xing yang. Unfortunately, these oppressed people have been living in wars that have been going on for four decades, in which educational institutions, schools and institutes have not developed. Rather, the war destroyed the infrastructure of this country, and no city or village remained in it but tasted the bloody wars. Now with the new government, we see that many government educational institutions are closed in this country, even if the state promises that it will open them quickly. As for universities and private institutions, they work in Afghanistan diligently and diligently, and among them, there is sharp competition in the use of professors and taking advantage of the available means for the sake of knowledge. It laid the building blocks for a bright dawn in which it seeks to keep pace with the procession of development and prosperity in the world.Keywords: Afghanistan, higher education, Herat province, opportunities, challenges
Procedia PDF Downloads 11925271 Idiopathic Gingival Fibromatosis
Authors: Bandana Koirala, Shivalal Sharma
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Introduction: Gingival enlargements are quite common and may be either inflammatory, non-inflammatory or a combination of both. Idiopathic gingival enlargement is a rare condition with a proliferative fibrous lesion of the gingival tissue that causes esthetic and functional problems. It is of undetermined etiology. Case Description: This case report addresses the diagnosis and treatment of a case of idiopathic gingival enlargement in a 9-year-old male patient. The patient presented with a generalized diffuse gingival enlargement involving the entire maxillary and the mandibular arch with extension on occlusal, buccal, lingual, and palatal surfaces with just parts of occlusal surfaces of few upper and lower molars visible resulting in open mouth, difficulty in mastication and speech. Biopsy report confirmed the diagnosis of fibromatosis gingivae. Gingivectomy was carried out in all four quadrants by using external bevel incision. Conclusion: Though total esthetics could not be restored due to unusual bony enlargement, the general appearance improved satisfactorily. Treatment after complete excision however, improved the masticatory competence to a great extent.Keywords: idiopathic gingival fibromatosis, gingival enlargement, gingivectomy, medical and health sciences
Procedia PDF Downloads 32925270 Productivity and Structural Design of Manufacturing Systems
Authors: Ryspek Usubamatov, Tan San Chin, Sarken Kapaeva
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Productivity of the manufacturing systems depends on technological processes, a technical data of machines and a structure of systems. Technology is presented by the machining mode and data, a technical data presents reliability parameters and auxiliary time for discrete production processes. The term structure of manufacturing systems includes the number of serial and parallel production machines and links between them. Structures of manufacturing systems depend on the complexity of technological processes. Mathematical models of productivity rate for manufacturing systems are important attributes that enable to define best structure by criterion of a productivity rate. These models are important tool in evaluation of the economical efficiency for production systems.Keywords: productivity, structure, manufacturing systems, structural design
Procedia PDF Downloads 58525269 The Effect of Tacit Knowledge for Intelligence Cycle
Authors: Bahadir Aydin
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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.Keywords: information, intelligence cycle, knowledge, tacit Knowledge
Procedia PDF Downloads 51425268 Electrochemical Corrosion Behavior of New Developed Titanium Alloys in Ringer’s Solution
Authors: Yasser M. Abd-elrhman, Mohamed A. Gepreel, Kiochi Nakamura, Ahmed Abd El-Moneim, Sengo Kobayashi, Mervat M. Ibrahim
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Titanium alloys are known as highly bio compatible metallic materials due to their high strength, low elastic modulus, and high corrosion resistance in biological media. Besides other important material features, the corrosion parameters and corrosion products are responsible for limiting the biological and chemical bio compatibility of metallic materials that produce undesirable reactions in implant-adjacent and/or more distant tissues. Electrochemical corrosion behaviors of novel beta titanium alloys, Ti-4.7Mo-4.5Fe, Ti-3Mo-0.5Fe, and Ti-2Mo-0.5Fe were characterized in naturally aerated Ringer’s solution at room temperature compared with common used biomedical titanium alloy, Ti-6Al-4V. The corrosion resistance of titanium alloys were investigated through open circuit potential (OCP), potentiodynamic polarization measurements and optical microscope (OM). A high corrosion resistance was obtained for all alloys due to the stable passive film formed on their surfaces. The new present alloys are promising metallic biomaterials for the future, owing to their very low elastic modulus and good corrosion resistance capabilities.Keywords: titanium alloys, corrosion resistance, Ringer’s solution, electrochemical corrosion
Procedia PDF Downloads 65925267 Mesquite (Prosopis juliflora) Pods as a Local Alternative to Feed Poultry
Authors: Abdulrahman Al-Soqeer, Osamah Fahmy
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This research was aimed to investigate the possibility of using Prosopis juliflora pods as a fodder source for poultry. The study have shown that the inclusion of ground Prosopis pods in a broiler diet added some positive effects on broiler performance such as improving carcasses weight and reducing the weights of the inedible parts. The obtained results encourage repeating the experiment with an increased percentage of Prosopis supplementation in the broiler diets, using some treatments on the Prosopis pods to reduce the undesirable effects of the antinutritional factors in the pods and to increase the percentage of the essential amino acids present in the pods (lysine, methionine, arginine, histidine, isoleucine, leucine and phenylealanine) up to the limits recommended for broilers by NRC 1990.Keywords: amino acids, arginine, broilers, lysine, methionine
Procedia PDF Downloads 23925266 Evaluation of the CRISP-DM Business Understanding Step: An Approach for Assessing the Predictive Power of Regression versus Classification for the Quality Prediction of Hydraulic Test Results
Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter
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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.Keywords: classification, CRISP-DM, machine learning, predictive quality, regression
Procedia PDF Downloads 14425265 Integration GIS–SCADA Power Systems to Enclosure Air Dispersion Model
Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey
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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system
Procedia PDF Downloads 36925264 Implementation Association Rule Method in Determining the Layout of Qita Supermarket as a Strategy in the Competitive Retail Industry in Indonesia
Authors: Dwipa Rizki Utama, Hanief Ibrahim
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The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.Keywords: industry retail, strategy, association rule, supermarket
Procedia PDF Downloads 18825263 Preparing Data for Calibration of Mechanistic-Empirical Pavement Design Guide in Central Saudi Arabia
Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman
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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh
Procedia PDF Downloads 22625262 The Role of Branding for Success in the Georgian Tea Market
Authors: Maia Seturi, Tamari Todua
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Economic growth is seen as the increase in the production capacity of a country. It enables a country to produce more and more material wealth and social benefits. Today, the success of any product on the market is closely related to the issue of branding. The brand is a source of information for a user/consumer, which helps to simplify the choice of goods and reduce consumer risk. The paper studies the role of branding in order to promote Georgian tea brands. The main focus of the research is directed to consumer attitudes regarding Georgian tea brands. The methodology of the paper is based on marketing research. The findings study revealed that the majority of consumers prefer foreign tea brands. The final part of the article presents the main recommendations.Keywords: marketing research, customer behavior, brand, successful brand
Procedia PDF Downloads 13625261 Fracture Toughness Characterizations of Single Edge Notch (SENB) Testing Using DIC System
Authors: Amr Mohamadien, Ali Imanpour, Sylvester Agbo, Nader Yoosef-Ghodsi, Samer Adeeb
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The fracture toughness resistance curve (e.g., J-R curve and crack tip opening displacement (CTOD) or δ-R curve) is important in facilitating strain-based design and integrity assessment of oil and gas pipelines. This paper aims to present laboratory experimental data to characterize the fracture behavior of pipeline steel. The influential parameters associated with the fracture of API 5L X52 pipeline steel, including different initial crack sizes, were experimentally investigated for a single notch edge bend (SENB). A total of 9 small-scale specimens with different crack length to specimen depth ratios were conducted and tested using single edge notch bending (SENB). ASTM E1820 and BS7448 provide testing procedures to construct the fracture resistance curve (Load-CTOD, CTOD-R, or J-R) from test results. However, these procedures are limited by standard specimens’ dimensions, displacement gauges, and calibration curves. To overcome these limitations, this paper presents the use of small-scale specimens and a 3D-digital image correlation (DIC) system to extract the parameters required for fracture toughness estimation. Fracture resistance curve parameters in terms of crack mouth open displacement (CMOD), crack tip opening displacement (CTOD), and crack growth length (∆a) were carried out from test results by utilizing the DIC system, and an improved regression fitting resistance function (CTOD Vs. crack growth), or (J-integral Vs. crack growth) that is dependent on a variety of initial crack sizes was constructed and presented. The obtained results were compared to the available results of the classical physical measurement techniques, and acceptable matchings were observed. Moreover, a case study was implemented to estimate the maximum strain value that initiates the stable crack growth. This might be of interest to developing more accurate strain-based damage models. The results of laboratory testing in this study offer a valuable database to develop and validate damage models that are able to predict crack propagation of pipeline steel, accounting for the influential parameters associated with fracture toughness.Keywords: fracture toughness, crack propagation in pipeline steels, CTOD-R, strain-based damage model
Procedia PDF Downloads 6325260 Transforming Data Science Curriculum Through Design Thinking
Authors: Samar Swaid
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Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.Keywords: data science, design thinking, AI, currculum, transformation
Procedia PDF Downloads 8125259 Economized Sensor Data Processing with Vehicle Platooning
Authors: Henry Hexmoor, Kailash Yelasani
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We present vehicular platooning as a special case of crowd-sensing framework where sharing sensory information among a crowd is used for their collective benefit. After offering an abstract policy that governs processes involving a vehicular platoon, we review several common scenarios and components surrounding vehicular platooning. We then present a simulated prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that one of the paramount benefits of platooning that is overlooked elsewhere, is the substantial computational savings (i.e., economizing benefits) in acquisition and processing of sensory data among vehicles sharing the road. The most capable vehicle can share data gathered from its sensors with nearby vehicles grouped into a platoon.Keywords: cloud network, collaboration, internet of things, social network
Procedia PDF Downloads 19425258 Association of Vulnerability and Behavioural Outcomes of FSWs Linked with TI Prevention HIV Program: An Evidence from Cross-Sectional Behavioural Study in Thane District of Maharashtra
Authors: Jayanta Bora, Sukhvinder Kaur, Ashok Agarwal, Sangeeta Kaul
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Background: It is important for targeted interventions to consider vulnerabilities of female sex workers (FSWs) such as poverty, work-related mobility and literacy for effective human immunodeficiency virus (HIV) prevention. This paper examines the association between vulnerability and behavioural outcomes among FSWs in Thane district, Maharashtra under USAID PHFI-PIPPSE project. Methods: Data were used from the Behavioural Tracking Survey, a cross-sectional behavioural study conducted in 2015 with 503 FSWs randomly selected from 12 TI-NGOs which were functioning and providing services to FSWs in Thane district prior to April 2014 in Thane district of Maharashtra. We have created the “vulnerability index”, a composite index of literacy, factors of dependence (alternative livelihood options, current debt), and aspects of sex work (mobility and duration in sex work) as a dependent variable. The key independent measures used were program exposure to intervention, service uptake, self-confidence, and self-identity. Bi-variate and multivariate logistic regressions were used to examine the study objectives. Results: A higher proportion of FSWs who were in the age-group 18–25 years from brothel/street /home/ lodge-based were categorized as highly vulnerable to HIV risk as compared to bar-based sex worker (74.1% versus 59.8%, P,0.002); regression analysis highlighted lower odds of vulnerability among FSWs who were aware of services and visited NGO clinic for medical check-up and counselling for STI [AOR= 0.092, 95% CI 0.018-0.460; P,0.004], However, lower odds of vulnerability on confident in supporting fellow sex worker in crisis [AOR= 0.601, 95% CI 0.476-0.758; P, 0.000] and were able to turn away clients when they refused to use a condom during sex [AOR= 0.524, 95% CI 0.342-0.802; P, 0.003]. Conclusion: The results highlight that FSWs associated with TIs and getting services are less vulnerable and highly empowered. As a result of behavioural change communication and other services provided by TIs, FSWs were able to successfully negotiate about condom use with their clients and manage solidarity in the crisis situation for fellow FSWs. Therefore, it is evident from study paper that TI prevention programs may transform the lives of masses considerably and may open a window of opportunity to infuse the information and awareness about HIV risk.Keywords: female sex worker, HIV prevention, HIV service uptake, vulnerability
Procedia PDF Downloads 25425257 Exchange Rate Forecasting by Econometric Models
Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir
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The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.Keywords: exchange rate, ARIMA, GARCH, PAK/USD
Procedia PDF Downloads 56125256 Short Term Distribution Load Forecasting Using Wavelet Transform and Artificial Neural Networks
Authors: S. Neelima, P. S. Subramanyam
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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)
Procedia PDF Downloads 43625255 Solar Energy: The Alternative Electric Power Resource in Tropical Nigeria
Authors: Okorowo Cyril Agochi
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More than ever human activity relating to uncontrolled greenhouse gas (GHG) and its effects on the earth is gaining greater attention in the global academic and policy discussions. Activities of man has greatly influenced climate change over the years as a result of consistent increase in the use of fossil fuel energy. Scientists and researchers globally are making significant and devoted efforts towards the development and implementation of renewable energy technologies that are harmless to the environment. One of such energy is solar energy with its source from the sun. There are currently two primary ways of harvesting this energy from the sun: through photovoltaic (PV) panels and through thermal collectors. This work discuses solar energy the abundant renewable energy in the tropical Nigeria, processes of harvesting and recommends same as an alternative means of electric power generation in a time the demand for power supersedes supply.Keywords: electric, power, renewable energy, solar energy, sun, tropical
Procedia PDF Downloads 54325254 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul
Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini
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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.Keywords: decision tree, breast cancer, probability, data mining
Procedia PDF Downloads 13825253 Image Steganography Using Least Significant Bit Technique
Authors: Preeti Kumari, Ridhi Kapoor
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In any communication, security is the most important issue in today’s world. In this paper, steganography is the process of hiding the important data into other data, such as text, audio, video, and image. The interest in this topic is to provide availability, confidentiality, integrity, and authenticity of data. The steganographic technique that embeds hides content with unremarkable cover media so as not to provoke eavesdropper’s suspicion or third party and hackers. In which many applications of compression, encryption, decryption, and embedding methods are used for digital image steganography. Due to compression, the nose produces in the image. To sustain noise in the image, the LSB insertion technique is used. The performance of the proposed embedding system with respect to providing security to secret message and robustness is discussed. We also demonstrate the maximum steganography capacity and visual distortion.Keywords: steganography, LSB, encoding, information hiding, color image
Procedia PDF Downloads 47425252 Towards a Distributed Computation Platform Tailored for Educational Process Discovery and Analysis
Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa
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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM
Procedia PDF Downloads 45425251 Assimilating Remote Sensing Data Into Crop Models: A Global Systematic Review
Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam
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Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.Keywords: crop models, remote sensing, data assimilation, crop yield estimation
Procedia PDF Downloads 13125250 Assimilating Remote Sensing Data into Crop Models: A Global Systematic Review
Authors: Luleka Dlamini, Olivier Crespo, Jos van Dam
Abstract:
Accurately estimating crop growth and yield is pivotal for timely sustainable agricultural management and ensuring food security. Crop models and remote sensing can complement each other and form a robust analysis tool to improve crop growth and yield estimations when combined. This study thus aims to systematically evaluate how research that exclusively focuses on assimilating RS data into crop models varies among countries, crops, data assimilation methods, and farming conditions. A strict search string was applied in the Scopus and Web of Science databases, and 497 potential publications were obtained. After screening for relevance with predefined inclusion/exclusion criteria, 123 publications were considered in the final review. Results indicate that over 81% of the studies were conducted in countries associated with high socio-economic and technological advancement, mainly China, the United States of America, France, Germany, and Italy. Many of these studies integrated MODIS or Landsat data into WOFOST to improve crop growth and yield estimation of staple crops at the field and regional scales. Most studies use recalibration or updating methods alongside various algorithms to assimilate remotely sensed leaf area index into crop models. However, these methods cannot account for the uncertainties in remote sensing observations and the crop model itself. l. Over 85% of the studies were based on commercial and irrigated farming systems. Despite a great global interest in data assimilation into crop models, limited research has been conducted in resource- and data-limited regions like Africa. We foresee a great potential for such application in those conditions. Hence facilitating and expanding the use of such an approach, from which developing farming communities could benefit.Keywords: crop models, remote sensing, data assimilation, crop yield estimation
Procedia PDF Downloads 8225249 Wind Speed Prediction Using Passive Aggregation Artificial Intelligence Model
Authors: Tarek Aboueldahab, Amin Mohamed Nassar
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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction
Procedia PDF Downloads 45025248 Enhancing Robustness in Federated Learning through Decentralized Oracle Consensus and Adaptive Evaluation
Authors: Peiming Li
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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.Keywords: federated learning system, block chain, decentralized oracles, hidden markov model
Procedia PDF Downloads 63