Search results for: automobile maintenance

Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

Abstract:

Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Mohamed Ahmed Khalil

Abstract:

The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

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Authors: R. O. Osaseri, A. R. Usiobaifo

Abstract:

The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Amarnath M., Ramachandra C. G., H. Chelladurai, P..Sateesh Kumar, K. Santhosh Kumar

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Journal bearings are extensively used sliding contact machine elements to support radial/axial loaded rotors used in various applications viz. automobile crankshaft, turbine propeller shaft, rope conveyer, heavy duty electric motors. The primary reasons for the failures of these bearings include unstable lubricant film, oil degradation, misalignment, etc. This paper describes the results of experimental investigations carried out to detect surface fatigue wear developed on load bearing the contact surfaces of journal bearing. The test bearing was subjected to fatigue load cycles over a period of 600 hours. The vibration signals were acquired from the journal bearing at regular intervals of 100 hrs. These signals were post-processed by using the vibration analysis technique to obtain diagnostic information of wear propagated in the journal-bearing system.

Keywords: fatigue, journal bearing, sound signals, vibration signals, wear

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Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

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Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

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Authors: M. Beheshti, S. Saegrov, T. M. Muthanna

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Separated sewer systems are designed to transfer the wastewater from houses and industrial sections to wastewater treatment plants. Unwanted water in the sewer systems is a well-known problem, i.e. storm-water inflow is around 50% of the foul sewer, and groundwater infiltration to the sewer system can exceed 50% of total wastewater volume in deteriorated networks. Infiltration and inflow of non-sewer water (I/I) into sewer systems is unfavorable in separated sewer systems and can trigger overloading the system and reducing the efficiency of wastewater treatment plants. Moreover, I/I has negative economic, environmental, and social impacts on urban areas. Therefore, for having sustainable management of urban sewer systems, I/I of unwanted water into the urban sewer systems should be considered carefully and maintenance and rehabilitation plan should be implemented on these water infrastructural assets. This study presents a methodology to identify and quantify the level of I/I into the sewer system. Amount of I/I is evaluated by accurate flow measurement in separated sewer systems for specified isolated catchments in Trondheim city (Norway). Advanced information about the characteristics of I/I is gained by CCTV inspection of sewer pipelines with high I/I contribution. Achieving enhanced knowledge about the detection and localization of non-sewer water in foul sewer system during the wet and dry weather conditions will enable the possibility for finding the problem of sewer system and prioritizing them and taking decisions for rehabilitation and renewal planning in the long-term. Furthermore, preventive measures and optimization of sewer systems functionality and efficiency can be executed by maintenance of sewer system. In this way, the exploitation of sewer system can be improved by maintenance and rehabilitation of existing pipelines in a sustainable way by more practical cost-effective and environmental friendly way. This study is conducted on specified catchments with different properties in Trondheim city. Risvollan catchment is one of these catchments with a measuring station to investigate hydrological parameters through the year, which also has a good database. For assessing the infiltration in a separated sewer system, applying the flow rate measurement method can be utilized in obtaining a general view of the network condition from infiltration point of view. This study discusses commonly used and advanced methods of localizing and quantifying I/I in sewer systems. A combination of these methods give sewer operators the possibility to compare different techniques and obtain reliable and accurate I/I data which is vital for long-term rehabilitation plans.

Keywords: flow rate measurement, infiltration and inflow (I/I), non-sewer water, separated sewer systems, sustainable management

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Authors: Amandeep Singh, Niraj Bala

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In the last decades, light-weight materials such as magnesium matrix composites have become hot topic for material research due to their excellent mechanical and physical properties. However, relatively very less work has been done related to the wear behavior of these composites. Magnesium matrix composites have wide applications in automobile and aerospace sector. In this review, attempt has been done to collect the literature related to wear behavior of magnesium matrix composites fabricated through various processing techniques such as stir casting, powder metallurgy, friction stir processing etc. Effect of different reinforcements, reinforcement content, reinforcement size, wear load, sliding speed and time have been studied by different researchers in detail. Wear mechanism under different experimental condition has been reviewed in detail. The wear resistance of magnesium and its alloys can be enhanced with the addition of different reinforcements. Wear resistance can further be enhanced by increasing the percentage of added reinforcements. Increase in applied load during wear test leads to increase in wear rate of magnesium composites.

Keywords: hardness, magnesium matrix composites, reinforcement, wear

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: monomial forms, rectangular surfaces, CAGD curves, monomial matrix applications

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Authors: Brajevic-gizdic Igna, Vuletic Gorka

Abstract:

Introduction: Research in opiate addiction is increasingly indicating the importance of substitution therapy in opiate addicts. Opiate addiction is a chronic relapsing disease that includes craving as a criterion. Craving has been considered a predictor of a relapse, which is defined as a strong desire with an excessive need to take a substance. The study aimed to measure the intensity of craving using the VAS (visual analog scale) in opioid addicts taking the Opioid Substitution Therapy (OST). Method: The total sample compromised of 30 participants in outpatient treatment. Two groups of opiate addicts were considered: Methadone-maintenance and buprenorphine-maintenance addicts. The participants completed the survey questionnaire during the outpatient treatment. Results: The results indicated high levels of cravings in patients during the treatment on OST, which is considered an important destabilization factor in abstinence. Thus, the use of methadone/buprenorphine dose should be considered. Conclusion: These findings provided an objective measurement of methadone /buprenorphine dosage and therapy options. The underdoes of OST can put patients at high risk of relapse, resulting in high levels of craving. Thus, when determining the therapeutic dose of OST, it is crucial to consider patients´ craving. This would achieve stabilization more quickly and avoid relapse in abstinence. Subjective physician assessment and patient’s statement are the main criteria to determine OST dosage. Future studies should use larger sample sizes and focus on the importance of intensity craving measurement on OST to objectify methadone /buprenorphine dosage.

Keywords: abstinence, addicts, methadone, OST, quality of life

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Abdallah Abu Madi, Dongmei Cao, Alexeis Garcia-Perez, Qile He

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The failure of Enterprise Resource Planning (ERP) implementation in higher education institutions (HEIs) worldwide is much higher in comparison to other sectors, such as banking or manufacturing, to our knowledge limited research has been conducted on this issue. To date, prior literature has identified some key success factors (KSFs) mostly either in the domain of information and system (IS) or in the industrial context. However, evidence of ERP implementation in the higher education sector has had little attention in the extant literature. Hence, this paper identifies and categories KSFs of ERP implementation in HEIs. Semi-structured face-to-face interviews were conducted with technicians and managers from three Jordanian HEIs. From these case studies, three new sector- and context-specific KSFs were identified and categorized according to two dimensions: organizational and technical. The first new KSF is the selection of the ERP system, which is an influential factor in the organizational dimension. Results show that an ERP solution that is suitable to one context may be disastrous in another. The second new KSF, which falls under the technical dimension, is the relationship between vendors and HEIs. This must be fair and impartial to enable successful decision-making and thus the achievement of pre-defined goals. Also within the technical dimension is the third factor: in-house maintenance. Once an appropriate system is selected and a strong relationship is established, the ERP system requires continuous maintenance for effective operation. HEIs should ensure that qualified IT support is in place and in-house to avoid excessive running expenses.

Keywords: Enterprise Resource Planning (ERP)implementation, key success factors, higher education institutions, Jordanian higher education

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Authors: Mohammed Mamdouh Mohammed, Ali Zain Elabdeen Heikal, Hassan Mahdy, Sherif El-Badawy

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The main purpose of this research is to assess the effectiveness of the Cold In-Place Recycling (CIR) technique in asphalt maintenance by analyzing performance outcomes. To achieve this, fifteen CIR mixtures were prepared using slow-setting emulsified asphalt as the recycling agent, with percentages ranging from 2% to 4% in 0.5% increments. Additionally, pure water was incorporated in percentages ranging from 2% to 4% in 1% increments, and Portland cement was added at a constant content of 1%. The components were mixed at room temperature and subsequently compacted using a gyratory compactor with 150 gyrations. Prior to testing, the samples underwent a two-stage treatment process: initially, they were placed in an oven at 60°C for 48 hours, followed by a 24-hour period of air curing. The Hamburg wheel tracking test was performed to evaluate the samples’ resistance to rutting. Additionally, the Indirect Tensile Strength (ITS) test and the Semi-Circular Beam (SCB) test were conducted to assess their resistance to cracking. Upon analyzing the test results, it was observed that the samples’ resistance to rutting decreased with higher asphalt and moisture content. In contrast, ITS and SCB tests revealed that the samples’ resistance to cracking initially increased with higher asphalt and moisture content, peaking at a certain point, and then decreased, forming a bell-curve pattern.

Keywords: cold in-place, indirect tensile strength, recycling, emulsified asphalt, semi-circular beam

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Authors: Maria Ulfa, Nur Awaliyah Putri

Abstract:

Madurese is known as Malayo-Sumbawan Austronesian language which is used by Madurese people in Madura Island, Indonesia. However, there was a massive migration of Madurese people due to Dutch colonization. The Madurese people were brought by force for cultivation system to the eastern salient north coast or called as Tapal Kuda that spread in region covers the regencies of Probolinggo, Lumajang, Jember, Situbondo, Bondowoso, and Banyuwangi, the eastern part of the Pasuruan Regency, as well as the city of Probolinggo. The city of Probolinggo has unique characteristic regarding the ethnic and language variation. Several ethnics can be found in this city, such as Madurese, Javanese, Tengger, Arabic, Mandhalungan, Osing, and Chinese. Hence, the hybrid culture happens in Probolinggo, they called the culture as Pendhalungan which is the combination of culture among Madurese and Javanese. Among those ethnics, Madurese is the strongest ethnic that still maintains their identity, such as their ethnic language. The massive growth of Madurese in Probolinggo city, East Java is interesting to be analyzed. The object of this study is to discover language ideology and literacy of Madurese to maintain their ethnic language in Probolinggo city, East Java. The researchers used the theory of language maintenance practice based on three types of practices social language, social literacy, and peripheral ritualized practices. The approach of this study was qualitative research with ethnography method. In order to collect the data, researchers used observation and interview techniques. The amount of informants were 20 families which consist of mother, father and children in 5 sub-districts in Probolinggo city and they were interviewed regarding language ideology and literacy of Madurese. In supporting the data, researchers employed the Madurese speakers outside family scope like in school, office, and market. The result of the study revealed that Madurese has been preserved heritably to young generations by ethnics of Madura in Probolinggo city. Primarily the language is being taught in the earlier age of their children as L1 and used as ethnic identity. The parents teach them with simple sentences that grammatically correct. This language literacy is applied to maintain ethnic language as their ethnicity marker since they inhabit in Javanese ethnic area. In fact, it is not the only ideology of Madurese ethnic but also the influence of economic situation like in trading communication. The usage of Madurese in the trading scope is very beneficial since people can bargain the goods cheaper and easier because most of the traders are from Madurese ethnic. In this situation, linguistic phenomena such as code mixing and code switching between Madurese and Javanese are emerged as the trading communication. From the result, it can be concluded that solidarity exists among Madurese people in many scopes.

Keywords: language literacy, language maintenance, Madurese, Probolinggo City

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Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: automation, hydroponics, internet of things, monitoring system, urban farming

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Authors: Rohollah Asadian Kohestani, Mustafa Hashemzadeh

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The present paper is the outcome of a field research that was conducted with the study objective of influencing factor's effect on the behavior of customers switching in the Saipa Emdad Khodro Company. To achieve this goal, six factors of service quality, service cost, waiting time to receive services, reputation of organization, costs of switching and the way to respond the needs of customers as the independent variables of research and their effect on the customer switching was studied as the variable related to the research. The statistical society of this research included all customers of the Saipa Emdad Khodro company that possess the vehicles of automobile manufacturing group of Saipa throughout the country and the statistical sample included 150 persons of such customers. The results of this research indicated that all under study factors excluding the reputation factor effect on the behavior of customer switching.

Keywords: customer services, switching cost, service price, customer switching behavior

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Authors: Minhee Son, Kyung Nam Kim

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This study explores the plan of the Korean and Japanese governments to transition into the hydrogen economy. Two motor companies, Hyundai Motor Company from Korea and Toyota from Japan, released the Hydrogen Fuel Cell Vehicle to monopolize the green energy automobile market. Although, they are the main countries which emit greenhouse gas, hydrogen energy can bring from a certain industry places, such as chemical plants and steel mills. Recent, the two countries have been focusing on the hydrogen industry including a fuel cell vehicle, a hydrogen station, a fuel cell plant, a residential fuel cell. The purpose of this paper is to find out the differences of the policies in the two countries to be hydrogen societies. We analyze the behavior of the public and private sectors in Korea and Japan about hydrogen energy and fuel cells for the transition of the hydrogen economy. Finally we show the similarities and differences of both countries in hydrogen fuel cells. And some cities have feature such as Hydrogen cities. Hydrogen energy can make impact environmental sustainability.

Keywords: fuel cell, hydrogen city, hydrogen fuel cell vehicle, hydrogen station, hydrogen energy

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Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. In this paper, the results for the reliability of diesel generator fans were calculated through Extreme Value Theory. The Extreme Value Theory is not widely used in the engineering field. Its usage is well known in other areas such as hydrology, meteorology, finance. The significance of this theory is in the fact that unlike the other statistical methods it is focused on rare and extreme values, and not on average. It should be noted that this theory is not designed exclusively for extreme events, but for extreme values in any event. Therefore, this is a great opportunity to apply the theory and test if it could be applied in this situation. The significance of the work is the calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know the time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. The results achieved in this method will show the approximation of time for which the fans will work as they should, and the percentage of probability of fans working more than certain estimated time. Extreme Value Theory can be applied not only for rare and extreme events, but for any event that has values which we can consider as extreme.

Keywords: extreme value theory, lifetime, reliability analysis, statistic, time to failure

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Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

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This paper presents the architecture of the “Intelligent cooperative integrated system for road safety and road infrastructure maintenance towards 2020” (ODOS2020) advanced infrastructure, which implements a number of cooperative ITS applications based on Internet of Things and Infrastructure-to-Vehicle (V2I) technologies with the purpose to enhance the active road safety level of vehicles through the provision of a fully automated V2I environment. The primary objective of the ODOS2020 project is to contribute to increased road safety but also to the optimization of time for maintenance of road infrastructure. The integrated technological solution presented in this paper addresses all types of vehicles and requires minimum vehicle equipment. Thus, the ODOS2020 comprises a low-cost solution, which is one of its main benefits. The system architecture includes an integrated notification system to transmit personalized information on road, traffic, and environmental conditions, in order for the drivers to receive real-time and reliable alerts concerning upcoming critical situations. The latter include potential dangers on the road, such as obstacles or road works ahead, extreme environmental conditions, etc., but also informative messages, such as information on upcoming tolls and their charging policies. At the core of the system architecture lies an integrated sensorial network embedded in special road infrastructures (strips) that constantly collect and transmit wirelessly information about passing vehicles’ identification, type, speed, moving direction and other traffic information in combination with environmental conditions and road wear monitoring and predictive maintenance data. Data collected from sensors is transmitted by roadside infrastructure, which supports a variety of communication technologies such as ITS-G5 (IEEE-802.11p) wireless network and Internet connectivity through cellular networks (3G, LTE). All information could be forwarded to both vehicles and Traffic Management Centers (TMC) operators, either directly through the ITS-G5 network, or to smart devices with Internet connectivity, through cloud-based services. Therefore, through its functionality, the system could send personalized notifications/information/warnings and recommendations for upcoming events to both road users and TMC operators. In the course of the ODOS2020 project pilot operation has been conducted to allow drivers of both C-ITS equipped and non-equipped vehicles to experience the provided added value services. For non-equipped vehicles, the provided information is transmitted to a smartphone application. Finally, the ODOS2020 system and infrastructure is appropriate for installation on both urban, rural, and highway environments. The paper presents the various parts of the system architecture and concludes by outlining the various challenges that had to be overcome during its design, development, and deployment in a real operational environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: infrastructure to vehicle, intelligent transportation systems, internet of things, road safety

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Farah Al-Mutairi, Hadeer Al-Jeeraan, Lima Ali, Raya Al-Dabbous, Sarah Baroun

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Lately, within the middle east, development has taken place in the construction area which increased the demand of a crucial component, where without it; stunning views from skyscrapers cannot been experienced, and natural light would not be able to be viewed from an indoor building. Glass has changed the path of living and building. Float glass is a type of glass that is flat and it is the type used in the construction and automobile sector. Facility design on the other hand is a study that improves the efficiency utilization of people, equipment, material and space. Kuwait's governmental future developing plan bears in mind the need of increase in industries to increase the growth domestic product(GDP) of the country. This project studies the feasibility of two designs of a float glass manufacture in Kuwait. The first Alternative, consists of one production line of capacity 500 tons of glass per day. The second alternative, consists of three production lines, each of capacity 500 tons of glass daily.

Keywords: float glass manufacture, Kuwait, feasibility float glass, facility design, float glass production

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Authors: Igna Brajevic-Gizdic, Magda Pletikosa Pavić

Abstract:

Introduction: Research in opiate addiction is increasingly indicating the importance of substitution therapy in opiate addicts. Opiate addiction is a chronic relapsing disease that includes craving as a criterion. Craving has been considered a predictor of a relapse, which is defined as a strong desire with an excessive need to take a substance. The study aimed to measure the intensity of craving using the VAS (visual analog scale) in opioid addicts taking Opioid Substitution Therapy (OST). Method: The total sample compromised of 30 participants in outpatient treatment. Two groups of opiate addicts were considered: Methadone-maintenance and buprenorphine-maintenance addicts. The participants completed the survey questionnaire during the outpatient treatment. Results: The results indicated high levels of cravings in patients during the treatment of OST, which is considered an important destabilization factor in abstinence. Thus, the use of methadone/buprenorphine dose should be considered. Conclusion: These findings provided an objective measurement of methadone /buprenorphine dosage and therapy options. The underdoes of OST can put patients at high risk of relapse, resulting in high levels of craving. Thus, when determining the therapeutic dose of OST, it is crucial to consider patients' cravings. This would achieve stabilization more quickly and avoid relapse in abstinence. Subjective physician assessment and patients' statement are the main criteria to determine OST dosage. Future studies should use larger sample sizes and focus on the importance of intensity craving measurement on OST to objectify methadone /buprenorphine dosage.

Keywords: buprenorphine, craving, heroin addicts, methadone, OST

Procedia PDF Downloads 88

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

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Authors: Jackson Becker

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Transportation produces the largest amount of carbon dioxide emissions in the United States of America. Today, cars are the predominant mode of transportation across the country, and our cities have been reshaped due to them. This was not always the case. Streetcars were seen in almost every American city of the early 1900s. These streetcar systems were viewed as obsolete with the rise of the automobile. With fewer streetcars came lower public transport ridership. Austin, Texas is one of the fastest growing cities in the country, and it used to have an extensive streetcar line. Today, it plans to build a light rail line with less rail mileage than 100 years ago. This research looks at the areas of Austin that are not included in the city’s new transit plan. Transit connectivity is one factor that goes into walkability rates for cities. This study also looks at the correlation between walkability ratings with median household income levels from the 2019 Census. The results showed a correlation between higher income neighborhoods having higher walkability rates, which was influenced by the lack of public transportation options.

Keywords: transportation, walkability, income, austin

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Authors: Krzysztof Buczak, Sonia Lachowska, Pawel Kucharski, Agnieszka Antonczyk

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Tiletamine - zolazepam combination is increasingly used in veterinary anaesthesiology in wild animals, including snakes. The available literature shows a lack of information about anesthesia in this mixture in ovoviviparous snakes. The studies show the possibility of using the combination at a dose of 20 mg/kg or more for snake immobilization. This paper presents an anesthetic protocol with the use of a combination of tiletamine - zolazepam at the dose of 10 mg/kg intramuscularly and maintenance with inhalant anesthesia with isoflurane in pure oxygen. The objective of this study was to evaluate the usefulness of the anesthetic protocol to proceed with coeliotomy in Amazon Tree Boa. The patient was a five years old bicolor female Amazon Tree Boa (Corallus hortulanus) with dystocia. The clinical examination reveals significant emaciation (bodyweight 520g), high degree of dehydration, heart rate (HR = 60 / min), pale mucous membranes and poor reactivity. Meloxicam (1 mg/kg) and tramadol (10 mg/kg) were administered subcutaneously and the patient was placed in an incubator with access to fresh oxygen. Four hours later, the combination of tiletamine - zolazepam (10 mg/kg) was administered intramuscularly for induction of anesthesia. The snake was intubated and connected to inhalant anesthesia equipment. For maintenance, the anesthesia isoflurane in pure oxygen was used due to apnea, which occurs 30 minutes after the induction semi-closed system was attached and the ventilator was turned on (PCV system, four breaths per minute, 8 cm of H2O). Cardiopulmonary parameters (HR, RR, SPO2, ETCO2, ETISO) were assessed throughout the procedure. During the entire procedure, the operating room was heated to a temperature of 26 degrees Celsius. Additionally, the hose was placed on a heating mat, which maintained a temperature of 30 degrees Celsius. For 15 minutes after induction, the loss of muscle tone was observed from the head to the tail. Induction of general anesthesia was scored as good because of the possibility of intubation. During the whole procedure, the heart rate was at the rate of 58 beats per minute (bpm). Ventilation parameters were stable throughout the procedure. The recovery period lasts for about 4 hours after the end of general anesthesia. The muscle tension returned from tail to head. The snake started to breathe spontaneously within 1,5 hours after the end of general anesthesia. The protocol of general anesthesia with the combination of tiletamine- zolazepam with a dose of 10 mg/kg is useful for proceeding with the emergency coeliotomy in maintenance with isoflurane in oxygen. Further study about the impact of the combination of tiletamine- zolazepam for the recovery period is needed.

Keywords: anesthesia, corallus hortulanus, ovoviparous, snake, tiletamine, zolazepam

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Authors: U. V. Okpala

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Flood is an overflow of water that submerges or ‘drowns’ land. In developing countries it occurs as a result of blocking of natural and man-made drainages and poor maintenance of water dams/reservoirs which seldom give way after persistent heavy down pours. In coastal lowlands and swamp lands, flooding is aided mainly by blocked channels and indiscriminate sand fling of coastal swamp areas and natural drainage channel for urban development/constructions. In this paper, the causes of flood and possible scientific, technological, political, economic and social impacts of flood disaster on the environment a case study of Anambra State have been studied. Often times flooding is caused by climate change, especially in the developed economy where scientific mitigating options are highly employed. Researchers have identified Green Houses Gases (GHG) as the cause of global climate change. The recent flood disaster in Anambra State which caused physical damage to structures, social dislocation, contamination of clean drinking water, spread of water-borne diseases, shortage of crops and food supplies, death of non-tolerant tree species, disruption in transportation system, serious economic loss and psychological trauma is a function of climate change. There is need to encourage generation of renewable energy sources, use of less carbon intensive fuels and other energy efficient sources. Carbon capture/sequestration, proper management of our drainage systems and good maintenance of our dams are good option towards saving the environment.

Keywords: flooding, climate change, carbon capture, energy systems

Procedia PDF Downloads 375

Authors: Brian Ceh, Alison Jackson-Holland

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Food deserts are a reality in some cities. These deserts can be described as a shortage of healthy food options within close proximity of consumers. The shortage in this case is typically facilitated by a lack of stores in an urban area that provide adequate fruit and vegetable choices. This study explores new avenues to better understand food deserts by examining modes of transportation that are available to shoppers or consumers, e.g. walking, automobile, or public transit. Further, this study is unique in that it not only explores the location of large grocery stores, but small grocery and convenience stores too. In this study, the relationship between some socio-economic indicators, such as personal income, are also explored to determine any possible association with food deserts. In addition, to help facilitate our understanding of food deserts, complex network spatial models that are built on adequate algorithms are used to investigate the possibility of food deserts in the city of Hamilton, Canada. It is found that Hamilton, Canada is adequate serviced by retailers who provide healthy food choices and that the food desert phenomena is almost absent.

Keywords: Canada, desert, food, Hamilton, store

Procedia PDF Downloads 241

Authors: Soroor Ghaziof, Wei Gao

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Zn alloy and composite coatings are widely used in buildings and structures, automobile and fasteners industries to protect steel component from corrosion. In this paper, Zn-Ni-Al2O3 nano-composite coatings were electrodeposited on mild steel using a novel sol enhanced electroplating method. In this method, transparent Al2O3 sol was added into the acidic Zn-Ni bath to produced Zn-Ni-Al2O3 nano-composite coatings. The effect of alumina sol on the electrodeposition process, and coating properties was investigated using cyclic voltammetry, XRD, ESEM and Tafel test. Results from XRD tests showed that the structure of all coatings was single γ-Ni5Zn21 phase. Cyclic voltammetry results showed that the electrodeposition overpotential was lower in the presence of alumina sol in the bath, and caused the reduction potential of Zn-Ni to shift to more positive values. Zn-Ni-Al2O3 nano composite coatings produced more uniform and compact deposits, with fine grained microstructure when compared to Zn-Ni coatings. The corrosion resistance of Zn-Ni coatings was improved significantly by incorporation of alumina nano particles into the coatings.

Keywords: Zn-Ni-Al2O3 composite coatings, steel, sol-enhanced electroplating, corrosion resistance

Procedia PDF Downloads 392

Authors: Tarek Hassan, Sanaa Abouras

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Some factors such as interaction of migration process, cultural identity have an impact in a way that may lead to cultural disinheritance. Even if migrants' culture would not be lost, it may be affected by the new society culture. Therefore, it is anticipated that migration of an ethnic group would impact the culture of that group. Nubians; an ethnic group originated in South Egypt, have experienced migration that took place in the sixties of the past century. Nubians were forced to leave their origin land and relocate to Kom Ombo; an Egyptian town to the north of Aswan. The effect of migration on national culture, social homogeneity or the interest of social contact influences the attitudes of natives towards migration. Hence, it is very important for societies to help migrants to adapt to the new culture and at the same time not to impede migrants' effort to maintain their own culture. This study aims to investigate the effect of internal migration on the culture of Egyptian Nubians in order to predict if Nubian can maintain their own culture after the migration. Research question: what is the cultural influence of Nubians' migration from Egyptian Nubia to their new destinations? The researchers' hypothesis: there is mutual influence between the two cultures of Nubians and non-Nubians in Egypt. Results supported researchers' hypothesis as they observed that the Nubians managed to reserve balance between the maintenance of their own culture and the adoption of some cultural features of the community of their new destination(s). Also, the study examined why Nubians adhere to their culture although they left their land forever. Questionnaire and interviews were used to collect data from 80 informants; 40 Nubians and 40 non-Nubians in Kom-Ombo and the two cities of Cairo and Alexandria. Results suggested that there is obvious mutual cultural impact between Nubians and non-Nubians. The findings of this study would trigger the researchers to conduct further research on minorities for the deeper understanding of the impact of/on the culture of minorities.

Keywords: culture change, culture influence, culture maintenance, minority migration

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Authors: Einat E. Peles, Shaul Schreiber, Miriam Adelson

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Background: Since established more than 50 years ago, methadone maintenance treatment (MMT) is the most effective treatment for opioid addiction, a chronic relapsing brain disorder that became an epidemic in western societies. Treatment includes daily individual optimal medication methadone dose (a long acting mu opioid receptor full agonist), accompanied with psychosocial therapy. It is well established that the longer retention in treatment the better outcome and survival occur. It reduces the likelihood to infectious diseases and overdose death that associated with drug injecting, enhanced social rehabilitation and eliminate criminal activity, and lead to healthy productive life. Aim: To evaluate predictors for long term retention in treatment we analyzed our prospective follow up of a major MMT clinic affiliated to a big tertiary medical center. Population Methods: Between June 25, 1993, and June 24, 2016, all 889 patients ( ≥ 18y) who ever admitted to the clinic were prospectively followed-up until May 2017. Duration in treatment from the first admission until the patient quit treatment or until the end of follow-up (24 years) was taken for calculating cumulative retention in treatment using survival analyses (Kaplan Meier) with log-rank and Cox regression for multivariate analyses. Results: Of the 889 patients, 25.2% were females who admitted to treatment at younger age (35.0 ± 7.9 vs. 40.6 ± 9.8, p < .0005), but started opioid usage at same age (22.3 ± 6.9). In addition to opioid use, on admission to MMT 58.5% had positive urine for benzodiazepines, 25% to cocaine, 12.4% to cannabis and 6.9% to amphetamines. Hepatitis C antibody tested positive in 55%, and HIV in 7.8% of the patients and 40%. Of all patients, 75.7% stayed at least one year in treatment, and of them, 67.7% stopped opioid usage (based on urine tests), and a net reduction observed in all other substance abuse (proportion of those who stopped minus proportion of those who have started). Long term retention up to 24 years was 8.0 years (95% Confidence Interval (CI) 7.4-8.6). Predictors for longer retention in treatment (Cox regression) were being older on admission ( ≥ 30y) Odds Ratio (OR) =1.4 (CI 1.1-1.8), not abusing opioids after one year OR=1.8 (CI 1.5-2.1), not abusing benzodiazepine after one year OR=1.7 (CI 1.4-2.1) and treating with methadone dose ≥ 100mg/day OR =1.8 (CI 1.5-2.3). Conclusions: Treating and following patients over 24 years indicate success of two main outcomes, high rate of retention after one year (75.7%) and high proportion of opiate abuse cessation (67.7%). As expected, longer cumulative retention was associated with patients treated with high adequate methadone dose that successfully result in opioid cessation. Based on these findings, in order to reduce morbidity and mortality, we find the establishment of more MMT clinics within a general hospital, a most urgent necessity.

Keywords: methadone maintenance treatment, epidemic, opioids, retention

Procedia PDF Downloads 192

Authors: Bedilu Tafesse

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Conservation of crop genetic resources presents a challenge of identifying specific determinants driving maintenance of diversity at farm and agroecosystems. The objectives of this study were to identify socioeconomic, market and agroecological determinants of farmers’ maintenance of wheat diversity at the household level and derive implications for policies in designing on-farm conservation programs. We assess wheat diversity at farm level using household survey data. A household decision making model is conceptualized using microeconomic theory to assess and identify factors influencing on-farm rice diversity. The model is then tested econometrically by using various factors affecting farmers’ variety choice and diversity decisions. The findings show that household-specific socioeconomic, agroecological and market factors are important in determining on-farm wheat diversity. The significant variables in explaining richness and evenness of wheat diversity include distance to the nearest market, subsistence ratio, modern variety sold, land types and adult labour working in agriculture. The statistical signs of the factors determining wheat diversity are consistent in explaining the richness, dominance and evenness among rice varieties. Finally, the study implies that the cost-effective means of promoting and sustaining on-farm conservation programmes is to target them in market isolated geographic locations of high crop diversity where farm households have more heterogeneity of agroecological conditions and more active family adult labour working on-farm.

Keywords: diversity indices, dominance, evenness, on-farm conservation, wheat diversity, richness

Procedia PDF Downloads 308