Search results for: demand estimation

Authors: Mykola G. Boichuk

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The paper concerns predatory pricing incentives and mechanisms in the markets of services, as well as its anti-competitive effects. As cost estimation at services markets is more complex in comparison to markets of goods, predatory pricing is more difficult to detect in the provision of services. For instance, this is often the case for professional services, which is analyzed in the paper. The special attention is given to employment markets as de-facto main supply markets for professional services markets. Also, the paper concerns such instances as travel agents' services, where predatory pricing may have implications not only on competition but on a wider range of public interest as well. Thus, the paper develops on effective ways to apply competition law rules on predatory pricing to the provision of services.

Keywords: employment markets, predatory pricing, services markets, unfair competition

Procedia PDF Downloads 317

Authors: Hassan Baji, Chun-Qing Li, Wei Yang

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Water seepage is one of the most common causes of damage in tunnel structures, which can cause direct and indirect e.g. reinforcement corrosion and calcium leaching damages. Estimation of water seepage or inflow is one of the main challenges in probabilistic assessment of tunnels. The methodology proposed in this study is an attempt for mathematically modeling the water seepage in tunnel structures and further predicting its service life. Using the time-dependent reliability, water seepage is formulated as a failure mode, which can be used for prediction of service life. Application of the formulated seepage failure mode to a case study tunnel is presented.

Keywords: water seepage, tunnels, time-dependent reliability, service life

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

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In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished through the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: analog to digital conversion, digitization, sampling rate, ultrasonic

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Authors: Max Moleke

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Manufacturing industries are faced with different types of problems. One of the most important role of controlling and monitoring a production process is to actually determine how to deal with unforeseen disruption when they arise. A majority of manufacturing tern to spend huge amount of money in order to meet up with their customers requirements and demand but due to instabilities within the manufacturing process, this objectives and goals are difficult to be achieved. In this research, we have developed a feedback control system that can minimize instability within the manufacturing system in order to boost the system output and productivity.

Keywords: disruption, scheduling, manufacturing, instability

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Authors: Ashhar Ahmed Shaikh, Ayush Tandon

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The swift reduction of fossil fuels from nature has crucial need for alternative energy sources to cater vital demand. It is essential to boost alternative energy sources to cover the continuously increasing demand for energy while minimizing the negative environmental impacts. Solar energy is one of the reliable sources that can generate energy. Solar energy is freely available in nature and is completely eco-friendly, and they are considered as the most promising power generating sources due to their easy availability and other advantages for the local power generation. This paper is to review the implementation of power electronic devices through Solar Energy Grid Integration System (SEGIS) to increase the efficiency. This paper will also concentrate on the future grid infrastructure and various other applications in order to make the grid smart. Development and implementation of a power electronic devices such as PV inverters and power controllers play an important role in power supply in the modern energy economy. Solar Energy Grid Integration System (SEGIS) opens pathways for promising solutions for new electronic and electrical components such as advanced innovative inverter/controller topologies and their functions, economical energy management systems, innovative energy storage systems with equipped advanced control algorithms, advanced maximum-power-point tracking (MPPT) suited for all PV technologies, protocols and the associated communications. In addition to advanced grid interconnection capabilities and features, the new hardware design results in small size, less maintenance, and higher reliability. The SEGIS systems will make the 'advanced integrated system' and 'smart grid' evolutionary processes to run in a better way. Since the last few years, there was a major development in the field of power electronics which led to more efficient systems and reduction of the cost per Kilo-watt. The inverters became more efficient and had reached efficiencies in excess of 98%, and commercial solar modules have reached almost 21% efficiency.

Keywords: solar energy grid integration systems, smart grid, advanced integrated system, power electronics

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Authors: O. Poleshchuk, E. Komarov

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This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

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Authors: G. Balakrishnan

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Stereo Correspondence plays a major role in estimation of distance of an object from the stereo camera pair for various applications. In this paper, a stereo correspondence algorithm based on block-matching technique is presented. Initially, an energy matrix is calculated for every disparity obtained using modified Sum of Absolute Difference (SAD). Higher energy matrix errors are removed by using threshold value in order to reduce the mismatch errors. A smoothening filter is applied to eliminate unreliable disparity estimate across the object boundaries. The purpose is to improve the reliability of calculation of disparity map. The experimental results obtained shows that the final depth map produce better results and can be used to all the applications using stereo cameras.

Keywords: stereo matching, filters, energy matrix, disparity

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Authors: Zhou Ziyi, Chen Qiuxiao, Wu Shuang

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Population diversification is very common in villages located in the developed coastal areas of China. Based on the analyses of the characteristics of the traditional rural society and its landscape, also in consideration of the diversified landscape demand due to the population diversification of the village, with the dual ideas of heritage and innovation, the ideas and methods of rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example.

Keywords: rural landscape, population diversification, landscape design, architecture

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Authors: Yong-Jun Kim, Jae-Hyun Ro, Chang-Bin Ha, Hyoung-Kyu Song

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This paper proposes the cooperative transmission scheme with pre-coding because the cellular communication requires high reliability. The cooperative transmission scheme uses pre-coding method with limited feedback information among small cells. Particularly, the proposed scheme has adaptive mode according to the position of mobile station. Thus, demand of recent wireless communication is resolved by this scheme. From the simulation results, the proposed scheme has better performance compared to the conventional scheme in the cellular network.

Keywords: CDD, cellular network, pre-coding, SPC

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Authors: Elena Carcano, Mirzi Betasolo

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This study helps Public Water Bureaus in giving reliable answers to water concession requests. Rapidly increasing water requests can be supported provided that further uses of a river course are not totally compromised, and environmental features are protected as well. Strictly speaking, a water concession can be considered a continuous drawing from the source and causes a mean annual streamflow reduction. Therefore, deciding if a water concession is appropriate or inappropriate seems to be easily solved by comparing the generic demand to the mean annual streamflow value at disposal. Still, the immediate shortcoming for such a comparison is that streamflow data are information available only for few catchments and, most often, limited to specific sites. Subsequently, comparing the generic water demand to mean daily discharge is indeed far from being completely satisfactory since the mean daily streamflow is greater than the water withdrawal for a long period of a year. Consequently, such a comparison appears to be of little significance in order to preserve the quality and the quantity of the river. In order to overcome such a limit, this study aims to complete the information provided by flow duration curves introducing a link between Flow Duration Curves (FDCs) and recession curves and aims to show the chronological sequence of flows with a particular focus on low flow data. The analysis is carried out on 25 catchments located in North-Eastern Italy for which daily data are provided. The results identify groups of catchments as hydrologically homogeneous, having the lower part of the FDCs (corresponding streamflow interval is streamflow Q between 300 and 335, namely: Q(300), Q(335)) smoothly reproduced by a common recession curve. In conclusion, the results are useful to provide more reliable answers to water request, especially for those catchments which show similar hydrological response and can be used for a focused regionalization approach on low flow data. A mathematical link between streamflow duration curves and recession curves is herein provided, thus furnishing streamflow duration curves information upon a temporal sequence of data. In such a way, by introducing assumptions on recession curves, the chronological sequence upon low flow data can also be attributed to FDCs, which are known to lack this information by nature.

Keywords: chronological sequence of discharges, recession curves, streamflow duration curves, water concession

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Muhammad Abdul Qyyum, Kinza Qadeer, Moonyong Lee

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Globally, liquefied natural gas (LNG) has drawn interest as a green energy source in comparison with other fossil fuels, mainly because of its ease of transport and low carbon dioxide emissions. It is expected that demand for LNG will grow steadily over the next few decades. In addition, because the demand for clean energy is increasing, LNG production facilities are expanding into new natural gas reserves across the globe. However, LNG production is an energy and cost intensive process because of the huge power requirements for compression and refrigeration. Therefore, one of the major challenges in the LNG industry is to improve the energy efficiency of existing LNG processes through economic and ecological strategies. The advancement in expansion devices such as two-phase cryogenic expander (TPE) and cryogenic hydraulic turbine (HT) were exploited for energy and cost benefits in natural gas liquefaction. Retrofitting the conventional Joule–Thompson (JT) valve with TPE and HT have the potential to improve the energy efficiency of LNG processes. This research investigated the potential feasibility of the retrofitting of a dual mixed refrigerant (DMR) process by replacing the isenthalpic expansion with isentropic expansion corresponding to energy efficient LNG production. To fully take the potential benefit of the proposed process retrofitting, the proposed DMR schemes were optimized by using a Coggins optimization approach, which was implemented in Microsoft Visual Studio (MVS) environment and linked to the rigorous HYSYS® model. The results showed that the required energy of the proposed isentropic expansion based DMR process could be saved up to 26.5% in comparison with the conventional isenthalpic based DMR process using the JT valves. Utilization of the recovered energy into boosting the natural gas feed pressure could further improve the energy efficiency of the LNG process up to 34% as compared to the base case. This work will help the process engineers to overcome the challenges relating to energy efficiency and safety concerns of LNG processes. Furthermore, the proposed retrofitting scheme can also be implemented to improve the energy efficiency of other isenthalpic expansion based energy intensive cryogenic processes.

Keywords: cryogenic liquid turbine, Coggins optimization, dual mixed refrigerant, energy efficient LNG process, two-phase expander

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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Authors: M. Bischoff, F. Schmidt, J. Herrmann, J. Mattheß, G. Seide, T. Gries

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Crop yields have not increased as dramatically as the demand for food. One method to counteract this is to use pesticides to keep away predators, e.g. several forms of insecticide are available to fight insects. These insecticides and pesticides are both controversial as their application and their residue in the food product can also harm humans. In this study an alternative method to combat insects is studied. A physical insect-killing effect of SiO₂ particles is used. The particles are applied on fibres to avoid erosion in the fields, which would occur when applied separately. The development of such SiO₂ functionalized PP fibres is shown.

Keywords: agriculture, environment, insects, protection, silica, textile

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: M. A. Ahmadu, S. S. Rabia

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During the past few decades, energy dissipation in the ionosphere resulting from the geomagnetic activity has caused an increasing number of major disruptions of important power and communication services, malfunctions and loss of expensive facilities. Here, the electron precipitation energy, w(ep) and joule heating energy, w(jh) was used in the computation of this dissipation using Østgaard’s empirical relation from hourly geomagnetic indices of 2012, under the assumption that the magnetosphere does not store any energy, so that at the beginning of the activity t1=0 and end at t2=t, the statistical results obtained show that ionospheric dissipation varies month to month, day to day and hour to hour and estimated with a value ~3.6 w(ep), which is in agreement with experimental result.

Keywords: Ostgaard's, ionospheric dissipation, joule heating, electron precipitation, geomagnetic indices, empirical relation

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Authors: Krishna Prasad Sharma

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Nepal’s financial sector has become deeper and wider, and the number and types of financial intermediaries have grown rapidly over the past two decades. However, access to financial services remains limited for many people in many parts of rural Nepal. While financial institutions have been expanding rapidly in an urban area in recent years, the access to the rural poor is excessively inadequate due to financial illiteracy and limited numbers of financial institutions that confined only to the district headquarters. Based on the focus group discussion, semi-structured interview of key people and literature review, this paper aims to examine the supply of and demand for financial services in Nepal and the constraints to increasing access to them, and offers way forward for making the financial sector work for all of Nepal’s people, especially the rural poor. While Nepal’s government has tried to increase access to formal financial services for small businesses and low-income households through directed lending programs for small businesses and low-income households, created specialized wholesale and retail institutions, and lowered market entry requirements, formal financial services are declining, and financial intermediation is stagnating. Supply and demand indicators show that, despite government efforts, formal financial institutions do not serve the needs of most of the Nepalese population. While access to and use of formal financial services are limited, in general, the problem is acute for small businesses and low-income households. Indeed, both access and use are closely correlated with business loan size and household income. This study concludes that banks and microfinance institutions with the use of mobile phones can connect hundreds of millions of unbanked and low-income people, especially rural poor to financial services at low costs. While there are many challenges ahead in expanding the service to rural areas, the mobile financial services will be beneficial that makes payments faster and cheaper, more convenient and accessible to a greater number of senders and recipients in rural areas. In rural areas, clients will benefit from money transfer and other mobile and online services.

Keywords: financial inclusion, financial enabling environment, microfinance, branchless banking, rural poor

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Authors: T. P. Muhammed Jamsheer

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This paper tries to explains some of differences between migrants and non-migrants households by taking ten indicators like land ownership, land distribution, lease in land, lease out land, demand of labour, supply of labour, land operational potential, holding of agriculture implements and livestock’s, irrigation potential of households and credit holding by the households of highly dry, drought affected, poverty stricken, multi caste and pluralistic sub castes village in very backward Mahabubnagar district of Andhra Pradesh. The paper is purely field work based research and conducted census survey of field work among the 298 households in highly dry village called Keppatta from Bhoothpur mandel. One of the main objectives of the paper is that, to find out the factors which differentiate migrants and non-migrants households and what are distress elements which forced the poor peasants migrants to outside the village. It concludes that among the migrants and non-migrants households and among the differences between the categories wise of both types of households, there are differences, except two indicators like lease in and lease out, all other indicators like land holding pattern, demand and supply of labour, land operation, irrigation potential, implements and livestock and credit facilities of migrants and non-migrants households shows that non-migrants have high share than the migrants households. This paper also showing the landed households are more migrants, means among the BC and FC households landed households are migrants while SC landless are more migrants which is contradictory to general/existing literatures conclusion that, landless are more migrant than landed households, here also showing that when the number of land in acres increases the share of SC is declining while the share of FC is increasing among the both migrants and non-migrants households. In the class wise SC households are more in distress situation than any other class and that might be leading to the highest share of migrants from the respective village. In the logistic econometric model to find out the relation between migration and other ten variables, the result shows that supply of labour, lease in of the land and size of the family are statically significantly related with migration and all other variables not significant relation with migration although the theoretical explanation shows the different results.

Keywords: class, migrants, non migrants, economic indicators, distress factors

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Authors: Eva L. Sanjuán, Jacinto Martín, M. Isabel Parra, Mario M. Pizarro

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In Extreme Value Theory, inference estimation for the parameters of the distribution is made employing a small part of the observation values. When block maxima values are taken, many data are discarded. We developed a new Bayesian inference model to seize all the information provided by the data, introducing informative priors and using the relations between baseline and limit parameters. Firstly, we studied the accuracy of the new model for three baseline distributions that lead to a Gumbel extreme distribution: Exponential, Normal and Gumbel. Secondly, we considered mixtures of Normal variables, to simulate practical situations when data do not adjust to pure distributions, because of perturbations (noise).

Keywords: bayesian inference, extreme value theory, Gumbel distribution, highly informative prior

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Authors: Enes Huylu, Sude Erkin, Nur A. Özdemir, Hatice K. Güney, Cemre S. Atılgan, Hüseyin Y. Altıntaş, Aysemin Top, Muammer Yılman, Özak Durmuş

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Remanufacturing (reman) applications allow manufacturers to contribute to the circular economy and help to introduce products with almost the same quality, environment-friendly, and lower cost. The objective of this study is to present that the carbon footprint of automotive spare parts used in vehicles could be reduced by reman applications based on Life Cycle Analysis which was framed with ISO 14040 principles. In that case, it was aimed to investigate reman applications for 21 parts in total. So far, research and calculations have been completed for the alternator, turbocharger, starter motor, compressor, manual transmission, auto transmission, and DPF (diesel particulate filter) parts, respectively. Since the aim of Ford Motor Company and Ford OTOSAN is to achieve net zero based on Science-Based Targets (SBT) and the Green Deal that the European Union sets out to make it climate neutral by 2050, the effects of reman applications are researched. In this case, firstly, remanufacturing articles available in the literature were searched based on the yearly high volume of spare parts sold. Paper review results related to their material composition and emissions released during incoming production and remanufacturing phases, the base part has been selected to take it as a reference. Then, the data of the selected base part from the research are used to make an approximate estimation of the carbon footprint reduction of the relevant part used in Ford OTOSAN. The estimation model is based on the weight, and material composition of the referenced paper reman activity. As a result of this study, it was seen that remanufacturing applications are feasible to apply technically and environmentally since it has significant effects on reducing the emissions released during the production phase of the vehicle components. For this reason, the research and calculations of the total number of targeted products in yearly volume have been completed to a large extent. Thus, based on the targeted parts whose research has been completed, in line with the net zero targets of Ford Motor Company and Ford OTOSAN by 2050, if remanufacturing applications are preferred instead of recent production methods, it is possible to reduce a significant amount of the associated greenhouse gas (GHG) emissions of spare parts used in vehicles. Besides, it is observed that remanufacturing helps to reduce the waste stream and causes less pollution than making products from raw materials by reusing the automotive components.

Keywords: greenhouse gas emissions, net zero targets, remanufacturing, spare parts, sustainability

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Authors: A. H. Nanher, N. P. Singh, Shashidhar Yadav, Sachin Tyagi

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Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals (including fertilizers). Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment the focus on enhancing the productivity during the Green Revolution coupled with total disregard of proper management of inputs and without considering the ecological impacts, has resulted into environmental degradation. To evaluate a new approach for site-specific nutrient management (SSNM). Large variation in initial soil fertility characteristics and indigenous supply of N, P, and K was observed among Field- and season-specific NPK applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine-tuned based on season-specific rules and field-specific monitoring of crop N status. The performance of SSNM did not differ significantly between high-yielding and low-yielding climatic seasons, but improved over time with larger benefits observed in the second year Future, strategies for nutrient management in intensive rice systems must become more site-specific and dynamic to manage spatially and temporally variable resources based on a quantitative understanding of the congruence between nutrient supply and crop demand. The SSNM concept has demonstrated promising agronomic and economic potential. It can be used for managing plant nutrients at any scale, i.e., ranging from a general recommendation for homogenous management of a larger domain to true management of between-field variability. Assessment of pest profiles in FFP and SSNM plots suggests that SSNM may also reduce pest incidence, particularly diseases that are often associated with excessive N use or unbalanced plant nutrition.

Keywords: nutrient, pesticide, crop, yield

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Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

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Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

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Authors: J. R. Wang, W. Y. Li, H. T. Lin, B. H. Lee, C. Shih, S. W. Chen

Abstract:

In this research, the TRACE/PARCS model of Lungmen ABWR has been developed for verification of ultimate response guideline (URG) efficiency. This ultimate measure was named as DIVing plan, abbreviated from system depressurization, water injection and containment venting. The simulation initial condition is 100% rated power/100% rated core flow. This research focuses on the estimation of the time when the fuel might be damaged with no water injection by using TRACE/PARCS first. Then, the effect of the reactor core isolation system (RCIC), control depressurization and ac-independent water addition system (ACIWA), which can provide the injection with 950 gpm are also estimated for the station blackout (SBO) transient.

Keywords: ABWR, TRACE, safety analysis, PARCS

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Authors: Chechen Liao, Pui-Lai To, Chiao-Ying Chen

Abstract:

An introduction of internet auction has significantly widened the pool of consumers who participate in auctions and increased the number of companies attempting to sell their products in an auction format. Previous research on auctions has focused almost exclusively on the behavior of professional bidders. In this study, we focus on the characteristic of seller, auction parameter and the effect of supply and demand, and examine these impacts on auction effectiveness. In particular, a framework for online auction effectiveness was developed. The framework will help researchers and practitioner to find ways to improve online auction effectiveness.

Keywords: Auction Effectiveness, Framework Developing, Online Auction, Selling Strategy

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Authors: Sylvain Fauveaux, T. Nowicki

Abstract:

Lightning protection is nowadays applied worldwide since the advent of international standards. Lightning protection is widely justified by the casualties and damages involved. As a matter of fact, the lightning business is constantly growing as more and more sensible areas need to be protected. However, the worldwide demand of copper materiel is increasing as well, its price too. Furthermore, the most frequently used method of protection is consuming a lot of copper. The copper production is also consuming a large amount of natural and power resources, not to mention the ecologic balance.

Keywords: ESEAT, Lightning protection , natural resources management, NF C 17-102, sustainable development

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Authors: Neumoin Anton Ivanovich, Opra Denis Pavlovich

Abstract:

Materials based on titanium oxide compounds are widely used in such areas as solar energy, photocatalysis, food industry and hygiene products, biomedical technologies, etc. Demand for them has also formed in the battery industry (an example of this is the commercialization of Li4Ti5O12), where much attention has recently been paid to the development of next-generation systems and technologies, such as sodium-ion batteries. This dictates the need to search for new materials with improved characteristics, as well as ways to obtain them that meet the requirements of scalability. One of the ways to solve these problems can be the creation of nanomaterials that often have a complex of physicochemical properties that radically differ from the characteristics of their counterparts in the micro- or macroscopic state. At the same time, it is important to control the texture (specific surface area, porosity) of such materials. In view of the above, among other methods, the hydrothermal technique seems to be suitable, allowing a wide range of control over the conditions of synthesis. In the present study, a method was developed for the preparation of mesoporous nanostructured sodium trititanate (Na2Ti3O7) with a hierarchical architecture. The materials were synthesized by hydrothermal processing and exhibit a complex hierarchically organized two-layer architecture. At the first level of the hierarchy, materials are represented by particles having a roughness surface, and at the second level, by one-dimensional nanotubes. The products were found to have high specific surface area and porosity with a narrow pore size distribution (about 6 nm). As it is known, the specific surface area and porosity are important characteristics of functional materials, which largely determine the possibilities and directions of their practical application. Electrochemical impedance spectroscopy data show that the resulting sodium trititanate has a sufficiently high electrical conductivity. As expected, the synthesized complexly organized nanoarchitecture based on sodium trititanate with a porous structure can be practically in demand, for example, in the field of new generation electrochemical storage and energy conversion devices.

Keywords: sodium trititanate, hierarchical materials, mesoporosity, nanotubes, hydrothermal synthesis

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Authors: G. W. Greubel, A. Kalam

Abstract:

This paper provides a review of the technical problems facing the South African electricity system and discusses a hypothetical ‘virtual grid’ concept that may assist in solving the problems. The proposed solution has potential application across emerging markets with constrained power infrastructure or for companies who wish to be entirely powered by renewable energy. South Africa finds itself at a confluence of forces where the national electricity supply system is constrained with under-supply primarily from old and failing coal-fired power stations and congested and inadequate transmission and distribution systems. Simultaneously, the country attempts to meet carbon reduction targets driven by both an alignment with international goals and a consumer-driven requirement. The constrained electricity system is an aspect of an economy characterized by very low economic growth, high unemployment, and frequent and significant load shedding. The fiscus does not have the funding to build new generation capacity or strengthen the grid. The under-supply is increasingly alleviated by the penetration of wind and solar generation capacity and embedded roof-top solar. However, this increased penetration results in less inertia, less synchronous generation, and less capability for fast frequency response, with resultant instability. The renewable energy facilities assist in solving the under-supply issues but merely ‘kick the can down the road’ by not contributing to grid stability or by substituting the lost inertia, thus creating an expanding issue for the grid to manage. By technically balancing its electricity demand and supply a company with facilities located across the country can be protected from the effects of load shedding, and thus ensure financial and production performance, protect jobs, and contribute meaningfully to the economy. By treating the company’s load (across the country) and its various distributed generation facilities as a ‘virtual grid’, which by design will provide ancillary services to the grid one is able to create a win-win situation for both the company and the grid.

Keywords: load shedding, renewable energy integration, smart grid, virtual grid, virtual power plant

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Authors: M. Golam Rabbi

Abstract:

Theme of wildlife crime is unique in Bangladesh. In earlier of 2010, wildlife crime was not designated as a crime, unlike other offenses. Forest Department and other enforcement agencies were not in full swing to find out the organized crime scene at that time and recorded few cases along with forest crime. However, after the establishment of Wildlife Crime Control Unitin 2012a, total of 374 offenses have been detected with 566 offenders and 37,039 wildlife and trophies were seized till November 2016. Most offenses seem to be committed outside the forests where the presence of the forest staff is minimal. Total detection percentage of offenses is not known, but offenders are not identified in 60% of detected cases (UDOR). Only 20% cases are decided by the courts even after eight years, conviction rate of the total disposal is 70.65%. Mostly six months imprisonment and BDT 5000 fine seems to be the modal penalty. The monetary value of wildlife crime in the country is approximate $0.72M per year and the maximum value counted for reptiles around $0.45M especially for high-level trafficking of geckos and turtles. The most common seizures of wildlife are birds (mynas, munias, parakeets, lorikeets, water birds, etc.) which have domestic demand for pet. Some other wildlife like turtles, lizards and small mammals are also on the list. Venison and migratory waterbirds often seized which has a large quantity demand for consuming at aristocratic level.Due to porous border and weak enforcement in border region poachers use the way for trafficking of geckos, turtles, and tortoises, snakes, venom, tiger and body parts, spotted deerskin, pangolinetc. Those have very high demand in East Asian countries for so-called medicinal purposes. The recent survey also demonstrates new route for illegal trade and trafficking for instance, after poaching of tiger and deer from the Sundarbans, the largest mangrove track of the planet to Thailand through the Bay of Bengal, sharks fins and ray fish through Chittagong seaport and directly by sea routes to Myanmar and Thailand. However, a good number of records of offense demonstrate the transition route from India to South and South East Asian countries. Star tortoises and Hamilton’s turtles are smuggled in from India which mostly seized at Benapole border of Jessore and Hazrat Shah Jajal International Airport of Dhaka, in very large numbers for transmission to East Asian countries. Most of the cases of wildlife trade routes leading to China, Thailand, Malaysia, and Myanmar. Most surprisingly African ivory was seized in Bangladesh recently, which was meant to be trafficked to the South-East Asia. However; forest department is working to fight against wildlife poaching, illegal trade and trafficking in collaboration with other law enforcement agencies. The department needs a clear mandate and to build technical capabilities for identifying, seizing and holding specimens. The department also needs to step out of the forests and must develop the capacity to surveillance and patrol all sensitive locations across the country.

Keywords: Bangladesh forest department, Sundarban, tiger, wildlife crime, wildlife trafficking

Procedia PDF Downloads 300