Search results for: undesirable outputs

Authors: Bahram Fathi, Seyedhossein Sajadifar, Naser Khiabani

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Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as byproducts of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 12 OPEC countries and the results obtained are presented.

Keywords: energy efficiency, undesirable outputs, data envelopment analysis

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Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

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Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

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Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

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Global awareness on energy security and climate change has created much interest in assessing energy efficiency performance. A number of previous studies have contributed to evaluate energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production frame work of desirable and undesirable outputs, in this paper we construct energy efficiency performance index for measuring energy efficiency performance by using environmental DEA model with CO2 emissions. We finally apply the index proposed to assess the energy efficiency performance in OPEC over time.

Keywords: energy efficiency, environmental, OPEC, data envelopment analysis

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Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

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Authors: Huey-Kuo Chen

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This paper applies directional marginal productivity model to study the shadow price of emissions by transportation modes in the years of 2011 and 2013 with the aim to provide a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) generated by road transportation modes were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the directional shadow price (DSP) of SOx is much higher than CO2 and NOx. Nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting public transportation and subsidizing electric vehicles to reduce the use of private vehicles.

Keywords: marginal productivity, road transportation modes, shadow price, undesirable outputs

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Authors: Elias K. Maragos, Petros E. Maravelakis

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In Dynamic Data Envelopment Analysis (DDEA), which is a subfield of Data Envelopment Analysis (DEA), the productivity of Decision Making Units (DMUs) is considered in relation to time. In this case, as it is accepted by the most of the researchers, there are outputs, which are produced by a DMU to be used as inputs in a future time. Those outputs are known as intermediates. The common models, in DDEA, do not take into account the shape of the distribution of those inputs, outputs or intermediates data, assuming that the distribution of the virtual value of them does not deviate from linearity. This weakness causes the limitation of the accuracy of the analytical power of the traditional DDEA models. In this paper, the authors, using the concept of piecewise linear inputs and outputs, propose an extended DDEA model. The proposed model increases the flexibility of the traditional DDEA models and improves the measurement of the dynamic performance of DMUs.

Keywords: Dynamic Data Envelopment Analysis, DDEA, piecewise linear inputs, piecewise linear outputs

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Authors: Farzad Sharifi, Raziyeh Shamsi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose molti-objective DEA-R model, because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduces the efficiency score), an efficient DMU is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other case, only the ratio of stochastic data may be available (e.g; the ratio of stochastic inputs to stochastic outputs). Thus, we provide multi objective DEA model without explicit outputs and prove that in-put oriented MOP DEA-R model in the invariable return to scale case can be replacing by MOP- DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model, yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA, MOLP, STOCHASTIC, DEA-R

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Authors: A. Novikova, L. Rocchi, G. Startiene

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Market and non-market outputs are produced jointly in agriculture. Their supply depends on the intensity and type of production. The role of agriculture as an economic activity and its effects are important for the Lithuanian case study, as agricultural land covers more than a half of country. Positive and negative externalities, created in agriculture are not considered in the market. Therefore, specific techniques such as stated preferences methods, in particular choice experiments (CE) are used for evaluation of non-market outputs in agriculture. The main aim of this paper is to present construction of the research path for evaluation of non-market farming system outputs in Lithuania. The conventional and organic farming, covering crops (including both cereal and industrial crops) and livestock (including dairy and cattle) production has been selected. The CE method and nested logit (NL) model were selected as appropriate for evaluation of non-market outputs of different farming systems in Lithuania. A pilot survey was implemented between October–November 2018, in order to test and improve the CE questionnaire. The results of the survey showed that the questionnaire is accepted and well understood by the respondents. The econometric modelling showed that the selected NL model could be used for the main survey. The understanding of the differences between organic and conventional farming by residents was identified. It was revealed that they are more willing to choose organic farming in comparison to conventional farming.

Keywords: choice experiments, farming system, Lithuania market outputs, non-market outputs

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Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper deals with a stabilization problem for multi-agent systems, when all agents in a multi-agent system receive the same broadcasting control signal and the controller can measure not each agent output but the sum of all agent outputs. It is analytically shown that when the sum of all agent outputs is bounded with a certain broadcasting controller for a given reference, each agent output is separately bounded:stabilization of the sum of agent outputs always results in the stability of every agent output. A numerical example is presented to illustrate our theoretic findings in this paper.

Keywords: broadcasting control, multi-agent system, transfer function, stabilization

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Authors: Sead A. Bakheet, Salah M. Elkoum, Asharaf A. Almaghribi

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Disturbance defined as activity that malfunction, intrusion, or interruption. We have to look around for the source of the disturbance affecting the inputs and outputs of engineering projects, take the necessary actions to control them. In this paper we will present and discuss a production system consisting of three elements, inputs, the production process and outputs. The production process which we chose is the production of large diameter pre-stressed concrete cylinder pipes (out puts), in reality, the outputs are the starting points of the operation (laying the concrete pipes for transporting drinkable water). The main objective also to address the controlling methods of the natural resources and raw materials (basic inputs), study the disturbances affecting them as well as the output quality. The importance of making the right decision, which effect the final product quality will be summarized. Finally, we will address the proposals regarding the managing of secure water supply to the customers.

Keywords: disturbances, management, inputs, outputs, decision

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Authors: Sanghoon Park, Ki-Jin Kim, Kwang-Ho Ahn

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This paper discusses the undesirable charge transfer through the parasitic capacitances of the input transistors in a multi-inputs voltage sense amplifier. Its intrinsic rail-to-rail voltage transitions at the output nodes inevitably disturb the input sides through the capacitive coupling between the outputs and inputs. Then, it can possible degrade the stabilities of the reference voltage levels. Moreover, it becomes more serious in multi-channel systems by altering them for other channels, and so degrades the linearity of the overall systems. In order to alleviate the internal node voltage transition, the internal node stabilization techniques are proposed. It achieves 45% and 40% improvements for node stabilization and input referred disturbance, respectively.

Keywords: voltage sense amplifier, multi-inputs, voltage transition, node stabilization, biasing circuits

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Authors: Thitima Plejai

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The practice in the operating room has been continually performed according to standards of services; however, undesirable incidents from surgical services are found such as surgical complications in the operating room. This participation action research aimed to develop practice guidelines for surgical safety management to reduce undesirable incidents from surgical services in the operating room of Songkhla Hospital. The target population was all 84 members of the multidisciplinary team who were involved in surgical services in the operating room consisting of 28 surgeons from five branches of surgery, 27 anesthetists and nurse anesthetists, and 29 surgical nurses. The data were collected through in-depth interviews, and non-participatory observations. The research instrument was tested by three experts, and the steps of the development consisted of four cycles, each consisting of assessment, planning, practice, practice reflection, and improvement until every step is practicable. The data were validated through triangulation research method, analyzed through content analysis and statistical analysis with number and percentage. The results of the development of practice guidelines surgical safety management to reduce undesirable incidents from surgical services could be concluded as follows. 1) The multidisciplinary team in surgery participated in the needs assessment for development of practice guidelines for surgical patient safety, and agreed on adapting the WHO Surgical Safety Checklists for use. 2) The WHO Surgical Safety Checklists was implemented, and meetings were held for the multidisciplinary team in surgery and the organizational risk committee to improve the practice guidelines to make them more practicable. 3) The multidisciplinary team consisting of surgeons from five branches of surgery, anesthetists, nurse anesthetists, surgical nurses, and the organizational risk committee announced policy on safety for surgical patients; the organizational risk committee designated the Surgical Safety Checklist as an instrument for surgical patient safety. The results of the safety management found that the surgical team members who could follow 100 percent of the guidelines were: professional nurses who checked patient identity and information before taking the patient to the operating room and kept complete records of data on the patients; surgical nurses who checked readiness of the patient before surgery; nurse anesthetists who assessed readiness before administering anesthetic drugs, and confirmed correctness of the patient; and circulating perioperative nurses who gave confirmation to the surgical team after completion of the surgery. The rates of undesirable incidents (surgical complications rates) before and after the implementation of the surgical safety management were 1.60 percent and 0.66 percent, respectively. The satisfaction of the surgery-related teams towards the use of the guidelines was 89 percent. The practice guidelines for surgical safety management to reduce undesirable incidents were taken as guidelines for surgical safety that the multidisciplinary team involved in the surgical process implemented correctly and in the same direction and clearly reduced undesirable incidents in surgical patients.

Keywords: practice guidelines, surgical safety management, reduce undesirable incidents, operating Room

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Authors: Diandra Cristache

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The transition of traditional manuscript studies into the digital framework closely affects the methodological premises upon which manuscript descriptions are modeled, created, and questioned for the purpose of research. This paper intends to explore the issue by presenting a methodological investigation into the process of modeling, creating, and questioning manuscript metadata. The investigation is founded on a close observation of the Polonsky Greek Manuscripts Project, a collaboration between the Universities of Cambridge and Heidelberg. More than just providing a realistic ground for methodological exploration, along with a complete metadata set for computational demonstration, the case study also contributes to a broader purpose: outlining general methodological principles for making the most out of manuscript metadata by means of research-oriented digital outputs. The analysis mainly focuses on the scholarly approach to manuscript descriptions, in the specific instance where the act of metadata recording does not have a programmatic research purpose. Close attention is paid to the encounter of 'traditional' practices in manuscript studies with the formal constraints of the digital framework: does the shift in practices (especially from the straight narrative of free writing towards the hierarchical constraints of the TEI encoding model) impact the structure of metadata and its capability to respond specific research questions? It is argued that flexible structure of TEI and traditional approaches to manuscript description lead to a proliferation of markup: does an 'encyclopedic' descriptive approach ensure the epistemological relevance of the digital outputs to metadata? To provide further insight on the computational approach to manuscript metadata, the metadata of the Polonsky project are processed with techniques of distant reading and data networking, thus resulting in a new group of digital outputs (relational graphs, geographic maps). The computational process and the digital outputs are thoroughly illustrated and discussed. Eventually, a retrospective analysis evaluates how the digital outputs respond to the scientific expectations of research, and the other way round, how the requirements of research questions feed back into the creation and enrichment of metadata in an iterative loop.

Keywords: digital manuscript studies, digital outputs to manuscripts metadata, metadata interoperability, methodological issues

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. Entropy-Based Principle is the principle with which we could estimate the unknown distribution under some limited conditions. As this paper defines two processes in Feed-Forward Neural Network, our limited condition is the abstracted features of samples which are worked out in the abstraction process. And the final outputs are the probability distribution for different clusters in the clustering process. As Entropy-Based Principle is considered into the feed-forward neural network, a clustering method is born. We have conducted some experiments on six open UCI data sets, comparing with a few baselines and applied purity as the measurement. The results illustrate that our method outperforms all the other baselines that are most popular clustering methods.

Keywords: feed-forward neural network, clustering, max-entropy principle, probabilistic models

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Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

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According to 1404 forecasting documentation, among the most fundamental ways of Iran’s success in competition with other regional countries are innovations, efficiency enhancements and domestic productivity. Therefore, in this study, the energy consumption efficiency of Iran and the neighbor countries has been measured in the period between 2007-2012 considering the simultaneous economic activities, CO2 emission, and consumption of energy through data envelopment analysis of undesirable output. The results of the study indicated that the energy efficiency changes in both Iran and the average neighbor countries has been on a descending trend and Iran’s energy efficiency status is not desirable compared to the other countries in the region.

Keywords: energy efficiency, environmental, undesirable output, data envelopment analysis

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Authors: Hsu-Yung Cheng, Kuo-Chang Hsu, Chi-Chang Chan, Mei-Hui Tseng, Chih-Chang Yu, Ya-Sheng Liu

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Photovoltaics modules are usually not installed horizontally to avoid water or dust accumulation. However, the measured irradiance data on tilted surfaces are rarely available since installing pyranometers with various tilt angles induces high costs. Therefore, estimating solar irradiance on tilted surfaces is an important research topic. In this work, artificial neural networks (ANN) are utilized to construct the transfer model to estimate solar irradiance on tilted surfaces. Instead of predicting tilted irradiance directly, the proposed method estimates the differences between the horizontal irradiance and the irradiance on a tilted surface. The outputs of the ANNs in the proposed design are differential values. The experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy compared to ANNs that estimate the titled irradiance directly.

Keywords: photovoltaics, artificial neural networks, tilted irradiance, solar energy

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Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: John Ayisi, Gideon M. Kivengea, George A. Ombakho

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In this emerging era of knowledge economy, universities, as major centres of learning and research, are becoming increasingly important as sources of ideas, knowledge, skills, innovation and technological advances. These ideas can be turned into new products, processes and systems needed to drive their respective national economies, and thus placing universities at the centre of the national innovation systems. Thus, commercialization of research outputs from universities to industry has become an area of strong policy interest in African countries. To assess the level of commercialization of research outputs in Kenyan universities, a standardized questionnaire covering seven sub-sections, namely: University Commercialization Environment, Management of Commercialization Activities, Commercialization Office, Intellectual Property Rights (IPRs), Early Stage Financing and Venture Capital; Industrial Linkages; and Technology Parks and Incubators was administered among a few selected public and private universities. Results show that all the universities have a strategic plan; though not all have innovation and commercialization as part of it. Half the nineteen surveyed universities indicated they have created designated offices for fostering commercialization. Majority have guidelines on IPRs which advocate IP to be co-owned by researcher/university. University-industry linkages are weak. Most universities are taking precursory steps to incentivise and encourage entrepreneurial activities among their academic staff and students, even though the level of resources devoted to them is low. It is recommended that building capacity in entrepreneurship among staff and students and committing more resources to R&D activities hold potential to increased commercialization of university research outputs.

Keywords: commercialization, knowledge, R&D, university

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Authors: Juan-Gabriel Cegarra-Navarro, Alexeis Garcia-Perez, Denise Bedford

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This paper provides guidelines for what constitutes a knowledge worker. Many graduates from non-managerial domains adopt, at some point in their professional careers, management roles at different levels, ranging from team leaders through to executive leadership. This is particularly relevant for professionals from an engineering background. Moving from a technical to an executive-level requires an understanding of those behaviour management techniques that can motivate and support individuals and their performance. Further, the transition to management also demands a shift of contextual enablers from tangible to intangible resources, which allows individuals to create new capacities, competencies, and capabilities. In this dynamic process, the knowledge worker becomes that key individual who can help members of the management board to transform information into relevant knowledge. However, despite its relevance in shaping the future of the organization in its transition to the knowledge economy, the role of a knowledge worker has not yet been studied to an appropriate level in the current literature. In this study, the authors review both the contextual enablers and behaviour outputs related to the role of the knowledge worker and relate these to their ability to deal with everyday management issues such as knowledge heterogeneity, varying motivations, information overload, or outdated information. This study highlights that the aggregate of capacities, competences and capabilities (CCCs) can be defined as knowledge structures, the study proposes several contextual enablers and behaviour outputs that knowledge workers can use to work cooperatively, acquire, distribute and knowledge. Therefore, this study contributes to a better comprehension of how CCCs can be managed at different levels through their contextual enablers and behaviour outputs.

Keywords: knowledge workers, capabilities, capacities, competences, knowledge structures

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Authors: Debrah Mtshelwane, Alewyn Nel, Lizelle Brink

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Social desirability is an important topic to study. It may be possible that different cultures experience social desirability in different ways. Different cultural groups exist within South Africa, however the focus of this study is specifically in the Zulu culture. This research aims to explore social desirability from an emic perspective within the social constructivist paradigm among individuals within the Zulu culture. The researcher intended to identify those features Zulu individuals deem as socially desirable and undesirable from their cultural viewpoint. The research was conducted using a qualitative research design and the constructivism paradigm was utilised in this study. Combined purposive and quota non-probability sampling was employed for this study. A sample of 30 employees (N = 30) working in various organisations from the provinces of Gauteng and KwaZulu-Natal formed part of this study and data were collected through semi-structured interviews. Thematic analysis was used to analyse the data. The main findings showed that Zulu people regard certain behaviours and actions as socially desirable and others as undesirable. The following are considered socially desirable: Conscientiousness, dominance, subjective expectations and positive relations, these are the themes that were reported on the most. These are positive features in the Zulu culture, and they reflect on behaviour patterns, attitudes and manners that people display, which are also seen as acceptable and good in the Zulu culture. The following are regarded as socially undesirable features that were identified by people who belong to the Zulu culture, the themes that were identified as undesirable are: non-conscientiousness, non-dominance (male), dominance (females), tradition, negative relations and subjective expectations. This study creates awareness on social desirability in the workplace and provides basic tools to management on how to deal with such behaviours relating to this phenomenon in the workplace. This knowledge informs employees on the concept of socially desirable behaviour, and provide more insight into behaviours and/or emotions Zulu individuals. The outcome of this study provided new indigenous, empirical knowledge on the phenomenon of social desirability within the South African context.

Keywords: cultural diversity, emic perspective, social constructivism paradigm, social desirability, Zulu culture

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Authors: Chandimal Jayawardena, Ridmal Mendis, Manoji Tennakoon, Theekshana Wijayathilaka, Randima Marasinghe

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This research paper defines the research area of the implementation of the socially assistive robot (SLIITBOT). It consists of the overall process implemented within the robot’s system and limitations, along with a literature survey. This project considers developing a socially assistive robot called SLIITBOT that will interact using its voice outputs and graphical user interface with people within the university and benefit them with updates and tasks. The robot will be able to detect a person when he/she enters the room, navigate towards the position the human is standing, welcome and greet the particular person with a simple conversation using its voice, introduce the services through its voice, and provide the person with services through an electronic input via an app while guiding the person with voice outputs.

Keywords: application, detection, dialogue, navigation

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Authors: Farzad Alaeimoghadam, Farnaz Alaeimoghadam

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Plants are always being threatened by biotic and abiotic elements in their abode. Although they have inherited mechanisms to defend themselves, sometimes due to overpowering of their enemies or weakening of themselves, they just suffer from those elements. Human, as to help plants defend themselves, have developed several methods among which application of terpenes via plant biotechnology is promising. Terpenes are the most frequent and diverse secondary metabolites in plants. In these plants, terpenes are involved in different protective aspects. In this field, by utilizing biotechnological approaches on them, a delicate, precise, and an economic intervention will be achieved. In this review, first, the importance of terpenes as guardians in plants, which include their allelopathy effect, a call for alliances, and a mitigation impact on abiotic stresses will be pointed out. Second, problems concerning terpenes application in plant biotechnology comprising: damage to cell, undesirable terpene production and undesirable concentration and proportion of terpenes will be discussed. At the end, the approaches in plant biotechnology of terpenes including tampering with terpene gene sequences, compartmentalization, and localization and utilization of membrane transporters will be expressed. It is concluded with some useful notions concerning the topic.

Keywords: plant biotechnology, plant protection, terpenes, terpenoids

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Abhisek Dash

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This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

Procedia PDF Downloads 324

Authors: Kamel A. Elshorbagy, Mohamed A. Hussein, Rola S. Afify

Abstract:

Natural gas pressure reduction is typically achieved using pressure reducing valves, where isenthalpic expansion takes place with considerable amount of wasted energy in an irreversible throttling process of the gas. Replacing gas-throttling process by an expansion process in a turbo expander (TE) converts the pressure of natural gas into mechanical energy transmitted to a loading device (i.e. an electric generator). This paper investigates the performance of a turboexpander system for power recovery at natural gas pressure reduction stations. There is a considerable temperature drop associated with the turboexpander process. Essential preheating is required, using gas fired boilers, to avoid undesirable effects of a low outlet temperature. Various system configurations were simulated by the general flow sheet simulator HYSYS and factors affecting the overall performance of the systems were investigated. Power outputs and fuel requirements were found using typical gas flow variation data. The simulation was performed for two case studies in which real input data are used. These case studies involve a domestic (commercial) and an industrial natural gas pressure reduction stations in Egypt. Economic studies of using the turboexpander system in both of the two natural gas pressure reduction stations are conducted using precise data obtained through communication with several companies working in this field. The results of economic analysis, for the two case studies, prove that using turboexpander systems in Egyptian natural gas reduction stations can be a successful project for energy conservation.

Keywords: natural gas, power recovery, reduction stations, turboexpander systems

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Authors: Chen Jun

Abstract:

This study investigates the impact of family involvement, a pivotal factor shaping the management structure of family firms, on the firm’s innovation outputs. The independent variable focuses on the percentage number of family members serving as directors, supervisors and senior management. Our hypothesis suggests that family involvement tends to make management more conservative, thereby increasing the likelihood of impeding innovation investments and resulting in adverse effects on innovation output. Our findings reveal that Chinese family firms with high family involvement exhibit poorer innovation outputs compared to those with lower family involvement. Subsample analyses indicate that this negative influence of family involvement on innovation output is strengthened as the firm faces higher industry competition and a low marketization context. The findings of our paper contribute to the literature on family involvement by empirically illustrating how family involvement hinders innovation efforts and performance in Chinese family firms.

Keywords: family firm, family involvement, firm innovation, Chinese family firm

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Authors: Thomas Ogilegwu Orohu

Abstract:

This paper highlights the effect of education on farmers’ productivity in rural Nigeria which includes potential to obtain paid employment or generate income through self-help employment using skills learnt in school. The paper emphasizes that education help farmers’ in agro-processing units in production to reduce post harvest wastage. It highlights the benefits of schooling for farmers’ productivity, particularly in terms of efficiency gains and increased farm productivity. As technological innovation spread more widely within the country, the importance of formal education in farm production ought to become more apparent. Education help farmers to improve attitudes, beliefs and habits that may lead to greater willingness to accept risk, adopts innovation, save investment and generally to embrace productive practices. Finally factors affecting farmers’ education and appropriate recommendation were given with the hope that if resolutely implemented would bring the attainment of desired farm education to farmers to improve farm productivity outputs.

Keywords: benefit, education, effect, productivity

Procedia PDF Downloads 318