Search results for: Supply chain management

Authors: Amado, M. P., Amado, A., Poggi, F., Correia de Freitas, J.

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Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.

In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.

Keywords: Solar urban planning, solar smart city, urban development, energy efficiency.

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Authors: Francis O. Iyoha, Daniel E. Gberevbie, Charles T. Iruonagbe, Matthew E. Egharevba

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Cost of governance in Nigeria has become a challenge to development and concern to practitioners and scholars alike in the field of business and social science research. In the 2010 national budget of NGN4.6 trillion or USD28.75billion for instance, only a pantry sum of NGN1.8trillion or USD11.15billion was earmarked for capital expenditure. Similarly, in 2013, out of a total national budget of NGN4.92trillion or USD30.75billion, only the sum of NGN1.50trllion or USD9.38billion was voted for capital expenditure. Therefore, based on the data sourced from the Nigerian Office of Statistics, Central bank of Nigeria Statistical Bulletin as well as from the United Nations Development Programme, this study examined the causes of high cost of governance in Nigeria. It found out that the high cost of governance in the country is in the interest of the ruling class, arising from their unethical behaviour – corrupt practices and the poor management of public resources. As a result, the study recommends the need to intensify the war against corruption and mismanagement of public resources by government officials as possible solution to overcome the high cost of governance in Nigeria. This could be achieved by strengthening the constitutional powers of the various anti-corruption agencies in the area of arrest, investigation and prosecution of offenders without the interference of the executive arm of government either at the local, state or federal level.

Keywords: Capital expenditure, Cost of governance, recurrent expenditure, unethical behaviour.

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Authors: L. M. Ben Ali

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A retrospective study was undertaken to record the occurrence and pattern of fractures in small animals (dogs and cats) from year 2005 to 2010. A total of 650 cases were presented in small animal surgery unit out of which of 116 (dogs and cats) were presented with history of fractures of different bones. A total of 17.8% (116/650) cases were of fractures which constituted dogs 67% while cats were 23%. The majority of animals were intact. Trauma in the form of road side accident was the principal cause of fractures in dogs whereas as in cats it was fall from height. The ages of the fractured dog ranged from 4 months to 12 years whereas in cat it was from 4 weeks to 10 years. The femoral fractures represented 37.5% and 25% respectively in dogs and cats. Diaphysis, distal metaphyseal and supracondylar fractures were the most affected sites in dog and cats. Tibial fracture in dogs and cats represented 21.5% and 10% while humoral fractures were 7.9% and 14% in dogs and cats respectively. Humoral condyler fractures were most commonly seen in puppies aged 4 to 6 months. Fractured radius-ulna incidence was 19% and 14% in dogs and cats respectively. Other fractures recorded were of lumbar vertebrae, mandible and metacarpals etc. The management comprised of external and internal fixation in both the species. The most common internal fixation technique employed was Intramedullary fixation in long followed by other methods like stack or cross pinning, wiring etc as per findings in the cases. The cast bandage was used majorly as mean for external coaptation. The paper discusses the outcome of the case as per the technique employed.

Keywords: Animal, Fracture, Incidence, Occurrence.

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Authors: C. Ardil

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This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.

Keywords: Facility Location Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, Preference Programming, Location Selection, WSM, TOPSIS, VIKOR

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Authors: M. Vogiatzis, K. Perakis

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Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: land use/land cover, random forest, Landsat-8 OLI, Sentinel-2A MSI, Corine land cover

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Authors: Aaron A. R. Nwabude

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The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.

Keywords: VLE, Mathematical Concepts Acquisition, PilotStudy, SENs, KS4, Education, Teacher

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: L. Edirisinghe, Zhihong Jin, A. W. Wijeratne, R. Mudunkotuwa

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The virtual container yard is an effective solution to the container inventory imbalance problem which is a global issue. It causes substantial cost to carriers, which inadvertently adds to the prices of consumer goods. The virtual container yard is rooted in the fundamentals of container interchange between carriers. If carriers opt to interchange their excess containers with those who are deficit, a substantial part of the empty reposition cost could be eliminated. Unlike in other types of ships, cargo cannot be directly loaded to a container ship. Slots and containers are supplementary components; thus, without containers, a carrier cannot ship cargo if the containers are not available and vice versa. Few decades ago, carriers recognized slot (the unit of space in a container ship) interchange as a viable solution for the imbalance of shipping space. Carriers interchange slots among them and it also increases the advantage of scale of economies in container shipping. Some of these service agreements between mega carriers have provisions to interchange containers too. However, the interchange mechanism is still not popular among carriers for containers. This is the paradox that prevails in the liner shipping industry. At present, carriers reposition their excess empty containers to areas where they are in demand. This research applied factor analysis statistical method. The paper reveals that five major components may influence the virtual container yard namely organisation, practice and culture, legal and environment, international nature, and marketing. There are 12 variables that may impact the virtual container yard, and these are explained in the paper.

Keywords: Virtual container yard, imbalance, management, inventory.

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps.

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Authors: Adekunle O. Afolabi, Pekka Toivanen

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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: Recommendation systems, healthcare, internet of things, real-time, homecare.

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Authors: Mpai Mokoena, Nsenda Lukumwena

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South Africa is one of the driest countries in the world and is facing a water crisis. In addition to inadequate infrastructure and poor planning, the country is experiencing high rates of water wastage due to pipe leaks. This study outlines the level of water wastage and develops a smart solution to efficiently manage and reduce the effects of pipe leaks, while monitoring the situation before and after fixing the pipe leaks. To understand the issue in depth, a literature review of journal papers and government reports was conducted. A questionnaire was designed and distributed to the general public. Additionally, the municipality office was contacted from a managerial perspective. The analysis from the study indicated that the majority of the citizens are aware of the water crisis and are willing to participate positively to decrease the level of water wasted. Furthermore, the response from the municipality acknowledged that more practical solutions are needed to reduce water wastage, and resources to attend to pipe leaks swiftly. Therefore, this paper proposes a specific solution for municipalities, local plumbers and citizens to minimize the effects of pipe leaks. The solution provides web and mobile application platforms to report and manage leaks swiftly. The solution is beneficial to the country in achieving water security and would promote a culture of responsibility toward water usage.

Keywords: Urban Distribution Networks, leak management, mobile application, responsible citizens, water crisis, water security.

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: Offshore fields of hydrocarbons of the Baltic Sea, Development of offshore oil and gas fields, Optimization of the field development scheme, Solution of multi-criteria tasks in the oil and gas complex, Quality management of technical and technological processes.

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Authors: Y. H. Wang, C. C. Hsieh

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Good service design can increase organization revenue and consumer satisfaction while reducing labor and time costs. The problems facing consumers in the original serve model for eyewear and optical industry includes the following issues: 1. Insufficient information on eyewear products 2. Passively dependent on recommendations, insufficient selection 3. Incomplete records on progression of vision conditions 4. Lack of complete customer records. This study investigates the case of Kobayashi Optical, applying the Theory of Inventive Problem Solving (TRIZ) to develop innovative solutions for eyewear and optical industry. Analysis results raise the following conclusions and management implications: In order to provide customers with improved professional information and recommendations, Kobayashi Optical is suggested to establish customer purchasing records. Overall service efficiency can be enhanced by applying data mining techniques to analyze past consumer preferences and purchase histories. Furthermore, Kobayashi Optical should continue to develop a 3D virtual trial service which can allow customers for easy browsing of different frame styles and colors. This 3D virtual trial service will save customer waiting times in during peak service times at stores.

Keywords: Theory of inventive problem solving, service design, augmented reality, eyewear and optical industry.

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Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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Fuel cells have become one of the major areas of research in the academia and the industry. The goal of most fish farmers is to maximize production and profits while holding labor and management efforts to the minimum. Risk of fish kills, disease outbreaks, poor water quality in most pond culture operations, aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by control input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC.

Keywords: PEM fuel cell, Diffused aeration system, Artificialintelligence (AI) techniques, neural network control, fuzzy logiccontrol

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: Automated external defibrillator, medical emergency, fire and rescue services, response time, unmanned aerial system.

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Authors: Lindsay Fink, Sarha Smith-Moyo, Leanne W. Charlesworth

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In recent years, the number of individuals experiencing homelessness has increased in the United States. This paper analyzes 2019 data from 16 different emergency shelters in Monroe County, located in Upstate New York. The data were collected through the County’s Homeless Management Information System (HMIS), and individuals were de-identified and de-duplicated for analysis. The purpose of this study is to explore the basic characteristics of the homeless population in Monroe County, and the dynamics of shelter use. The results of this study showed gender as a significant factor when analyzing the relationship between demographic variables and recorded reasons for shelter entry. Results also indicated that age and ethnicity did not significantly influence odds of re-entering a shelter, but did significantly influence reasons for shelter entry. Overall, the most common recorded cause of shelter entry in 2019 in the examined county was eviction by primary tenant. Recommendations to better address recurrent shelter entry and potential chronic homelessness include more consideration for the diversity existing within the homeless population, and the dynamics leading to shelter stays, including enhanced funding and training for shelter staff, as well as expanded access to permanent supportive housing programs.

Keywords: Chronic homelessness, homeless shelter stays, permanent supportive housing, shelter population dynamics.

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: Air pollution, linear programming, mining, optimization, treatment technologies.

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Authors: Cecilia Perri, Vincenzo Corvello

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The aim of the present study is to investigate consumers' determinants of intention toward the adoption of Smart Grid solutions and technologies. Ajzen's Theory of Planned Behaviour (TPB) model is applied and tested to explain the formation of such adoption intention. An exogenous variable, taking into account the resistance to change of individuals, was added to the basic model. The elicitation study allowed obtaining salient modal beliefs, which were used, with the support of literature, to design the questionnaire. After the screening phase, data collected from the main survey were analysed for evaluating measurement model's reliability and validity. Consistent with the theory, the results of structural equation analysis revealed that attitude, subjective norm, and perceived behavioural control positively, which affected the adoption intention. Specifically, the variable with the highest estimate loading factor was found to be the perceived behavioural control, and, the most important belief related to each construct was determined (e.g., energy saving was observed to be the most significant belief linked with attitude). Further investigation indicated that the added exogenous variable has a negative influence on intention; this finding confirmed partially the hypothesis, since this influence was indirect: such relationship was mediated by attitude. Implications and suggestions for future research are discussed.

Keywords: Adoption of innovation, consumers behaviour, energy management, smart grid, theory of planned behaviour.

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Authors: Pegah Farshadmanesh, Jamshid Mohammadi, Mehdi Modares

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In nearly all earthquakes of the past century that resulted in moderate to significant damage, the occurrence of postearthquake fire ignition (PEFI) has imposed a serious hazard and caused severe damage, especially in urban areas. In order to reduce the loss of life and property caused by post-earthquake fires, there is a crucial need for predictive models to estimate the PEFI risk. The parameters affecting PEFI risk can be categorized as: 1) factors influencing fire ignition in normal (non-earthquake) condition, including floor area, building category, ignitability, type of appliance, and prevention devices, and 2) earthquake related factors contributing to the PEFI risk, including building vulnerability and earthquake characteristics such as intensity, peak ground acceleration, and peak ground velocity. State-of-the-art statistical PEFI risk models are solely based on limited available earthquake data, and therefore they cannot predict the PEFI risk for areas with insufficient earthquake records since such records are needed in estimating the PEFI model parameters. In this paper, the correlation between normal condition ignition risk, peak ground acceleration, and PEFI risk is examined in an effort to offer a means for predicting post-earthquake ignition events. An illustrative example is presented to demonstrate how such correlation can be employed in a seismic area to predict PEFI hazard.

Keywords: Fire risk, post-earthquake fire ignition (PEFI), risk management, seismicity.

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Authors: Masoud Nasri, Sadat Feiznia, Mohammad Jafari, Hasan Ahmadi

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Today, incorrect use of lands and land use changes, excessive grazing, no suitable using of agricultural farms, plowing on steep slopes, road construct, building construct, mine excavation etc have been caused increasing of soil erosion and sediment yield. For erosion and sediment estimation one can use statistical and empirical methods. This needs to identify land unit map and the map of effective factors. However, these empirical methods are usually time consuming and do not give accurate estimation of erosion. In this study, we applied GIS techniques to estimate erosion and sediment of Menderjan watershed at upstream Zayandehrud river in center of Iran. Erosion faces at each land unit were defined on the basis of land use, geology and land unit map using GIS. The UTM coordinates of each erosion type that showed more erosion amounts such as rills and gullies were inserted in GIS using GPS data. The frequency of erosion indicators at each land unit, land use and their sediment yield of these indices were calculated. Also using tendency analysis of sediment yield changes in watershed outlet (Menderjan hydrometric gauge station), was calculated related parameters and estimation errors. The results of this study according to implemented watershed management projects can be used for more rapid and more accurate estimation of erosion than traditional methods. These results can also be used for regional erosion assessment and can be used for remote sensing image processing.

Keywords: Erosion and sedimentation, Gully, Rill, GIS, GPS, Menderjan Watershed

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Authors: D. Garg, S. Luthra, A. Haleem

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Due to growing concern about environmental and social consequences throughout the world, a need has been felt to incorporate sustainability concepts in conventional manufacturing. This paper is an attempt to identify and evaluate drivers in implementing sustainable manufacturing in Indian context. Nine possible drivers for successful implementation of sustainable manufacturing have been identified from extensive review. Further, Decision Making Trial and Evaluation Laboratory (DEMATEL) approach has been utilized to evaluate and categorize these identified drivers for implementing sustainable manufacturing in to the cause and effect groups. Five drivers (Societal Pressure and Public Concerns; Regulations and Government Policies; Top Management Involvement, Commitment and Support; Effective Strategies and Activities towards Socially Responsible Manufacturing and Market Trends) have been categorized into the cause group and four drivers (Holistic View in Manufacturing Systems; Supplier Participation; Building Sustainable culture in Organization; and Corporate Image and Benefits) have been categorized into the effect group. “Societal Pressure and Public Concerns” has been found the most critical driver and “Corporate Image and Benefits” as least critical or the most easily influenced driver to implementing sustainable manufacturing in Indian context. This paper may surely help practitioners in better understanding of these drivers and their priorities towards effective implementation of sustainable manufacturing.

Keywords: Drivers, Decision Making Trial and Evaluation Laboratory (DEMATEL), India, Sustainable Manufacturing (SM).

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems.

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Authors: Abdullah M. Algarni, Yashwant K. Malaiya

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Some of the key aspects of vulnerability—discovery, dissemination, and disclosure—have received some attention recently. However, the role of interaction among the vulnerability discoverers and vulnerability acquirers has not yet been adequately addressed. Our study suggests that a major percentage of discoverers, a majority in some cases, are unaffiliated with the software developers and thus are free to disseminate the vulnerabilities they discover in any way they like. As a result, multiple vulnerability markets have emerged. In some of these markets, the exchange is regulated, but in others, there is little or no regulation. In recent vulnerability discovery literature, the vulnerability discoverers have remained anonymous individuals. Although there has been an attempt to model the level of their efforts, information regarding their identities, modes of operation, and what they are doing with the discovered vulnerabilities has not been explored.

Reports of buying and selling of the vulnerabilities are now appearing in the press; however, the existence of such markets requires validation, and the natures of the markets need to be analyzed. To address this need, we have attempted to collect detailed information. We have identified the most prolific vulnerability discoverers throughout the past decade and examined their motivation and methods. A large percentage of these discoverers are located in Eastern and Western Europe and in the Far East. We have contacted several of them in order to collect firsthand information regarding their techniques, motivations, and involvement in the vulnerability markets. We examine why many of the discoverers appear to retire after a highly successful vulnerability-finding career. The paper identifies the actual vulnerability markets, rather than the hypothetical ideal markets that are often examined. The emergence of worldwide government agencies as vulnerability buyers has significant implications. We discuss potential factors that can impact the risk to society and the need for detailed exploration.

Keywords: Risk management, software security, vulnerability discoverers, vulnerability markets.

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Authors: Fatemeh Behjati Ardakani, Fatemeh Khademian, Abbas Nowzari Dalini, Reza Ebrahimpour

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Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.

Keywords: Low resolution face recognition, Multilayered neuralnetwork, Mixture of experts neural network, Principal componentanalysis, Bicubic interpolation, Nearest neighbor interpolation.

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Authors: K. Okubo, Y. Kurihara, T. Kaburagi, K. Watanabe

Abstract:

Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: Brain activities, NIRS, PASAT, running shoes.

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Authors: Petr Gurný

Abstract:

One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the creditscoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: Credit-scoring Models, Multidimensional Subordinated Lévy Model, Probability of Default.

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Authors: S. A. Nta

Abstract:

Application of health risk assessment methods is important in order to comprehend the risk of human exposure to heavy metals and other dangerous pollutants. Four soil samples were collected at distances of 10, 20, 30 m and the control 100 m away from the dump site at depths of 0.3, 0.6 and 0.9 m. The collected soil samples were examined for Zn, Cu, Pb, Cd and Ni using standard methods. The health risks via the main pathways of human exposure to heavy metal were detected using relevant standard equations. Hazard quotient was calculated to determine non-carcinogenic health risk for each individual heavy metal. Life time cancer risk was calculated to determine the cumulative life cancer rating for each exposure pathway. The estimated health risk values for adults and children were generally lower than the reference dose. The calculated hazard quotient for the ingestion, inhalation and dermal contact pathways were less than unity. This means that there is no detrimental concern to the health on human exposure to heavy metals in contaminated soil. The life time cancer risk 5.4 × 10^-2 was higher than the acceptable threshold value of 1 × 10^-4 which is reflected to have significant health effects on human exposure to heavy metals in contaminated soil. Good hygienic practices are recommended to ease the potential risk to children and adult who are exposed to contaminated soils. Also, the local authorities should be made aware of such health risks for the purpose of planning the management strategy accordingly.

Keywords: Health risk assessment, pollution, heavy metals, soil.

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Authors: Nastaran Rezaei, Mohammad Saeed Mossadegh, Farhan Kocheyli, Khalil Talebi Jahromi, Aurang Kavousi

Abstract:

Integrated Pest Management (IPM) aims to combine biological and chemical strategies and measures, hence highlighting the study of acute toxicity and sub-lethal effects of pesticides comprehensively. The present research focused on the side effects of thiamethoxam and pirimicarb sub-lethal concentrations on demographic parameters of Diaeretiella rapae (McIntosh Laboratory) (Hymenoptera: Braconidae). Adult parasitoids were exposed to LC₂₅ of insecticides as well as distilled water as the control. The results showed that thiamethoxam adversely affected population parameters (r, λ, R₀, T), adults' longevity, females' oviposition period and mean fecundity, and a similar trend was obtained for pirimicarb with the exception of generation time (T), the latter did not significantly change compared to the control. The intrinsic rate of increase (r) in the control and those treated with pirimicarb and thiamethoxam were 0.2801, 0.2064, 0.1525 days^-1, respectively, and the sex ratio was biased toward females in all treatments. Furthermore, none of the insecticides influenced total pre-oviposition period (TPOP) and offspring emergence rate. In general, these results indicated that both insecticides potentially distort the demographic parameters of the parasitoid even at sub-lethal concentrations, and then they should not be considered for IPM program in the presence of D. rapae.

Keywords: Diaeretiella rapae, Lipaphis erysimi, life-table study, pirimicarb, thiamethoxam.

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Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

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Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: Factors of social innovation, methodological combination, social innovation process, supporting decision-making.

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Authors: Indiramma M., K. R. Anandakumar

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Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

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