Search results for: large privately owned enterprises

Authors: Muhammad Afiq Anaqi Bin Baharudin, Muhammad Izamuddin Bin Mohd Nasir, Syarifuddin Bin Sujuanda, Muhammad Syahmi Rusyaidi Bin Sham Suddin, Danish Hakimi Bin kamaruzaman, Muhammad Haqimi Nazim Bin Hasmanizam, Mohammad Akmal Zakwan Bin Amran, Muhammad Alparizi Bin Latif

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In particular, for small and medium enterprises (SMBs) in Malaysia, process safety management (PSM) is a crucial component of industrial safety. Limited resources, a lack of technical know-how, and linguistic and cultural obstacles are just a few of the difficulties SMBs in Malaysia encounter while putting PSM programmes into practice. A number of studies have emphasised the significance of leadership commitment, hazard identification and assessment, and employee involvement in the execution of effective PSM programmes, which are crucial for preventing accidents and incidents. In the literature, there has been a lot of discussion on the creation of specialised PSM frameworks for SMBs in Malaysia. Several studies have proposed implementation frameworks for PSM programmes that are based on recognised worldwide standards. Despite the significance of PSM in ensuring industrial safety, there are still a number of gaps in the literature on PSM in Malaysian SMBs. These gaps include the need for additional research on the efficiency of PSM programmes in reducing accidents and incidents in SMBs as well as the development of more specialised approaches to implementing PSM programmes in SMBs with limited resources and technical expertise. The goal of this review is to give a thorough overview of the body of research on PSM in Malaysian SMBs while highlighting important findings, points of contention, and knowledge gaps that need to be filled in.

Keywords: process safety management, occupational safety and health (OSH), small businesses, medium businesses, malaysia

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Authors: Xiaoxue Jin, Qiong Zhang

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The rapid influx and ongoing flow of young migrants in large cities, alongside the emergence and evolution of new social media, have led to increased interpersonal alienation and weakened place attachment. In the interplay between individuals and space, urban public spaces play a pivotal role in meeting the multifaceted needs of individuals and fostering a sense of attachment. This article aims to investigate the relationship between the place characteristics of public spaces and individuals' needs and perceptions, with an aim to identify the factors influencing place attachment among the youth. This study is conducted in the Shekou community of Shenzhen, focusing on the youth residents to evaluate their place attachment levels and to analyze their perceptions of the place characteristics of selected public spaces. The influencing factors of public spaces on place attachment were sorted out through detailed data analysis. Research has found that rapid urbanization has led to spatial homogenization and spatial segregation caused by uneven resource distribution, which in turn diminishes the utilization of public spaces. The social characteristics of public spaces, such as the quality of social activities and spatial openness, are critical in forming place attachment. In this research, place characteristics impacting place attachment are categorized, aiming to reconstruct the characteristics of public space places and use them as a medium to explore the place attachment of young people, promote their independent creation and participation in public life, and enhance the dynamism between individuals and spaces.

Keywords: place attachment, place characteristics, public spaces, spatial perception

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Sujata Upgupta, Prasoon Kumar Singh

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The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: forest, coal mining, indicators, vulnerability

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Authors: E. Al-Essa, R. Bello-Mendoza, D. G. Wareham

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Anaerobic batch experiments were conducted to investigate the effect of magnetite-supplementation (7 mM) on methane production from digested sludge undergoing two different microbial growth phases, namely fresh sludge (exponential growth phase) and degassed sludge (endogenous decay phase). Three different particle sizes were assessed: small (50 - 150 nm), medium (168 – 490 nm) and large (800 nm - 4.5 µm) particles. Results show that, in the case of the fresh sludge, magnetite significantly enhanced the methane production rate (up to 32%) and reduced the lag phase (by 15% - 41%) as compared to the control, regardless of the particle size used. However, the cumulative methane produced at the end of the incubation was comparable in all treatment and control bottles. In the case of the degassed sludge, only the medium-sized magnetite particles increased significantly the methane production rate (12% higher) as compared to the control. Small and large particles had little effect on the methane production rate but did result in an extended lag phase which led to significantly lower cumulative methane production at the end of the incubation period. These results suggest that magnetite produces a clear and positive effect on methane production only when an active and balanced microbial community is present in the anaerobic digester. It is concluded that, (i) the effect of magnetite particle size on increasing the methane production rate and reducing lag phase duration is strongly influenced by the initial metabolic state of the microbial consortium, and (ii) the particle size would positively affect the methane production if it is provided within the nanometer size range.

Keywords: anaerobic digestion, iron oxide, methanogenesis, nanoparticle

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Authors: Nosheen Fatima Warraich

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One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: M. Kamal, Y. Wang, R. Kennon

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Quality Function Deployment is a useful tool in product development with the application of voice of customer. In this paper, it aims to be applied as a product development tool in redesigning fashion and textile product. The purpose of these studies is to apply the effective use of Voice of Customer in redesigning cultural fashion product. The data collection from Voice of Customer or consumers’ feedback might help the producer to improve the quality of merchandise ahead. Voice of Customer could give a specific detailing for quality which needs to be redesigned according to customers’ requirements. Meanwhile, the next objective is to differentiate design specifications and characteristics using House of Quality. In product designing phase, it is very important to distinguish each specification and characteristic which translated from Voice of Customer to House of Quality matrix. This matrix would help designers to development according to qualities that customer wants for the better and successful product in the market. It is hope this research would indicate the customers’ requirements and production team idea might be measured and translated to a systematic data. The specific technical data could be planned ahead with specific design details as well. This could be a sustainable approach for a traditional product which could control the material that they use and sustain the quality as the past production. As a conclusion, this study would benefit the Small Medium Enterprises design team or the designers to style an item from customers view with organised projection of the product. The finding also could assist designers or batik producers’ to recognise specific details Batik sarong from consumers as well as in in advertising and marketing strategy plan.

Keywords: house of quality, Malaysia batik sarong, quality function deployment, voice of customer

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Authors: Irfan Ameer

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Bribery control in developing countries is the biggest challenge for multinational enterprises (MNEs). Bribery practices are socially embedded and institutionalized, and therefore may achieve collective legitimacy in the society. MNEs often have better and strict norms, codes and standards about such corrupt practices. Bribery in B2B sales relationships has been researched but studies focusing on the role of firm in controlling bribery are scarce. The main objective of this paper is to explore MNEs strategies to control bribery in an environment where bribery is institutionalized. This qualitative study uses narrative approach and focuses on key events, actors and their role in controlling bribery in B2B sales relationships. The context of this study is pharmaceutical industry of Pakistan and data is collected through 23 episodic interviews supported by secondary data. The Corporate social responsibility (CSR) literature e.g. CSR three domain model and CSR pyramid is used to make sense of MNEs strategies to control bribery in developing countries. Results show that MNEs’ bribery control strategies are rather emerging based on the role of some key stakeholders and events which shape bribery strategies. Five key bribery control strategies were found through which MNEs can control both demand and supply side of bribery: bribery related codes development; bribery related codes implementation; focusing on competitive advantage; find mutually beneficial ethical solution; and collaboration with ethical stakeholders. The results also highlight the problems associated with each strategy. Study is unique in a sense that it focuses on stakeholders having unethical interests and provides guidelines to MNEs in controlling bribery practices in B2B sales relationships.

Keywords: bribery, developing countries, CSR, narrative research, B2B sales, MNEs

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Authors: Oibar Martinez, Clara Oliver

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The Cherenkov Telescope Array Project (CTA) aims to build two different observatories of Cherenkov Telescopes, located in Cerro del Paranal, Chile, and La Palma, Spain. These facilities are used in this paper as a case study to investigate how to apply standard Directives on Electromagnetic Compatibility to astronomical observatories. Cherenkov Telescopes are able to provide valuable information from both Galactic and Extragalactic sources by measuring Cherenkov radiation, which is produced by particles which travel faster than light in the atmosphere. The construction requirements demand compliance with the European Electromagnetic Compatibility Directive. The largest telescopes of these observatories, called Large Scale Telescopes (LSTs), are high precision instruments with advanced photomultipliers able to detect the faint sub-nanosecond blue light pulses produced by Cherenkov Radiation. They have a 23-meter parabolic reflective surface. This surface focuses the radiation on a camera composed of an array of high-speed photosensors which are highly sensitive to the radio spectrum pollution. The camera has a field of view of about 4.5 degrees and has been designed for maximum compactness and lowest weight, cost and power consumption. Each pixel incorporates a photo-sensor able to discriminate single photons and the corresponding readout electronics. The first LST is already commissioned and intends to be operated as a service to Scientific Community. Because of this, it must comply with a series of reliability and functional requirements and must have a Conformité Européen (CE) marking. This demands compliance with Directive 2014/30/EU on electromagnetic compatibility. The main difficulty of accomplishing this goal resides on the fact that Conformité Européen marking setups and procedures were implemented for industrial products, whereas no clear protocols have been defined for scientific installations. In this paper, we aim to give an answer to the question on how the directive should be applied to our installation to guarantee the fulfillment of all the requirements and the proper functioning of the telescope itself. Experts in Optics and Electromagnetism were both needed to make these kinds of decisions and match tests which were designed to be made over the equipment of limited dimensions on large scientific plants. An analysis of the elements and configurations most likely to be affected by external interferences and those that are most likely to cause the maximum disturbances was also performed. Obtaining the Conformité Européen mark requires knowing what the harmonized standards are and how the elaboration of the specific requirement is defined. For this type of large installations, one needs to adapt and develop the tests to be carried out. In addition, throughout this process, certification entities and notified bodies play a key role in preparing and agreeing the required technical documentation. We have focused our attention mostly on the technical aspects of each point. We believe that this contribution will be of interest for other scientists involved in applying industrial quality assurance standards to large scientific plant.

Keywords: CE marking, electromagnetic compatibility, european directive, scientific installations

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Dušan Bojović, Wei Huang, Zdravko Stojanović, Jovan Ilić

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In an era of ever-growing electricity generation from renewable energy sources, namely wind and solar, a need for reliable energy storage and intensive balancing of the electric power system gains significance. For decades, pump storage hydroelectric power plants have proven to be an important asset regarding the storage of generated electricity. However, with the increasing overall share of wind and solar in electric systems at large, the importance of electric grid stability keeps growing. A large pump storage project, the Bistrica Pump Storage Plant (PSP), is currently under development in Serbia. The Bistrica PSP will be designed as a 600+ MW power plant, which is envisaged as a significant contributor to the Serbian power grid stability as more and more renewable energy sources are implemented over time. PSP Bistrica is seen as a strategically important project on the green agenda path of the Electric Power Industry of Serbia as a necessary pre-condition for the safe implementation of other renewable energy sources. The importance of such a plant would also play an important role in reducing the electricity production from coal, i.e., thermoelectric power plants. During the project’s development, various techniques and technologies are evaluated for the purpose of determining the optimum (the most profitable) solution. Over the course of this paper, these technologies – such as frequency-regulated pump turbines and ternary sets will be presented, with a detailed explanation of their possible application within the Bistrica PSP project and their relative advantages/disadvantages in this particular case.

Keywords: hydraulic turbines, pumped storage, renewable energy, competing technologies

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Authors: Ross J. Maestas

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Biofuels are derived from multiple renewable bioenergy feedstocks including animal fats, wood, starchy grains, and oil seeds. Transportation agencies have considered growing the latter two on underutilized and nontraditional lands that they manage, such as in the Right of Way (ROW), abandoned weigh stations, and at maintenance yards. These crops provide the opportunity to generate revenue or supplement fuel once converted and offer a solution to increasing fuel costs and instability by creating a ‘home-grown’ alternative. Biofuels are non-toxic, biodegradable, and emit less Green House Gasses (GHG) than fossil fuels, therefore allowing agencies to meet sustainability goals and regulations. Furthermore, they enable land managers to achieve soil erosion and roadside aesthetic strategies. The research sought to understand if the cultivation of a biofuel feedstock within the Arkansas State Highway Transportation Department’s (AHTD) managed and marginalized lands is feasible by identifying potential land areas and crops. To determine potential plots the parcel data was downloaded from Arkansas’s GIS office. ArcGIS was used to query the data for all variations of the names of property owned by AHTD and a KML file was created that identifies the queried parcel data in Google Earth. Furthermore, biofuel refineries in the state were identified to optimize the harvest to transesterification process. Agricultural data was collected from federal and state agencies and universities to assess various oil seed crops suitable for conversion and suited to grow in Arkansas’s climate and ROW conditions. Research data determined that soybean is the best adapted biofuel feedstock for Arkansas with camelina and canola showing possibilities as well. Agriculture is Arkansas’s largest industry and soybean is grown in over half of the state’s counties. Successful cultivation of a feedstock in the aforementioned areas could potentially offer significant employment opportunity for which the skilled farmers already exist. Based on compiled data, AHTD manages 21,489 acres of marginalized land. The result of the feasibility assessment offer suggestions and guidance should AHTD decide to further investigate this type of initiative.

Keywords: Arkansas highways, biofuels, renewable energy initiative, marginalized lands

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Authors: Abdul Mutolib, Yonariza Mahdi, Hanung Ismono

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The existence of forests is essential to human lives on earth, but its existence is threatened by forest deforestations and degradations. Forest deforestations and degradations in Indonesia is not only caused by the illegal activity by the company or the like, even today many cases in Indonesia forest damage caused by human activities, one of which cut down forests for agriculture and plantations. In West Sumatra, community forest management are the result supported the enactment of customary land tenure, including ownership of land within the forest. Indigenous forest management have a positive benefit, which gives the community an opportunity to get livelihood and income, but if forest management practices by indigenous peoples is not done wisely, then there is the destruction of forests and cause adverse effects on the environment. Based on intensive field works in Dhamasraya District employing some data collection techniques such as key informant interviews, household surveys, secondary data analysis, and satellite image interpretation. This paper answers the following questions; how the impact of forest management by local communities on forest conditions (foccus in Forest Production and Limited Production Forest) and knowledge of the local community on the benefits of forests. The site is a Nagari Bonjol, Dharmasraya District, because most of the forest in Dharmasraya located and owned by Nagari Bonjol community. The result shows that there is damage to forests in Dharmasraya because of forest management activities by local communities. Damage to the forest area of 33,500 ha in Dharmasraya because forests are converted into oil palm and rubber plantations with monocultures. As a result of the destruction of forests, water resources are also diminishing, and the community has experienced a drought in the dry season due to forest cut down and replaced by oil palm plantations. Knowledge of the local community on the benefits of low forest, the people considered that the forest does not have better benefits and cut down and converted into oil palm or rubber plantations. Local people do not understand the benefits of ecological and environmental services that forests. From the phenomena in Dharmasraya on land ownership, need to educate the local community about the importance of protecting the forest, and need a strategy to integrate forests management to keep the ecological functions that resemble the woods and counts the economic benefits for the welfare of local communities. One alternative that can be taken is to use forest management models agroforestry smallholders in accordance with the characteristics of the local community who still consider the economic, social and environmental.

Keywords: community, customary land, farmer plantations, and forests

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Authors: Shalini Singh, Sanjay K. Srivastava, Govind, Mukhtar. A. Khan, P. K. Singh

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Nanotechnology is revolutionizing the development of biosensors. Nanomaterials and nanofabrication technologies are increasingly being used to design novel biosensors. Sensitivity and other attributes of biosensors can be improved by using nanomaterials with unique chemical, physical, and mechanical properties in their construction. Silicon is a promising biomaterial that is non-toxic and biodegradable and can be exploited in chemical and biological sensing. Present study demonstrated the streptavidin–biotin interaction on silicon surfaces with different topographies such as flat and nanostructured silicon (nanowires) surfaces. Silicon nanowires with wide range of surface to volume ratio were prepared by electrochemical etching of silicon wafer. The large specific surface of silicon nanowires can be chemically modified to link different molecular probes (DNA strands, enzymes, proteins and so on), which recognize the target analytes, in order to enhance the selectivity and specificity of the sensor device. The interaction of streptavidin with biotin was carried out on 3-aminopropyltriethoxysilane (APTS) functionalized silicon surfaces. Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS) studies have been performed to characterize the surface characteristics to ensure the protein attachment. Silicon nanowires showed the enhance protein attachment, as compared to flat silicon surface due to its large surface area and good molecular penetration to its surface. The methodology developed herein could be generalized to a wide range of protein-ligand interactions, since it is relatively easy to conjugate biotin with diverse biomolecules such as antibodies, enzymes, peptides, and nucleotides.

Keywords: FTIR, silicon nanowires, streptavidin-biotin, XPS

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Authors: Reza Karimpour

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Ports play a decisive role in the EU's external and internal trade, as about 74% of imports and exports and 37% of exchanges go through ports. Although ports, especially Deep Sea Shipping (DSS) ports, are integral nodes within multimodal logistic flows, Short Sea Shipping (SSS) and inland waterways are not so well integrated. The automated vessels and supply chain optimisations for sustainable shortsea shipping (MOSES) project aims to enhance the short sea shipping component of the European supply chain by addressing the vulnerabilities and strains related to the operation of large containerships. The MOSES concept can be shortly described as a large containership (mother-vessel) approaching a DSS port (or a large container terminal). Upon her arrival, a combined intelligent mega-system consisting of the MOSES Autonomous tugboat swarm for manoeuvring and the MOSES adapted AutoMoor system. Then, container handling processes are ready to start moving containers to their destination via hinterland connections (trucks and/or rail) or to be shipped to destinations near small ports (on the mainland or island). For the first case, containers are stored in a dedicated port area (Storage area), waiting to be moved via trucks and/or rail. For the second case, containers are stacked by existing port equipment near-dedicated berths of the DSS port. They then are loaded on the MOSES Innovative Feeder Vessel, equipped with the MOSES Robotic Container-Handling System that provides (semi-) autonomous (un) feeding of the feeder. The Robotic Container-Handling System is remotely monitored through a Shore Control Centre. When the MOSES innovative Feeder vessel approaches the small port, where her docking is achieved without tugboats, she automatically unloads the containers using the Robotic Container-Handling System on the quay or directly on trucks. As a result, ports with minimal or no available infrastructure may be effectively integrated with the container supply chain. Then, the MOSES innovative feeder vessel continues her voyage to the next small port, or she returns to the DSS port. MOSES exploitation activity mainly aims to exploit research outcomes beyond the project, facilitate utilisation of the pilot results by others, and continue the pilot service after the project ends. By the mid-lifetime of the project, the exploitation plan introduces the reader to the MOSES project and its key exploitable results. It provides a plan for delivering the MOSES innovations to the market as part of the overall exploitation plan.

Keywords: automated vessels, exploitation, shortsea shipping, supply chain

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Julia Cristina Bonaldo, Christophe L. Martin, Severine Romero Baivier, Stephane Mazerat

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Alumina refractories are commonly used in steel and foundry industries. These refractories are prepared through a powder metallurgy route. They are a mixture of hard alumina particles and graphite platelets embedded into a soft carbonic matrix (binder). The powder can be cold pressed isostatically or uniaxially, depending on the application. The compact is then fired to obtain the final product. The quality of the product is governed by the microstructure of the composite and by the process parameters. The compaction behavior and the mechanical properties of the fired product depend greatly on the amount of each phase, on their morphology and on the initial microstructure. In order to better understand the link between these parameters and the macroscopic behavior, we use the Discrete Element Method (DEM) to simulate the compaction process and the fracture behavior of the fired composite. These simulations are coupled with well-designed experiments. Four mixes with various amounts of Al₂O₃ and binder were tested both experimentally and numerically. In DEM, each particle is modelled and the interactions between particles are taken into account through appropriate contact or bonding laws. Here, we model a bimodal mixture of large Al₂O₃ and small Al₂O₃ covered with a soft binder. This composite is itself mixed with graphite platelets. X-ray tomography images are used to analyze the morphologies of the different components. Large Al₂O₃ particles and graphite platelets are modelled in DEM as sets of particles bonded together. The binder is modelled as a soft shell that covers both large and small Al₂O₃ particles. When two particles with binder indent each other, they first interact through this soft shell. Once a critical indentation is reached (towards the end of compaction), hard Al₂O₃ - Al₂O₃ contacts appear. In accordance with experimental data, DEM simulations show that the amount of Al₂O₃ and the amount of binder play a major role for the compaction behavior. The graphite platelets bend and break during the compaction, also contributing to the macroscopic stress. Firing step is modeled in DEM by ascribing bonds to particles which contact each other after compaction. The fracture behavior of the compacted mixture is also simulated and compared with experimental data. Both diametrical tests (Brazilian tests) and triaxial tests are carried out. Again, the link between the amount of Al₂O₃ particles and the fracture behavior is investigated. The methodology described here can be generalized to other particulate materials that are used in the ceramic industry.

Keywords: cold compaction, composites, discrete element method, refractory materials, x-ray tomography

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Authors: Finn Lannon, Jenny Roth, Roland Deutsch, Eric Igou

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The world continues to be rife with economic inequality, which has an impact on how people think and behaves in response to large and often growing gaps in wealth. Large gaps in earnings between groups within a particular organization, area or society can create tension between groups. Collective action tendencies (to protest, sign a petition, vote on behalf of an ingroup etc.) are also a growing phenomenon globally. Research shows that economic inequality promotes social processes such as appraisals of illegitimacy, which are recognized antecedents of collective action. This paper examines different types of collective action intentions among middle-status group members in response to economic inequality in two studies. Study 1 (N = 72) demonstrates a causal link between high economic inequality and collective action intentions of middle-status group members both to reduce inequality and to improve group status. A second pre-registered study (N = 432) examines key drivers of these relationships, including illegitimacy appraisals and direction of intergroup comparison. Adding to the current understanding of the topic, distinctions between the illegitimacy of one’s group status and the illegitimacy of societal inequality are found to mediate key relationships between economic inequality and relevant collective action types. The direction of intergroup comparison (upwards vs. downwards) is also shown to have a significant impact on collective action intentions to improve group status. Findings add to the understanding of the consequences of economic inequality and drivers of collective action intentions.

Keywords: economic inequality, collective action, legitimacy, social psychology

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Authors: Shutchapol Chopvitayakun

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Nowadays, especially for the last 5 years, mobile devices, mobile applications and mobile users, through the deployment of wireless communication and mobile phone cellular network, all these components are growing significantly bigger and stronger. They are being integrated into each other to create multiple purposes and pervasive deployments into every business and non-business sector such as education, medicine, traveling, finance, real estate and many more. Objective of this study was to develop a mobile application for seniors or last-year students who enroll the internship program at each tertiary school (undergraduate school) and do onsite practice at real field sties, real organizations and real workspaces. During the internship session, all students as the interns are required to exercise, drilling and training onsite with specific locations and specific tasks or may be some assignments from their supervisor. Their work spaces are both private and government corporates and enterprises. This mobile application is developed under schema of a transactional processing system that enables users to keep daily work or practice log, monitor true working locations and ability to follow daily tasks of each trainee. Moreover, it provides useful guidance from each intern’s advisor, in case of emergency. Finally, it can summarize all transactional data then calculate each internship cumulated hours from the field practice session for each individual intern.

Keywords: internship, mobile application, Android OS, smart phone devices, mobile transactional processing system, guidance and monitoring, tertiary education, senior students, model view controller (MVC)

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Authors: Deepika Verma, Runa Sarkar

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One of the prominent debates in the social entrepreneurship literature has been to establish whether entrepreneurial work for social well-being by for-profit organizations can be classified as social entrepreneurship or not. Of late, the scholarship has reached a consensus. It concludes that there seems little sense in confining social entrepreneurship to just non-profit organizations. Boosted by this research, increasingly a lot of businesses engaged in filling the social infrastructure gaps in developing countries are calling themselves social enterprise. These organizations are diverse in their ownership, size, objectives, operations and business models. The lack of a comprehensive definition of social enterprise leads to three issues. Firstly, researchers may face difficulty in creating a database for social enterprises because the choice of an entity as a social enterprise becomes subjective or based on some pre-defined parameters by the researcher which is not replicable. Secondly, practitioners who use ‘social enterprise’ in their vision/mission statement(s) may find it difficult to adjust their business models accordingly especially during the times when they face the dilemma of choosing social well-being over business viability. Thirdly, social enterprise and social entrepreneurship attract a lot of donor funding and venture capital. In the paucity of a comprehensive definitional guide, the donors or investors may find assigning grants and investments difficult. It becomes necessary to develop an exhaustive and objective definition of social enterprise and examine whether the understanding of the academicians and practitioners about social enterprise match. This paper develops a dictionary of words often associated with social enterprise or (and) social entrepreneurship. It further compares two lexicographic definitions of social enterprise imputed from the abstracts of academic journal papers and trade publications extracted from the EBSCO database using the ‘tm’ package in R software.

Keywords: EBSCO database, lexicographic definition, social enterprise, text mining

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Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

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Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Almaz Negash, Dessie Tibebe, Marye Mulugeta, Yezbie Kassa

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Large-scale textile industries use large amounts of toxic chemicals, which are very hazardous to human health and environmental sustainability. In this study, the removal of various dyes from effluents of textile industries using the electrocoagulation process was investigated. The studied dyes were Reactive Red 120 (RR-120), Basic Blue 3 (BB-3), and Basic Red 46 (BR-46), which were found in samples collected from effluents of three major textile factories in the Amhara region, Ethiopia. For maximum removal, the dye BB-3 required an acidic pH 3, RR120 basic pH 11, while BR-46 neutral pH 7 conditions. BB-3 required a longer treatment time of 80 min than BR46 and RR-120, which required 30 and 40 min, respectively. The best removal efficiency of 99.5%, 93.5%, and 96.3% was achieved for BR-46, BB-3, and RR-120, respectively, from synthetic wastewater containing 10 mg L1of each dye at an applied potential of 10 V. The method was applied to real textile wastewaters and 73.0 to 99.5% removal of the dyes was achieved, Indicating Electrocoagulation can be used as a simple, and reliable method for the treatment of real wastewater from textile industries. It is used as a potentially viable and inexpensive tool for the treatment of textile dyes. Analysis of the electrochemically generated sludge by X-ray Diffraction, Scanning Electron Microscope, and Fourier Transform Infrared Spectroscopy revealed the expected crystalline aluminum oxides (bayerite (Al(OH)3 diaspore (AlO(OH)) found in the sludge. The amorphous phase was also found in the floc. Textile industry owners should be aware of the impact of the discharge of effluents on the Ecosystem and should use the investigated electrocoagulation method for effluent treatment before discharging into the environment.

Keywords: electrocoagulation, aluminum electrodes, Basic Blue 3, Basic Red 46, Reactive Red 120, textile industry, wastewater

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Authors: Tian Yangyang, Xu Zihe, Lu Junping, Yang Jizhou, Xu Yiqun, Wang Jiansong, Chen Chao, Yang Mengmeng, Guo Jianhua, Mu Wenjun, Wang Guiyao, Xue Chaoqun, Liang Taibo, Hu Liwei

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Cherry-red tobacco is receiving constant attention from cigarette enterprises because of its special flavor. This study aims to explore the material basis for the formation of the characteristic flavor of cherry-red tobacco and to clarify the distribution characteristics of the acidic aroma component groups in its mainstream smoke. In order to reach the aims of current study, this study employs GC/MS to examine the differences of distribution characteristics in particulate matter of mainstream cigarette smoke between cherry-red and common tobacco, meanwhile the aroma activity values (OVA) was used to compare the contribution of acidic aroma of cherry-red tobacco. The results showed that: 1) Isovaleric acid, acetic acid and butyric acid were the key acidic components in the mainstream smoke of the samples, followed by 3-methylvaleric acid, 4-methylvaleric acid and n-valeric acid. 2)Analysis of the release of these key sour fragrance components showed that the acidic aroma of "YUN 85" mainstream smoke was stronger than the leaf group, cherry-red tobacco was the weakest. In addition, aging had the effect of reducing the acidic components of cherry-red tobacco and the addition of cherry-red tobacco had little effect on the acidic components of the original leaf group. 3) For 14 acidic aroma(OAV>1) in smoke of cherry-red tobacco, 3-methylpentanoic acid, 4-methylpentanoic acid, pentanoic acid, and isovaleric acid were very prominent in contributing to acidic aroma, while pyruvic acid, 2-methylbutyric acid, hydrogenated acid, and propionic acid were less contribution.

Keywords: cherry-red tobacco, acidic aroma, GC/MS, mainstream cigarette smoke, odor activity value

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Authors: Hassan Parandvar, Mehrdad Farid

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In this paper, a finite element modeling is presented for large amplitude vibration of functionally graded material (FGM) plates subjected to combined random pressure and thermal load. The material properties of the plates are assumed to vary continuously in the thickness direction by a simple power law distribution in terms of the volume fractions of the constituents. The material properties depend on the temperature whose distribution along the thickness can be expressed explicitly. The von Karman large deflection strain displacement and extended Hamilton's principle are used to obtain the governing system of equations of motion in structural node degrees of freedom (DOF) using finite element method. Three-node triangular Mindlin plate element with shear correction factor is used. The nonlinear equations of motion in structural degrees of freedom are reduced by using modal reduction method. The reduced equations of motion are solved numerically by 4th order Runge-Kutta scheme. In this study, the random pressure is generated using Monte Carlo method. The modeling is verified and the nonlinear dynamic response of FGM plates is studied for various values of volume fraction and sound pressure level under different thermal loads. Snap-through type behavior of FGM plates is studied too.

Keywords: nonlinear vibration, finite element method, functionally graded material (FGM) plates, snap-through, random vibration, thermal effect

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Authors: Abdelghani Boudiaf

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The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Keywords: changing mentalities, continuing training, organizational learning, quality management system, skills development

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Authors: Marina Kapsali, John S. Anagnostopoulos

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Greek islands’ interconnection (IC) with larger power systems, such as the mainland grid, is a crucial issue that has attracted a lot of interest; however, the recent economic recession that the country undergoes together with the highly capital intensive nature of this kind of projects have stalled or sifted the development of many of those on a more long-term basis. On the other hand, most of Greek islands are still heavily dependent on the lengthy and costly supply chain of oil imports whilst the majority of them exhibit excellent potential for wind energy (WE) applications. In this respect, the main purpose of the present work is to investigate −through a parametric study which varies both in wind farm (WF) and submarine IC capacities− the impact of large-scale WE development on the IC of the third in size island of Greece (Lesbos) with the mainland system. The energy and economic performance of the system is simulated over a 25-year evaluation period assuming two possible scenarios, i.e. S(a): without the contribution of the local Thermal Power Plant (TPP) and S(b): the TPP is maintained to ensure electrification of the island. The economic feasibility of the two options is investigated in terms of determining their Levelized Cost of Energy (LCOE) including also a sensitivity analysis on the worst/reference/best Cases. According to the results, Lesbos island IC presents considerable economic interest for covering part of island’s future electrification needs with WE having a vital role in this challenging venture.

Keywords: electricity generation cost, levelized cost of energy, mainland grid, wind energy rejection

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Authors: Piyaphan Changwatchai

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Global value chain is important for current world economy through foreign direct investment. Multinational enterprises' efficient location seeking for each stage of production lead to global production network and more global value chain participation of several countries. Global value chain participation has several effects on participating countries in several aspects including the environment. The effect of global value chain participation on the environment is ambiguous. As a result, this research aims to study the effect of global value chain participation on countries' CO₂ emission and methane emission by using quantitative analysis with secondary panel data of sixty countries. The analysis is divided into two types of global value chain participation, which are forward global value chain participation and backward global value chain participation. The results show that, for forward global value chain participation, GDP per capita affects two types of pollutants in downward bell curve shape. Forward global value chain participation negatively affects CO₂ emission and methane emission. As for backward global value chain participation, GDP per capita affects two types of pollutants in downward bell curve shape. Backward global value chain participation negatively affects methane emission only. However, when considering Asian countries, forward global value chain participation positively affects CO₂ emission. The recommendations of this research are that countries participating in global value chain should promote production with effective environmental management in each stage of value chain. The examples of policies are providing incentives to private sectors, including domestic producers and MNEs, for green production technology and efficient environment management and engaging in international agreements in terms of green production. Furthermore, government should regulate each stage of production in value chain toward green production, especially for Asia countries.

Keywords: CO₂ emission, environment, global value chain participation, methane emission

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