Search results for: loss distribution approach

Authors: Jo Rhodes, Bruce Bergstrom, Peter Lok, Vincent Cheng

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The aim of this study is to determine key factors and processes for multinationals (MNCs) to develop an effective stakeholder engagement and sustainable development framework. A qualitative multiple-case approach was used. A triangulation method was adopted (interviews, archival documents and observations) to collect data on three global firms (MNCs). 9 senior executives were interviewed for this study (3 from each firm). An initial literature review was conducted to explore possible practices and factors (the deductive approach) to sustainable development. Interview data were analysed using Nvivo to obtain appropriate nodes and themes for the framework. A comparison of findings from interview data and themes, factors developed from the literature review and cross cases comparison were used to develop the final conceptual framework (the inductive approach). The results suggested that stakeholder engagement is a key mediator between ‘stakeholder network’ (internal and external factors) and outcomes (corporate social responsibility, social capital, shared value and sustainable development). Key internal factors such as human capital/talent, technology, culture, leadership and processes such as collaboration, knowledge sharing and co-creation of value with stakeholders were identified. These internal factors and processes must be integrated and aligned with external factors such as social, political, cultural, environment and NGOs to achieve effective stakeholder engagement.

Keywords: stakeholder, engagement, sustainable development, shared value, corporate social responsibility

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Authors: R. Andreola, O. A. A. Santos, L. M. M. Jorge

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An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papé is, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.

Keywords: causticizing, lime, prediction, process

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Authors: Sara Cumming, Julianne DiSanto, Leah Burton

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Homelessness in Canada is a persistent problem. It has been widely argued that the best tactic for eradicating homelessness is to approach social issues from a Housing First perspective—an approach that centers on quickly moving people into permanent and independent housing and then providing them additional support and services as needed. It is recognized that life skills training is both necessary and an effective way to reduce cyclical homelessness; however, there is a scarcity of research on effective ways to teach life skills; this problem was exacerbated in a pandemic context, where in-person delivery was severely restricted or no longer possible. Very little attention has been paid to the diverse cultural needs of clients in a multicultural context and the need to foster cultural knowledge/awareness in individuals to successfully contribute to the cultural safety of communities. This research attempts to fill these gaps in the literature and in practice by employing a community-engaged research (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, equity, diversity, and inclusion (EDI) informed life skill learning management system. We employed a triangulation methodology for this research. An environmental scan was conducted for best practices. Two separate Creative Problem Solving Sessions were held with over 100 front-line workers, managers, and executive directors who work with homeless populations. Quantitative and open-ended surveys were completed by over 200 individuals with experience with homelessness. All sections of this research aimed to discover the areas of skills that individuals need to maintain housing and to ascertain what a more client-driven EDI approach to life skills training should include. This research will showcase which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, Housing First, life skills, community engaged research

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Hee Joon Lee

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There are many difficulties in measuring a small flow rate of an order of milli grams per minute (LPM) or less using a conventional flowmeter. Therefore, a flow meter with minimal loss and based on a new concept was designed as part of this paper. A chamber was manufactured with a level transmitter and an on-off control valve. When the level of the collected condensed water reaches the top of the chamber, the valve opens to allow the collected water to drain back into the tank. To allow the water to continue to drain when the signal is lost, the valve is held open for a few seconds by a time delay switch and then closed. After an examination, the condensing flow rate was successfully measured with the uncertainty of ±5.7% of the full scale for the chamber.

Keywords: chamber, condensation, flow meter, milli-grams

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Authors: José Carlos Rodríguez, Mario Gómez, Medardo Serna

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This paper analyses managing higher education institutions in emerging economies. The paper investigates the case of postgraduate studies development at public universities. In so doing, it adopts the complex theory approach to evaluate how postgraduate studies have evolved in these countries. The investigation suggests that the postgraduate studies sector at public universities can be seen as a complex adaptive system (CAS). Therefore, the paper adopts system dynamics (SD) methods to develop this analysis. The case of postgraduate studies at Universidad Michoacana de San Nicolás de Hidalgo in Mexico is investigated in this paper.

Keywords: complex adaptive systems, higher education institutions, Mexico, system dynamics

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Authors: Ekele Alih, Enejo Jalija

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Female Genital Mutilation (FGM) is made up of three types namely: Clitoridectomy, Excision and Infibulation. In this study, we examine the factors responsible for FGM in order to identify the causality variables in a logistic regression approach. From the result of the survey conducted by the Public Health Division, Nigeria Institute of Medical Research, Yaba, Lagos State, the tau statistic, τ was used to screen 9 factors that causes FGM in order to select few of the predictors before multiple regression equation is obtained. The need for this may be that the sample size may not be able to sustain having a regression with all the predictors or to avoid multi-collinearity. A total of 300 respondents, comprising 150 adult males and 150 adult females were selected for the household survey based on the multi-stage sampling procedure. The tau statistic,

Keywords: female genital mutilation, logistic regression, tau statistic, African society

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Authors: Nelson K. Lujara

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The performance characteristics of a photovoltaic induction motor drive water pumping system with and without maximum power tracker is analyzed and presented. The analysis is done through determination and assessment of critical loss components in the system using computer aided design (CAD) tools for optimal operation of the system. The results can be used to formulate a well-calibrated computer aided design package of photovoltaic water pumping systems based on the induction motor drive. The results allow the design engineer to pre-determine the flow rate and efficiency of the system to suit particular application.

Keywords: photovoltaic, water pumping, losses, induction motor

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Authors: Mina Mortazavi

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The common approach in the construction industry for restraint requirements in existing structures or new constructions is to have Non-Structural Components (NSCs) assembled and installed on-site by different MEP subcontractors. This leads to a lack of coordination and higher costs, construction time, and complications due to inaccurate building information modelling (BIM) systems. Introducing NSCs to a consistent BIM system from the beginning of the design process and considering their seismic loads in the analysis and design process can improve coordination and reduce costs and time. One solution is to use prefabricated mounts with attached MEPs delivered as an integral module. This eliminates the majority of coordination complications and reduces design and installation costs and time. An advanced approach is to have as many NSCs as possible installed in the same prefabricated module, which gives the structural engineer the opportunity to consider the involved component weights and locations in the analysis and design of the prefabricated support. This efficient approach eliminates coordination and access issues, leading to enhanced quality control. This research will focus on the existing literature on modular sub-assemblies that are integrated with architectural and structural components. Modular MEP systems take advantage of the precision provided by BIM tools to meet exact requirements and achieve a buildable design every time. Modular installations that include MEP systems provide efficient solutions for the installation of MEP services or components.

Keywords: building services, modularisation, prefabrication, integral building design

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Authors: Anjali G. Pillai, S. Chadrakaran

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The extensive amount of sludge generated throughout the world, as a part of water treatment works, have caused various social and economic issues, such as a demand on landfill spaces, increase in environmental pollution and raising the waste management cost. With growing social awareness about toxic incinerator emissions and the increasing concern over the disposal of sludge on the agricultural land, the recovery of sewage sludge as a building and construction raw material can be considered as an innovative approach to tackle the sludge disposal problem. The proposed work aims at studying the recycling ability of the sludge, generated from the water treatment process, by incorporating it into the fired clay brick units. The work involves initial study of the geotechnical characteristics of the brick-clay and the sludge. Chemical compatibility of both the materials will be analyzed by X-ray fluorescence technique. The variation in the strength aspects with varying proportions of sludge i.e. 10%, 20%, 30% and 40% in the sludge-clay mix will also be determined by the proctor density test. Based on the optimum moisture content, the sludge-clay bricks will be manufactured in a brick manufacturing plant and the modified brick units will be tested to determine the variation in compressive strength, bulk density, firing shrinkage, shrinkage loss and initial water absorption rate with respect to the conventional clay bricks. The results will be compared with the specifications given in Indian Standards to arrive at the potential use of the new bricks. The durability aspect will be studied by conducting the leachate analysis test using atomic adsorption spectrometry. The lightweight characteristics of the sludge modified bricks will be ascertained with the scanning electron microscope technique which will be indicative of the variation in pore structure with the increase in sludge content within the bricks. The work will determine the suitable proportion of the sludge – clay mix in the brick which can then be effectively implemented. The feasibility aspect of the work will be determined for commercial production of the units. The work involves providing a strategy for conversion of waste to resource. Moreover, it provides an alternative solution to the problem of growing scarcity of brick-clay for the manufacturing of fired clay bricks.

Keywords: eco-bricks, green construction material, sludge amended bricks, sludge disposal, waste management

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Authors: M. U. Arshid, M. A. Kamal

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The engineering design process is the activities formulation, to help an engineer raising a plan with a specified goal and performance. The engineering design process is a multi-stage course of action including the conceptualization, research, feasibility studies, establishment of design parameters, preliminary and finally the detailed design. It is a progression from the abstract to the concrete; starting with probably abstract ideas about need, and thereafter elaborating detailed specifications of the object that would satisfy the needs, identified. Engineering design issues, problems, and solutions are discussed in this paper using qualitative approach from an information structure perspective. The objective is to identify the problems, to analyze them and propose solutions by integrating; innovation, practical experience, time and resource management, communications skills, isolating the problem in coordination with all stakeholders. Consequently, this would be beneficial for the engineering community to improve the Engineering design practices.

Keywords: engineering design, engineering design issues, innovation, public sector projects

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Endalew Jibat, Feyera Senbeta, Tesfaye Zeleke, Fitsum Hagos

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Water governance considers multi-sector participation beyond the state; and for sustainable use of water resources, appropriate laws, policies, regulations, and institutions needs to be developed and put in place. Water policy, a critical and integral instrument of water governance, guided water use schemes and ensures equitable water distribution among users. The Ethiopian Central Rift Valley (CRV) is wealthy of water resources, but these water resources are currently under severe strain owing to an imbalance in human-water interactions. The main aim of the study was to examine the state of water resources governance in the CRV of Ethiopia, and the impact of the Ethiopian Water Resources Management Policy on water governance. Key informant interviews (KII), focused group discussions, and document reviews were used to gather data for the study. The NVivo 11 program was used to organize, code, and analyze the data. The results revealed that water resources governance practices such as water allocation and apportionment, comprehensive and integrated water management plans, water resources protection, and conservation activities were rarely implemented. Water resources management policy mechanisms were not fully put in place. Lack of coherence in water policy implementation, absence of clear roles and responsibilities of stakeholders, absence of transparency and accountability in irrigation water service delivery, and lack of meaningful participation of key actors in water governance decision-making were the primary shortcomings observed. Factors such as over-abstraction, deterioration of buffer zone, and chemical erosion from surrounding farming have contributed to the reduction in water volume and quality in the CRV. These challenges have influenced aquatic ecosystem services and threaten the livelihoods of the surrounding communities. Hence, reforms relating to policy coherence and enforcement, stakeholder involvement, water distribution strategies, and the application of water governance principles must be given more emphasis.

Keywords: water resources, irrigation, governance, water allocation, governance principles, stakeholders engagement, central rift valley

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Authors: Perizat Balkhimbekova

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Evolutionary changes in cognitive world view taking place in the last decades are followed by changes in perception of the key concepts which are related to the certain lingua-cultural sphere. Also, such concepts reflect the person’s attitude to essential processes in the sphere of concepts, e.g. the opposite operations like creation and destruction. These changes in people’s life and thinking are displayed in a language world view. In order to open the maintenance of mental structures and concepts we should use language means as observable results of people’s cognitive activity. Semantics of words, free phrases and idioms should be considered as an authoritative source of information concerning concepts. The regularized set of concepts in people consciousness forms the sphere of concepts. Cognitive linguistics widely discusses the sphere of concepts as its crucial category defining it as the field of knowledge which is made of concepts. It is considered that a sphere of concepts comprises the various types of association and forms conceptual fields. As a material for the given research, the data from Russian National Corpus and British National Corpus were used. In is necessary to point out that data provided by computational studies, are intrinsic and verifiable; so that we have used them in order to get the reliable results. The procedure of study was based on such techniques as extracting of the context containing concepts of creation|destruction from the Russian National Corpus (RNC), and British National Corpus (BNC); analyzing and interpreting of those context on the basis of cognitive approach; finding of correspondence between the given concepts in the Russian and English world view. The key problem of our study is to find the correspondence between the elements of world view represented by opposite concepts such as creation and destruction. Findings: The concept of "destruction" indicates a process which leads to full or partial destruction of an object. In other words, it is a loss of the object primary essence: structures, properties, distinctive signs and its initial integrity. The concept of "creation", on the contrary, comprises positive characteristics, represents the activity aimed at improvement of the certain object, at the creation of ideal models of the world. On the other hand, destruction is represented much more widely in RNC than creation (1254 cases of the first concept by comparison to 192 cases for the second one). Our hypothesis consists in the antinomy represented by the aforementioned concepts. Being opposite both in respect of semantics and pragmatics, and from the point of view of axiology, they are at the same time complementary and interrelated concepts.

Keywords: creation, destruction, concept, world view

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Shonuga Olajumoke Adedoyinsola

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Staffing and Compensation are at the core of any employment exchange, and they serve as the defining characteristics of any employment relationship. Most organizations understand the benefits that a longer term approach to staff planning can bring and the answer to this problem lies not in trying to implement the traditional approach more effectively, but in implementing a completely different kind of process for strategic staffing. The study focuses on critical points of compensation, staffing and personnel management. The fundamentals of these programs include the elements of vision, potential, communication and motivation. The aim of the paper is to identify the most important attributes of compensation and incentives, staffing and personnel management. Research method is the analysis and synthesis of scientific literature, logical, comparative and graphic representation. On the basis of analysis, the author presents the models of these systems for positive employee attitudes and behaviors.

Keywords: compensation, employees, incentives, staffing, personnel management

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

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Authors: M. J. Shofa, A. Hidayatno, O. M. Armand

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MRP as a production control system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic. Demand-Driven MRP (DDMRP) is a new approach for inventory control system, and it deals with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP work for a long lead time and uncertain demand in terms of on-hand inventory levels. The evaluation is conducted through a discrete event simulation using purchased part data from an automotive company. The result is MRP gives 50,759 pcs / day while DDMRP gives 34,835 pcs / day (reduce 32%), it means DDMRP is more effective inventory control than MRP in terms of on-hand inventory levels.

Keywords: Demand-Driven MRP, long lead time, MRP, uncertain demand

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Authors: Kotaro Sasai, Daijiro Mizutani, Kiyoyuki Kaito

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Expressways in Japan have been built in an accelerating manner since the 1960s with the aid of rapid economic growth. About 40 percent in length of expressways in Japan is now 30 years and older and has become superannuated. Time-related deterioration has therefore reached to a degree that administrators, from a standpoint of operation and maintenance, are forced to take prompt measures on a large scale aiming at repairing inner damage deep in pavements. These measures have already been performed for bridge management in Japan and are also expected to be embodied for pavement management. Thus, planning methods for the measures are increasingly demanded. Deterioration of layers around road surface such as surface course and binder course is brought about at the early stages of whole pavement deterioration process, around 10 to 30 years after construction. These layers have been repaired primarily because inner damage usually becomes significant after outer damage, and because surveys for measuring inner damage such as Falling Weight Deflectometer (FWD) survey and open-cut survey are costly and time-consuming process, which has made it difficult for administrators to focus on inner damage as much as they have been supposed to. As expressways today have serious time-related deterioration within them deriving from the long time span since they started to be used, it is obvious the idea of repairing layers deep in pavements such as base course and subgrade must be taken into consideration when planning maintenance on a large scale. This sort of maintenance requires precisely predicting degrees of deterioration as well as grasping the present situations of pavements. Methods for predicting deterioration are determined to be either mechanical or statistical. While few mechanical models have been presented, as far as the authors know of, previous studies have presented statistical methods for predicting deterioration in pavements. One describes deterioration process by estimating Markov deterioration hazard model, while another study illustrates it by estimating Proportional deterioration hazard model. Both of the studies analyze deflection data obtained from FWD surveys and present statistical methods for predicting deterioration process of layers around road surface. However, layers of base course and subgrade remain unanalyzed. In this study, data collected from FWD surveys are analyzed to predict deterioration process of layers deep in pavements in addition to surface layers by a means of estimating a deterioration hazard model using continuous indexes. This model can prevent the loss of information of data when setting rating categories in Markov deterioration hazard model when evaluating degrees of deterioration in roadbeds and subgrades. As a result of portraying continuous indexes, the model can predict deterioration in each layer of pavements and evaluate it quantitatively. Additionally, as the model can also depict probability distribution of the indexes at an arbitrary point and establish a risk control level arbitrarily, it is expected that this study will provide knowledge like life cycle cost and informative content during decision making process referring to where to do maintenance on as well as when.

Keywords: deterioration hazard model, falling weight deflectometer, inner damage, load bearing capacity, pavement

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Authors: Ziaullah, Shah Wahab Ali

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Micro-grid equipped with heterogeneous energy resources present the idea of small scale distributed energy management (DEM). DEM helps in minimizing the transmission and operation costs, power management and peak load demands. Micro-grids are collections of small, independent controllable power-generating units and renewable energy resources. Micro-grids also motivate to enable active customer participation by giving accessibility of real-time information and control to the customer. The capability of fast restoration against faulty situation, integration of renewable energy resources and Information and Communication Technologies (ICT) make micro-grid as an ideal system for distributed power systems. Micro-grids can have a bank of energy storage devices. The energy management system of micro-grid can perform real-time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short-term scheduling to minimize total operating costs. We present a review of existing micro-grids optimization objectives/goals, constraints, solution approaches and tools used in micro-grids for energy management. Cost-benefit analysis of micro-grid reveals that cooperation among different micro-grids can play a vital role in the reduction of import energy cost and system stability. Cooperative micro-grids energy trading is an approach to electrical distribution energy resources that allows local energy demands more control over the optimization of power resources and uses. Cooperation among different micro-grids brings the interconnectivity and power trading issues. According to the literature, it shows that open area of research is available for cooperative micro-grids energy trading. In this paper, we proposed and formulated the efficient energy management/trading module for interconnected micro-grids. It is believed that this research will open new directions in future for energy trading in cooperative micro-grids/interconnected micro-grids.

Keywords: distributed energy management, information and communication technologies, microgrid, energy management

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Authors: George B. Abaka-Wood, Massimiliano Zanin, Jonas Addai-Mensah, William Skinner

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The versatility of froth flotation has made it vital in the beneficiation of rare earth elements minerals from either high or low-grade ores. There has been a significant increase in the quantity of iron oxide silicate-rich tailings generated from the extraction of primary commodities such as copper and gold in Australia, which have been identified to contain very low-grade rare earth oxides (≤ 1%). There is a vast knowledge gap in the beneficiation of rare earth oxides from such tailings. The aim of this research is to investigate the feasibility of using fatty acids as collectors for the flotation recovery and upgrade of rare earth oxides from selected iron-oxide silicate-rich tailings. Two forms of fatty acid collectors (oleic acid and sodium oleate) were tested in this investigation. Flotation tests were carried out using a 1.2 L Denver D-12 cell. The effects of pulp pH, fatty acid dosage, particle size distribution (-150 +75 µm, -75 +38 µm and -38 µm) and conventional depressants (sodium silicate and starch) dosage on flotation recovery of rare earth oxides were investigated. A comparison of the flotation results indicated that sodium oleate was the more efficient fatty acid for rare earth oxides flotation at all the pulp pH investigated. The flotation performance was found to be particle size-dependent. Both sodium silicate and starch were unselective in decreasing the recovery of iron oxides and silicate minerals, respectively with the corresponding decrease in rare earth oxides recovery. Generally, iron oxides and silicate minerals formed the substantial fraction of the flotation concentrates obtained, both in the absence and presence of depressants, resulting in a generally low rare earth oxides upgrade, even though rare earth oxides recoveries were high. The flotation tests carried out on the tailings sample suggest the feasibility of rare earth oxides recovery using fatty acids, although particle size distribution and minerals liberation are key limiting factors in achieving selective rare earth oxides upgrade.

Keywords: depressants, flotation, oleic acid, sodium oleate

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Authors: P. Azimi, B. Behtoiy, A. A. Najafi, H. R. Charmchi

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According to the previous studies, one of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: assembly line balancing problem, optimization via simulation, production planning

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Authors: Y. Kim, H. Lee, M. Park, B. Lee

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Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

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Authors: Althaf Marsoof

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The blocking injunction, giving rise to a ‘notice and block’ regime, has become the new approach to curtail the infringement of Intellectual Property rights on the Internet. As such, the blocking injunction is an addition to the arsenal of copyright owners, and more recently has also benefited trademark owners, in their battle against piracy and counterfeiting. Yet, the blocking injunction, notwithstanding the usefulness of its ‘notice and block’ outcome, is not without limitations. In the circumstances, it is argued that ‘notice and takedown’, the approach that has been adopted by right-holders for some years, is still an important remedy against the proliferation of online content that infringe the rights of copyright and trademark owners, which is both viable and effective. Thus, it is suggested that the battle against online piracy and counterfeiting could be won only if both the blocking injunction and the practice of ‘notice and takedown’ are utilised by right-holders as complementary and simultaneous remedies.

Keywords: blocking injunctions, internet intermediaries, notice and takedown, intellectual property

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Tomiwa, Akinyemi Clement

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Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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Authors: Anatoliy A. Alabugin, Nikolay K. Topuzov, Sergei V. Aliukov

Abstract:

It is well known, that while we do a quantitative evaluation of the quality control of some economic processes (in particular, resource saving) with help innovation factors, there are three groups of problems: high uncertainty of indicators of the quality management, their considerable ambiguity, and high costs to provide a large-scale research. These problems are defined by the use of contradictory objectives of enhancing of the quality control in accordance with innovation factors and preservation of economic stability of the enterprise. The most acutely, such factors are felt in the countries lagging behind developed economies of the world according to criteria of innovativeness and effectiveness of management of the resource saving. In our opinion, the following two methods for reconciling of the above-mentioned objectives and reducing of conflictness of the problems are to solve this task most effectively: 1) the use of paradigms and concepts of evolutionary improvement of quality of resource-saving management in the cycle "from the project of an innovative product (technology) - to its commercialization and update parameters of customer value"; 2) the application of the so-called integrative-cyclical approach which consistent with complexity and type of the concept, to studies allowing to get quantitative assessment of the stages of achieving of the consistency of these objectives (from baseline of imbalance, their compromise to achievement of positive synergies). For implementation, the following mathematical tools are included in the integrative-cyclical approach: index-factor analysis (to identify the most relevant factors); regression analysis of relationship between the quality control and the factors; the use of results of the analysis in the model of fuzzy sets (to adjust the feature space); method of non-parametric statistics (for a decision on the completion or repetition of the cycle in the approach in depending on the focus and the closeness of the connection of indicator ranks of disbalance of purposes). The repetition is performed after partial substitution of technical and technological factors ("hard") by management factors ("soft") in accordance with our proposed methodology. Testing of the proposed approach has shown that in comparison with the world practice there are opportunities to improve the quality of resource-saving management using innovation factors. We believe that the implementation of this promising research, to provide consistent management decisions for reducing the severity of the above-mentioned contradictions and increasing the validity of the choice of resource-development strategies in terms of parameters of quality management and sustainability of enterprise, is perspective. Our existing experience in the field of quality resource-saving management and the achieved level of scientific competence of the authors allow us to hope that the use of the integrative-cyclical approach to the study and evaluation of the resulting and factor indicators will help raise the level of resource-saving characteristics up to the value existing in the developed economies of post-industrial type.

Keywords: integrative-cyclical approach, quality control, evaluation, innovation factors. economic sustainability, innovation cycle of management, disbalance of goals of development

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Authors: Weihao Wang, Zhulin Zong

Abstract:

Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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Authors: Abbas Ahmadi, Nasser Aliasgharzad, Ali Asghar Jafarzadeh

Abstract:

Nowadays, drying of the Urmia Lake as a largest saline lake in the world and emerging its saline bed from water has caused the risk of salty dune storms, which threats the health of human society and also plants and animal communities living in the region. Biological soil crusts (BSCs) as a dust stabilizer attracted the attention of Soil conservation experts in recent years. Although the presence of water by the impenetrable lake bed and endorheic basin can be an advantage to create BSCs, but the extraordinary of the lake bed salinity is a factor for prevention of its establishment in the region. Therefore, the present research work has been carried out to investigate the effects of inoculating the Cyanobacteria, algae and their combination to create BSCs for dust control. In this study, an algae attributed to Chlamydomonas sp and a cyanobacteria attributed to Anabaena sp isolated from the soils of Urmia Lake margin were used to create BSC in four soil samples which collected from 0-10 cm of the current margin (A), the previous bed (B), affected lands by lake (C) and Quomtappe sand dune (D). The main characteristics of the A, B and C soil samples are their highly salinity (their ECe are 108, 140 and 118 dS/m, respectively) and sodicity. Also, texture class of the soil A was loamy sand, and other two soils had clay textures. Soil D was Non-saline, but it was sodic with a sandy texture class. This study was conducted separately in each soil in a completely randomized design under four inoculation treatments of non-inoculated (T0), Algae (T1), cyanobacteria (T2) and equal mixture of algae and cyanobacteria (T3) with three replications. In the experiment, the soil was placed into wind tunnel trays, and a suspension containing microorganisms mixed with the trays surface soil. During the experiment, water was sprayed to the trays at the morning and evening of every day. After passing the incubation period (30 days), some characteristics of samples such as pH, EC, cold water extractable carbohydrate (CWEC), hot water extractable carbohydrate (HWEC), sulfuric acid extractable carbohydrate (SAEC), organic matter, crust thickness, penetration resistance, wind erosion threshold velocity and soil loss in the wind tunnel were measured, and Correlation between the measured characteristics was obtained through the SPSS software. Analysis of variance and so comparison between the means of treatments were analyzed with MSTATC software. In this research, Chlorophyll, an amount, was used as an indicator of the microorganism's population in the samples. Based on obtained results, the amount of Chlorophyll a in the T2 treatment of soil A and all treatments of soil D was significantly increased in comparison to the control and crust thickness showed increase in all treatments by microorganism’s inoculation. But effect of the treatments was significant in soils A and D. At all treatment’s inoculation of microorganisms in soil A caused to increase %46, %34 and %55 of the wind erosion threshold velocity in T1, T2 and T3 treatments in comparison to the control, respectively, and in soil D all treatments caused wind erosion threshold velocity became two times more than control. However, soil loss in the wind tunnel experiments was significant in T2 and T3 treatments of these soils and T1 treatment had no effect in reducing soil loss. Correlation between Chlorophyll a and salinity shows the important role of salinity in microbial growth prevention and formation of BSCs in the studied samples. In general, according to the obtained results, it can be concluded that salinity reduces the growth of microorganisms in saline soils of the region, and in soils with fine textures, salinity role in prevention of the microbial growth is clear. Also, using the mix of algae and cyanobacteria together caused the synergistic growth of them and consequently, better protection of the soil against wind erosion was provided.

Keywords: wind erosion, algae, cyanobacteria, carbohydrate

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

Abstract:

Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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