Search results for: real earning management

Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

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The security of the power distribution grid remains a paramount to the utility professionals while enhancing and making it more efficient. The most serious threat to the system can be maintaining the transformers, as the load is ever increasing with the addition of elements like electric vehicles. In this paper, intelligent transformer monitoring and grid management has been proposed. The engineering is done to use the evolving data from the smart meter for grid analytics and diagnostics for preventive maintenance. The two-tier architecture for hardware and software integration is coupled to form a robust system for the smart grid. The proposal also presents interoperable meter standards for easy integration. Distribution transformer analytics based on real-time data benefits utilities preventing outages, protects the revenue loss, improves the return on asset and reduces overall maintenance cost by predictive monitoring.

Keywords: electric vehicle charging, transformer monitoring, data analytics, intelligent grid

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Authors: Ersin Bozkurt

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The aim of the study is to develop materials for understanding image formations through virtual objects in geometric optics. The images in physics course books are formed by using real objects. This results in mistakes in the features of images because of generalizations which leads to conceptual misunderstandings in learning. In this study it was intended to identify pre-service physics teachers misunderstandings arising from false generalizations. Focused group interview was used as a qualitative method. The findings of the study show that students have several misconceptions such as "the image in a plain mirror is always virtual". However a real image can be formed in a plain mirror. To explain a virtual object's image formation in a more understandable way an overhead projector and episcope and their design was illustrated. The illustrations are original and several computer simulations will be suggested.

Keywords: computer simulations, geometric optics, physics education, students' misconceptions in physics

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Authors: Kai-Wei Ji, Dung-Ying Lin

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This study investigates the impact of transportation on housing prices in regions surrounding Taiwan's science parks. As these parks evolve into crucial economic and population growth centers, they attract an increasing number of residents and workers, significantly influencing local housing markets. This demographic shift raises important questions about the role of transportation in shaping real estate values. Our research examines four major science parks in Taiwan, providing a comparative analysis of how transportation conditions and population dynamics interact to affect housing price premiums. We employ an origin-destination (OD) matrix derived from pervasive traffic data to model travel patterns and their effects on real estate values. The methodology utilizes a bi-level framework: a genetic algorithm optimizes OD demand estimation at the upper level, while a user equilibrium (UE) model simulates traffic flow at the lower level. This approach enables a nuanced exploration of how population growth impacts transportation conditions and housing price premiums. By analyzing the interplay between travel costs based on OD demand estimation and housing prices, we offer valuable insights for urban planners and policymakers. These findings are crucial for informed decision-making in rapidly developing areas, where understanding the relationship between mobility and real estate values is essential for sustainable urban development.

Keywords: demand estimation, genetic algorithm, housing price, transportation

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Authors: Ebrahim Mansoori, Datin Joriah Muhammad

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Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB.

Keywords: ASEAN, corruption indexes, panel data analysis, working capital management

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Authors: Saja Al Zoubi, Humam Wardeh

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This study aims to shed light on the work conditions of female refugees and the most important constraints and challenges preventing them from accessing good earning work. The study was conducted in the Syrian refugee camps in Bekaa province, Lebanon, with a field survey carried out between 2016-2017 through face-to-face interviews of 69 female refugee workers, in addition to 4 focus groups. The results show that 97% of the Syrian female refugees are agricultural workers, they form more than 53% of the agricultural labor work among the refugees. Women predominantly perform all agricultural activities (Planting, weeding, fertilization, irrigation, compacting, cutting, sorting, packaging), except the carriage of heavy objects and sometimes irrigation are exclusive for men. The female child labor is 66% of the child labor. To maintain the livelihoods of their families, women accept to be paid for 4-8 $/day with gender gap around 6 $/day. Women’s acceptance of these low wages is one of the main reasons for landowners’ preference of hiring women under bad work conditions. The less educated and skilled (40% of the women are illiterate, and 2% have some skills) women are more likely to be limited to farm work. In addition, there are other reasons as traditions, labor market demand and other challenges related to security and legal issues. This study finds that enhancing the women capacities (for both refugees and host community) through vocational training and cooperative micro enterprises matched with income generating activities and opening new market channels for local manufactured products can play important role to improve the work skills and conditions, and that can improve the livelihood of their families. The study also recommends to adopt a strategy by all humanitarian agencies to make the aid on educating children condition.

Keywords: agricultural work conditions, gender wage gap, women refugees, work constraints

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Authors: Odd Ivar Haugen

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This paper explores the relationship between assurance, risk, and risk management in the context of complex safety-related systems. It introduces a nuanced understanding of assurance and argues that the foundation for grounds for justified confidence in claims made about a complex system is related to the system behaviour. It emphasises the importance of knowledge as the cornerstone of assurance. The paper addresses the challenges of epistemic and aleatory uncertainties inherent in safety-critical systems. A systems approach is proposed to model emergent properties and complexity using the composition, environment, structure, mechanisms (CESM) metamodel, offering a structured framework for analysing system behaviour. The interplay between assurance and risk management is conceptualised through two models: the domain model and the control model. Assurance and risk management are mutually dependent on each other to reduce uncertainty and control risk levels. This work highlights the dual roles of assurance in risk management, acting as an epistemic actuator on the one side and providing feedback about the strength of the justification on the other. Assurance and risk management have inseparable roles in ensuring safety in complex systems.

Keywords: assurance, CESM metamodel, confidence, emergent properties, knowledge, objectivity, risk, system behaviour, system safety

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Authors: Abdelrahman Elsehsah, Abdelazim Negm, Eid Ashour, Mohamed Elsahabi

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Water resources management is a critical field that encompasses the planning, development, conservation, and allocation of water resources to meet societal needs while ensuring environmental sustainability. This paper reviews the key concepts and challenges in water resources management, emphasizing the significance of a holistic approach that integrates social, economic, and environmental factors. Traditional water management practices, characterized by supply-oriented strategies and centralized control, are increasingly inadequate in addressing contemporary challenges such as water scarcity, climate change impacts, and ecosystem degradation. Emerging technologies, particularly machine learning and remote sensing, offer innovative solutions to enhance decision-making processes in water management. Machine learning algorithms facilitate accurate water demand forecasting, quality monitoring, and leak detection, while remote sensing technologies provide vital data for assessing water availability and quality. This review highlights the need for integrated water management strategies that leverage these technologies to promote sustainable practices and foster resilience in water systems. Future research should focus on improving data quality, accessibility, and the integration of diverse datasets to optimize the benefits of these technological advancements.

Keywords: water resources management, water scarcity, climate change, machine learning, remote sensing, water quality, water governance, sustainable practices, ecosystem management

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Sukanya Sripho

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The purpose of this research was to study the role of local administration management to promote culture based on philosophy of sufficiency economy to many communities in Thailand. The philosophy was given to the Thai people by their King and become one of the important policies from the Thai government. A total of 375 local people in main district, Amnadcharoen province were selected by random sampling. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analysis. The findings revealed that the role of facilitator was utilized the most from the management in order to promote culture based on philosophy of sufficiency economy to many communities in Thailand.

Keywords: administration, management, philosophy of sufficiency economy, facilitator

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Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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Authors: Promothes Saha

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Recently, transportation engineering industry members at the study university showed concern that students lacked the skills needed to solve real-world engineering problems using spreadsheet data analysis. In response to the concerns shown by industry members, this study investigated how to engage students in a better way by incorporating spreadsheet analysis during class - also, help them learn the course topics. Helping students link theoretical knowledge to real-world problems can be a challenge. In this effort, in-class activities and worksheets were redesigned to integrate with Excel to solve example problems using built-in tools including cell referencing, equations, data analysis tool pack, solver tool, conditional formatting, charts, etc. The effectiveness of this technique was investigated using students’ evaluations of the course, enrollment data, and students’ comments. Based on the data of those criteria, it is evident that the spreadsheet activities may increase student learning.

Keywords: civil, engineering, active learning, transportation

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Authors: Ilef Ketata, Mohamed Khalil Baazaoui, Robert Fromm, Ahmad Fakhfakh, Faouzi Derbel

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The integration of wireless communication, e. g. in real-or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, latency, quality of service, and reliability. To minimize the latency without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works. Low-noise amplifiers (LNAs) are introduced to improve the WuRx sensitivity but increase the supply current severely. Different WuRx approaches exist with always-on, power-gated, or duty-cycled receiver designs. This paper presents a comparative study for improving communication range and decreasing the energy consumption of wireless sensor nodes.

Keywords: wireless sensor network, wake-up receiver, duty-cycled, low-noise amplifier, envelope detector, range study

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Authors: Bilal Haider, Farhan Aadil

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A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

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Authors: Nattida Wannaruk, Wasawat Nakkiew

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This research aims to study the factors that affect the performance of green supply chain management in the Lampang ceramics industry. The data investigation of this research was questionnaires which were gathered from 20 factories in the Lampang ceramics industry. The research factors are divided into five major groups which are green design, green purchasing, green manufacturing, green logistics and reverse logistics. The questionnaire has consisted of four parts that related to factors green supply chain management and general information of the Lampang ceramics industry. Then, the data were analyzed using descriptive statistic and priority of each factor by using the analytic hierarchy process (AHP). The understanding of factors affecting the green supply chain management of Lampang ceramics industry was indicated in the summary result along with each factor weight. The result of this research could be contributed to the development of indicators or performance evaluation in the future.

Keywords: Lampang ceramics industry, green supply chain management, analysis hierarchy process (AHP), factors affecting

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Authors: Joy Winston James, Abdul Kadher Jilani

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This review article provides a comprehensive overview of social engineering attacks, specifically those executed through the Kali Linux operating system. It aims to present an in-depth analysis of the background and importance of social engineering in cybersecurity, the tools, and techniques used in these attacks, real-world case studies that demonstrate their effectiveness, and ethical considerations that need to be taken into account while using them. The article highlights the Kali Linux tools that are commonly used in social engineering attacks, including SET, Metasploit, and BeEF, and discusses techniques such as phishing, pretexting, and baiting that are crucial in conducting successful social engineering attacks. It further explores real-world case studies that demonstrate the effectiveness of these techniques, emphasizing the importance of implementing effective countermeasures to reduce the risk of successful social engineering attacks. Moreover, the article sheds light on ethical considerations that need to be taken into account while using social engineering tools, emphasizing the importance of using them ethically and legally. Finally, the article provides potential countermeasures such as two-factor authentication, strong password policies, and regular security audits to help individuals and organizations better protect themselves against this growing threat. By understanding the tools and techniques used in social engineering attacks and implementing appropriate countermeasures, individuals and organizations can minimize the risk of successful social engineering attacks and improve their cybersecurity posture. To illustrate the effectiveness of social engineering attacks, we present real-world case studies that demonstrate how easily individuals and organizations can fall prey to these attacks. We also discuss ethical considerations that must be taken into account while using social engineering tools, emphasizing the need for responsible and legal use of these tools.

Keywords: pen testing, hacking, Kali Linux, social engineering

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Authors: Suleman Bawa, Ayiku Emmanuel Lartey

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Purpose - This paper aims to examine the association between knowledge capital and multinational firms’ innovation management. We again explored the impact of transboundary investment and assimilative capacity between knowledge capital and multinational firms’ innovation management. The vital position of knowledge capital and multinational firms’ innovation management in today’s increasingly volatile environment coupled with fierce competition has been extensively acknowledged by academics and industry investment capitals. Design/methodology/approach - The theoretical association model and an empirical correlation analysis were constructed based on relevant research using data collected from 19 multinational firms in Ghana as the subject, and path analysis was constructed using SPSS 22.0 and AMOS 24.0 to test the formulated hypotheses. Findings - Varied conclusions are drawn consequential from theoretical inferences and empirical tests. For multinational firms, knowledge capital relics positively significant to multinational firms’ innovation management. Multinational firms with advanced knowledge capital likely spawn greater corporations’ innovation management. Second, transboundary investment efficiently intermediates the association between knowledge physical capital, knowledge interactive capital, and corporations’ innovation management. At the same time, this impact is insignificant between knowledge of empirical capital and corporations’ innovation management. Lastly, the impact of transboundary investment and assimilative capacity on the association between knowledge capital and corporations’ innovation management is established. We summarized the implications for managers based on our outcomes. Research limitations/implications - Multinational firms must dynamically build knowledge capital to augment corporations’ innovation management. Conversely, knowledge capital motivates multinational firms to implement transboundary investment and cultivate assimilative capacity. Accordingly, multinational firms can efficiently exploit diverse information to augment their corporate innovation management. Practical implications – This paper presents a comprehensive justification of knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry, its sequential progress, and its associated challenges. Originality/value – This paper is amongst the first to find empirical results to back knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry. Additionally, aligning knowledge as a coordinative instrument is a significant input to our discernment in this area.

Keywords: knowledge capital, transboundary investment, innovation management, assimilative capacity

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Atour Taghipour

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In the real world each manufacturing company is an independent business unit. These business units are linked to each other through upstream and downstream linkages. The management of these linkages is called coordination which, could be considered as a difficult engineering task. The degree of difficulty of coordination depends on the type and the nature of information exchanged between partners as well as the structure of relationship from mutual to the network structure. The literature of manufacturing systems comprises a wide range of varieties of methods and approaches of coordination. In fact, two main streams of research can be distinguished: central coordination versus decentralized coordination. In the centralized systems a high degree of information exchanges is required. The high degree of information exchanges sometimes leads to difficulties when independent members do not want to share information. In order to address these difficulties, decentralized approaches of coordination of operations planning decisions based on some minimal information sharing have been proposed in many academic disciplines. This paper first proposes a framework of analysis in order to analyze the proposed approaches in the literature, based on this framework which includes the similarities between approaches we categorize the existing approaches. This classification can be used as a research map for future researches. The result of our paper highlights several opportunities for future research. First, it is proposed to develop more dynamic and stochastic mechanisms of planning coordination of manufacturing units. Second, in order to exploit the complementarities of approaches proposed by diverse science discipline, we propose to integrate the techniques of coordination. Finally, based on our approach we proposed to develop coordination standards to guaranty both the complementarity of these approaches as well as the freedom of companies to adopt any planning tools.

Keywords: network coordination, manufacturing, operations planning, supply chain

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Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

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In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

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Authors: John Sodeau, David O'Connor, Shane Daly, Stig Hellebust

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This study is the first to employ the online WIBS (Waveband Integrated Biosensor Sensor) technique for the monitoring of bioaerosol emissions and non-fluorescing “dust” released from a composting/green waste site. The purpose of the research was to provide a “proof of principle” for using WIBS to monitor such a location continually over days and nights in order to construct comparative “bioaerosol site profiles”. Current impaction/culturing methods take many days to achieve results available by the WIBS technique in seconds.The real-time data obtained was then used to assess variations of the bioaerosol counts as a function of size, “shape”, site location, working activity levels, time of day, relative humidity, wind speeds and wind directions. Three short campaigns were undertaken, one classified as a “light” workload period, another as a “heavy” workload period and finally a weekend when the site was closed. One main bioaerosol size regime was found to predominate: 0.5 micron to 3 micron with morphologies ranging from elongated to elipsoidal/spherical. The real-time number-concentration data were consistent with an Andersen sampling protocol that was employed at the site. The number-concentrations of fluorescent particles as a proportion of total particles counted amounted, on average, to ~1% for the “light” workday period, ~7% for the “heavy” workday period and ~18% for the weekend. The bioaerosol release profiles at the weekend were considerably different from those monitored during the working weekdays.

Keywords: bioaerosols, composting, fluorescence, particle counting in real-time

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Authors: Ebissa Gadissa Kedir

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This paper presents the potential groundwater assessment and sustainable management in the selected study area. It is the most preferred water source in all climatic zones for its convenient availability, drought dependability, excellent quality, and low development cost. The rural areas, which account for more than 85% of the country's population, are encountered a shortage of potable water supply which can be solved by proper groundwater utilization. For the present study area, the groundwater potential is assessed and analysed. Thus, the study area falls in four potential groundwater zones ranging from poor to high. However, the current groundwater management practices in the study area are poor. Despite the pervasive and devastating challenges, immediate and proper responses have not yet been given to the problem. Thus, such frustrating threats and challenges have initiated the researcher to work in the project area.

Keywords: GW potential, GW management, GW sustainability, South gonder, Ethiopia

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Authors: Lan Nguyen, Kien Le Tan, Bao Nguyen Pham Gia

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Due to the high cost, specialized dynamic measurement devices for industrial lands are difficult for many colleges to equip for hands-on teaching. This study connects a dynamic measurement sensor and receiver utilizing an inexpensive Raspberry Pi 4 board, some 24-bit ADC circuits, a geophone vibration sensor, and embedded Python open-source programming. Gather and analyze signals for dynamic measuring, ground vibration monitoring, and structure vibration monitoring. The system may wirelessly communicate data to the computer and is set up as a communication node network, enabling real-time monitoring of background vibrations at various locations. The device can be utilized for a variety of dynamic measurement and monitoring tasks, including monitoring earthquake vibrations, ground vibrations from construction operations, traffic, and vibrations of building structures.

Keywords: sensors, FFT, signal processing, real-time data monitoring, ground propagation wave, python, raspberry Pi 4

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Authors: Lizette Grobler

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Although the notion of environmental citizenship has become an established concept linked to scholarship on sustainability internationally, it is not the case in South Africa. This literature review aims to investigate whether the concept is a viable construct in the South African household waste management context. This literature review firstly examines different approaches to environmental citizenship and the normative notions of environmental values, attitudes, and behaviour advocated by proponents of each tradition. Secondly, this paper deals with the application of environmental citizenship as a measure to address household waste. Thirdly, this paper interrogates the utilization of the concept in South African scholarly literature on waste management. The paper argues for the introduction of the concept as a potential approach to behavioural change in the household waste management context.

Keywords: environmental citizenship, environmental responsibility, household waste, ownership of waste

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Bakhtiar Amen, Sardasht Mahmood, Joan Lu

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The adoption of smartphones and the usages of mobile applications are increasing rapidly. Consequently, within limited time-range, mobile Internet usages have managed to take over the desktop usages particularly since the first smartphone-touched application released by iPhone in 2007. This paper is proposed to provide solution and answer the most demandable questions related to mobile application automated and manual testing limitations. Moreover, Mobile application testing requires agility and physically testing. Agile testing is to detect bugs through automated tools, whereas the compatibility testing is more to ensure that the apps operates on mobile OS (Operation Systems) as well as on the different real devices. Moreover, we have managed to answer automated or manual questions through two mobile application case studies MES (Mobile Exam System) and MLM (Mobile Lab Mate) by creating test scripts for both case studies and our experiment results have been discussed and evaluated on whether to adopt test on real devices or on emulators? In addition to this, we have introduced new mobile application testing matrix for the testers and some enterprises to obtain knowledge from.

Keywords: mobile app testing, testing matrix, automated, manual testing

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Authors: Leandro da S. Nascimento, Maristela J. Melo

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The increased competition in the globalization drives organizations to innovate in their products and services to remain competitive. Innovation and creativity are incorporated as key aspects to creating value for consumers and for the creation of competitive advantage in organizations. However, there are factors that contribute strong with development of innovation and creation in organizations. These factors are the intellectual capital and knowledge management, which together with sustainability, ensure the development of competitive strategies. However, it is understood that the role of the leader is essential to stimulate the development of human capital, because the human capital is essential for organizations of knowledge. It is the leader who drives the dissemination and sharing of knowledge, an essential aspect for the formation of intellectual capital and therefore should be managed. And it turns out that the management of knowledge through intellectual capital allows the development of environmental initiatives efficiently and effectively. Thus, the research demonstrates the importance of the role of leader / manager in organizations and seeks to analyze how managers can contribute to the adoption of sustainability through intellectual capital and knowledge management.

Keywords: intellectual capital, knowledge management, leadership role, sustainability

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Authors: Radia Bernaoui, Mohamed Hassoun

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Our survey deals a theme of the measurement of the management knowledge of actors in Algerian agricultural sector, through a study carried out with professionals affiliated to agro-alimentary 'agribusinesses'. Taking into account the creation of a national device of information on the agronomic research in Algeria, the aim is to analyze their informational practices and to assess how they rate the sharing of knowledge and the process of collective intelligence. The results of our study reveal a more crucial need: The creation a suitable framework to the division of the knowledge, to produce 'knowledge shared social' where the scientific community could interact with firms. It is a question of promoting processes for the adaptation and the spreading of knowledge, through a partnership between the R&D sector and the production one, to increase the competitiveness of the firms, even the sustainable development of the country.

Keywords: knowledge management, pole of competitiveness, knowledge management, economy of knowledge, agro-alimentary, agribusiness, information system, Algeria

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Authors: Doga Erisik, Ahmet Karaman, Gulfem Alptekin, Ozlem Durmaz Incel

Abstract:

Augmented reality (AR) is a type of virtual reality aiming to duplicate real world’s environment on a computer’s video feed. The mobile application, which is built for this project (called SARAS), enables annotating real world point of interests (POIs) that are located near mobile user. In this paper, we aim at introducing a robust and simple algorithm for placing labels in an augmented reality system. The system places labels of the POIs on the mobile device screen whose GPS coordinates are given. The proposed algorithm is compared to an existing one in terms of energy consumption and accuracy. The results show that the proposed algorithm gives better results in energy consumption and accuracy while standing still, and acceptably accurate results when driving. The technique provides benefits to AR browsers with its open access algorithm. Going forward, the algorithm will be improved to more rapidly react to position changes while driving.

Keywords: accurate tagging algorithm, augmented reality, localization, location-based AR

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

Abstract:

Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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