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Abstract

This study involves the implementation of an economic order quantity (EOQ) model which is an inventory control method in a ceramic factory. Two different methods were applied for the calculation of EOQs. The first method is to determine EOQ values using a response surface method-based approach (RSM). The second method uses conventional EOQ calculations. To produce a ceramic product, 281 different and additive materials may be used. First, Pareto (ABC) analysis was performed to determine which of the materials have higher priority. Because of this analysis, the value of 21 items among 281 different materials and additives were compared to the ratio of the total product. The ratio was found to be 70.4% so calculations were made for 21 items. Usage value for every single item for the years 2011, 2012, 2013 and 2014, respectively, were obtained from the company records. Eight different demand forecasting methods were applied to find the amount of the demand in EOQ. As a result of forecasting, the EOQ of the items were calculated by establishing a model. Also, EOQ and RSM calculations for the items were made and both calculation results were compared to each other. Considering the obtained results, it is understood that RSM can be used in EOQ calculations rather than the conventional EOQ model. Also, there are big differences between the EOQ values which were implemented by the company and the values calculated. Because of this work, the RSM-based EOQ approach can be used to decide on the EOQ calculations as a way of improving the system performance.
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Authors and Affiliations

Ramazan Yıldız
Ramazan Yaman
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Abstract

In literature as well as in the university debate, we can observe the increase of interest regarding converting agricultural residues into energy. Furthermore, the energy and climate policies have encouraged the development of biogas plants for energy production. One of the most significant reasons of this escalation is that this technology may be both convenient and beneficial. The produced biogas is not only supposed to cover the energy demand like heat and electricity, the resulting digestate has the prospect of a beneficial fertilizer and can thereby influence the energy management plans. This technology is widely introduced to countries, which have large income from agriculture. Not only does this reduce the use of industrial fertilizers, but also finds use for agricultural residues. One of the countries of this type is Vietnam, which is the fifth largest exporter of rice in the world. Over 55% of greenhouse gas emission in Vietnam comes from agriculture. Using innovative technologies such as biogas, may decrease this value in near future. It may also contribute to more sustainable agriculture by decreasing traditional fields burning after the harvesting period. The goal of this research paper is to estimate the possible production of biogas from rice straw to cover the energy demand of the rice mill. Four possible scenarios have been considered in this paper, the present situation and where electricity, energy or both were covered by biogas from agricultural residues. An attempt was made to answer the question whether the amount of biogas produced from agricultural residues is enough for both: electricity and energy supply, for the rice mill. If not, how much rice straw must be delivered from other sources, from which rice is not delivered to the rice mill. The base of the assumptions during the estimation of various values were statistics from FAO and other organizations, secondary sources and data from the existing rice mill in Hậu Mỹ Bắc B in Mekong delta in Vietnam.

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Authors and Affiliations

Berenika Lewicka
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Abstract

In Poland, there is a growing awareness of the need to change the sources of electricity and heat. An expression of this is the adoption of the document entitled Poland’s Energy Policy until 2040 (PEP 2040) in February 2020 by the Council of Ministers. The goal of the Polish Energy Policy until 2040 is “energy security – ensuring the competitiveness of the economy, energy efficiency and reducing the environmental impact of the energy sector – taking into account the optimal use of own energy resources”. In PEP 2040, the previous assumptions of the state’s long-term energy policy were amended and an increase in the use of low- or non-emission sources was declared. In addition, the energy policy guidelines contain forecasts for the production of steam coal and the demand for this raw material. Based on the provisions of the document, as well as forecasts of the coal-production volume prepared by the authors and the assessments of experts in the fields related to energy and mining, the article contains considerations on the validity of the developed forecasts together with the determination of the production capacity of domestic mining enterprises in terms of covering the demand for steam coal used for the production of electricity and heat. It is planned, inter alia, that blocks of coal-fired power plants will be decommissioned and, in their place, there is to be the expansion of solar and wind energy and the commissioning of the first blocks of a nuclear power plant. Such activities, which cause a decrease in the demand for coal, are also related to the plans of changes in the functioning of mining enterprises – there will be successive closures of individual mines and mining plants.
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Authors and Affiliations

Marian Czesław Turek
1
Patrycja Bąk
2
ORCID: ORCID

  1. Central Mining Institute, Katowice, Poland
  2. AGH University of Science and Technology, Kraków, Poland
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Abstract

Metallurgy is one of the key industries both in Russia and in the world. It has a significant influence on the situation in related industries. Therefore, the current state analysis of ferrous metallurgy production and its formation based on the short-term technological forecast is essential. Based on the foregoing, the research was aimed at analyzing the current state of ferrous metallurgy production in Russia and the impact of the COVID-19 pandemic on the prospects for industry development in the short term. The research studies the state of the ferrous metallurgy production in Russia and abroad before the COVID-19 pandemic, as well as the volume of industrial production in ferrous metallurgy and the industry structure. The COVID-19 pandemic has triggered a serious global recession, necessitating an analysis of the forecast for the development of the ferrous metallurgy industry. The research concludes that the Russian ferrous metals market is so far affected to a lesser extent compared to the European one.
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Bibliography

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Authors and Affiliations

S.S. Golubev
1
V.D. Sekerin
1
A.E. Gorokhova
1
D.A. Shevchenko
1
A.Z. Gusov
2

  1. Moscow Polytechnic University, Bolshaya Semenovskaya Street, 38, Moscow, 107023, Russian Federation
  2. Peoples Friendship University of Russia (RUDN University), Miklukho-Maklaya Street, 6, Moscow, 117198, Russian Federation
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Abstract

Challenging job demands are those which require the use of high energy and thus may impair health but bring positive consequences too. The present study aimed to construct a measure for challenging job demands for university teachers.
Methods: The study is based upon the model developed by Makhdoom and Malik (2018) which proposed three challenging job demands including Regulatory Load, Social Load, and Cognitive Demands. On the basis of the literature review, Time Pressure was also studied as a factor. First of all, the authors created an initial item pool of 19 items which were categorized into four factors. The finalized item pool was administered on two independent samples drawn from various universities of Pakistan. In the first stage, the university teachers (N = 201) from three universities of the Punjab province were approached. EFA concluded three-factor and 13 items, which were then administered upon a sample of university teachers (N = 600).
Results: The CFA confirmed the three-factor structure of challenging job demands including Time Pressure, Cognitive Demands and Social Load. All the fit indices were within an acceptable range. The values of factor loadings and Cronbach Alpha justified the internal consistency and psychometric soundness of the newly developed measure.
Discussion: The study concludes a psychometrically sound scale to measure challenging job demands in university teachers which will be helpful in future studies. The limitations of the study along with suggestions for future research and important theoretical and practical implications are discussed.
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Bibliography

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Authors and Affiliations

Irsa Fatima Makhdoom
1
Najma Iqbal Malik
1
ORCID: ORCID
Mohsin Atta
1

  1. University of Sargosha, Pakistan
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Abstract

A lot of interest has recently been put into the so-called ‘virtual cryptographic currencies’, commonly known as cryptocurrencies, along with its surrounding market. The blockchain technology that stands behind them is also becoming increasingly popular. From the perspective of maintaining energy security, an important issue is the process of mining individual cryptocurrencies, which is associated with very high energy consumption. This operation is usually related to the approval of new blocks in the blockchain network and attaching them to the chain. This process is carried out through performing complex mathematical operations by various devices, which in turn require high power and respectively consume a lot of energy. The impact of cryptocurrency miners on the power and energy demand level might gradually increase over time, therefore this issue shouldn’t be ignored. Comparing the above information in parallel with the growing need for providing demand side response (DSR) services in the Polish Power System, raises the question whether devices used for mining cryptocurrencies can be used for the purpose of balancing the power system. This paper presents an analysis of the possibility to provide the demand side response services by groups of cryptocurrency miners users. The analysis was carried out taking basic functional, technological and economical aspects of these devices’ operations into account.

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Authors and Affiliations

Damian Mrowiec
Piotr Saługa
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Abstract

The observation of trends in the demand for minerals is of fundamental importance in the long- -term assessment of prospects for economic development in Poland.
From among 148 minerals analyzed, 42 minerals are indicated as key minerals for the country’s economy, of which 22 were recognized as deficit minerals. These minerals have been the subject of this paper.
For each of these minerals the forecasts of demand by the years 2030, 2040 and 2050 have been made taking the current trends in domestic economy and premises for the development of industries that are main users of these minerals into account. The most promising prospects for growth of domestic demand – with at least a two-fold increase by 2050 – have been determined for manganese dioxide, metallic: magnesium, nickel, silicon, as well as talc and steatite, while an increase by at least 50% have been anticipated for metallic aluminum, tin, metallic manganese, and elemental phosphorus. For natural gas and crude oil growing tendencies have also been predicted, but only by 2030. On the other hand, the most probable decline in domestic demand by 2050 may be foreseen for iron ores and concentrates, bauxite, metallic tungsten, magnesite and magnesia, as well as for crude oil and natural gas, especially after 2040.
It seems inevitable that the deficit in the foreign trade of minerals will continue to deepen in the coming years. By 2030 this will mainly result from the growing importation of crude oil and natural gas, but beyond – by 2050 – further deepening in the trade deficit will be related to the growing importation of many metals as well as of some industrial minerals. After 2040, the negative trade balance can be mitigated by a possible decrease in foreign deliveries of hydrocarbons and iron ores and concentrates.
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Bibliography


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Authors and Affiliations

Krzysztof Galos
1
ORCID: ORCID
Ewa Danuta Lewicka
1
ORCID: ORCID
Jarosław Kamyk
1
ORCID: ORCID
Jarosław Szlugaj
1
ORCID: ORCID
Hubert Czerw
1
ORCID: ORCID
Anna Burkowicz
1
ORCID: ORCID
Alicja Kot-Niewiadomska
1
ORCID: ORCID
Katarzyna Guzik
1
ORCID: ORCID

  1. Mineral and Energy Economy Research Institute, Polish Academy of Sciences, Kraków, Poland
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Abstract

The stable supply of iron ore resources is not only related to energy security, but also to a country’s sustainable development. The accurate forecast of iron ore demand is of great significance to the industrialization development of a country and even the world. Researchers have not yet reached a consensus about the methods of forecasting iron ore demand. Combining different algorithms and making full use of the advantages of each algorithm is an effective way to develop a prediction model with high accuracy, reliability and generalization performance. The traditional statistical and econometric techniques of the Holt–Winters (HW) non-seasonal exponential smoothing model and autoregressive integrated moving average (ARIMA) model can capture linear processes in data time series. The machine learning methods of support vector machine (SVM) and extreme learning machine (ELM) have the ability to obtain nonlinear features from data of iron ore demand. The advantages of the HW, ARIMA, SVM, and ELM methods are combined in various degrees by intelligent optimization algorithms, including the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and simulated annealing (SA) algorithm. Then the combined forecast models are constructed. The contrastive results clearly show that how a high forecasting accuracy and an excellent robustness could be achieved by the particle swarm optimization algorithm combined model, it is more suitable for predicting data pertaining to the iron ore demand.
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Authors and Affiliations

Min Ren
1
Jianyong Dai
2
Wancheng Zhu
3
Feng Dai
3
ORCID: ORCID

  1. Northeastern University, Shenyang, China
  2. University of South China, Hengyang, China
  3. Northeastern University, Shenyang
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Abstract

In cities with large educational institutions, the inflow of educational migrants is important for con-sumption demand, and can trigger multiplier effects. The main aim of this article is to show the mecha-nism of the aggregate demand-income effect created by educational migration in the Polish city of Opole. An estimate of this effect is provided, based on questionnaire research among a sample of 1 075 students from all institutions of higher education located in the city. The estimated effects analysed concern the direct consumption impulse, as well as the indirect job creation and increase in income for providers of accommodation for students, in turn triggering increased consumption demand. While the results must be interpreted with care, an estimated 15 per cent of consumption demand created through expenditure of migrant students (about PLN 175 400 000) and 485 extra job show the significance of such expenditure for the local economy.

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Authors and Affiliations

Diana Rokita-Poskart
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Abstract

This article examines the short- and long-run effects of water price, system input, income, temperature on domestic water demand for Amman area over the period of 1980–2012. An empirical, dynamic autoregressive distributed lag (ARDL) model for water demand is developed on a yearly basis. This approach is capable of testing and analysing the dynamic relationship with time series data using a single equation regressions. Results show the ability of the model to predicting future trends (short- and long-run association). The main results indicate that water demand in limited water environment is partially captured in the long-run by the amount of water reaching the customer. The short- and long-run elasticities of water price (–0.061, –0.028) and high temperature (0.023, 0.054) indicate inelastic behaviour on water demand both in short- and long-run, while the lagged water price has a significant effect on demand. Income represented by gross domestic product (GDP) slightly affects water consumption in the long-run and insignificantly in the short-run (0.24, 0.24). Water consumption is strongly linked to consumption habits measured by lagged billed amount 0.35, and is strongly linked to amount of supplied water both in short- and long-run (0.47, 0.53). These results suggest that water needs should be satisfied first to allow controlling water demand through a good pricing system.
Moreover, the association identified between demand and water system input, and the lesser elasticities of water price and other explanatory variables confirm the condition of water deficit in Amman area and Jordan. The results could be rolled out to similar cities suffering scarce water resources with arid and semi-arid weather conditions.
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Authors and Affiliations

Duaa B. Telfah
1
ORCID: ORCID
Nawal Louzi
1 2
ORCID: ORCID
Tala M. AlBashir
2
ORCID: ORCID

  1. Yarmouk University, Hijjawi Faculty of Engineering Technology, P.O. Box 566 ZipCode 21163, Irbid, Jordan
  2. Al-Ahliyya Amman University Al-Saro, Faculty of Engineering, Amman, Jordan
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Abstract

The pressure on the use of water and climate change has caused a decreased availability of water resources in semi-arid areas in the last decades. The Setif Province is one of the semi-arid zones of Algeria as it receives an average less than 400 mm∙year–1. The question of the evolution of demographic pressures and their impacts on water resources arise. By applying WEAP software (water evaluation and planning), the aim is to develop a model of water resources management and its uti-lization, assess the proportion of the resource-needs balance and analyse the future situation of water according to different scenarios. This approach allows to identify the most vulnerable sites to climatic and anthropogenic pressures. The estima-tion of the needs for drinking water and wastewater in the Setif Province has shown that these needs increase over time and happening when the offer is not able to cover the demand in a suitable way. It is acknowledged that there is a poor exploita-tion of water resources including underground resources, which translates into unmet demand in all sites of demand.

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Authors and Affiliations

Imad E. Bouznad
Omar Elahcene
Mohamed S. Belksier
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Abstract

The Internet of Vehicles (IoVs) has become a vital research area in order to enhance passenger and road safety, increasing traffic efficiency and enhanced reliable connectivity. In this regard, for monitoring and controlling the communication between IoVs, routing protocols are deployed. Frequent changes that occur in the topology often leads to major challenges in IoVs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is “clustering”. This study focuses on IoVs’ stability and to create an efficient routing protocol in dynamic environment. In this context, we proposed a novel algorithm called Cluster-based enhanced AODV for IoVs (AODV-CD) to achieve stable and efficient clustering for simplifying routing and ensuring quality of service (QoS). Our proposed protocol enhances the overall network throughput and delivery ratio, with less routing load and less delay compared to AODV. Thus, extensive simulations are carried out in SUMO and NS2 for evaluating the efficiency of the AODV-CD that is superior to the classic AODV and other recent modified AODV algorithms.
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Authors and Affiliations

Sahar Ebadinezhad
1

  1. Department of Computer Information System, Near East University. Nicosia TRNC, Mersin 10, Turkey
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Abstract

This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting.
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Authors and Affiliations

Piotr Kapler
1
ORCID: ORCID

  1. Warsaw University of Technology, Faculty of Electrical Engineering, Electrical Power Engineering Institute, Koszykowa 75, 00-662 Warsaw, Poland
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Abstract

The paper considers the negative pandemic-type demand shocks in the mean-variance newsvendor problem. It extends the previous results to investigate the case when the actual additive demand may attain negative values due to high prices or considerable, negative demand shocks. The results indicate that the general optimal solution may differ to the solution corresponding exclusively to the non-negative realizations of demand.
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Authors and Affiliations

Milena Bieniek
1

  1. Maria Curie-Sklodowska University, Lublin, Poland
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Abstract

In the over 150 years of hydrocarbon history, the year 2017 will be one of the many similar. However, it will be a breakthrough year for liquefied natural gas. In Asia, China grew to become the leader of import growth, becoming the second world importer, overtaking even South Korea and chasing Japan. The Panama Canal for LNG trade and the “Northern Passage” was opened, so that Russian LNG supplies appeared in Europe. The year 2017 was marked by a dramatic shortening of the length of long-term concluded contracts, their shorter tenure and reduction of volumes – that is, it was another period of market commoditization of this energy resource. The article describes the current state of LNG production and trade till 2018. It focuses on natural gas production in the United States, Qatar, Australia, Russia as countries that can produce and supply LNG to the European Union. The issue of prices and the contracts terms in 2017 was analyzed in detail. The authors stress that the market is currently characterized by an oversupply and will last at least until mid–2020. Novatek, Total – Yamal-LNG project leaders have put the condensing facility at 5.5 million tons into operation. The Christophe de Margerie oil tanker was the first commercial unit to cross the route to Norway and then further to the UK without icebreakers and set a new record on the North Sea Road. In 2017, the Russian company increased its share in the European gas market from 33.1 to 34.7%. In 2017, Russia and Norway exported record volumes of „tubular” – classic natural gas to Europe (and Turkey), 194 and 122 billion m3 respectively, which is 15 and 9 billion m3 more natural gas than in 2016. The thesis was put forward that Russia would not easily give up its sphere of influence and would do everything and use various mechanisms, not only on the market, that it would simply be more expensive and economically unprofitable than natural gas. It was also emphasized that the pressure of the technically possible and economically viable redirection to European terminals of methane carriers landed in the American LNG, results in Gazprom not having a choice but to adjust its prices. The Americans, but also any other supplier (Australia?) can simply do the same and this awareness alone is enough for Russian gas to be present in Europe at a good price.

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Authors and Affiliations

Andrzej P. Sikora
Mateusz Sikora
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Abstract

In recent decades, two different approaches to mine ventilation control have been developed: ventilation on demand (VOD) and automatic ventilation control (AVC) systems. The latter was primarily developed in Russia and the CIS countries. This paper presents a comparative analysis of these two approaches; it was concluded that the approaches have much in common. The only significant difference between them is the optimal control algorithm used in automatic ventilation control systems. The paper describes in greater detail the algorithm for optimal control of ventilation devices that was developed at the scientific school of the Perm Mining Institute with the direct participation of the authors. One feature of the algorithm is that the search for optimal airflow distribution in the mine is performed by the system in a fully automated mode. The algorithm does not require information about the actual topology of the mine and target airflows for the fans. It can be easily programmed into microcontrollers of main fans and ventilation doors. Based on this algorithm, an automated ventilation control system was developed, which minimizes energy consumption through three strategies: automated search for optimal air distribution, dynamic air distribution control depending on the type of shift, and controlled air recirculation systems. Two examples of the implementation of an automated ventilation control system in potash mines in Belarus are presented. A significant reduction in the energy consumption for main fans’ operation obtained for both potash mines.

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Authors and Affiliations

Mikhail A. Semin
Lev Y. Levin
Stanislav V. Maltsev
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Abstract

This paper presents the results of analyses of structure, volume and trends of demand for selected major critical raw materials (CRMs) suitable for the EU’s photovoltaic industry (PV). In order to achieve the EU’s goals in terms of the reduction of greenhouse gas emission and climate neutrality by 2050, the deployment of energy from renewable sources is of key importance. As a result, a substantial development of wind and solar technologies is expected. It is forecasted that increasing the production of PV panels will cause a significant growth in the demand for raw materials, including CRMs. Among these, silicon metal, gallium, germanium and indium were selected for detailed analyses while boron and phosphorus were excluded owing to small quantities being utilized in the PV sector. The estimated volume of the apparent consumption in the EU does not usually exceed 0.1 million tonnes for high purity silicon metal, a hundred tonnes for gallium and indium and several dozen tonnes for germanium. The major net-importers of analyzed CRMs were Germany, France, Spain, Czech Republic, the Netherlands, Slovakia and Italy. The largest quantities of these metals have been utilized by Germany, France, Belgium, Slovakia and Italy. The PV applications constitute a marginal share in the total volume of analyzed metal total end-uses in the EU (10% for silicon metal, 5% for gallium, 13% for germanium and 9% for indium). As a result, there is a number of applications that compete for the same raw materials, particularly including the production of electronic equipment. The volume of the future demand for individual CRMs in PV sector will be strictly related to trends in the development of PV-panel production with crystalline silicon technology currently strongly dominating the global market.
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Authors and Affiliations

Katarzyna Guzik
1
ORCID: ORCID
Anna Burkowicz
1
ORCID: ORCID
Jarosław Szlugaj
1
ORCID: ORCID

  1. Mineral and Energy Economy Research Institute, Polish Academy of Sciences, Kraków, Poland
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Abstract

Biological treatment in wastewater treatment plants appears to be one of the most crucial factors in water quality management and planning. Though, measuring this important factor is challenging, and obtaining reliable results requires signifi can`t effort. However, the use of artificial neural network (ANN) modeling can help to more reliably and cost-effectively monitor the pollutant characteristics of wastewater treatment plants and regulate the processing of these pollutants. To create an artificial neural network model, a study of the Samsun Eastern Advanced Biological WWTP was carried out. It provides a laboratory simulation and prediction option for flexible treatment process simulations. The models were created to forecast influent features that would affect effluent quality metrics. For ANN models, the correlation coefficients RTRAINING and RALL are more than 0.8080. The MSE, RMSE, and MAPE were less than 0.8704. The model’s results showed compliance with the permitted wastewater quality standards set forth in the Turkish water pollution control law for the environment where the treated wastewater is discharged. This is a useful tool for plant management to enhance the quality of the treatment while enhancing the facility’s dependability and efficiency.
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Authors and Affiliations

Hussein Y.H. Alnajjar
1
ORCID: ORCID
Osman Üçüncü
1

  1. Karadeniz Technical University Civil Engineering Faculty Hydraulic Department, Trabzon, Turkey
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Abstract

This work describes the behaviour of organic pollutants along the wadi Mouillah watercourse and its main tributaries and their impacts on the Hammam Boughrara dam, located in the NW of Algeria, in the Wilaya of Tlemcen. The use of a database relating to physico-chemical, biotic and hydrological variables, covering the period from January 2006 to December 2009, contributed to the understanding of the spatiotemporal evolution of each variable. The application of a mathematical model of the diffusion by convection-dispersion with a reaction on two characteristic parameters of organic pollution, the biochemical oxygen demand (BOD 5) which records values above the norm, with peaks that can reach 614%, and total phosphorus (P tot), which the concentration is always higher with maxima reaching 53 mg∙dm –3 favouring eutrophication; this made it possible with precision to synthesise the propagation of pollutants in the liquid mass. The results obtained on the waters of Wadi Mouillah are therefore of poor quality; there is a need to set up a rigorous water quality monitoring system, with water treatment and decontamination devices to preserve the water resources. This will allow to contribute to better management of water quality in terms of combating the spread of pollution. Therefore, they can be used to support decisions in the context of sustainable development.
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Authors and Affiliations

Lotfi Benadda
1
ORCID: ORCID
Belkheir Djelita
2
ORCID: ORCID
Abdelghani Chiboub-Fellah
1
ORCID: ORCID

  1. University of Tlemcen, Research Laboratory No. 60: Valorization of Water Resources, PO Box 230, 13000 Tlemcen, Algeria
  2. Ziane Achour University of Djelfa, Department of Hydraulic, Djelfa, Algeria
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Abstract

Load profiles of residential consumers are very diverse. This paper proposes the usage of a continuous wavelet transform and wavelet coherence to perform analysis of residential power consumer load profiles. The importance of load profiles in power engineering and common shapes of profiles along with the factors that cause them are described. The continuous wavelet transform and wavelet coherence has been presented. In contrast with other studies, this research has been conducted using detailed (not averaged) load profiles. Presented load profiles were measured separately on working day and weekend during winter in two urban households. Results of applying the continuous wavelet transform for load profiles analysis are presented as coloured scalograms. Moreover, the wavelet coherence was used to detect potential relationships between two consumers in power usage patterns. Results of coherence analysis are also presented in a colourful plots. The conducted studies show that the Morlet wavelet is slightly better suitable for load profiles analysis than the Meyer’s wavelet. Research of this type may be valuable for a power system operator and companies selling electricity in order to match their offer to customers better or for people managing electricity consumption in buildings.
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Authors and Affiliations

Piotr Kapler
1
ORCID: ORCID

  1. Warsaw University of Technology, Faculty of Electrical Engineering, Power Engineering Institute, ul. Koszykowa 75, 00-662, Warsaw, Poland
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Abstract

This paper discusses three variants of how e-mobility development will affect the Polish Power System. Multivariate forecasts of annual new registrations of electric vehicles for up to seven years are developed. The forecasts use the direct trend extrapolation methods, methods based on the deterministic chaos theory, multiple regression models, and the Grey model. The number of electric vehicles in use was determined for 2019‒2025 based on the forecast new registrations. The forecasts were conducted in three variants for the annual electric energy demand in 2019‒2025, using the forecast number of electric vehicles and the forecast annual demand for electric energy excluding e-mobility. Forecasts were conducted in three variants for the daily load profile of power system for winter and summer seasons in the Polish Power system in 2019‒2025 based on three variants of the forecast number of electric vehicles and forecast relative daily load profiles.

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Authors and Affiliations

P. Piotrowski
D. Baczyński
S. Robak
M. Kopyt
M. Piekarz
M. Polewaczyk
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Abstract

Improper planning of inventory will affect the factory operating costs, building costs, the cost of loss, and the cost of product defects due to being stored for too long which will eventually become a loss. This research discusses the processing industry which is experiencing lumpy demand. In carrying out the production process, the company has never made plans for future demand, resulting in a waste of message costs due to repeated orders of raw materials ordered to suppliers. This paper contributes to overcoming this issue by simulating future demand by using the Material Requirement Planning (MRP) method with a probabilistic Economic Order Quantity (EOQ) and Periodic Order Quantity (POQ) model. The demand in the coming period is determined using the Autoregressive Integrated Moving Average (ARIMA) method, and an aggregate plan is carried out to determine the regular cost of raw material production and optimal subcontracting. The final analysis states that the calculation of MRP on the selected items using POQ produces the lowest cost for planning S45C-F, SGT-R, and SKD11-R, while SLD-R uses the probabilistic EOQ method.
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Authors and Affiliations

Filscha Nurprihatin
1
Glisina Dwinoor Rembulan
2
Yohanes Dwi Pratama
2

  1. Department of Industrial Engineering, Sampoerna University, Indonesia
  2. Department of Industrial Engineering, Universitas Bunda Mulia, Indonesia
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Abstract

The road network development programme, as well as planning and design of transport systems of cities and agglomerations require complex analyses and traffic forecasts. It particularly applies to higher-class roads (motorways and expressways), which in urban areas, support different types of traffic. Usually there is a conflict between the needs of long-distance traffic, in the interest of which higher-class roads run through undeveloped areas, and the needs of bringing such road closer to potential destinations, cities [1]. By recognising the importance of this problem it is necessary to develop the research and methodology of traffic analysis, especially trip models. The current experience shows that agglomeration models are usually simplified in comparison to large city models, what results from misunderstanding of the significance of these movements for the entire model functioning, or the lack of input data. The article presents the INMOP 3 research project results, within the framework of which it was attempted to increase the accuracy of traffic generation in agglomeration model owing to the use of BigData – the mobile operator’s data on SIM card movements in the Warsaw agglomeration.

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Authors and Affiliations

A. Brzeziński
T. Dybicz
Ł. Szymański
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Abstract

In the academic community within Poland, there is an ongoing debate about the optimal strategies for a redesign of PhD programs; however, the views of PhD students in relation to contemporary doctoral study programs are not widely known. Therefore, in this article, we aim to answer the following questions: (1) what are the demands and the resources for doctoral studies at the Jagiellonian University (JU) as experienced by PhD students? (2) how are these demands and resources related to study burnout and engagement? To gain answers to these questions, we conducted an on-line opinion-based survey of doctoral students. As a result, 326 JU PhD students completed a questionnaire measuring 26 demands and 23 resources along with measures of study burnout and levels of engagement. The results revealed that the demands of doctoral studies at the JU (as declared by at least half of the respondents) are: the requirement to participate in classes that are perceived as an unproductive use of time, the lack of remuneration for tutoring courses with students, a lack of information about possible career paths subsequent to graduation, the use of PhD students as low-paid workers at the university, a lack of opportunities for financing their own research projects, and an inability to take up employment while studying for a doctoral degree. In terms of resources, at least half of the doctoral students pointed to: discounts on public transport and the provision of free-of-charge access to scientific journals. Analyzing both the frequency and strength of the relationships between resources/demands and burnout/engagement, we have identified four key problem areas: a lack of support from their supervisor, role ambiguity within University structures for PhD students, the conflict between paid work and doctoral studies, and the mandatory participation in classes as a student.

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Authors and Affiliations

Konrad Kulikowski
Rafał Damaziak
Anna Kańtoch

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