Search results for: panel data modelling

Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: Andre Kadandji, Mouhamadou Fall, Francois Koum Ekalle

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This paper aims to analyze the sound banking through the effects of the damage of the loan portfolio in the Cameroonian banking sector through the Z-score. The approach is to test the effect of other CAMEL indicators and macroeconomics indicators on the relationship between the non-performing loan and the soundness of Cameroonian banks. We use a dynamic panel data, made by 13 banks for the period 2010-2013. The analysis provides a model equations embedded in panel data. For the estimation, we use the generalized method of moments to understand the effects of macroeconomic and CAMEL type variables on the ability of Cameroonian banks to face a shock. We find that the management quality and macroeconomic variables neutralize the effects of the non-performing loan on the banks soundness.

Keywords: loan portfolio, sound banking, Z-score, dynamic panel

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Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia

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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.

Keywords: modeling, battery, MPPT, charging, PV Panel

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Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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Authors: Viriyavudh Sim, Woo Young Jung

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Performance of Basalt Fiber Reinforced Polymer (BFRP) sandwich infill panel system under diagonal compression was studied by means of numerical analysis. Furthermore, the variation of temperature was considered to affect the mechanical properties of BFRP, since their composition was based on polymeric material. Moreover, commercial finite element analysis platform ABAQUS was used to model and analyze this infill panel system. Consequently, results of the analyses show that the overall performance of BFRP panel had a 15% increase compared to that of GFRP infill panel system. However, the variation of buckling load in terms of temperature for the BFRP system showed a more sensitive nature compared to those of GFRP system.

Keywords: basalt fiber reinforced polymer (BFRP), buckling performance, numerical simulation, temperature dependent materials

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Authors: Xu Chen, Zhao Caiqi

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In addition to the advantages of light weight, resistant corrosion and ease of processing, aluminum is also applied to the long-span spatial structures. However, the elastic modulus of aluminum is lower than that of the steel. This paper combines the high performance aluminum honeycomb panel with the aluminum latticed shell, forming a new panel-and-rod composite shell structure. Through comparative analysis between the static and dynamic performance, the conclusion that the structure of composite shell is noticeably superior to the structure combined before.

Keywords: combination of aluminum honeycomb panel, rod latticed shell, dynamic performence, response spectrum analysis, seismic properties

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Authors: Malraj Bharatha Kiriella

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The purpose of this paper is to investigate the determinants of tourism foreign direct investment (TFDI) to selected developing countries during 1978-2017. The study used pooled panel data to estimate an econometric model. The findings show that market size and institutional barriers are determining factors for TFDI in countries, while other variables of positive country conditions, FDI-related government policy, tourism-related infrastructure and labor conditions are insignificant. The result shows that institutional effects are positive, while market size negatively affects TFDI inflows. The research is limited to eight developing countries. The results can be used to support government policy on TFDI. The paper makes the following contributions: First, it provides important insight and understanding into the TFDI decision-making process in developing countries. Second, both TFDI theory and evidence are minimal, and an econometric model developed on the basis of available literature has been empirically tested.

Keywords: determinants, developing countries, FDI in tourism, panel data

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Rudra P. Pradhan

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This paper examines the Granger causal nexus between financial development and energy consumption in the group of 35 Financial Action Task Force (FATF) Countries over the period 1988-2012. The study uses two financial development indicators such as private sector credit and stock market capitalization and seven energy consumption indicators such as coal, oil, gas, electricity, hydro-electrical, nuclear and biomass. Using panel cointegration tests, the study finds that financial development and energy consumption are cointegrated, indicating the presence of a long-run relationship between the two. Using a panel vector error correction model (VECM), the study detects both bidirectional and unidirectional causality between financial development and energy consumption. The variation of this causality is due to the use of different proxies for both financial development and energy consumption. The policy implication of this study is that economic policies should recognize the differences in the financial development-energy consumption nexus in order to maintain sustainable development in the selected 35 FATF countries.

Keywords: energy consumption, financial development, FATF countries, Panel VECM

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Authors: Seyed M. Zahrai, Saeid Lotfi

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If an infill panel does not have enough ductility against the loading, it breaks and gets damaged before depreciation and load transfer. As steel infill panel has appropriate ductility before fracture, it can be used as an alternative to typical infill panels under blast loading. Concerning enough ductility of out-of-plane behavior the infill panel, the impact force enters the horizontal diaphragm and is distributed among the lateral elements which can be made from steel infill panels. This article investigates the behavior of steel infill panels with different thickness and stiffeners using finite element analysis with geometric and material nonlinearities for optimization of the steel plate thickness and stiffeners arrangement to obtain more efficient design for its out-of-plane behavior.

Keywords: blast loading, ductility, maximum displacement, steel infill panel

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Authors: Dib Djalel, Mordjaoui Mourad

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The current trend towards the exploitation of various renewable energy resources has become indispensable, so it is important to improve the efficiency and reliability of the GPV photovoltaic systems. Maximum Power Point Tracking (MPPT) plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions. This paper presents a new fuzzy logic control based MPPT algorithm for solar panel. The solar panel is modeled and analyzed in Matlab/Simulink. The Solar panel can produce maximum power at a particular operating point called Maximum Power Point(MPP). To produce maximum power and to get maximum efficiency, the entire photovoltaic panel must operate at this particular point. Maximum power point of PV panel keeps on changing with changing environmental conditions such as solar irradiance and cell temperature. Thus, to extract maximum available power from a PV module, MPPT algorithms are implemented and Perturb and Observe (P&O) MPPT and fuzzy logic control FLC, MPPT are developed and compared. Simulation results show the effectiveness of the fuzzy control technique to produce a more stable power.

Keywords: MPPT, photovoltaic panel, fuzzy logic control, modeling, solar power

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Authors: Karolína Vozková, Matěj Kuc

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Net fee and commission income is one of the key elements of a bank’s core income. In the current low-interest rate environment, this type of income is gaining importance relative to net interest income. This paper analyses the effects of bank and country specific determinants of net fee and commission income on a set of cooperative banks from European countries in the 2007-2014 period. In order to do that, dynamic panel data methods (system Generalized Methods of Moments) were employed. Subsequently, alternative panel data methods were run as robustness checks of the analysis. Strong positive impact of bank concentration on the share of net fee and commission income was found, which proves that cooperative banks tend to display a higher share of fee income in less competitive markets. This is probably connected with the fact that they stick with their traditional deposit-taking and loan-providing model and fees on these services are driven down by the competitors. Moreover, compared to commercial banks, cooperatives do not expand heavily into non-traditional fee bearing services under competition and their overall fee income share is therefore decreasing with the increased competitiveness of the sector.

Keywords: cooperative banking, dynamic panel data models, net fee and commission income, system GMM

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

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Authors: Joanne Moyer

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El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community.

Keywords: landscape metrics, CA-Markov, El Paso, Texas, panel data

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Banan Aljumaiah

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In recent years, the construction industry has leveraged the information revolution, which makes it possible to view the entire construction process of new buildings before they are built with the advent of Building Information Modelling (BIM). Although BIM is an integration of the building model with the data and documents about the building, however, its implementation is limited to individual buildings missing the large picture of the city infrastructure. This limitation of BIM led to the birth of City Information Modelling. Three years ago, Eastern Province Municipality (EPM) in Saudi Arabia mandated that all major projects be delivered with collaborative 3D BIM. After three years of implementation, EPM started to implement City Information Modelling (CIM) as a part of the Smart City Plan to link infrastructure and public services and modelling how people move around and interact with the city. This paper demonstrates a local case study of BIM implementation in EPM and its future as a part of project management automation; the paper also highlights the ambitious plan of EPM to transform CIM towards building smart cities.

Keywords: BIM, BIM to CIM

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Ravi Verma

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Cryosorption pump is the best solution to achieve clean, vibration free ultra-high vacuum. Furthermore, the operation of cryosorption pump is free from the influence of electric and magnetic fields. Due to these attributes, this pump is used in the space simulation chamber to create the ultra-high vacuum. The cryosorption pump comprises of three parts (a) panel which is cooled with the help of cryogen or cryocooler, (b) an adsorbent which is used to adsorb the gas molecules, (c) an epoxy which holds the adsorbent and the panel together thereby aiding in heat transfer from adsorbent to the panel. The performance of cryosorption pump depends on the temperature of the adsorbent and hence, on the thermal conductivity of the epoxy. Therefore we have made an attempt to increase the thermal conductivity of epoxy adhesive by mixing nano-sized graphene filler particles. The thermal conductivity of epoxy-graphene composite adhesive is measured with the help of indigenously developed experimental setup in the temperature range from 4.5 K to 7 K, which is generally the operating temperature range of cryosorption pump for efficiently pumping of hydrogen and helium gas. In this article, we have presented the experimental results of epoxy-graphene composite adhesive in the temperature range from 4.5 K to 7 K. We have also proposed an analytical heat conduction model to find the thermal conductivity of the composite. In this case, the filler particles, such as graphene, are randomly distributed in a base matrix of epoxy. The developed model considers the complete spatial random distribution of filler particles and this distribution is explained by Binomial distribution. The results obtained by the model have been compared with the experimental results as well as with the other established models. The developed model is able to predict the thermal conductivity in both isotropic regions as well as in anisotropic region over the required temperature range from 4.5 K to 7 K. Due to the non-empirical nature of the proposed model, it will be useful for the prediction of other properties of composite materials involving the filler in a base matrix. The present studies will aid in the understanding of low temperature heat transfer which in turn will be useful towards the development of high performance cryosorption pump.

Keywords: composite adhesive, computational modelling, cryosorption pump, thermal conductivity

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: J. B. G. Ibarra, J. M. A. Gagui, E. J. T. Jonson, J. A. V. Lim

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This paper focused on studying the performance of the solar panels that were equipped with water-spray cooling system, solar tracking system, and combination of both systems. The efficiencies were compared with the solar panels without any efficiency improvement technique. The efficiency of each setup was computed on an hourly basis every day for a month. The study compared the efficiencies and combined systems that significantly improved at a specific time of the day. The data showed that the solar tracking system had the highest efficiency during 6:00 AM to 7:45 AM. Then after 7:45 AM, the combination of both solar tracking and water-spray cooling system was the most efficient to use up to 12:00 NN. Meanwhile, from 12:00 NN to 12:45 PM, the water-spray cooling system had the significant contribution on efficiency. From 12:45 PM up to 4:30 PM, the combination of both systems was the most efficient, and lastly, from 4:30 PM to 6:00 PM, the solar tracking system was the best to use. The study intended to use solar tracking or water-spray cooling system or combined systems alternately to improve the solar panel efficiency on a specific time of the day.

Keywords: solar panel efficiency, solar panel efficiency technique, solar tracking system, water-spray cooling system

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Authors: Julide Yildirim, Nadir Ocal

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Even though there are many studies investigating the extent and determinants of poverty, there is paucity of research investigating the issue of energy poverty in Turkey. The aim of this paper is threefold: First to investigate the extend of energy poverty in Turkey by using Household Budget Survey datasets belonging to 2005 - 2016 period. Second, to examine the risk factors for energy poverty. Finally, to assess the impact of social assistance program participation on energy poverty. Existing literature employs alternative methods to measure energy poverty. In this study energy poverty is measured by employing expenditure approach, where people are considered as energy poor if they disburse more than 10 per cent of their income to meet their energy requirements. Empirical results indicate that energy poverty rate is around 20 per cent during the time period under consideration. Since Household Budget Survey panel data is not available for 2005 - 2016 period, a pseudo panel has been constructed. Panel logistic regression method is utilized to determine the risk factors for energy poverty. The empirical results demonstrate that there is a statistically significant impact of work status and education level on energy poverty likelihood. In the final part of the paper the impact of social transfers on energy poverty has been examined by utilizing panel biprobit model, where social transfer participation and energy poverty incidences are jointly modeled. The empirical findings indicate that social transfer program participation reduces energy poverty. The negative association between energy poverty and social transfer program participation is more pronounced in urban areas compared with the rural areas.

Keywords: energy poverty, social transfers, panel data models, Turkey

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Authors: Danlei Yang, Luofeng Huang

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The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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Authors: Chae Hoon Park, Jong Kang Park, Jong Tae Kim

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Electrical characteristics of capacitive touchscreen need to be accurately analyzed to result in better performance for multi-channel capacitance sensing. In this paper, we extracted the panel resistances and capacitances of the touchscreen by comparing measurement data and model data. By employing a lumped RC model for driver-to-receiver paths in touchscreen, we estimated resistance and capacitance values according to the physical lengths of channel paths which are proportional to the RC model. As a result, we obtained the model having 95.54% accuracy of the measurement data.

Keywords: electrical characteristics of capacitive touchscreen, iterative extraction, lumped RC model, physical lengths of channel paths

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Authors: Ahmed S. Elamary

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Ultimate shear resistance (USR) of slender plate girders can be predicted theoretically using Cardiff theory or Hӧglund theory. This paper will be concerned with predicting the USR using Hӧglund theory and EC3. Two main factors can affect the USR, the panel width “b” and the web depth “d”, consequently, the panel aspect ratio (b/d) has to be identified by limits. In most of the previous study, there is no limit for panel aspect ratio indicated. In this paper theoretical analysis has been conducted to study the effect of (b/d) on the USR. The analysis based on ninety-six test results of steel plate girders subjected to shear executed and collected by others. New formula proposed to predict the percentage of the distance between the plastic hinges form in the flanges “c” to panel width “b”. Conservative limits of (c/b) have been suggested to get a consistent value of USR.

Keywords: ultimate shear resistance, plate girder, Hӧglund’s theory, EC3

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Authors: Jonardan Koner

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The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

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Authors: Wesam Hamed

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This paper contributes to the existing literature by investigating the impact of political risks on the capital adequacy ratio in the banking sector of Gulf Cooperation Council (GCC) countries, which is the first attempt for this nexus to the best of our knowledge. The dynamic panel data model (System‐GMM) showed that political risks significantly decrease the capital adequacy ratio in the banking sector. For this purpose, we used political risks, bank-specific, profitability, and macroeconomic variables that are utilized from the data stream database for the period 2005-2017. The results also actively support the “too big to fail” hypothesis. Finally, the robustness results confirm the conclusions derived from the baseline System‐GMM model.

Keywords: capital adequacy ratio, system GMM, GCC, political risks

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Authors: Marinko Skare, Malgorzata Porada Rochon

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This paper study the link between energy justice and economic growth. The link between energy justice and growth has not been extensively studied. Here we study the impact and importance of energy justice, as a part of the energy transition process, on economic growth. Our study shows energy justice growth is an important determinant of economic growth and development that should be addressed at the industry and economic levels. We use panel data modeling and causality testing to research the empirical link between energy justice and economic growth. Industry and economy-level policies designed to support energy justice initiatives are beneficial to economic growth. Energy justice is a necessary condition for green growth and sustainability targets.

Keywords: energy justice, economic growth, panel data, energy transition

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Authors: Othmane Fahim, Naoual Belouaggadia. Charifa David, Mohamed Ezzine

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To make better use of cooling resources, systems have been derived on the basis of the use of night radiator systems for heat pumping. Using the TRNSYS tool we determined the influence of the climatic characteristics of the two zones in Morocco on the temperature of the outer surface of a Photovoltaic Thermal Panel “PVT” made of aluminum. The proposal to improve the performance of the panel allowed us to have little heat absorption during the day and give the same performance of a panel made of aluminum at night. The variation in the granite-based panel temperature recorded a deviation from the other materials of 0.5 °C, 2.5 °C on the first day respectively in Marrakech and Casablanca, and 0.2 °C and 3.2 °C on the second night. Power varied between 110.16 and 32.01 W/m² marked in Marrakech, to be the most suitable area to practice night cooling by night radiation.

Keywords: smart buildings, energy efficiency, Morocco, radiative cooling

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Authors: Conrad Weber

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The modelling of railway noise over large projects areas can be very time consuming in terms of preparing the noise models and calculation time. An open-source GIS program has been utilised to assist with the modelling of operational noise levels for 675km of railway corridor. A range of GIS algorithms were utilised to break up the noise model area into manageable calculation sizes. GIS was utilised to prepare and filter a range of noise modelling inputs, including building files, land uses and ground terrain. A spreadsheet was utilised to manage the accuracy of key input parameters, including train speeds, train types, curve corrections, bridge corrections and engine notch settings. GIS was utilised to present the final noise modelling results. This paper explains the noise modelling process and how the spreadsheet and GIS were utilised to accurately model this massive project efficiently.

Keywords: noise, modeling, GIS, rail

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Authors: Sayyed Abdolmajid Jalaee Esfand Abadi, Sepideh Samimi

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Since one of the major difficulties to develop small manufacturing enterpriser in developing countries is the limitations of financing activities, this paper want to answer the question: “what is the role and status of micro finance in improving the labor productivity of small industries in Iran?” The results of panel data estimation show that micro finance in Iran has not yet been able to work efficiently and provide the required credit and investment. Also, reducing economy’s dependence on oil revenues reduced and increasing its reliance on domestic production and exports of industrial production can increase the productivity of workforce in Iranian small industries.

Keywords: microfinance, small manufacturing enterprises (SME), workforce productivity, Iran, panel data

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