Search results for: efficiency analysis and selection bias

Authors: Rafia Akbar

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This paper assesses different Energy Efficiency Measures (EEMs) and their impact on energy consumption and carbon footprint of an educational building located in Islamabad. A base case was first developed in accordance with typical construction practices in Pakistan. Several EEMs were separately applied to the baseline design to quantify their impact on operational energy reduction of the building and the resultant carbon emissions. Results indicate that by applying these measures, there is a potential to reduce energy consumption up to 49% as compared to the base case. It was observed that energy efficient ceiling fans and lights, insulation of the walls and roof and an efficient air conditioning system for the building can provide significant energy savings. The results further indicate that the initial investment cost of these energy efficiency measures can be recovered within 6 to 7 years of building’s service life.

Keywords: CO2 savings, educational building, energy efficiency measures, payback period

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Authors: Ramonika Sengupta, Stuti Kachhwaha, Asha Adhiya, K. Satya Raja Sekhar, Rajwinder Kaur

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Numerous efforts have been done in the past decade to develop the methods of secure communication that are free from interception and eavesdropping. In fiber optic communication, chaotic optical carrier signals are used for data encryption in secure data transmission. Mach-Zehnder Modulators (MZM) are the key components for generating the chaotic signals to be used as optical carriers. This paper presents the dynamics of a lithium niobate MZM modulator under various biasing conditions. The chaotic fluctuations of the intensity of a laser diode have been generated using the electro-optic MZM modulator operating in a highly nonlinear regime. The modulator is driven in closed loop by its own output at an earlier time. When used as an electro-optic oscillator employing delayed feedback, the MZM displays a wide range of output waveforms of varying complexity. The dynamical behavior of the system ranges from periodic to nonlinear oscillations. The nonlinearity displayed by the system is reproducible and is easily controllable. In this paper, we demonstrate a wide variety of optical signals generated by MZM using easily controllable device parameters in both open and close loop bias conditions.

Keywords: chaotic carrier, fiber optic communication, Mach-Zehnder modulator, secure data transmission

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Authors: S. T. Kumbhar, M. S. Bhatia, R. C. Khairate

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An effective nanodrug delivery system was developed by using chitosan for increased encapsulation efficiency and retarded release of curcumin. Potential ionotropic gelation method was used for the development of chitosan nanoparticles with TPP as cross-linker. The characterization was done for analysis of size, structure, surface morphology, and thermal behavior of synthesized chitosan nanoparticles. The encapsulation efficiency was more than 80%, with improved drug loading capacity. The in-vitro drug release study showed that curcumin release rate was decreased significantly. These chitosan nanoparticles could be a suitable platform for co-delivery of curcumin and anticancer agent for enhanced cytotoxic effect on tumor cells.

Keywords: Curcumin, chitosan, nanoparticles, anticancer activity

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Authors: SeungHee Ryu, Junil Moon

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The magnetic resonance wireless power transfer system is widely researched due to its benefits such as spatial freedom. In this paper, power transmitting unit and power receiving unit of wireless battery charger for mobile devices is presented. Power transmitting unit efficiency is measured under different test conditions with power receiving units.

Keywords: magnetic resonance coupling, wireless power transfer, power transfer efficiency.

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Authors: F. Keller, G. Reinhart

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The efficient and economic allocation of resources is one main goal in the field of production planning and control. Nowadays, a new variable gains in importance throughout the planning process: Energy. Energy-efficiency has already been widely discussed in literature, but with a strong focus on reducing the overall amount of energy used in production. This paper provides a brief systematic approach, how energy-supply-orientation can be used for an energy-cost-efficient production planning and thus combining the idea of energy-efficiency and energy-flexibility.

Keywords: production planning, production control, energy-efficiency, energy-flexibility, energy-supply

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Mao Ju

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The system of general counsel (GC) is an important governance structure designed for the construction of state-owned enterprises (SOEs) under the rule of law. This article is based on the setting of mergers and acquisitions (M&As) and takes the efficiency of M&As to examine the implementation effect of the system of GC for SOEs. Research has found that: (1) companies implementing the system of GC for SOEs have higher efficiency in M&As, manifested in better operational and market performance, and this effect depends on the professional ability and power of the GC. This indicates that the GC of SOEs has played a positive role in the decision-making process of M&As, which helps to improve the efficiency of M&As. (2) The impact of the GC of SOEs on the efficiency of M&As is heterogeneous, and this positive effect is mainly reflected in local and commercial SOEs. (3) The path of this impact is that the GC of SOEs can help reduce ineffective M&As in advance, enhance the ability to integrate M&As after the fact and reduce the risk of goodwill impairment and bankruptcy. This article reveals the impact of the construction of SOEs under the rule of law with the system of GC as the core of M&As activities, providing intuitive evidence for the implementation effect of the GC of SOEs. The research conclusion has important practical guiding value for comprehensively deepening the construction of the rule of SOEs under the rule of law and writing a good chapter on the Chinese path to modernization of SOEs.

Keywords: the system of general counsel, merger and acquisition efficiency, state-owned enterprises, mergers and acquisitions

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Authors: Innocent Pangapanga, Eric Mungatana

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Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

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Authors: Meysam Abedinpour

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Water limitation is the main challenge for crop production in a semi-arid environment. Deficit irrigation is a strategy that allows a crop to sustain some degree of water deficit in order to reduce costs and potentially increase income. For this goal, a field experimental carried out at Asrieh fields of Gorgan city in the north of Iran, during summer season 2011. The treatments imposed were different irrigation water regimes (i.e. W1:70, W2:80, W3:90, and W4:100) percent of field capacity (FC). The results showed that there was Significant difference between the yield and (WUE) under different levels of irrigation, excepting of soil moisture content at field capacity (W4) and 90% of field capacity (W3) on yield and water use efficiency (WUE). The seasonal irrigation water applied were (i.e. 375, 338, 300, and 263 mm ha-1) under different irrigation water treatments (100, 90, 80, 80 and 70%) of FC, respectively. Grain yield productions under treatments were 4180, 3955, 3640, and 3355 (kg ha-1) respectively. Furthermore, the results showed that water use efficiency (WUE) at different treatments were 7.67, 7.79, 7.74, and 7.75 Kg mm ha-1 for (100, 90, 80, and 70) per cent of field capacity, therefore the 90 % of FC treatment (W3) is recommended for Soybean irrigation for water saving. Furthermore, the result showed that the treatment of 90 % of filed capacity (W3) seemed to be better adapted to product a high crop yield with acceptable yield coupling with water use efficiency in Golestan province.

Keywords: deficit irrigation, water use efficiency, yield, soybean

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Authors: Yathreb Sabsaby

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Energy efficiency retrofitting of existing buildings was long ignored by public authorities who favored energy efficiency policies in new buildings, which are easier to implement. Indeed, retrofitting is more complex and difficult to organize because of the extreme diversity in existing buildings, administrative situations and occupation. Energy efficiency retrofitting of existing buildings has now become indispensable in all economies—even emerging countries—given the constraints imposed by energy security and climate change, and because it represents considerable potential energy savings. Addressing energy efficiency in the existing building stock has been acknowledged as one of the most critical yet challenging aspects of reducing our environmental footprint on the ecosystem. Tripoli, Lebanon chosen as case study area is a typical Mediterranean metropolis in the North Lebanon, where multifamily residential buildings are all around the city. This generally implies that the density of energy demand is extremely high, even the renewable energy facilities are involved, they can just play as a minor energy provider at the current technology level in the single family house. It seems only the low energy design for buildings can be made possible, not the zero energy certainly in developing country. This study reviews the latest research and experience and provides recommendations for deep energy retrofits that aim to save more than 50% of the energy used in a typical Tripoli apartment building.

Keywords: energy-efficiency, existing building, multifamily residential building, retrofit

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Authors: Saim Iftikhar Awan, Farhan Ali

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Wind power has now become one of the most important resources of renewable energy. The machine which extracts kinetic energy from wind is wind turbine. This work is all about the electrical power analysis of horizontal axis wind turbine to check the efficiency of different configurations of wind turbines to get maximum output and comparison of experimental and Computational Fluid Dynamics (CFD) results. Different experiments have been performed to obtain that configuration with the help of which we can get the maximum electrical power output by changing the different parameters like the number of blades, blade shape, wind speed, etc. in first step experimentation is done, and then the similar configuration is designed in 3D CAD software. After a series of experiments, it has been found that the turbine with four blades at an angle of 75° gives maximum power output and increase in wind speed increases the power output. The models designed on CAD software are imported on ANSYS-FLUENT to predict mechanical power. This mechanical power is then converted into electrical power, and the results were approximately the same in both cases. In the end, a comparison has been done to compare the results of experiments and ANSYS-FLUENT.

Keywords: computational analysis, power efficiency, wind energy, wind turbine

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: Saqib Warsi

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The Internet of Things (IoT) has become an essential component of modern communication networks, with IPv6 playing a pivotal role in addressing the challenges posed by the rapidly growing number of connected devices. IPv6 provides an expanded address space, offering a solution to the limitations of IPv4 while enhancing routing efficiency and security. This paper explores the impact of IPv6 in improving IoT communication, focusing on its operational benefits for businesses. Additionally, we examine the integration of green communication principles, which aim to reduce energy consumption and operational costs, thus promoting environmental sustainability and business efficiency. Through qualitative analysis and simulation-based modeling, this paper investigates the benefits of IPv6 in IoT environments and evaluates the role of green communication strategies in optimizing network performance. Traffic measurement tools and network performance simulators were employed to analyze the efficiency, sustainability, and scalability of IPv6 networks. By presenting a comprehensive framework for traffic analysis, modeling, and optimization, this research highlights the potential of combining IPv6 and green communication practices to drive business growth while promoting environmental sustainability. The findings provide valuable insights for businesses adopting more sustainable and efficient communication networks.

Keywords: IPv6, Internet of Things (IoT), green communications, traffic measurement and modeling, network virtualization

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Ergham Al Bachir

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This study adopts strategic leadership (Upper Echelons) as the core theory and contextual leadership theory as the research lens. This research asks how the external context impacts strategic leadership effectiveness to achieve the outcomes in pluralistic organizations (PO). The study explores how the context influences the selection of CEOs, top management teams (TMT), and their leadership effectiveness. POs are characterized by the multiple objectives of their top management teams, divergent objectives, multiple strategies, and multiple governing authorities. The research question is explored by means of a qualitative multiple-case study focusing on healthcare, real estate, and financial services organizations. The data sources are semi-structured interviews, documents, and direct observations. The data analysis strategy is inductive and deploys thematic analysis and cross-case synthesis. The findings differentiate between national and international CEOs' delegation of authority and relationship with the Board of Directors. The findings identify the elements of the dynamic context that influence TMT and PO outcomes. The emergent hybrid strategic and contextual leadership framework shows how the different contextual factors influence strategic direction, PO context, selection of CEOs and TMT, and the outcomes in four pluralistic organizations. The study offers seven theoretical contributions to Upper Echelons, strategic leadership, and contextual leadership research. (1) The integration of two theories revealed how CEO’s impact on the organization is complementary to the contextual impact. (2) Conducting this study in the Middle East contributes to strategic leadership and contextual leadership research. (3) The demonstration of the significant contextual effects on the selection of CEOs. (4 and 5) Two contributions revealed new links between the context, the Board role, internal versus external CEOs, and national versus international CEOs. (6 and 7) This study offered two definitions: what accounts for CEO leadership effectiveness and organizational outcomes. Two methodological contributions were also identified: (1) Previous strategic leadership and Upper Echelons research are mainly quantitative, while this study adopts qualitative multiple-case research with face-to-face interviews. (2) The extrication of the CEO from the TMT advanced the data analysis in strategic leadership research. Four contributions are offered to practice: (1) The CEO's leadership effectiveness inside and outside the organization. (2) Rapid turnover of predecessor CEOs signifies the need for a strategic and contextual approach to CEOs' succession. (3) TMT composition and education impact on TMT-CEO and TMT-TMT interface. (4) Multilevel strategic contextual leadership development framework.

Keywords: strategic leadership, contextual leadership, upper echelons, pluralistic organizations, cross-cultural leadership

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Authors: Najmul Hasan, Shiping Li, Chunli Liu

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The synergy effect of surface modifications using the acid treatment and noble metal (Au) deposition on the efficiency of SnFe2O4 (SFO) nano-octahedron photocatalyst has been investigated. Inorganic acids (H2SO4 and HNO3) were employed to compare the effects of different acids. It has been found that after corrosion treatment using H2SO4 and deposition of Au nanoparticles, SnFe2O4 nano-octahedron (Au-S-SFO) showed significantly enhanced photocatalytic activity under simulated light irradiation. Au-S-SFO was characterized by XRD, XPS, EDS, FTIR, Uv-vis-DRS, SEM, PL, and EIS analysis. The mechanism for CO2 reduction was investigated by scavenger tests. The stability of Au-S-SFO was confirmed by continuously repeated tests followed by XRD analysis. The surface corrosion treatment of SFO octahedron with H2SO4 could produce hydroxyl group (-OH) and sulfonic acid group (-SO3H) as reaction sites. These active sites not only enhanced the Au nanoparticles deposition to the acid treated SFO surface but also acted as the Brønsted acid sites that enhance the water adsorption and provide protons for CTC degradation and CO2 reduction. These effects improved the carrier separation and transfer efficiency. In addition, the photocatalytic efficiency was further enhanced by the surface plasmon resonance (SPR) effect of Au nanoparticles deposited on the surface of acid-treated SFO. As a result of the synergy of both acid treatment and SPR effect from the Au NPs, Au-S-SFO exhibited the highest CO2 reduction activity with 2.81, 1.92, and 2.69 times higher evolution rates for CO, CH4, and H2, respectively than that of pure SFO.

Keywords: surface modification, CO2 reduction, Au deposition, Gas-liquid interfacial plasma

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Authors: Abhishek Priyam, Prabha Chand

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Channel depth is an important design parameter to be fixed in designing a solar air heater. In this paper, a mathematical model has been developed to study the influence of channel duct on the thermal performance of solar air heaters. The channel depth has been varied from 1.5 cm to 3.5 cm for the mass flow range 0.01 to 0.11 kg/s. Based on first law of thermodynamics, the channel depth of 1.5 cm shows better thermal performance for all the mass flow range. Also, better thermohydraulic performance has been found up to 0.05 kg/s, and beyond this, thermohydraulic efficiency starts decreasing. It has been seen that, with the increase in the mass flow rate, the difference between thermal and thermohydraulic efficiency increases because of the increase in pressure drop. At lower mass flow rate, 0.01 kg/s, the thermal and thermohydraulic efficiencies for respective channel depth remain the same.

Keywords: channel depth, thermal efficiency, wavy fin, thermohydraulic efficiency

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Authors: Huang Haoxin

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Large dark current at room temperature has long been the major bottleneck that impedes the development of high-performance infrared photodetectors towards miniaturization and integration. Although infrared photodetectors based on layered 2D narrow bandgap semiconductors have shown admirable advantages compared with those based on conventional compounds, which typically suffer from expensive cryogenic operations, it is still urgent to develop a simple but effective strategy to further reduce the dark current. Herein, a tellurium (Te) based infrared photodetector is reported with a specifically designed asymmetric electrical contact area. The deliberately introduced asymmetric electrical contact raises the electric field intensity difference in the Te channel near the drain and the source electrodes, resulting in spontaneous asymmetric carrier diffusion under global infrared light illumination under zero bias. Specifically, the Te-based photodetector presents promising detector performance at room temperature, including a low dark current of≈1 nA, an ultrahigh photocurrent/dark current ratio of 1.57×10⁴, a high specific detectivity (D*) of 3.24×10⁹ Jones, and relatively fast response speed of ≈720 μs at zero bias. The results prove that the simple design of asymmetric electrical contact areas can provide a promising solution to high-performance 2D semiconductor-based infrared photodetectors working at room temperature.

Keywords: asymmetrical contact, tellurium, dark current, infrared photodetector, sensitivity

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: B. Käfer, V. K. Bheemineni, H. Lammer, M. Kotnik, F. O. Riemelmoser

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Axial compression tests are performed on circular tubes made of Aluminum EN AW 6060 (AlMgSi0.5 alloy) in T66 state. All the received tubes have the uniform outer diameter of 40mm and thickness of 1.5mm. Two different lengths 100mm and 200mm are used in the analysis. After performing compression tests on the uniform tube, important crashworthy parameters like peak force, average force, crush efficiency and energy absorption are measured. The present paper has given importance to increase the percentage of crush efficiency without decreasing the value energy absorption of a tube, so a circumferential notch was introduced on the top section of the tube. The effects of position and cut-out lengths of a circumferential notch on the crush efficiency are well explained with relative deformation modes and force-displacement curves. The numerical simulations were carried on the software tool ANSYS/LS-DYNA. It is seen that the numerical results are reasonably good in agreement with the experimental results. 

Keywords: crash box, Notch triggering, energy absorption, FEM simulation

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Authors: M. Manohari, Himanshu Gupta, S. Priyadharshini, R. Santhanam, S. Chandrasekaran, B. Venkatraman

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Injection is one of the potential routes of intake in a radioactive facility. The internal dose due to this intake is monitored at the radiation emergency medical centre, IGCAR using a portable planar HPGe detector. The contaminated wound may be having different shapes. In a reprocessing potential of wound contamination with actinide is more. Efficiency is one of the input parameters for estimation of internal dose. Estimating these efficiencies experimentally would be tedious and cumbersome. Numerical estimation can be a supplement to experiment. As an initial step in this study 241Am contamination of different shapes are studied. In this study portable planar HPGe detector was modeled using Monte Carlo code FLUKA and the effect of different parameters like distance of the contamination from the detector, radius of the circular contamination were studied. Efficiency values for point and surface contamination located at different distances were estimated. The effect of efficiency on the radius of the surface source was more predominant when the source is at 1 cm distance compared to when the source to detector distance is 10 cm. At 1 cm the efficiency decreased quadratically as the radius increased and at 10 cm it decreased linearly. The point source efficiency varied exponentially with source to detector distance.

Keywords: Planar HPGe, efficiency value, injection, surface source

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Authors: Peng Lu, Liu Ting

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Because of the difficulty of financing from the external capital market, the reorganization and merger of private enterprises have formed a family group, seeking the help of the internal capital market to alleviate the capital demand. However, the inefficiency of the internal capital market can damage the effect it should have played, and even hinder the development of enterprises. This paper takes the "Tomorrow Group" as the research object to carry on the case analysis. After using the improved cash flow sensitivity coefficient to measure the efficiency of the internal capital market of Tomorrow Group, the inefficiency phenomenon is found. Then the analysis reveals that the reasons for its inefficiency include that the pyramidal equity structure is conducive to control, the separation of cash flow rights and control rights, the concentration of equity leads to poor balance, the abandonment of real industries and information asymmetry.

Keywords: tomorrow group, internal capital market, related-party transactions, Baotou tomorrow technology Co., LTD

Procedia PDF Downloads 137

Authors: Ljerka Kratofil Krehula, Martina Perlog, Jasmina Stjepanović, Vanja Gilja, Marijana Kraljić Roković, Zlata Hrnjak-Murgić

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The composite preparation of titanium dioxide and zinc oxide photocatalysts with the conductive polymers gives the opportunity to carry out the catalysis reactions not only under UV light but also under visible light. Such processes may efficiently use sunlight in degradation of different organic pollutants and present new design for wastewater treatment. The paper presents the preparation procedure, material characteristics and photocatalytic efficiency of polypyrrole/titanium dioxide and polypyrrole/zinc oxide composites (PPy/TiO2 and PPy/ZnO). The obtained composite samples were characterized by Fourier transform infrared spectroscopy (FTIR), UV-Vis spectroscopy and thermogravimetric analysis (TGA). The photocatalytic efficiency of the samples was determined following the decomposition of Acid Blue 25 dye (AB 25) under UV and visible light by UV/Vis spectroscopy. The efficiency of degradation is determined by total organic carbon content (TOC) after photocatalysis processes. The results show enhanced photocatalytic efficiency of the samples under visible light, so the prepared composite samples are recognized as efficient catalysts in degradation process of AB 25 dye. It can be concluded that the preparation of TiO2 or ZnO composites with PPy can serve as a very efficient method for the improvement of TiO2 and ZnO photocatalytic performance under visible light.

Keywords: composite, photocatalysis, polypyrrole, titanium dioxide, zinc oxide

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Authors: Reina Kawase

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Japan set the goal of 80% reduction in GHG emissions by 2050. To consider countermeasures for reducing GHG emission, the production estimation of energy intensive materials, such as steel, is essential. About 50% of steel production is exported in Japan, so it is necessary to consider steel production including export. Steel productions from 2005-2050 in Japan were estimated under various global assumptions based on combination of scenarios such as goods trade scenarios and steel making process selection scenarios. Process selection scenarios decide volume of steel production by process (basic oxygen furnace and electric arc furnace) with considering steel consumption projection, supply-demand balance of steel, and scrap surplus. The range of steel production by process was analyzed. Maximum steel production was estimated under the scenario which consumes scrap in domestic steel production at maximum level. In 2035, steel production reaches 149 million ton because of increase in electric arc furnace steel. However, it decreases towards 2050 and amounts to 120 million ton, which is almost same as a current level. Minimum steel production is under the scenario which assumes technology progress in steel making and supply-demand balance consideration in each region. Steel production decreases from base year and is 44 million ton in 2050.

Keywords: goods trade scenario, steel making process selection scenario, steel production, global warming

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Eric Wilson Santos Cabral, Marta Monteiro Da Costa Cruz, Fabio Luis Maciel Machado, Henrique Andrade, Rodrigo Pirola Pestana, Vivian Andrea Parreira

Abstract:

The large variation in the price of diesel in Brazil directly affects the variable cost of companies operating in the transportation sector. In rail transport, the great challenge is to overcome the annual budget, cargo and ore transported with cost reduction in relation to previous years, becoming more efficient every year. Some effective measures are necessary to achieve the reduction of the liter ratio consumed by KTKB (Gross Ton per Kilometer multiplied by thousand). This acronym represents the indicator of energy efficiency of some railroads in the world. This study is divided into two parts: the first, to identify using statistical tools, part of the controlled variables in the railways, which have a correlation with the energy efficiency indicator, seeking to aid decision-making. The second, with the use of the train dynamics simulator, within scenarios defined in the operational reality of a railroad, seeks to optimize the train formations and the train stop model for the change of train drivers. With the completion of the study, companies in the rail sector are expected to be able to reduce some of their transportation costs.

Keywords: railway transport, railway simulation, energy efficiency, fuel consumption

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Authors: Abdelkader Guendouz, Fatima Zohra Adel

Abstract:

Since about two decades, the Algerian government created a new instrument in the field of its fiscal policy, which is the FRR (Fonds de Régulation des Recettes). The FRR is a sovereign fund, which the initial role was saving the surplus generated by the fixation of a referential oil price to establish the state budget in the aim equilibrium between budgetary incomes and public expenditures. After a while, the government turns to use this instrument in boosting the public investment more than keeping for funding a deficit budget in periods of crisis. This lead to ask some justified questions about the efficiency of this sovereign fund and its real role.

Keywords: FRR sovereign fund, public expenditures, public investment, efficiency

Procedia PDF Downloads 338

Authors: Vijayendra Anil Menon, Ashwath Narayan Murali

Abstract:

The present day vehicles do not reuse the energy expelled in running the vehicle. The energy used to run the vehicle is expelled immediately.This has remained a constant for many decades. With all the vehicles running on non-renewable resources like fossil fuels, there is an urgent need to improve efficiency of the vehicles until a reliable replacement for fossil fuels is found.Our design is based on the concept of Kinetic energy recovery systems. Though our design lies in principle with the KERS, our design can be used in day-to-day driving. With our design, efficiency of vehicles increases and fuel conservation is possible thereby reducing the carbon footprint.

Keywords: KERS, Battery, Wheels, Efficiency.

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Authors: Taha Anjamrooz, Sareh Rajabi, Ayman Alzaatreh

Abstract:

Smart cities are playing important roles in real life. Integration and automation between different features of modern cities and information technologies improve smart city efficiency, energy management, human and equipment resource management, life quality and better utilization of resources for the customers. One of difficulties in this path, is use, interface and link between software, hardware, and other IT technologies to develop and optimize processes in various business fields such as construction, supply chain management and transportation in parallel to cost-effective and resource reduction impacts. Also, Smart cities are certainly intended to demonstrate a vital role in offering a sustainable and efficient model for smart houses while mitigating environmental and ecological matters. Energy management is one of the most important matters within smart houses in the smart cities and communities, because of the sensitivity of energy systems, reduction in energy wastage and maximization in utilizing the required energy. Specially, the consumption of energy in the smart houses is important and considerable in the economic balance and energy management in smart city as it causes significant increment in energy-saving and energy-wastage reduction. This research paper develops features and concept of smart city in term of overall efficiency through various effective variables. The selected variables and observations are analyzed through data analysis processes to demonstrate the efficiency of smart city and compare the effectiveness of each variable. There are ten chosen variables in this study to improve overall efficiency of smart city through increasing effectiveness of smart houses using an automated solar photovoltaic system, RFID System, smart meter and other major elements by interfacing between software and hardware devices as well as IT technologies. Secondly to enhance aspect of energy management by energy-saving within smart house through efficient variables. The main objective of smart city and smart houses is to reproduce energy and increase its efficiency through selected variables with a comfortable and harmless atmosphere for the customers within a smart city in combination of control over the energy consumption in smart house using developed IT technologies. Initially the comparison between traditional housing and smart city samples is conducted to indicate more efficient system. Moreover, the main variables involved in measuring overall efficiency of system are analyzed through various processes to identify and prioritize the variables in accordance to their influence over the model. The result analysis of this model can be used as comparison and benchmarking with traditional life style to demonstrate the privileges of smart cities. Furthermore, due to expensive and expected shortage of natural resources in near future, insufficient and developed research study in the region, and available potential due to climate and governmental vision, the result and analysis of this study can be used as key indicator to select most effective variables or devices during construction phase and design

Keywords: smart city, traditional housing, RFID, photovoltaic system, energy efficiency, energy saving

Procedia PDF Downloads 113