Search results for: high performance polypropylene fibre

Authors: Razika Ihaddadene, Nabila Ihaddadene

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This paper aims to highlight the importance of the application of the IEC 61724 standard in the study of the performance analysis of photovoltaic power plants on a monthly and annual scale. Likewise, the comparison of two photovoltaic power plants with two different climates was carried out in order to determine the effect of climatic parameters on the analysis of photovoltaic performances. All data from the Ain Skhouna and Adrar photovoltaic power plants for 2018 and the data from the Saida1 field for one month in 2019 were used. The results of the performance analysis according to the indicated standard show that the Saida PV power plant performs better than the Adrar PV power plant, which is due to the effect of increasing the ambient temperature. Increasing ambient temperature increases losses decreases system efficiency and performance ratio. It presents a key element in the proper functioning of PV plants.

Keywords: pv power plants, IEC 61724 norm, grid connected pv, algeria

Procedia PDF Downloads 77

Authors: Mukesh Kumar, Onkar Singh, Naveen Kumar, Amar Deep

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The waste cooking oil is taken as feedstock for biodiesel production. For this research, waste cooking oil is collected from many hotels and restaurants, and then biodiesel is prepared for experimentation purpose. The prepared biodiesel is mixed with mineral diesel in the proportion of 10%, 20%, and 30% to perform tests on a diesel engine. The experimental analysis is carried out at different load conditions to analyze the impact of the blending ratio on the performance and emission parameters. When the blending proportion of biodiesel is increased, then the highest pressure reduces due to the fall in the calorific value of the blended mixture. Experimental analysis shows a promising decrease in nitrogen oxides (NOx). A mixture of 20% biodiesel and mineral diesel is the best negotiation, mixing ratio, and beyond that, a remarkable reduction in the outcome of the performance has been observed.

Keywords: alternative sources, diesel engine, emissions, performance

Procedia PDF Downloads 179

Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

Procedia PDF Downloads 374

Authors: Intissar Benrhouma, Marta Victoria, Ignacio Anton, Bechir Chaouachi

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Concentrating photovoltaic systems CPV use optical elements, such as Fresnel lenses, to concentrate solar intensity. The concentrated solar energy is delivered to the solar cell from 20 to 100 W/cm². Some of this energy is converted to electricity, while the rest must be disposed of as a residual heat. Solar cells cooling should be a necessary part of CPV modeling because these systems allowed increasing the power received by the cell. This high power can rise the electrons’ potential causing the heating of the cell, which reduces the global module’s efficiency. This work consists of modeling a concentrating photovoltaic module with and without a cooling system. We have established a theoretical model based on energy balances carried out on a photovoltaic module using solar radiation concentration cells. Subsequently, we developed a calculation program on Matlab which allowed us to simulate the functioning of this module. The obtained results show that the addition of a cooling system to the module improves greatly the performance of our CPV system.

Keywords: solar energy, photovoltaic, concentration, cooling, performance improvement

Procedia PDF Downloads 398

Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Nurul Nadrah

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As a result of the COVID-19 pandemic, a movement control order was implemented, leading to the adoption of online learning as a substitute for conventional classroom instruction. Thus, this study aims to determine the differences in skill performance between online learning and conventional methods among nursing students. We employed a quasi-experimental design with purposive sampling, involving a total of 59 nursing students, and used online learning as the intervention. As a result, the study found there was a significant difference in student skill performance between online learning and conventional methods. As a conclusion, in times of hardship, it is necessary to implement alternative pedagogical approaches, especially in critical fields like nursing, to ensure the uninterrupted progression of educational programs. This study suggests that online learning can be effectively employed as a means of imparting knowledge to nursing students during their training.

Keywords: nursing education, online learning, skill performance, conventional learning method

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Authors: Yazid Abdullahi Abubakar, Jay Mitra

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This paper is concerned with entrepreneurial high-impact firms, which are firms that generate ‘both’ disproportionate levels of employment and sales growth, and have high levels of innovative activity. It investigates differences in factors influencing high-impact growth between indigenous and foreign firms. The study is based on an analysis of data from United Kingdom (UK) Innovation Scoreboard on 865 firms, which were divided into high-impact firms (those achieving positive growth in both sales and employment) and low-impact firms (negative or no growth in sales or employment); in order to identifying the critical differences in regional, sectorial and size related factors that facilitate knowledge spillovers and high-impact growth between indigenous and foreign firms. The findings suggest that: 1) Firms’ access to regional knowledge spillovers (from businesses and higher education institutions) is more significantly associated with high-impact growth of UK firms in comparison to foreign firms, 2) Because high-tech sectors have greater use of knowledge spillovers (compared to low-tech sectors), high-tech sectors are more associated with high-impact growth, but the relationship is stronger for UK firms compared to foreign firms, 3) Because small firms have greater need for knowledge spillovers (relative to large firms), there is a negative relationship between firm size and high-impact growth, but the negative relationship is greater for UK firms in comparison to foreign firms.

Keywords: entrepreneurship, high-growth, indigenous firms, foreign firms, small firms, large firms

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Authors: Eudjen Cinc

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Work with a human voice, especially with a child s voice and cultivating the sound of the choir, presents an area of crucial importance for a conductor. We use the term conductor because it needs to be understood that regardless of whether we have in front of us an amateur or a professional choir, whether they are singers with a wealth of experience or children who are still developing and educating their inner ear so that in the future they could contribute to the development of choir music, the person who stands in front of the group and works with them, needs to have the characteristics of a conductor. Voice formation is a long-term process, without which there is no success in both solo and collective music performance.

Keywords: music group, conductor, collective, performance

Procedia PDF Downloads 219

Authors: Amit Gill, Lalith Wijerathne, Sebastian Poledna

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This research presents the details of the implementation of high performance computing (HPC) extension of agent-based economic models (ABEMs) to simulate hundreds of millions of heterogeneous agents. ABEMs offer an alternative approach to study the economy as a dynamic system of interacting heterogeneous agents, and are gaining popularity as an alternative to standard economic models. Over the last decade, ABEMs have been increasingly applied to study various problems related to monetary policy, bank regulations, etc. When it comes to predicting the effects of local economic disruptions, like major disasters, changes in policies, exogenous shocks, etc., on the economy of the country or the region, it is pertinent to study how the disruptions cascade through every single economic entity affecting its decisions and interactions, and eventually affect the economic macro parameters. However, such simulations with hundreds of millions of agents are hindered by the lack of HPC enhanced ABEMs. In order to address this, a scalable Distributed Memory Parallel (DMP) implementation of ABEMs has been developed using message passing interface (MPI). A balanced distribution of computational load among MPI-processes (i.e. CPU cores) of computer clusters while taking all the interactions among agents into account is a major challenge for scalable DMP implementations. Economic agents interact on several random graphs, some of which are centralized (e.g. credit networks, etc.) whereas others are dense with random links (e.g. consumption markets, etc.). The agents are partitioned into mutually-exclusive subsets based on a representative employer-employee interaction graph, while the remaining graphs are made available at a minimum communication cost. To minimize the number of communications among MPI processes, real-life solutions like the introduction of recruitment agencies, sales outlets, local banks, and local branches of government in each MPI-process, are adopted. Efficient communication among MPI-processes is achieved by combining MPI derived data types with the new features of the latest MPI functions. Most of the communications are overlapped with computations, thereby significantly reducing the communication overhead. The current implementation is capable of simulating a small open economy. As an example, a single time step of a 1:1 scale model of Austria (i.e. about 9 million inhabitants and 600,000 businesses) can be simulated in 15 seconds. The implementation is further being enhanced to simulate 1:1 model of Euro-zone (i.e. 322 million agents).

Keywords: agent-based economic model, high performance computing, MPI-communication, MPI-process

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Authors: Ying Xin, Shigeki Kametani

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This paper deals the energy saving performance of GHP (Gas engine heat pump) air conditioning system has improved with time-series variation. There are two types of air conditioning systems, VRF (Variable refrigerant flow) and central cooling and heating system. VRF is classified as EHP (Electric driven heat pump) and GHP. EHP drives the compressor with electric motor. GHP drives the compressor with the gas engine. The electric consumption of GHP is less than one tenth of EHP does. In this study, the energy consumption data of GHP installed the junior high schools was collected. An annual and monthly energy consumption per rated thermal output power of each apparatus was calculated, and then their energy efficiency was analyzed. From these data, we investigated improvement of the energy saving of the GHP air conditioning system by the change in the generation.

Keywords: energy-saving, variable refrigerant flow, gas engine heat pump, electric driven heat pump, air conditioning system

Procedia PDF Downloads 298

Authors: P. Chaipanya, R. Keawchai, W. Sombatsanongkhun, S. Jantaramporn

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To manage the demand of wireless communication that has been dramatically increased, switched beam antenna in smart antenna system is focused. Implementation of switched beam antennas at mobile terminals such as notebook or mobile handset is a preferable choice to increase the performance of the wireless communication systems. This paper proposes the low complexity switched beam antenna using single element of antenna which is suitable to implement at mobile terminal. Main beam direction is switched by changing the positions of short circuit on the radiating patch. There are four cases of switching that provide four different directions of main beam. Moreover, the performance in terms of Signal to Interference Ratio when utilizing the proposed antenna is compared with the one using omni-directional antenna to confirm the performance improvable.

Keywords: switched beam, shorted circuit, single element, signal to interference ratio

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Authors: Farhina Haque, Chanyeop Park

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The high efficiency, high field, and high power density provided by wide bandgap (WBG) semiconductors and advanced power electronic converter (PEC) topologies enabled the dynamic control of power in medium to high voltage systems. Although WBG semiconductors outperform the conventional Silicon based devices in terms of voltage rating, switching speed, and efficiency, the increased voltage handling properties, high dv/dt, and compact device packaging increase local electric fields, which are the main causes of partial discharge (PD) in the advanced medium and high voltage applications. PD, which occurs actively in voids, triple points, and airgaps, is an inevitable dielectric challenge that causes insulation and device aging. The aging process accelerates over time and eventually leads to the complete failure of the applications. Hence, it is critical to mitigating PD. Sharp edges, airgaps, triple points, and bubbles are common defects that exist in any medium to high voltage device. The defects are created during the manufacturing processes of the devices and are prone to high-electric-field-induced PD due to the low permittivity and low breakdown strength of the gaseous medium filling the defects. A contemporary approach of mitigating PD by neutralizing electric fields in high power density applications is introduced in this study. To neutralize the locally enhanced electric fields that occur around the triple points, airgaps, sharp edges, and bubbles, electrets are developed and incorporated into high voltage applications. Electrets are electric fields emitting dielectric materials that are embedded with electrical charges on the surface and in bulk. In this study, electrets are fabricated by electrically charging polyvinylidene difluoride (PVDF) films based on the widely used triode corona discharge method. To investigate the PD mitigation performance of the fabricated electret films, a series of PD experiments are conducted on both the charged and uncharged PVDF films under square voltage stimuli that represent PWM waveform. In addition to the use of single layer electrets, multiple layers of electrets are also experimented with to mitigate PD caused by higher system voltages. The electret-based approach shows great promise in mitigating PD by neutralizing the local electric field. The results of the PD measurements suggest that the development of an ultimate solution to the decades-long dielectric challenge would be possible with further developments in the fabrication process of electrets.

Keywords: electrets, high power density, partial discharge, triode corona discharge

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Yusuf Ziya Ayık, Ferhat Kahveci

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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.

Keywords: cost of query, database management systems, materialized view, query performance

Procedia PDF Downloads 280

Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

Procedia PDF Downloads 211

Authors: Fitri D. Jaswar, Tharek A. Rahman, Yasser A. Ahmad

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CubeSat in low earth orbit (LEO) mainly uses ultra high frequency (UHF) transmitter with fixed radio frequency (RF) output power to download the telemetry and the payload data. The transmitter consumes large amount of electrical energy during the transmission considering the limited satellite size of a CubeSat. A transmitter with power control ability is designed to achieve optimize the signal to noise ratio (SNR) and efficient power consumption. In this paper, the thermal vacuum chamber (TVAC) test is performed to validate the performance of the UHF band transmitter with power control capability. The TVAC is used to simulate the satellite condition in the outer space environment. The TVAC test was conducted at the Laboratory of Spacecraft Environment Interaction Engineering, Kyushu Institute of Technology, Japan. The TVAC test used 4 thermal cycles starting from +60°C to -20°C for the temperature setting. The pressure condition inside chamber was less than 10-5Pa. During the test, the UHF transmitter is integrated in a CubeSat configuration with other CubeSat subsystem such as on board computer (OBC), power module, and satellite structure. The system is validated and verified through its performance in terms of its frequency stability and the RF output power. The UHF band transmitter output power is tested from 0.5W to 2W according the satellite mode of operations and the satellite power limitations. The frequency stability is measured and the performance obtained is less than 2 ppm in the tested operating temperature range. The test demonstrates the RF output power is adjustable in a thermal vacuum condition.

Keywords: communication system, CubeSat, SNR, UHF transmitter

Procedia PDF Downloads 264

Authors: Hussain Al-Baghli

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In comparison to hot mix asphalt (HMAs) composed of non-modified bitumens, the superior performance of rubberized HMAs is very well documented, and numerous trials in the USA and elsewhere have demonstrated excellent performance in terms of creep, fatigue, and durability. In this investigation, rubberized HMA technology was examined to address the most critical forms of pavement distresses in the State of Kuwait, namely, high-temperature rutting and moisture-induced raveling. Pelletpave additive was selected as the preferred technology since it offered a convenient method of directly modifying the exiting local HMA recipe without having to polymer modify the bitumen. Experimental work using various Pelletpave contents was carried out at Kuwait Institute for Scientific Research (KISR) to design an optimum rubberized HMA formulation prior to conducting a pilot-scale road trial. With the aid of a gyratory compactor, the compaction and volumetric properties of HMAs containing 2.5% and 3.0% Pelletpave additive were investigated at a range of bitumen contents, all by mass of total mix.

Keywords: modified bitumen, rubberized hot mix asphalt, gyratory compaction, volumetric properties

Procedia PDF Downloads 182

Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: H. Farokhi, A. Bahadoran

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This paper is focused on the absorbance and magnetic properties of a novel nanocomposite based on conducting polymer, carbon black and barium hexaferrite in epoxy resin on the E-glass fibre substrate. The highly conductive nanocomposite was provided by in-situ polymerization of aniline in the presence of carbon black (C) and barium hexaferrite (BaFe12O19) as electromagnetic absorbance material. The structure, morphology, and magnetic properties of samples were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). SEM images showed the uniformly coated PAni on the surface of carbon black and barium hexaferrite. XRD peaks also verified the presence of carbon black and barium hexaferrite in the nanocomposite. The microwave characteristics determined from the magnetic and dielectric properties of the elastomeric composites obtained from scattering data by fitting the samples in a waveguide, where measured in the frequency in X-band frequency range, the range of 8 to 12 GHz. The reflection losses were evaluated to be less than −5dB over the whole X-band frequency (8–12 GHz) for the thickness of 1.4mm.

Keywords: conductive polymer, magnetic materials, capacitance, electrochemical cell

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Authors: M. Y. Ismail, Arslan Kiyani

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Narrow bandwidth and high loss performance limits the use of reflectarray antennas in some applications. This article reports on the feasibility of employing strategic reflectarray resonant elements to characterize the reflectivity performance of reflectarrays in X-band frequency range. Strategic reflectarray resonant elements incorporating variable substrate thicknesses ranging from 0.016λ to 0.052λ have been analyzed in terms of reflection loss and reflection phase performance. The effect of substrate thickness has been validated by using waveguide scattering parameter technique. It has been demonstrated that as the substrate thickness is increased from 0.508mm to 1.57mm the measured reflection loss of dipole element decreased from 5.66dB to 3.70dB with increment in 10% bandwidth of 39MHz to 64MHz. Similarly the measured reflection loss of triangular loop element is decreased from 20.25dB to 7.02dB with an increment in 10% bandwidth of 12MHz to 23MHz. The results also show a significant decrease in the slope of reflection phase curve as well. A Figure of Merit (FoM) has also been defined for the comparison of static phase range of resonant elements under consideration. Moreover, a novel numerical model based on analytical equations has been established incorporating the material properties of dielectric substrate and electrical properties of different reflectarray resonant elements to obtain the progressive phase distribution for each individual reflectarray resonant element.

Keywords: numerical model, reflectarray resonant elements, scattering parameter measurements, variable substrate thickness

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Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

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Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

Procedia PDF Downloads 249

Authors: Mohamed El-Khateeb

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: low-cost, recycling, reuse, solid waste, wastewater treatment

Procedia PDF Downloads 196

Authors: Armin Shirbazo, Hamed Lamei Ramandi, Mohammad Vahab, Jalal Fahimpour

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Hydraulic fracturing, especially multi-stage hydraulic fracturing, is a practical solution for wells with uneconomic production. The wide range of applications is appraised appropriately to have a stable well-production. Production logging tool, which is known as PLT in the oil and gas industry, is counted as one of the most reliable methods to evaluate the efficiency of fractures jobs. This tool has a number of benefits and can be used to prevent subsequent production failure. It also distinguishes different problems that occurred during well-production. In this study, the effectiveness of hydraulic fracturing jobs is examined by using the PLT in various cases and situations. The performance of hydraulically fractured wells is investigated. Then, the PLT is employed to gives more information about the properties of different layers. The PLT is also used to selecting an optimum fracturing design. The results show that one fracture and three-stage fractures behave differently. In general, the one-stage fracture should be created in high-quality areas of the reservoir to have better performance, and conversely, in three-stage fractures, low-quality areas are a better candidate for fracturing

Keywords: multi-stage fracturing, horizontal well, PLT, fracture length, number of stages

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Authors: N. Hiranmai, M. L. S. Deva Kumar

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In this project, it is planned to carry out an experimental investigation on 4- stroke Direct Injection Diesel Engine, which is a single-cylinder, four-stroke, water-cooled, and constant speed engine capable of developing a power output of 3.7 kW at 1500 rpm, run with diesel fuel and also with different proportions of Safflower oil methyl esters, with a piston having five number of grooves on its crown to create turbulence. Various performance parameters, such as brake power, specific fuel consumption, and thermal efficiency, are calculated. At all the load conditions, the performance of the engine is obtained better for blend B40 (40% Safflower oil + 60% of Diesel). At different load conditions, Brake thermal Efficiency (ηbth) is comparatively more for all blends than that for Diesel. At different load conditions, ηith is less for blend B40.

Keywords: four-stroke engine, diesel, safflower oil, engine performance, emissions.

Procedia PDF Downloads 98

Authors: Parham Bakhtiari

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Music performance anxiety (MPA) is a prevalent concern among musicians, manifesting through cognitive, physiological, and behavioral symptoms that can severely impact performance quality and overall well-being. This systematic review synthesizes research on coping strategies employed by musicians to manage MPA from 2016 to 2023, identifying a range of psychological and physical interventions, including acceptance and commitment therapy (ACT), cognitive behavioral therapy (CBT), mindfulness, and yoga. Findings reveal that these interventions significantly reduce anxiety and enhance psychological resilience, with ACT showing notable improvements in psychological flexibility. Physical approaches also proved effective in mitigating physiological symptoms associated with MPA. However, challenges such as small sample sizes and methodological limitations hinder the generalizability of results. The review underscores the necessity for multi-faceted intervention strategies tailored to the unique needs of different musicians and emphasizes the importance of future research employing larger, randomized controlled designs to further validate these findings. Overall, this review serves as a comprehensive resource for musicians seeking effective coping strategies for managing performance anxiety, highlighting the critical interplay between mental and physical approaches in promoting optimal performance outcomes.

Keywords: anxiety, performance, coping, music, strategy

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Authors: N. K. Chougule, G. V. Parishwad

Abstract:

The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

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Authors: Nora Mohammed Al-Kehayez

Abstract:

This present investigation was performed to study the effect of low fat yogurt on serum and liver lipids profile of male albino rats (weighing 100 g+or- 5 gram) when fed balanced or high fat high cholesterol diets and given yogurt ad libitum compared with control groups. Rats were divided into 4 groups, each group contains 6 rats. The groups of rats were fed as follows: Group(1) was fed balanced diet + water(control). Group(2) was fed balanced diet + low fat yogurt. Group(3) was fed high fat high cholesterol diet + water(Control). Group(4) was fed high fat high cholesterol diet + low fat yogurt. The obtained results could be summarized as follows: When rats were given low fat yogurt and fed balanced or high fat high cholesterol diets a significantly greater weight gains resulted in comparison with the control groups given water instead of yogurt. The data on the weights of liver and heart expressed' as percentage increased the body weight in case of rats which were fed balanced diet with low fat yogurt while in case of rats which were fed high fat high cholesterol diet with low fat yogurt the increment scenes to be less. Results of serum cholesterol levels in serum of rats were given balanced or high fat high cholesterol diets and consuming low fat yogurt was showed a significant reduction values. However the low fat yogurt produced the highest significant decrease values. The values of serum cholesterol go hand in hand with serum lipoprotein fractions in rats given low fat yogurt with both balanced or high fat high cholesterol diets. An increase of high density lipoprotein HDL-C and a decrease of low density lipoprotein LDL-C values were obtained. When rats ingested low fat yogurt a significant decrease in serum and liver triglycerides content was obtained wether with balanced or high fat high cholesterol diets. Rats consuming high fat high cholesterol diets with water showed a significant increase in liver total lipids, total cholesterol and phospholipides levels in comparison with the same liver parameters in rats given balanced diet with water. Supplement with low fat yogurt significantly suppressed these effects.

Keywords: yogurt, lipids profile, albino, rats

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Authors: K. Thawichai, R. Pornthep

Abstract:

The purpose of this study was to compare the effects of a four week training period of combined plyometric and resistance training or resistance training alone on muscle strength and sprint performance in wheelchair racing athletes. The participants were sixteen healthy male wheelchair racing athletes of the Thai national team. All participants were randomly assignments into two groups in the plyometric and resistance training group (n = 8) performed plyometric exercises followed by resistance training, whereas the resistance training group (n = 8) performed static stretching and the same resistance training program. At baseline and after training all participants were tested on 1-RM bench press for muscle strength and 100-m cycling sprint performance. The results of this study show that the plyometric and resistance training group made significantly greater improvements in overall muscle strength and sprint performance than the resistance training group following training. In conclusion, these findings suggest that the addition of a four week plyometric and resistance training program more beneficial than resistance training alone on muscle strength and sprint performance in wheelchair racing athletes.

Keywords: plyometric, resistance training, strength, sprint, wheelchair athletes

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Authors: Sherif K. El Dyasti, Esam A. Hagras, Adel E. El-Hennawy

Abstract:

This paper addresses the performance of antenna array beam-forming on Chip-Interleaved Code Division Multiple Access (CI_CDMA) system based on Minimum Mean Square Error (MMSE) detector in aeronautical mobile radio channel. Multipath fading, Doppler shifts caused by the speed of the aircraft, and Multiple Access Interference (MAI) are the most important reasons that affect and reduce the performance of aeronautical system. In this paper, we suggested the CI-CDMA with antenna array to combat this fading and improve the bit error rate (BER) performance. We further evaluate the performance of the proposed system in the four standard scenarios in aeronautical mobile radio channel.

Keywords: aeronautical channel, CI-CDMA, beamforming, communication, information

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Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

Abstract:

The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

Procedia PDF Downloads 89