Search results for: Performance

Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Mohammed A. Hajeeh

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This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: repairable models, imperfect, availability, exponential distribution

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Authors: Nora Arbaoui, Rachid Tadili

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The substantial increase of areas cultivated under glasshouses compels the use of other natural heating and cooling procedures to make a profit as well as avoid both exorbitant fuel consumption and CO₂ emissions. This experimental study is designed to examine the functioning of a solar heating system that will increase positive consequences in terms of both quantity and quality while successfully enhancing greenhouse microclimate during wintertime. Those configurations have been tested in a miniaturized greenhouse simply after having optimized the operating parameters. These were noteworthy results when compared to an unheated witness greenhouse.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: Yolanda Ramirez, Angel Tejada, Agustin Baidez

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In the knowledge-based economy, intangible elements are considered essential in order to achieve competitive advantage in organizations. In this sense, the Balanced Scorecard is a very suitable tool to recognize value and manage intangibles because it translates an organization’s strategic objectives into a set of performance indicators from a financial, as well as customer perspective, internal process and learning and growth perspectives. The aim of this paper is to expose and justify the benefits that the Balanced Scorecard might have for identifying, measuring and managing intellectual capital at universities, by means of reviewing the most important Balanced Scorecard implementations at Spanish public universities.

Keywords: knowledge management, balanced scorecard, universities, Spain

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Authors: M. Zyczkowski, P. Markowski, M. Karol

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The security industry is making many efforts to lower the costs of system installation. However, the dominant technique is the application of fiber optic sensors. It is necessary to determine the location of the disorder of long optical fiber cables. For a number of years, many research centers developed their own solutions. The article presents the construction of the sensor systems with the possibility of disorder location. We present a methodology for determining location of the disorder. The aim of investigations is to answer the question of which of optical sensor configuration offer the best performance for location of the disorder.

Keywords: fiber optic sensor, security sensor, fiber cables, system instillation

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Authors: Bakari Mohammed

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Sports performance and achievements have been the avenue through which great nations of the world exhibit their supremacy over others through sports development strategy. Effective sports development, therefore, requires variables like sports policy, sports funding, sports programme, sports facilities and sponsorship. The extent to what these variables are met shall no doubt affects the effectiveness of any sports development. Two distinguishing features of the Nigerian sports system are its central organization and its employment for specific socio-political objectives, it is against this backdrop that this paper will x-ray the politicization of sports which parallels sports development in the enhanced role of sports and in contrast with developed nations system and management.

Keywords: sport development, sport policy, personnel, program, facilities, funding, sponsorship

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Authors: Meriem Boukais, B. Dennai, A. Ould- Abbas

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The efficiency of SiGe solar cells might be improved by a wide-band-gap window layer. In this work we were simulated using the one dimensional simulation program called analysis of microelectronic and photonic structures (AMPS-1D). In the modeling, the thickness of silicon window was varied from 80 to 150 nm. The rest of layer’s thicknesses were kept constant, by varying thickness of window layer the simulated device performance was demonstrate in the form of current-voltage (I-V) characteristics and quantum efficiency (QE).

Keywords: modeling, SiGe, AMPS-1D, quantum efficiency, conversion, efficiency

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Authors: Chiu-Neng Su, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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In lithium-ion batteries (LIBs) the solid–electrolyte interphase (SEI) layer, which forms on the anode surface, plays a crucial role in stabilizing battery performance. Over the past two decades, efforts to enhance LIB electrolytes have primarily focused on refining the quality of SEI components. Despite these endeavors, several observed phenomena remain inadequately improved the SEI layer. Consequently, there has been a significant surge in research interest regarding the behavior of electrolyte solvation structures to elucidate improvements in battery performance. Thus, in this study, we aimed to explore the solvation structures of LiPF₆ in a mixture of organic solvents, tetrahydrofuran (THF) and 2-methyl-tetrahydrofuran (MTHF) using ab-initio molecular dynamics (AIMD) simulations. Our work investigated the solvation structure of electrolytes with different salt concentrations: low-concentration electrolyte (1.0M LiPF6 in 1:1v/v mixture of THF and MTHF), and high-concentration electrolyte (2.0M LiPF₆ in 1:1v/v mixture of THF and MTHF) and compared them with that of conventional electrolyte (1.0M LiPF₆ in 1:1v/v mixture of ethylene carbonate (EC) and dimethyl carbonate (DMC)). Furthermore, the reduction stability of Li+ solvation structures in these electrolyte systems are investigated. It is found that the first solvation shell of Li+ primary consists of THF. We also analyzed the molecular orbital energy levels to understand the reducing stability of these solvents. Compared with the solvation sheath of commercial electrolyte, the THF/MTHF-containing electrolytes have a higher lowest unoccupied molecular orbital (LUMO) energy level, resulting in improved reduction and interface stability. It has been shown that Li-Al alloy can significantly improve cycle life and promote the formation of a dense SEI layer. Therefore, this study aims to construct the solvation structures obtained from calculations of the pure electrolyte system on the surface of Al-Li alloy. Additionally, AIMD simulations will be conducted to investigate chemical reactions at the interface. This investigation aims to elucidate the composition of the SEI layer formed. Furthermore, Bader charges are used to determine the origin and flow of electrons, thereby revealing the sequence of reduction reactions for generating SEI layers.

Keywords: lithium, aluminum, alloy, battery, solvation structure

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Authors: S. J. Bindhu, Edwina G. Rodrigues, Jijo Balakrishnan

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A grid-connected photovoltaic (PV) micro inverter with good performance properties is proposed in this paper. The proposed inverter with a quadrupler, having more efficiency and less voltage stress across the diodes. The stress that come across the diodes that use in the inverter section is considerably low in the proposed converter, also the protection scheme that we provided can eliminate the chances of the error due to fault. The proposed converter is implemented using perturb and observe algorithm so that the fluctuation in the voltage can be reduce and can attain maximum power point. Finally, some simulation and experimental results are also presented to demonstrate the effectiveness of the proposed converter.

Keywords: DC-DC converter, MPPT, quadrupler, PV panel

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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Authors: Mohammad Reza Babaei, Sanaz Kamrani

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The main problems That arise In adopting most Enterprise resources planning (ERP) strategies come from organizational, complex information systems like the ERP integrate the data of all business areas within the organization. The implementation of ERP is a difficult process as it involves different types of end users. Based on literature, we proposed a conceptual framework and examined it to find the effect of some of the individual, organizational, and technological factors on the usage of ERP and its impact on the end user. The results of the analysis suggest that computer self-efficacy, organizational support, training, and compatibility have a positive influence on ERP usage which in turn has significant influence on panoptic empowerment and individual performance.

Keywords: factor, influencing, enterprise, system

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Authors: Shiying Fan, Xinyong Li

Abstract:

The development of highly efficient multifunctional catalytic materials towards HER, ORR and Photo-fuel cell applications in terms of combined electrochemical and photo-electrochemical principles have currently confronted with dire challenges. In this study, novel palladium (Pd) and ruthenium (Ru) Bimetal Quantum Dots (BQDs) co-anchored on Titania nanotube (NTs) arrays electrodes have been successfully constructed by facial two-step electrochemical strategy. Double Schottky junctions with superior performance in electrocatalytic (EC) hydrogen generations and solar fuel cell energy conversions (PE) have been found. Various physicochemical techniques including UV-vis spectroscopy, TEM/EDX/HRTEM, SPV/TRV and electro-chemical strategy including EIS, C-V, I-V, and I-T, etc. were chronically utilized to systematically characterize the crystal-, electronic and micro-interfacial structures of the composites with double Schottky junction, respectively. The characterizations have implied that the marvelous enhancement of separation efficiency of electron-hole pairs generations is mainly caused by the Schottky-barriers within the nanocomposites, which would greatly facilitate the interfacial charge transfer for H₂ generations and solar fuel cell energy conversions. Moreover, the DFT calculations clearly indicated that the oriented growth of Ru and Pd bimetal atoms at the anatase (101) surface is mainly driven by the interaction between Ru/Pd and surface atoms, and the most active site for bimetal Ru and Pd adatoms on the perfect TiO₂ (101) surface is the 2cO-6cTi-3cO bridge sites and the 2cO-bridge sites with the highest adsorption energy of 9.17 eV. Furthermore, the electronic calculations show that in the nanocomposites, the number of impurity (i.e., co-anchored Ru-Pd BQDs) energy levels near Fermi surface increased and some were overlapped with original energy level, promoting electron energy transition and reduces the band gap. Therefore, this work shall provide a deeper insight for the molecular design of Bimetal Quantum Dots (BQDs) assembled onto Tatiana NTs composites with superior performance for electrocatalytic hydrogen productions and solar fuel cell energy conversions (PE) simultaneously.

Keywords: eletrocatalytic, Ru-Pd bimetallic quantum dots, titania nanotube arrays, double Schottky junctions, hydrogen production

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Authors: Yanin Hosakun, Sujitra Wongkasemjit, Thanyalak Chaisuwan

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Carbon dioxide removal from natural gas is an important process because the existence of carbon dioxide in natural gas contributes to pipeline corrosion, reduces the heating value, and takes up volume in the pipeline. In this study, bacterial cellulose was chosen for the CO2/CH4 gas separation membrane due to its unique structure and prominent properties. Additionally, it can simply be obtained by culturing the bacteria so called “Acetobacter xylinum” through fermentation of coconut juice. Bacterial cellulose membranes with and without silver ions were prepared and studied for the separation performance of CO2 and CH4.

Keywords: bacterial cellulose, CO2, CH4 separation, membrane, nata de coco

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Authors: Sruthi Raveendran

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Developmental dyslexia, characterized by reading difficulties despite normal intelligence, presents a significant challenge for bilingual children navigating languages with varying degrees of orthographic transparency. This study bridges a critical gap in dyslexia interventions for bilingual populations in India by examining how consistency and predictability of letter-sound relationships in a writing system (orthographic transparency) influence the ability to understand and manipulate the building blocks of sound in language (phonological processing). The study employed a computerized visual rhyme-judgment task with concurrent EEG (electroencephalogram) recording. The task compared reaction times, accuracy of performance, and event-related potential (ERP) components (N170, N400, and LPC) for rhyming and non-rhyming stimuli in two orthographies: English (opaque orthography) and Kannada (transparent orthography). As hypothesized, the results revealed advantages in phonological processing tasks for transparent orthography (Kannada). Children with dyslexia were faster and more accurate when judging rhymes in Kannada compared to English. This suggests that a language with consistent letter-sound relationships (transparent orthography) facilitates processing, especially for tasks that involve manipulating sounds within words (rhyming). Furthermore, brain activity measured by event-related potentials (ERP) showed less effort required for processing words in Kannada, as reflected by smaller N170, N400, and LPC amplitudes. These findings highlight the crucial role of orthographic transparency in optimizing reading performance for bilingual children with dyslexia. These findings emphasize the need for language-specific intervention strategies that consider the unique linguistic characteristics of each language. While acknowledging the complexity of factors influencing dyslexia, this research contributes valuable insights into the impact of orthographic transparency on phonological awareness in bilingual children. This knowledge paves the way for developing tailored interventions that promote linguistic inclusivity and optimize literacy outcomes for children with dyslexia.

Keywords: developmental dyslexia, phonological awareness, rhyme judgment, orthographic transparency, Kannada, English, N170, N400, LPC

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu, Tigray

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Sesame is an important oilseed crop in Ethiopia; which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool; which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validated the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates; 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99; and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99, and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, sesame, normalized water productivity, nitrogen fertilizer

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Authors: Xiaohuan Li, Wangmin Yi, Xinghui Wu

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In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. Moreover, the test equipment is necessary for the test. The functions and the key points of the equipment is presented to satisfy the requirements of the test，and the design scheme is proposed. The composition, the major function and the critical parts’ design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved.

Keywords: landing-impact test, lunar lander, releasing device, test equipment

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Authors: Onyinyechi Joy Kingdom

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Mergers and Acquisitions (M&A) have been proposed as a mechanism through which, problems associated with inefficiency or poor performance in financial institution could be addressed. The aim of this study is to examine the proposition that recapitalization of banks, which encouraged Mergers and Acquisitions in Nigeria banking system, would strengthen the domestic banks, improve financial deepening and the confidence of depositors. Hence, this study examines the impact of the 2005 M&A in the Nigerian-banking sector on financial deepening using mixed method (quantitative and qualitative approach). The quantitative process of this study utilised annual time series for financial deepening indicator for the period of 1997 to 2012. While, the qualitative aspect adopted semi-structured interview to collate data from three merged banks and three stand-alone banks to explore, understand and complement the quantitative results. Furthermore, a framework thematic analysis is employed to analyse the themes developed using NVivo 11 software. Using the quantitative approach, findings from the equality of mean test (EMT) used suggests that M&A have significant impact on financial deepening. However, this method is not robust enough given its weak validity as it does not control for other potential factors that may determine financial deepening. Thus, to control for other factors that may affect the level of financial deepening, a Multiple Regression Model (MRM) and Interrupted Times Series Analysis (ITSA) were applied. The coefficient for M&A dummy turned negative and insignificant using MRM. In addition, the estimated linear trend of the post intervention when ITSA was applied suggests that after M&A, the level of financial deepening decreased annually; however, this was statistically insignificant. Similarly, using the qualitative approach, the results from the interview supported the quantitative results from ITSA and MRM. The result suggests that interest rate should fall when capital base is increased to improve financial deepening. Hence, this study contributes to the existing literature the importance of other factors that may affect financial deepening and the economy when policies that will enhance bank performance and the economy are made. In addition, this study will enable the use of valuable policy instruments relevant to monetary authorities when formulating policies that will strengthen the Nigerian banking sector and the economy.

Keywords: mergers and acquisitions, recapitalization, financial deepening, efficiency, financial crisis

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Authors: Fulya Zaralı, Harun Resit Yazgan

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Logistics centers represent areas that all national and international logistics and activities related to logistics can be implemented by the various businesses. Logistics centers have a key importance in joining the transport stream and the transport system operations. Therefore, it is important where these centers are positioned to be effective and efficient and to show the expected performance of the centers. In this study, the location selection problem to position the logistics center is discussed. Alternative centers are evaluated according certain criteria. The most appropriate center is identified using the axiomatic design method.

Keywords: axiomatic design, logistic center, facility location, information systems

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Authors: Asinguza P. Allan

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The Advocacy for Better Health aims to equip citizens with enabling environment and systems to effectively advocate for strong action plans to improve health services. This is because the 2020 Government target for Uganda to transform into a middle income country will be achieved if investment is made in keeping the population healthy and productive. Citizen participation as an important foundation for change has been emphasized to gather data through participatory rural appraisal and inform evidence-based advocacy for recruitment and motivation of human resources. Citizens conduct problem ranking during advocacy forums on staffing levels and health worker absenteeism. Citizens prioritised inadequate number of midwives and absenteeism. On triangulation, health worker to population ratio in Uganda remains at 0.25/1,000 which is far below the World Health Organization (WHO) threshold of 2.3/1,000. Working with IntraHealth, the project advocated for recruitment of critical skilled staff (doctors and midwives) and scale up health workers motivation strategy to reduce Uganda’s Neonatal Mortality Rate of 22/1,000 and Maternal Mortality Ratio of 320/100,000. Government has committed to increase staffing to 80% by 2018 (10 districts have passed ordinances and revived use of duty rosters to address health worker absenteeism. On the other hand, the better health advocacy debate has been elevated with need to increase health sector budget allocations from 8% to 10%. The project has learnt that building a body of evidence from citizens enhances the advocacy agenda. Communities will further monitor government commitments to reduce Neonatal Mortality Rate and Maternal Mortality Ratio. The project has learnt that interface meeting between duty bearers and the community allows for immediate feedback and the process is a strong instrument for empowerment. It facilitates monitoring and performance evaluation of services, projects and government administrative units (like district assemblies) by the community members themselves. This, in turn, makes the human resources in health to be accountable, transparent and responsive to communities where they work. This, in turn, promotes human resource performance.

Keywords: advocacy, empowerment, evidence, human resources

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Authors: Keunhong Chae, Seokho Yoon

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This paper proposes a cooperative Alamouti space time transmission scheme with low relay complexity for the cooperative communication systems. In the proposed scheme, the source node combines the data symbols to construct the Alamouti-coded form at the destination node, while the conventional scheme performs the corresponding operations at the relay nodes. In simulation results, it is shown that the proposed scheme achieves the second order cooperative diversity while maintaining the same bit error rate (BER) performance as that of the conventional scheme.

Keywords: Space-time transmission, cooperative communication system, MIMO.

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Authors: Fahad Al Yahyaey, Ihab Shaat, Russell Bush

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This study was conducted at the Livestock Research Centre, Ministry of Agriculture and Fisheries, Oman, on two local goat breeds (Jabbali and Sahrawi) due to their importance to Omani livestock production and food security. The Jabbali is characterized by increased growth rates and a higher twinning rate, while the Sahrawi has increased milk production. The aim of the study was to investigate the effect of Spirulina supplementation on live weight (BWT), average daily gain (ADG), and body conformation measurements; chest girth (CG), wither height (WH), body length (BL), and body condition score (BCS). Thirty-six males (approximately nine-months-old and 16.44 ± 0.33 kg average of initial body weight) were used across an eleven-week study from November–February 2019-2020. Each breed was divided into three groups (n = 6/group) and fed one of three rations: (1) concentrate mixture (Control) with crude protein 14% and energy 11.97% MJ/kg DM; (2) the same concentrate feed with the addition of 2 gm /capita daily Spirulina platensis (Treatment 1) and (3) the same concentrate feed with the addition of 4 gm /capita daily Spirulina platensis (Treatment 2). Analysis of weekly data collections for all traits indicated a significant effect of feeding Spirulina on all the studied traits except WH and BL. Analysis of variance for fixed effects in this study (damage and kid birth type i.e., single, twin or triple) were not significant for all studied traits. However, the breed effect was highly significant (P < 0.001) on BWT, ADG, BCS, and CG traits. On the other hand, when the analysis was done for the treatment effect within breeds for ADG, the Sahrawi breed had a significant effect (P < 0.05) at 56.52, 85.51, and 85.50 g/day for control, treatment 1 and treatment 2, respectively. This is a 51% difference between the control and treatment 1 (2 gm /capita). Whereas for the Jabbali breed, the treatment effect was not significant for ADG (P =0.55), and the actual ADG was 104.59, 118.84, and 114.25 g/day for control, treatment 1, and treatment 2, respectively, providing a 14% difference between the control group and the treated group (4 gm /capita). These findings indicate using Spirulina supplementation in Omani goat diets is recommended at 2 gm per capita as there was no benefit in feeding at 4 gm per capita for either breed. Farmers feeding Spirulina supplementation to kids after weaning at six-months could increase their herd performance and growth rate and facilitate buck selection at an earlier age.

Keywords: body conformation, goats, live weight, spirulina

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Authors: R. Schurig, T. Désesquelles, A. Dumont, E. Lefranc, A. Lux

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A cost-efficient alternative is proposed to the use of a single drone carrying multiple cameras in order to take stereoscopic images and videos during its flight. Such drone has to be particularly large enough to take off with its equipment, and stable enough in order to make valid measurements. Corresponding performance for a single aircraft usually comes with a large cost. Proposed solution consists in using multiple smaller and cheaper aircrafts carrying one camera each instead of a single expensive one. To give a proof of concept, AR drones, quad-rotor UAVs from Parrot Inc., are experimentally used.

Keywords: drone squadron, flight control, rotorcraft, Unmanned Aerial Vehicle (UAV), AR drone, stereoscopic vision

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Authors: Boukais Meriem, B. Dennai, A. Ould-Abbas

Abstract:

The efficiency of SiGe solar cells might be improved by a wide-band-gap window layer. In this work we were simulated using the one dimensional simulation program called analysis of microelectronic and photonic structures (AMPS-1D). In the simulation, the thickness of silicon window was varied from 80 to 150 nm. The rest of layer’s thicknesses were kept constant, by varying thickness of window layer the simulated device performance was demonstrate in the form of current-voltage (I-V) characteristics and quantum efficiency (QE).

Keywords: SiGe, AMPS-1D, simulation, conversion, efficiency, quantum efficiency

Procedia PDF Downloads 805

Authors: Rituraj Deka, Nomi Baruah

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The development of information technology during the past few years resulted in designing of more and more complex software. The outsourcing of software development makes a higher requirement for the management of software development project. Various software enterprises follow various paths in their pursuit of excellence, applying various principles, methods and techniques along the way. The new research is proving that CMMI and Agile methodologies can benefit from using both methods within organizations with the potential to dramatically improve business performance. The paper describes a mapping between CMMI key process areas (KPAs) and Feature-Driven Development (FDD) communication perspective, so as to increase the understanding of how improvements can be made in the software development process.

Keywords: Agile, CMMI, FDD, KPAs

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Authors: Laura Beckmann, Sabrina Rutter, Isabell Van Ackeren, Nina Bremm, Esther Dominique Klein, Kathrin Racherbäumer

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Current evidence demonstrates that schools in socially disadvantaged contexts are often characterized by lower school performance and lower educational qualifications among the student body, compared to schools in more privileged socio-spacial contexts. At the same time, national and international findings on schools with structural and social challenges show that certain school and classroom development strategies, as well as human and material resources, can significantly contribute to improved school performance of students. The aim of this contribution is to present a 6-year mixed-methods study (Talent Schools in North Rhine-Westphalia), which is designed as a school experiment addressing the well-acknowledged inequality of educational opportunities in the German school system. Started in the year 2019 and funded by the Ministry for School and Education of the State of North Rhine-Westphalia, the study targets schools in socio-spatially disadvantaged areas, which have increasingly been the focus of both public debate and educational policy. In the German-speaking countries, however, there is little knowledge available on the structure and design of complex strategies for school and classroom development that describe successful approaches to the further development of schools in disadvantaged locations in a process-oriented manner. Given these shortcomings, the present study aims at a longitudinal analysis of school and classroom development processes within 60 ‘talent schools’, whereby concrete micro-progressions within individual schools are documented and aggregated to general processes that may either impede or promote development. The main research question is the following: With the help of which strategies and (teaching) concepts, with which use of resources and with which forms of cooperation can schools contribute to the development of student achievement, including educational qualifications and transition rates in education and employment? Thus, the ‘talent schools’ may serve as examples of how social background can successfully be decoupled from educational success at schools with special structural and procedural challenges. The major chances and challenges of this project will be discussed.

Keywords: educational inequality, school development, student achievement, mixed-methods study

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Authors: Tomomi Uchiyama, Tomoko Okayama, Yukio Ide

Abstract:

This study is concerned with the development of a micro-hydraulic turbine for power generation installed in sewer pipes. The runner has a circular hollow around the central (rotating) axis so that solid materials included in water can be easily flow through the runner without blocking the turbine. The laboratory experiments are also conducted. The hollow is very effective to make polyester fibers pass through the turbine. The guide vane is useful to heighten the turbine performance. But it is easily blocked by the fibers, making the turbine lose the function.

Keywords: micro-hydraulic turbine, power generation, sewage, sewer pipe

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Authors: Aymen Bouzid, Jihen Ben Smida

Abstract:

In this paper, we propose to prove the importance of the application of blind source separation methods on remote sensing data in order to index multispectral images. The proposed method starts with Gabor Filtering and the application of a Blind Source Separation to get a more effective representation of the information contained on the observation images. After that, a feature vector is extracted from each image in order to index them. Experimental results show the superior performance of this approach.

Keywords: blind source separation, content based image retrieval, feature extraction multispectral, satellite images

Procedia PDF Downloads 403

Authors: Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor

Abstract:

During the last years, the number of extreme weather events has increased. A variety of extreme weather events, including river floods, rain-induced landslides, droughts, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions worldwide. These events have a devastating impact on critical infrastructure systems resulting in high social, economical and environmental costs. These events have a huge impact in transport systems. Since, transport networks are completely exposed to every kind of climatological perturbations, and its performance is closely related with these events. When a traffic network is affected by a climatological hazard, the quality of its service is threatened, and the level of the traffic conditions usually decreases. With the aim of understanding this process, the concept of resilience has become most popular in the area of transport. Transport resilience analyses the behavior of a traffic network when a perturbation takes place. This holistic concept studies the complete process, from the beginning of the perturbation until the total recovery of the system, when the perturbation has finished. Many concepts are included in the definition of resilience, such as vulnerability, redundancy, adaptability, and safety. Once the resilience of a transport network can be evaluated, in this case, the methodology used is a dynamic equilibrium-restricted assignment model that allows the quantification of the concept, the next step is its improvement. Through the improvement of this concept, it will be possible to create transport networks that are able to withstand and have a better performance under the presence of climatological hazards. Analyzing the impact of a perturbation in a traffic network, it is observed that the response of the different links, which are part of the network, can be completely different from one to another. Consequently and due to this effect, many questions arise, as what makes a link more critical before an extreme weather event? or how is it possible to identify these critical links? With this aim, and knowing that most of the times the owners or managers of the transport systems have limited resources, the identification of the critical links of a transport network before extreme weather events, becomes a crucial objective. For that reason, using the available resources in the areas that will generate a higher improvement of the resilience, will contribute to the global development of the network. Therefore, this paper wants to analyze what kind of characteristic makes a link a critical one when an extreme weather event damages a transport network and finally identify them.

Keywords: critical links, extreme weather events, hazard, resilience, transport network

Procedia PDF Downloads 286