Search results for: quantitative performance measurement

Authors: Lawal Kado

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This paper investigates the perceptions of academic staff at Umaru Musa Yar’adua University regarding the influences of librarians and working colleagues on the awareness and use of electronic databases. The study aims to provide insights into the effectiveness of these influences and suggest strategies to improve the usage of electronic databases. Research aim: The aim of this study is to determine the perceptions of academic staff on the influence of librarians and working colleagues towards the awareness and use of electronic databases in Umaru Musa Yar’adua University, Katsina. Methodology: The study adopts a quantitative method and survey research design. The survey questionnaire is distributed to 110 respondents selected through simple random sampling from a population of 523 academic staff. The collected data is analyzed using the Statistical Package for Social Sciences (SPSS) version 23. Findings: The study reveals a high level of general awareness of electronic databases in the university, largely influenced by librarians and colleagues. Librarians have played a crucial role in making academic staff aware of the available databases. The sources of information for awareness include colleagues, social media, e-mails from the library, and internet searching. Theoretical importance: This study contributes to the literature by examining the perceptions of academic staff, which can inform policymakers and stakeholders in developing strategies to maximize the use of electronic databases. Data collection and analysis procedures: The data is collected through a survey questionnaire that utilizes the Likert scaling technique. The closed-ended questions are analyzed using SPSS 23. Question addressed: The paper addresses the question of how librarians and working colleagues influence the awareness and use of electronic databases among academic staff. Conclusion: The study concludes that the influence of librarians and working colleagues significantly contributes to the awareness and use of electronic databases among academic staff. The paper recommends the establishment of dedicated departments or units for marketing library resources to further promote the usage of electronic databases.

Keywords: awareness, electronic databases, academic staff, unified theory of acceptance and use of technology, social influence

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Authors: Lopez J., Mehrvar M., Quinones E., Suarez A., RomeroC.

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The Silver Nanoparticles (AgNP) are used as deliver of heat on surface of Membrane Distillation in order to fight against Thermal Polarization and improving the Desalination Process. In this study AgNPwere deposited by dip coating process over PVDF, FG hydrophilic, and PTFE hydrophobic commercial membranes as substrate. Membranes were characterized by SEM, EDS, contact angle, Pore size distributionand using a UV lamp and a thermal camera were measured the performance of heat deliver. The presence of AgNP 50 – 150 nm and the increase in absorption of energy over membrane were verified.

Keywords: silver nanoparticles, membrane distillation, plasmon effect, heat deliver

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Authors: V. Sankaranarayanan, V. Amrita Sundari, Sunit P. Gopal

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This paper presents the design and implementation of a nonlinear controller for the point to point control of a mobile inverted pendulum (MIP). The controller is designed based on the kinematic model of the MIP to stabilize all the four coordinates. The stability of the closed-loop system is proved using Lyapunov stability theory. The proposed controller is validated through numerical simulations and also implemented in a laboratory prototype. The results are presented to evaluate the performance of the proposed closed loop system.

Keywords: mobile inverted pendulum, switched control, nonlinear systems, lyapunov stability

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Sandra Ghavam Shirazi, Komeil Valipourian, Mohammad Reza Golhashem

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This paper represents the basic idea and mechanisms associated with the durability of geomembranes and discusses the factors influencing the service life and temperature of geomembrane liners. Geomembrane durability is stated as field performance and laboratory test outcomes under various conditions. Due to the high demand of geomembranes as landfill barriers and their crucial role in sensitive projects, sufficient service life of geomembranes is very important, therefore in this paper, the durability, the effect of temperature on geomembrane and the role of this type of reinforcement in different types of soil will be discussed. Also, the role of geomembrane in the earthquake will be considered in the last part of the paper.

Keywords: geomembrane, durability temperature soil mechanic, soil

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Authors: Felix Golla

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In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula.

Keywords: chatbot design in education, high-performance cycle model application, qualitative research in AI, student-centered learning technologies

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Authors: Fang Liu, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun, JunShuai Xue

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The explosive increasing needs of data processing and information storage strongly drive the advancement of the binary logic system to multiple-valued logic system. Inherent negative differential resistance characteristic, ultra-high-speed switching time, and robust anti-irradiation capability make III-nitride resonant tunneling diode one of the most promising candidates for multi-valued logic devices. Here we report the monolithic integration of GaN resonant tunneling diodes in series to realize multiple negative differential resistance regions, obtaining at least three stable operating states. A multiply-by-three circuit is achieved by this combination, increasing the frequency of the input triangular wave from f0 to 3f0. The resonant tunneling diodes are grown by plasma-assistedmolecular beam epitaxy on free-standing c-plane GaN substrates, comprising double barriers and a single quantum well both at the atomic level. Device with a peak current density of 183kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed, which is the best result reported in nitride-based resonant tunneling diodes. Microwave oscillation event at room temperature was discovered with a fundamental frequency of 0.31GHz and an output power of 5.37μW, verifying the high repeatability and robustness of our device. The switching behavior measurement was successfully carried out, featuring rise and fall times in the order of picoseconds, which can be used in high-speed digital circuits. Limited by the measuring equipment and the layer structure, the switching time can be further improved. In general, this article presents a novel nitride device with multiple negative differential regions driven by the resonant tunneling mechanism, which can be used in high-speed multiple value logic field with reduced circuit complexity, demonstrating a new solution of nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, negative differential resistance, multiple-valued logic system, switching time, peak-to-valley current ratio

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Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

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Authors: Julio Jesus Salazar, Max Jesus De Lama

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The challenges of water management are aggravated by global change, which implies high complexity and associated uncertainty; water management is difficult because water networks cross domains (natural, societal, and political), scales (space, time, jurisdictional, institutional, knowledge, etc.) and levels (area: patches to global; knowledge: a specific case to generalized principles). In this context, we need to apply natural and non-natural measures to manage water and soil. The Basin Management Methodology considers multifunctional measures of natural water retention and erosion control and soil formation to protect water resources and address the challenges related to the recovery or conservation of the ecosystem, as well as natural characteristics of water bodies, to improve the quantitative status of water bodies and reduce vulnerability to floods and droughts. This method of water management focuses on the positive impacts of the chemical and ecological status of water bodies, restoration of the functioning of the ecosystem and its natural services; thus, contributing to both adaptation and mitigation of climate change. This methodology was applied in 7 interventions in the sub-basin of the Shullcas River in Huancayo-Junín-Peru, obtaining great benefits in the framework of the participation of alliances of actors and integrated planning scenarios. To implement the methodology in the sub-basin of the Shullcas River, a process called Climate Smart Territories (CST) was used; with which the variables were characterized in a highly complex space. The diagnosis was then worked using risk management and adaptation to climate change. Finally, it was concluded with the selection of alternatives and projects of this type. Therefore, the CST approach and process face the challenges of climate change through integrated, systematic, interdisciplinary and collective responses at different scales that fit the needs of ecosystems and their services that are vital to human well-being. This methodology is now replicated at the level of the Mantaro river basin, improving with other initiatives that lead to the model of a resilient basin.

Keywords: climate-smart territories, climate change, ecosystem services, natural measures, Climate Smart Territories (CST) approach

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Authors: Narges Shayesteh Moghaddam

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Tungsten (W), a refractory metal known for its remarkably high melting temperature, offers tremendous potential for use in challenging environments prevalent in sectors such as space exploration, defense, and nuclear industries. Additive manufacturing, especially the Laser Powder-Bed Fusion (LPBF) technique, emerges as a beneficial method for fabricating tungsten parts. This technique enables the production of intricate components while simultaneously reducing production lead times and associated costs. However, the inherent brittleness of tungsten and its tendency to crack under high-temperature conditions pose significant challenges to the manufacturing process. Our research primarily focuses on the process of rolling tungsten parts in a layer-by-layer manner in LPBF and the subsequent changes in microstructure. Our objective is not only to identify the alterations in the microstructure but also to assess their implications on the physical properties and performance of the fabricated tungsten parts. To examine these aspects, we conducted an extensive series of experiments that included the fabrication of tungsten samples through LPBF and subsequent characterization using advanced materials analysis techniques. These investigations allowed us to scrutinize shifts in various microstructural features, including, but not limited to, grain size and grain boundaries occurring during the rolling process. The results of our study provide crucial insights into how specific factors, such as plastic deformation occurring during the rolling process, influence the microstructural characteristics of the fabricated parts. This information is vital as it provides a foundation for understanding how the parameters of the layer-by-layer rolling process affect the final tungsten parts. Our research significantly broadens the current understanding of microstructural evolution in tungsten parts produced via the layer-by-layer rolling process in LPBF. The insights obtained will play a pivotal role in refining and optimizing manufacturing parameters, thus improving the mechanical properties of tungsten parts and, therefore, enhancing their performance. Furthermore, these findings will contribute to the advancement of manufacturing techniques, facilitating the wider application of tungsten parts in various high-demand sectors. Through these advancements, this research represents a significant step towards harnessing the full potential of tungsten in high-temperature and high-stress applications.

Keywords: additive manufacturing, rolling, tungsten, refractory materials

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Renuka H. Deshmukh, Snehal Nifadkar, Anil P. Dongre

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The research study aims to analyze the financial performance of the companies associated with CDM projects implemented in India from 2001 to 2014 by calculating net profit with and without CDM revenue. Further the study also highlights the Year-wise and sector-wise lending to CDM projects in India as well as in the state of Maharashtra. The study further aims to examine the year-wise trend of Certified Emission Reductions (CER) issued by the CDM projects implemented in Maharashtra from 2001-2014. The study as well analyses the responses of selected corporate with respect to the challenges in implementing and obtaining finance from commercial banks.

Keywords: adaptation costs, internal rate of return, mitigation, vulnerability, CER

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Authors: Natasha Yasmin Felles, Gerard Riley

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Background and Aims: Relationship breakdown is typical when one partner lives with an acquired brain injury caused by issues like a stroke. Research has found that the perception of relationship satisfaction decreases following such an injury among non-injured partners. Non-injured partners also are found to experience caregiver stress/burden as they immediately have to take the role of a caregiver along with being a partner of the injured. Research has also found that the perception of a continuous relationship, i.e. the perception of the relationship to be essentially the same as it was before the injury, also changes among those caregiving partners. However, there is a lack of available intervention strategies that can help those partners with both individual and relationship difficulties. The aim of this case study was to conduct a pilot test of an intervention aimed to explore whether it is possible to support a partner to experience greater continuity within the relationship poststroke, and what benefits such a change might have. Method: A couple, where one partner experienced an acquired brain injury poststroke were provided with Integrated Behavioural Couples Therapy for 3-months. The intervention addressed goals identified as necessary by the couple and by the formulation of their individual and relationship difficulties, alongside the goal of promoting relationship continuity. Before and after measures were taken using a battery of six questionnaires to evaluate changes in perceptions of continuity, stress, and other aspects of the relationship. Results: Both quantitative and qualitative data showed that relationship continuity was improved after the therapy, as were the measures of stress and other aspects of the relationship. The stress felt by the person with the acquired brain injury also showed some evidence of improvement. Conclusion: The study found that perceptions of relationship continuity can be improved by therapy and that improving these might have a beneficial impact on the stress felt by the carer, their satisfaction with the relationship and overall levels of conflict and closeness within the relationship. The study suggested the value of further research on enhancing perceptions of continuity in the relationship after an acquired brain injury. Currently, the findings of the study have been used to develop a pilot feasibility study to collect substantive evidence on the impact of the intervention on the couples and assess its feasibility and acceptability, which will help in further developing a specific generalized relationship continuity intervention, that will be beneficial in preventing relationship breakdown in the future.

Keywords: acquired brain injury, couples therapy, relationship continuity, stroke

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Authors: Suharni Mohamad Suharni Mohamad, Nurul Izzati Hamzan Nurul Izzati Hamzan, Norhayu Abdul Rahman Norhayu Abdul Rahman, Siti Suraiya Md Noor Siti Suraiya Md Noor

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Human papillomavirus (HPV) is an important risk factor for development of oral cancer. HPV16 is the most common type found in HPV-positive squamous cell carcinoma. In the present study, we established a real-time loop-mediated isothermal amplification (real-time LAMP) for detection of HPV16. A set of six primers was specially designed to recognize eight distinct sequences of HPV16-E6. Detection and quantification was achieved by real-time monitoring using a real-time turbidimeter based on threshold time required for turbidity in the LAMP reaction. LAMP reagents (MgSO4, dNTPs, Bst polymerase concentrations) and various incubation times and temperatures were optimized. The sensitivity was determined using 10-fold serial dilutions of HPV16 standard strain. The specificity of was evaluated using other HPV genotypes. The optimized method was established with specifically designed primers by real-time detection in approximately 30 min at 65°C. The limit of detection of HPV16 using the LAMP assay was 10 pg/ml that could be detected in 30 min. The LAMP assay was 10 times more sensitive than the conventional PCR in detecting HPV16. No cross-reactivity with other HPV genotypes was observed. This quantitative real-time LAMP assay may improve diagnostic potential for the detection and quantification of HPV16 in clinical samples and epidemiological studies due to its rapidity, simplicity, high sensitivity and specificity. This assay will be further evaluated with HPV DNAs of saliva from patients with oral squamous cell carcinoma. Acknowledgement: This study was financially supported by the ScienceFund Grant, Ministry of Science, Technology and Innovation (305/PPSG/6113219).

Keywords: Oral Squamous Cell Carcinoma (OSCC), Human Papillomavirus 16 (HPV16), Loop-Mediated Isothermal Amplification (LAMP), rapid detection

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Authors: Tegene Nigussie

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Introduction: Maize is the most domesticated of all the field crops. Wild maize has not been found to date and there has been much speculation on its origin. Regardless of the validity of different theories, it is generally agreed that the center of origin of maize is Central America, primarily Mexico and the Caribbean. Maize in Africa is of a recent introduction although data suggest that it was present in Nigeria even before Columbus voyages. After being taken to Europe in 1493, maize was introduced to Africa and distributed through the continent by different routes. Maize is an important cereal crop in Ethiopia. In general, it is the primarily stable food, and rural households show a strong preference. For human food, the important constituents of grain are carbohydrates (starch and sugars), protein, fat or oil (in the embryo) and minerals. About 75 percent of the kernel is starch, a range of 60.80 percent, but low protein content (8-15). In Ethiopia, the introduction of modern farming techniques appears to be a priority. However, the adoption of modern inputs by peasant farmers is found to be very slow; for example, the adoption rate of fertilizer, an input that is relatively adopted, is very slow. The difference socio economic factors lied behind the low rate of technology adoption, including price &marketing input. Objective: The objective of this study is to determine the optimum application rate or level of different nitrogen fertilizers for the vegetative growth of maize and to identify the effect of different nitrogen rates on the growth and development of maize. Methods: The vegetative parameter (above ground) measurement from five plants randomly sampled from the middle rows of each plot. Results: The interaction of nitrogen and maize variety showed a significant at (p<0.01) effect on plant height, with the application of 60kg/ha and BH140 maize variety in combination and root length with the application of 60kg/ha of nitrogen and BH140 variety of maize. The highest mean (12.33) of the number of leaves per plant and mean (7.1) of the number of nodes per plant can be used as an alternative for better vegetative growth of maize. Conclusion: Maize is one of the most popular and cultivated crops in Ethiopia. The study was conducted to investigate the best dosage of nitrogen for vegetative growth, yield, and better quality of maize variety and to recommend a level of nitrogen rate and the best variety adaptable to the specific soil condition or area.

Keywords: parameter, chlorosis, germination, flood, sesbania, cultivar

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Authors: Aharouay Soumaya

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Efficiency is a relative concept. It is measured by comparing the productivity obtained in what is intended as standard or objective criteria. The quantity and quality of output achieved and the level of service are also compared to targets or standards, to determine to what extent they could cause changes in efficiency. Efficiency improves when more outputs of a specified quality are produced with the same resource inputs or less, or when the same amount of output is produced with fewer resources. This article proposes a review of the literature on strategies adopted by firms in the age of the financial crisis to overcome these negative effects, and tracks progress chosen by the organization to remain successful despite the plight of firms.

Keywords: effectiveness, efficiency, organizational capacity, strategy, management tool, progress, performance

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Authors: Ardalan Sabamehr, Ashutosh Bagchi

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Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods.

Keywords: ambient vibration, frequency domain decomposition, stochastic subspace identification, continuous wavelet transform

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Authors: David Muyise

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Mixed Integer Programming (MIP) is an approach that involves the optimization of a range of decision variables in order to minimize or maximize a particular objective function. The main objective of this study was to apply the MIP approach to optimize the deployment of waste plastic to fuel oil processing plants in Uganda. The processing plants are meant to reduce plastic pollution by pyrolyzing the waste plastic into a cleaner fuel that can be used to power diesel/paraffin engines, so as (1) to reduce the negative environmental impacts associated with plastic pollution and also (2) to curb down the energy gap by utilizing the fuel oil. A programming model was established and tested in two case study applications that are, small-scale applications in rural towns and large-scale deployment across major cities in the country. In order to design the supply chain, optimal decisions on the types of waste plastic to be processed, size, location and number of plants, and downstream fuel applications were concurrently made based on the payback period, investor requirements for capital cost and production cost of fuel and electricity. The model comprises qualitative data gathered from waste plastic pickers at landfills and potential investors, and quantitative data obtained from primary research. It was found out from the study that a distributed system is suitable for small rural towns, whereas a decentralized system is only suitable for big cities. Small towns of Kalagi, Mukono, Ishaka, and Jinja were found to be the ideal locations for the deployment of distributed processing systems, whereas Kampala, Mbarara, and Gulu cities were found to be the ideal locations initially utilize the decentralized pyrolysis technology system. We conclude that the model findings will be most important to investors, engineers, plant developers, and municipalities interested in waste plastic to fuel processing in Uganda and elsewhere in developing economy.

Keywords: mixed integer programming, fuel oil plants, optimisation of waste plastics, plastic pollution, pyrolyzing

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Authors: Talha Shafiq

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The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

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Authors: Qin Yao

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Content and language integrated instruction provides second language learners instruction in subject matter and language, and is greatly valued, particularly in the language immersion classroom where a language other than students’ first language is the vehicle for teaching school curriculum. Corrective feedback is an essential instructional technique for teachers to integrate a focus on language into their content instruction. This study aims to fill a gap in the literature on immersion—the lack of studies examining corrective feedback in Chinese immersion classrooms, by studying learning opportunities brought by oral corrective feedback in a Chinese immersion classroom. Specifically, it examines what is the distribution of different types of teacher corrective feedback and how students respond to each feedback type, as well as how the focus of the teacher-student interactional exchanges affect the effect of feedback. Two Chinese immersion teachers and their immersion classes were involved, and data were collected through classroom observations interviews. Observations document teachers’ provision of oral corrective feedback and students’ responses following the feedback in class, and interviews with teachers collected teachers’ reflective thoughts about their teaching. A primary quantitative and qualitative analysis of the data revealed that, among different types of corrective feedback, recast occurred most frequently. Metalinguistic clue and repetition were the least occurring feedback types. Clarification request lead to highest percentage of learner uptake manifested by learners’ oral production immediately following the feedback, while explicit correction came the second and recast the third. In addition, the results also showed the interactional context played a role in the effectiveness of the feedback: teachers were most likely to give feedback in conversational exchanges that focused on explicit language and content, while students were most likely to use feedback in exchanges that focused on explicit language. In conclusion, the results of this study indicate recasts are preferred by Chinese immersion teachers, confirming results of previous studies on corrective feedback in non-Chinese immersion classrooms; and clarification request and explicit language instruction elicit more target language production from students and are facilitative in their target language development, thus should not be overlooked in immersion and other content and language integrated classrooms.

Keywords: Chinese immersion, content and language integrated instruction, corrective feedback, interaction

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Authors: Frederick M. Dumisani Xaba, Nokuthula G. Khanyile

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There is a growing demand for greater accountability, transparency and ethical conduct based on sound governance principles in the developing world. Funders, donors and sponsors are increasingly demanding more transparency, better value for money and adherence to good governance standards. The drive towards improved governance measures is largely influenced by the need to ‘plug the leaks’, deal with malfeasance, engender greater levels of accountability and good governance and to ultimately attract further funding or investment. This is the case with the Non-Profit Organizations (NPOs) in South Africa in general, and in the province of KwaZulu-Natal in particular. The paper draws from the good governance theory, stakeholder theory and systems thinking to critically examine the requirements for good governance for the NPO sector from a theoretical and legislative point and to systematically looks at the contours of governance currently among the NPOs. The paper did this through the rigorous examination of the vignettes of cases of governance among selected NPOs based in KwaZulu-Natal. The study used qualitative and quantitative research methodologies through document analysis, literature review, semi-structured interviews, focus groups and statistical analysis from the various primary and secondary sources. It found some good cases of good governance but also found frightening levels of poor governance. There was an exponential growth of NPOs registered during the period under review, equally so there was an increase in cases of non-compliance to good governance practices. NPOs operate in an increasingly complex environment. There is contestation for influence and access to resources. Stakeholder management is poorly conceptualized and executed. Recognizing that the NPO sector operates in an environment characterized by complexity, constant changes, unpredictability, contestation, diversity and divergent views of different stakeholders, there is a need to apply legislative and systems thinking approaches to strengthen governance to withstand this turbulence through a capacity development model that recognizes these contextual and environmental challenges.

Keywords: good governance, non-profit organizations, stakeholder theory, systems theory

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Singara Singh Kasana, Pankaj Garg

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In this paper, a blind data hiding technique based on interpolation of sub sampled versions of a cover image is proposed. Sub sampled image is taken as a reference image and an interpolated image is generated from this reference image. Then difference between original cover image and interpolated image is used to embed secret data. Comparisons with the existing interpolation based techniques show that proposed technique provides higher embedding capacity and better visual quality marked images. Moreover, the performance of the proposed technique is more stable for different images.

Keywords: interpolation, image subsampling, PSNR, SIM

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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Authors: Dionyssia Lyra, Shoaib Ismail

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Salinization of natural resources constitutes a significant component of the degradation force that leads to depletion of productive lands and fresh water reserves. The global extent of salt-affected soils is approximately 7% of the earth’s land surface and is expanding. The problems of excessive salt accumulation are most widespread in coastal, arid and semi-arid regions, where agricultural production is substantially hindered. The use of crops that can withstand high saline conditions is extremely interesting in such a context. Salt-loving plants or else ‘halophytes’ thrive when grown in hostile saline conditions, where traditional crops cannot survive. Salicornia bigelovii, a halophytic crop with multiple uses (vegetable, forage, biofuel), has demonstrated remarkable adaptability to harsh climatic conditions prevailing in dry areas with great potential for its expansion. Since 2011, the International Center for Biosaline Agriculture (ICBA) with Masdar Institute (MI) and King Abdul Aziz University of Science & Technology (KAUST) to look into the potential for growing S. bigelovii under hot and dry conditions. Through the projects undertaken, 50 different S. bigelovii genotypes were assessed under high saline conditions. The overall goal was to select the best performing S. bigelovii populations in terms of seed and biomass production for future breeding. Specific objectives included: 1) evaluation of selected S. bigelovii genotypes for various agronomic and growth parameters under field conditions, 2) seed multiplication of S. bigelovii using saline groundwater and 3) acquisition of inbred lines for further breeding. Field trials were conducted for four consecutive years at ICBA headquarters. During the first year, one Salicornia population was evaluated for seed and biomass production at different salinity levels, fertilizer treatments and planting methods. All growth parameters and biomass productivity for the salicornia population showed better performance with optimal biomass production in terms of both salinity level and fertilizer application. During the second year, 46 Salicornia populations (obtained from KAUST and Masdar Institute) were evaluated for 24 growth parameters and treated with groundwater through drip irrigation. The plant material originated from wild collections. Six populations were also assessed for their growth performance under full-strength seawater. Salicornia populations were highly variable for all characteristics under study for both irrigation treatments, indicating that there is a large pool of genetic information available for breeding. Irrigation with the highest level of salinity had a negative impact on the agronomic performance. The maximum seed yield obtained was 2 t/ha at 20 dS/m (groundwater treatment) at 25 cm x 25 cm planting distance. The best performing Salicornia populations for fresh biomass and seed yield were selected for the following season. After continuous selection, the best performing salicornia will be adopted for scaling-up options. Taking into account the results of the production field trials, salicornia expansion will be targeted in coastal areas of the Arabian Peninsula. As a crop with high biofuel and forage potential, its cultivation can improve the livelihood of local farmers.

Keywords: biosaline agriculture, genotypes selection, halophytes, Salicornia bigelovii

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Authors: D. Habibinia, M. R. Feyzi

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Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

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Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

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Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: H. Ishii, S. Araki, H. Yamamoto

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In recent years, the carbon dioxide (CO2) separation technology is required in terms of the reduction of emission of global warming gases and the efficient use of fossil fuels. Since the emission amount of CO2 gas occupies the large part of greenhouse effect gases, it is considered that CO2 have the most influence on global warming. Therefore, we need to establish the CO2 separation technologies with high efficiency at low cost. In this study, we focused on the membrane separation compared with conventional separation technique such as distillation or cryogenic separation. In this study, we prepared carbonate-ceramic dual-phase membranes to separate CO2 at high temperature. As porous ceramic substrate, the (Pr0.9La0.1)2(Ni0.74Cu0.21Ga0.05)O4+σ, La0.6Sr0.4Ti0.3 Fe0.7O3 and Ca0.8Sr0.2Ti0.7Fe0.3O3-α (PLNCG, LSTF and CSTF) were examined. PLNCG, LSTF and CSTF have the perovskite structure. The perovskite structure has high stability and shows ion-conducting doped by another metal ion. PLNCG, LSTF and CSTF have perovskite structure and has high stability and high oxygen ion diffusivity. PLNCG, LSTF and CSTF powders were prepared by a solid-phase process using the appropriate carbonates or oxides. To prepare porous substrates, these powders mixed with carbon black (20 wt%) and a few drops of polyvinyl alcohol (5 wt%) aqueous solution. The powder mixture were packed into stainless steel mold (13 mm) and uniaxially pressed into disk shape under a pressure of 20 MPa for 1 minute. PLNCG, LSTF and CSTF disks were calcined in air for 6 h at 1473, 1573 and 1473 K, respectively. The carbonate mixture (Li2CO3/Na2CO3/K2CO3: 42.5/32.5/25 in mole percent ratio) was placed inside a crucible and heated to 793 K. Porous substrates were infiltrated with the molten carbonate mixture at 793 K. Crystalline structures of the fresh membranes and after the infiltration with the molten carbonate mixtures were determined by X-ray diffraction (XRD) measurement. We confirmed the crystal structure of PLNCG and CSTF slightly changed after infiltration with the molten carbonate mixture. CO2 permeation experiments with PLNCG-carbonate, LSTF-carbonate and CSTF-carbonate membranes were carried out at 773-1173 K. The gas mixture of CO2 (20 mol%) and He was introduced at the flow rate of 50 ml/min to one side of membrane. The permeated CO2 was swept by N2 (50 ml/min). We confirmed the effect of ceramic materials and temperature on the CO2 permeation at high temperature.

Keywords: membrane, perovskite structure, dual-phase, carbonate

Procedia PDF Downloads 363