Search results for: hybrid ventilation techniques

Authors: Harminder Kaur, Manpreet Kaur, Akanksha Kapila, Reenu

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Schiff base with general formula H₂L was derived from condensation of o-vanillin and 3-nitro-o-phenylenediamine. This Schiff base was used for the synthesis of organotin(IV) complexes with general formula R₂SnL [R=Phenyl or n-octyl] using equimolar quantities. Elemental analysis UV-Vis, FTIR, and multinuclear spectroscopic techniques (¹H, ¹³C, and ¹¹⁹Sn) NMR were carried out for the characterization of the synthesized complexes. These complexes were coloured and soluble in polar solvents. Computational studies have been performed to obtain the details of the geometry and electronic structures of ligand as well as complexes. Geometry of the ligands and complexes have been optimized at the level of Density Functional Theory with B3LYP/6-311G (d,p) and B3LYP/MPW1PW91 respectively followed by vibrational frequency analysis using Gaussian 09. Observed ¹¹⁹Sn NMR chemical shifts of one of the synthesized complexes showed tetrahedral geometry around Tin atom which is also confirmed by DFT. HOMO-LUMO energy distribution was calculated. FTIR, ¹HNMR and ¹³CNMR spectra were also obtained theoretically using DFT. Further IRC calculations were employed to determine the transition state for the reaction and to get the theoretical information about the reaction pathway. Moreover, molecular docking studies can be explored to ensure the anticancer activity of the newly synthesized organotin(IV) complexes.

Keywords: DFT, molecular docking, organotin(IV) complexes, o-vanillin, 3-nitro-o-phenylenediamine

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: David E. Esezobor, Friday I. Apeh, Harrison O. Onovo, Ademola A. Agbeleye

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Available indigenous refractory bricks in Nigeria can only be used in the lining of furnaces for melting of cast iron operating at less than 1,400°C or in preheating furnaces due to their low refractoriness less than 1,500°C. The bricks crack and shatter on heating at 1350 to 1450°C. In this paper, a simple and adaptable technology of manufacturing high-quality refractory bricks from selected Nigerian clays for furnace linings was developed. Fireclays from Onibode, Owode-Ketu in Ogun State and Kwoi in Kaduna State were crushed, ground, and sieved into various grain sizes using standard techniques. The pulverized clays were blended with alumina in various mix ratios and indurated in the furnace at 900 – 16000C. Their chemical, microstructure and mineralogical properties were characterized using atomic absorption spectrophotometry, scanning electron microscopy and x-ray diffraction spectrometry respectively. The mineralogical and spectrochemical analyses suggested that the clays are of siliceous alumino-silicate and acidic in nature. The appropriate blending of fireclays with alumina provided the tremendous improvement in the refractoriness of the bricks and other acceptable service properties comparable with imported refractory bricks. The change in microstructure from pseudo-hexagonal grains to equiaxed grains of well – ordered sequence of structural layers could be responsible for the improved properties.

Keywords: alumina, furnace, industry, manufacturing, refractoriness

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Authors: Olha Yarova

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This study is a collaborative project between the American University of Central Asia and parent association of children with Down syndrome ‘Sunterra’ that took place in Bishkek, Kyrgyzstan. The purpose of the study was to explore whether principles and techniques of applied behavior analysis (ABA) could be used to teach children with Down syndrome socially significant behaviors. ABA is considered to be one of the most effective treatment for children with autism, but little research is done on the particularity of using ABA to children with Down syndrome. The data for the study was received during clinical observations; work with children with Down syndrome and interviews with their mothers. The results show that many ABA principles make the work with children with Down syndrome more effective. Although such children very rarely demonstrate aggressive behavior, they show a lot of escape-driven and attention seeking behaviors that are reinforced by their parents and educators. Thus functional assessment can be done to assess the function of problem behavior and to determine appropriate treatment. Prompting and prompting fading should be used to develop receptive and expressive language skills, and enhance motor development. Even though many children with Down syndrome work for praise, it is still relevant to use tangible reinforcement and to know how to remove them. Based on the results of the study, the training for parents of children with Down syndrome will be developed in Kyrgyzstan, country, where children with Down syndrome are not accepted to regular kindergartens and where doctors in maternity hospitals tell parents that their child will never talk, walk and recognize them

Keywords: down syndrome, applied behavior analysis, functional assessment, problem behavior, reinforcement

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Authors: Felipe M. de Freitas, Ícaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

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There is a dispersed energy in Radio Frequencies (RF) that can be reused to power electronics circuits such as: sensors, actuators, identification devices, among other systems, without wire connections or a battery supply requirement. In this context, there are different types of energy harvesting systems, including rectennas, coil systems, graphene and new materials. A secondary step of an energy harvesting system is the rectification of the collected signal which may be carried out, for example, by the combination of one or more Schottky diodes connected in series or shunt. In the case of a rectenna-based system, for instance, the diode used must be able to receive low power signals at ultra-high frequencies. Therefore, it is required low values of series resistance, junction capacitance and potential barrier voltage. Due to this low-power condition, voltage multiplier configurations are used such as voltage doublers or modified bridge converters. Lowpass filter (LPF) at the input, DC output filter, and a resistive load are also commonly used in the rectifier design. The electronic circuits projects are commonly analyzed through simulation in SPICE (Simulation Program with Integrated Circuit Emphasis) environment. Despite the remarkable potential of SPICE-based simulators for complex circuit modeling and analysis of quasi-static electromagnetic fields interaction, i.e., at low frequency, these simulators are limited and they cannot model properly applications of microwave hybrid circuits in which there are both, lumped elements as well as distributed elements. This work proposes, therefore, the electromagnetic modelling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-high frequencies, with application in rectifiers coupled to antennas, as in energy harvesting systems, that is, in rectennas. For this purpose, the numerical method FDTD (Finite-Difference Time-Domain) is applied and SPICE computational tools are used for comparison. In the present work, initially the Ampere-Maxwell equation is applied to the equations of current density and electric field within the FDTD method and its circuital relation with the voltage drop in the modeled component for the case of lumped parameter using the FDTD (Lumped-Element Finite-Difference Time-Domain) proposed in for the passive components and the one proposed in for the diode. Next, a rectifier is built with the essential requirements for operating rectenna energy harvesting systems and the FDTD results are compared with experimental measurements.

Keywords: energy harvesting system, LE-FDTD, rectenna, rectifier, wireless power systems

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: E. Erdem, M. Şahin, M. Saçak

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Smectite is a layered silicate and modified with alkyl ammonium salts to make both the hydrophilic silicate surfaces organophilic, and to expand the clay layers. Thus, a nanocomposite structure can be formed enabling to enter various types of polymers between the layers. In this study, Na-smectite crystals were prepared by purification of bentonite. Benzyltributylammonium bromide (BTBAB) was used as a swelling agent. The mixing time and additive concentration were changed during the swelling process. It was determined that the 4 h of mixing time and 0.2 g of BTBAB were sufficient and the usage of higher amounts of salt did not increase the interlayer space between the clay layers. Then, the conductive poly(o-toluidine) (POT)/smectite nanocomposite was prepared in the presence of swollen Na-smectite using ammonium persulfate (APS) as oxidant in aqueous acidic medium. The POT content and conductivity of the prepared nanocomposite were systematically investigated as a function of polymerization conditions such as the treatment time of swollen smectite in monomer solution and o-toluidine/APS mol ratio. The POT content and conductivity of nanocomposite increased with increasing monomer/oxidant mol ratio up to 1 and did not change at higher ratios. The maximum polymer yield and the highest conductivity value of the composite were 26.0% and 4.0×10-5 S/cm, respectively. The structural and morphological analyses of the POT/smectite nanocomposite were carried out by XRD, FTIR and SEM techniques, respectively.

Keywords: clay, composite, conducting polymer, poly(o-anisidine)

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Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

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Authors: Abdel Ghany F. Shoair, Mai M. A. H. Shanab

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The basic aqueous systems NiSO4.6H₂O / K₂S₂O₈ (PH= 14) or NiSO₄.6H₂O / KBrO₃ (PH = 11.5) were ‎investigated ‎for the ‎catalytic conversion benzyl alcohol and ‎some para-substituted benzyl ‎alcohols to their ‎corresponding ‎acids in 75-97 % yield at room ‎temperature. The active species ‎was isolated and characterized by scanning ‎electron ‎microscopy (SEM), ‎‎transmission electron microscopy (TEM), X-ray ‎powder diffraction, EDX and ‎‎FT-IR ‎techniques and identified as NiO₂ nanoparticles (NPNPs). The SEM and ‎TEM images of nickel peroxide samples show a fine spherical-like ‎aggregation of ‎NiO₂ molecules with a nearly homogeneous partial size and confirm the ‎aggregation's size ‎to ‎be in the range of 2-3 nm. The yields, turnover (TO) and turn ‎over frequencies (TOF) were calculated. ‎It was noticed ‎that the aromatic alcohols ‎containing para-substituted electron donation groups gave better ‎‎yields than ‎those having electron-withdrawing groups. The optimum conditions for this ‎‎catalytic reaction ‎were studied using benzyl alcohol as a model. The mechanism ‎of the ‎catalytic conversion reaction was ‎suggested, in which the produced ‎(NPNPs) convert alcohols ‎to acids in two steps through the formation of the ‎‎corresponding aldehyde. The produced ‎NiO, because of this conversion, is ‎converted again to (NPNPs) by ‎an excess of K₂S₂O₈ or KBrO₃. This ‎catalytic cycle continues ‎until all the substrate is oxidized.

Keywords: Nickel, oxidation, catalysts, benzyl alcohol

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Authors: Theoni Soublis

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The COVID-19 pandemic created a severe interruption in teaching and learning in K-12 schools. It is essential that educational researchers, teachers, and administrators understand the long term effects that COVID-19 had on a variety of stakeholders in education. This investigation aims to analyze the research since the beginning of the pandemic that focuses specifically on teacher retention, resilience, and training. The results of this investigation will help to inform future research in order to better understand how the institution of education can continue to be prepared and to better prepare for future significant shifts in the modalities of instruction. The results of this analysis will directly impact the field of education as it will broaden the scope of understanding regarding how COVID- 19 impacted teaching and learning. The themes that will emerge from the data analysis will directly inform policy makers, administrators, and researchers about how to best implement training and curriculum design in order to support teacher effectiveness this in the classroom. Educational researchers have written about how teacher morale plummeted and how many teachers reported early burnout and higher stress levels. Teachers’ stress and anxiety soared during the COVID-19 pandemic, but so has their resilience and dedication to the field of education. This research aims to understand how public-school teachers overcame teaching obstacles presented to them during COVID-19. Research has been conducted to identify a variety of information regarding the impact the pandemic has had on K-12 teachers, students, and families. This research aims to understand how teachers continued to pursue their teaching objectives without significant training of effective online instruction methods. Not many educators even heard of the video conferencing platform Zoom before the spring of 2020. Researchers are interested in understanding how teachers used their expertise, prior knowledge, and training to institute immediate and effective online learning environments, what types of relationships did teachers build with students while teaching 100% remotely, and how did relationships change with students while teaching remotely? Furthermore, did the teacher-student relationship propel teacher resolve to be successful while teaching during a pandemic. Recent world events have significantly impacted the field of public-school teaching. The pandemic forced teachers to shift their paradigm about how to maintain high academic expectations, meet state curriculum standards, and assess students learning gains to make data-informed decisions while simultaneously adapting modes of instruction through multiple outlets with little to no training on remote, synchronous, asynchronous, virtual, and hybrid teaching. While it would be very interesting to study how teaching positively impacted students learning during the pandemic, I am more interested in understanding how teaches stayed the course and maintained their mental health while dealing with the stress and pressure of teaching during COVID-19.

Keywords: teacher retention, COVID-19, teacher education, teacher moral

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Edo O. Ekanem, Eme S. Ndeh, Ubong M. Nkok

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The role of educational technology in teaching is of great importance because of its systematic way of conceptualizing the execution and evaluation of Educational process. This study therefore examines the use of Educational Technology for teaching in Colleges of Education in south south geo-political zone of Nigeria. Four specific purposes, four research questions and four null hypotheses guided the study. The study adopted descriptive research design of the survey type. A sample of 295 lecturers from six colleges of education was selected using stratified and simple random sampling techniques. The data for this study were collected through a self-designed questionnaire and was analyzed using frequency counts, percentage scores and t-test statistics. The hypotheses for the study were tested at 0.05 significance. Findings from the study reveal that Educational Technology facilities such as Internet, electronic notice boards and projectors were not adequately used for teaching in the Colleges. It was also found that most lecturers use more of visual media than electronic/digital media in the classrooms. Moreover, the study shows that lecturers’ use of educational technology is influenced by their highest academic qualification while their level of awareness about the value of technology in education is not gender based. Lecturers’ lack of competence, inadequate Educational Technology facilities and Power are among the factors that inhibit the adequate use of the facilities. Based on the findings, recommendations were made on how to ensure effective use of Educational Technology for teaching in the Colleges in Nigeria.

Keywords: colleges of education, educational technology, teaching, Nigeria

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Authors: Rana Th. A. Al-Rubaye, Arthur A. Garforth

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This work details the generation of thin films of structured zeolite catalysts (ZSM–5 and Y) onto the surface of a metal substrate (FeCrAlloy) using in-situ hydrothermal synthesis. In addition, the zeolite Y is post-synthetically modified by acidified ammonium ion exchange to generate US-Y. Finally the catalytic activity of the structured ZSM-5 catalyst films (Si/Al = 11, thickness 146 µm) and structured US–Y catalyst film (Si/Al = 8, thickness 23µm) were compared with the pelleted powder form of ZSM–5 and USY catalysts of similar Si/Al ratios. The structured catalyst films have been characterised using a range of techniques, including X-ray diffraction (XRD), Electron microscopy (SEM), Energy Dispersive X–ray analysis (EDX) and Thermogravimetric Analysis (TGA). The transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces was followed using SEM and XRD. In addition, the robustness of the prepared coating was confirmed by subjecting these to thermal cycling (ambient to 550°C). The cracking of n–heptane over the pellets and structured catalysts for both ZSM–5 and Y zeolite showed very similar product selectivities for similar amounts of catalyst with an apparent activation energy of around 60 kJ mol-1. This paper demonstrates that structured catalysts can be manufactured with excellent zeolite adherence and when suitably activated/modified give comparable cracking results to the pelleted powder forms. These structured catalysts will improve temperature distribution in highly exothermic and endothermic catalysed processes.

Keywords: FeCrAlloy, structured catalyst, zeolite Y, zeolite ZSM-5

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Authors: Shoufeng Cao, Kim Bryceson, Damian Hine

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The existing supply chain risk management (SCRM) research is currently chaotic and somewhat disorganized, and the topic has been addressed conceptually more often than empirically. This paper, using both qualitative and quantitative data, employs a modified Meta-study method to investigate the SCRM empirical research published in quality journals over the period of 12 years (2004-2015). The purpose is to outline the extent research trends and the employed research methodologies (i.e., research method, data collection and data analysis) across the sub-field that will guide future research. The synthesized findings indicate that empirical study on risk ripple effect along an entire supply chain, industry-specific supply chain risk management and global/export supply chain risk management has not yet given much attention than it deserves in the SCRM field. Besides, it is suggested that future empirical research should employ multiple and/or mixed methods and multi-source data collection techniques to reduce common method bias and single-source bias, thus improving research validity and reliability. In conclusion, this paper helps to stimulate more quality empirical research in the SCRM field via identifying promising research directions and providing some methodology guidelines.

Keywords: empirical research, meta-study, methodology guideline, research direction, supply chain risk management

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Authors: Eman M. Eissa, Hany M. Hasanin, Mahmoud Abd-Elhamid, S. M. Muyeen, T. Fernando, H. H. C. Iu

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Among all available wind energy conversion systems (WECS), the direct driven permanent magnet synchronous generator integrated with power electronic interfaces is becoming popular due to its capability of extracting optimal energy capture, reduced mechanical stresses, no need to external excitation current, meaning less losses, and more compact size. Simple structure, low maintenance cost; and its decoupling control performance is much less sensitive to the parameter variations of the generator. This paper attempts to present a review of the control and optimization strategies of WECS based on permanent magnet synchronous generator (PMSG) and overview the most recent research trends in this field. The main aims of this review include; the generalized overall WECS starting from turbines, generators, and control strategies including converters, maximum power point tracking (MPPT), ending with DC-link control. The optimization methods of the controller parameters necessary to guarantee the operation of the system efficiently and safely, especially when connected to the power grid are also presented.

Keywords: control and optimization techniques, permanent magnet synchronous generator, variable speed wind turbines, wind energy conversion system

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Authors: Carla Caiazza, Valentina Preziosi, Giovanna Tomaiuolo, Denis O'Sullivan, Vincenzo Guida, Stefano Guido

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In the last decades, wormlike micellar solutions have been extensively used to tune the rheological behavior of home care and personal care products. This and other successful applications underlie the growing attention that both basic and applied research are devoting to these systems, and to their unique rheological and flow properties. One of the key research topics is the occurrence of flow instabilities at high shear rates (such as shear banding), with the possibility of appearance of flow induced structures. In this scenario, microfluidics is a powerful tool to get a deeper insight into the flow behavior of a wormlike micellar solution, as the high confinement of a microfluidic device facilitates the onset of the flow instabilities; furthermore, thanks to its small dimensions, it can be coupled with optical microscopy, allowing a direct visualization of flow structuring phenomena. Here, the flow of a widely used wormlike micellar solution through a glass capillary has been studied, by coupling the microfluidic device with μPIV techniques. The direct visualization of flow-induced structures and the flow visualization analysis highlight a relationship between solution structuring and the onset of discontinuities in the velocity profile.

Keywords: flow instabilities, flow-induced structures, μPIV, wormlike micelles

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: distribution system, loss, photovoltaic generation, primal-dual interior point method

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: Rudolf Egger

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This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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Authors: Oladejo Olagoke Peter, Adagunodo T. A., Ogunkoya C. O.

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The research investigated the arrangement of some geological features under Ilesa employing aeromagnetic data. The obtained data was subjected to various data filtering and processing techniques, which are Total Horizontal Derivative (THD), Depth Continuation and Analytical Signal Amplitude using Geosoft Oasis Montaj 6.4.2 software. The Reduced to the Equator –Total Magnetic Intensity (TRE-TMI) outcomes reveal significant magnetic anomalies, with high magnitude (55.1 to 155 nT) predominantly at the Northwest half of the area. Intermediate magnetic susceptibility, ranging between 6.0 to 55.1 nT, dominates the eastern part, separated by depressions and uplifts. The southern part of the area exhibits a magnetic field of low intensity, ranging from -76.6 to 6.0 nT. The lineaments exhibit varying lengths ranging from 2.5 and 16.0 km. Analyzing the Rose Diagram and the analytical signal amplitude indicates structural styles mainly of E-W and NE-SW orientations, particularly evident in the western, SW and NE regions with an amplitude of 0.0318nT/m. The identified faults in the area demonstrate orientations of NNW-SSE, NNE-SSW and WNW-ESE, situated at depths ranging from 500 to 750 m. Considering the divergence magnetic susceptibility, structural style or orientation of the lineaments, identified fault and their depth, these lithological features could serve as a valuable foundation for assessing ground motion, particularly in the presence of sufficient seismic energy.

Keywords: lineament, aeromagnetic, anomaly, fault, magnetic

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Authors: P. Christodoulou, M. Gerasimou, S. Mantzoukis, N. Varsamis, G. Kolliopoulou, N. Zotos

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Abstract— Purpose: The Intensive Care Unit (ICU) environment is conducive to the growth of microorganisms. A variety of microorganisms gain access to the intravascular area and are transported throughout the circulatory system. Therefore, examination of the catheters used in ICU patients is of paramount importance. Material and Method: The culture medium is a catheter tip, which is enriched with Tryptic soy broth (TSB). After one day of incubation, the broth is passaged in the following selective media: Blood, Mac conkey No. 2, chocolate, Mueller Hinton, Chapman, and Saboureaud agar. The above selective media is incubated for 2 days. After this period, if any number of microbial colonies is detected, gram staining is performed and then the microorganisms are identified by biochemical techniques in the automated Microscan (Siemens) system followed by a sensitivity test in the same system using the minimum inhibitory concentration (MIC) technique. The sensitivity test is verified by a Kirby Bauer test. Results: In 2017, the Microbiology Laboratory received 84 catheters from the ICU. 42 were found positive. Of these, S. epidermidis was identified at 8, A. baumannii in 10, K. pneumoniae in 6, P. aeruginosa in 6, P. mirabilis in 3, S. simulans in 1, S. haemolyticus in 4, S. aureus in 3 and S. hominis in 1. Conclusions: The results show that the placement and maintenance of the catheters in ICU patients are relatively successful, despite the unfavorable environment of the unit.

Keywords: culture, intensive care unit, microorganisms, vascular catheters

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Authors: Madhumita Sahu, S. S. Tiwary

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The Radiotherapy of Carcinoma Lung has always been difficult and a matter of great concern. The significant movement due to fractional motion caused due to non-rhythmic respiratory motion poses a great challenge for the treatment of Lung cancer using Ionizing Radiation. The present study compares the accuracy in the measurement of Target Volume using Slow-CT and 4DCT Imaging in SBRT for Lung Tumor. The experimental samples were extracted from patients with Lung Cancer who underwent SBRT. Slow-CT and 4DCT images were acquired under free breathing for each patient. PTV were delineated on Slow CT images. Similarly, ITV was also delineated on each of the 4DCT volumes. Volumetric and Statistical analysis were performed for each patient by measuring corresponding PTV and ITV volumes. The study showed (1) The Maximum Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 248.58 cc. (2) The Minimum Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 5.22 cc. (3) The Mean Deviation observed between Slow-CT-based PTV and 4DCT imaging-based ITV is 63.21 cc. The present study concludes that irradiated volume ITV with 4DCT is less as compared to the PTV with Slow-CT. A better and more precise treatment could be given more accurately with 4DCT Imaging by sparing 63.21 CC of mean body volume.

Keywords: CT imaging, 4DCT imaging, lung cancer, statistical analysis

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Authors: Michael Aupetit, Mahmoud Al-ismail, Khaled Mohamed

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Cancer is a major public health problem all over the world. Breast cancer has the highest incidence rate over all cancers for women in Qatar making its study a top priority of the country. Human cancer is a dynamic disease that develops over an extended period through the accumulation of a series of genetic alterations. A Darwinian process drives the tumor cells toward higher malignancy growing the branches of a progression tree in the space of genes expression. Although it is not possible to track these genetic alterations dynamically for one patient, it is possible to reconstruct the progression tree from the aggregation of thousands of tumor cells’ genetic profiles from thousands of different patients at different stages of the disease. Analyzing the progression tree is a way to detect pivotal molecular events that drive the malignant evolution and to provide a guide for the development of cancer diagnostics, prognostics and targeted therapeutics. In this work we present the development of a Visual Analytic web platform CanVis enabling users to upload gene-expression data and analyze their progression tree. The server computes the progression tree based on state-of-the-art techniques and allows an interactive visual exploration of this tree and the gene-expression data along its branching structure helping to discover potential driver genes.

Keywords: breast cancer, progression tree, visual analytics, web platform

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Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

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Authors: Jarbas Lopes Cardoso Jr., Frederic Andres, Alexandre Guitton, Asanee Kawtrakul, Silvio E. Barbin

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The important objective of the CyberBrain Mass Agriculture Alarm Acquisition and Analysis (CBMa4) project is to minimize the impacts of diseases and disasters on rice cultivation. For example, early detection of insects will reduce the volume of insecticides that is applied to the rice fields through the use of CBMa4 platform. In order to reach this goal, two major factors need to be considered: (1) the social network of smart farmers; and (2) the warning data alarm acquisition and analysis component. This paper outlines the process for collecting the warning and improving the decision-making result to the warning. It involves two sub-processes: the warning collection and the understanding enrichment. Human sensors combine basic suitable data processing techniques in order to extract warning related semantic according to collective intelligence. We identify each warning by a semantic content called 'warncons' with multimedia metaphors and metadata related to these metaphors. It is important to describe the metric to measuring the relation among warncons. With this knowledge, a collective intelligence-based decision-making approach determines the action(s) to be launched regarding one or a set of warncons.

Keywords: agricultural engineering, warning systems, social network services, context awareness

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Authors: L. Ngowi, N. H. Mvungi

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This paper critically examines the evolution of socio-technical systems theory, its practices, and challenges in system design and development. It examines concepts put forward by researchers focusing on the application of the theory in software engineering. There are various methods developed that use socio-technical concepts based on systems engineering without remarkable success. The main constraint is the large amount of data and inefficient techniques used in the application of the concepts in system engineering for developing time-bound systems and within a limited/controlled budget. This paper critically examines each of the methods, highlight bottlenecks and suggest the way forward. Since socio-technical systems theory only explains what to do, but not how doing it, hence engineers are not using the concept to save time, costs and reduce risks associated with new frameworks. Hence, a new framework, which can be considered as a practical approach is proposed that borrows concepts from soft systems method, agile systems development and object-oriented analysis and design to bridge the gap between theory and practice. The approach will enable the development of systems using socio-technical systems theory to attract/enable the system engineers/software developers to use socio-technical systems theory in building worthwhile information systems to avoid fragilities and hostilities in the work environment.

Keywords: socio-technical systems, human centered design, software engineering, cognitive engineering, soft systems, systems engineering

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Authors: Aisami A., Z. A. Adamu, Lawan Bulama

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Due to growing issues of crude oil pollution in both marine and terrestrial environments, Billions to Trillions of US Dollars were spent over the years for the treatment of this spill. There is an urgent need for effective bioremediation strategies. This current study focuses on the isolation and characterization of a crude oil-degrading bacterium from hydrocarbon-contaminated soil samples. Soil samples were collected from an oil spill site and subjected to enrichment culture techniques in a mineral salt medium supplemented with crude oil as the singular carbon source. The isolates were screened for their crude oil-degrading capabilities using gravimetric analysis. The most efficient isolation was identified through 16S rRNA gene sequencing. Cultural and physical conditions such pH, temperature salinity and crude oil concentrations were optimized. The isolates showed significant crude oil degradation efficiency, reducing oil concentration (2.5%) by 75% within 15 days of incubation. The strain was identified as Providencia sp. through molecular characterization, the sequence was deposited at the NCBI Genbank with accession number MN880494. The bacterium exhibited optimal growth at 32.5°C, pH 7.0 to 7.5, and in the presence of 1.5% (w/v) NaCl. The isolated Providencia sp. shows encouraging potential for bioremediation of crude oil-contaminated environments. This study successfully isolated and characterized a crude oil-degrading Providencia sp., highlighting its potential in bioremediation.

Keywords: crude oil degradation, providencia sp., bioremediation, hydrocarbon utilization, environmental pollution.

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Authors: Ayed S. Al-Shihri, Abul Kalam, Abdullah G. Al-Sehemi, Gaohui Du, Tokeer Ahmad, Ahmad Irfan

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We report here the synthesis of nickel oxide (NiO) nanoparticles by microwave-assisted method, using a common precipitating agent followed by calcination in air at 400°C. The effect of the microwave and pH on the crystallite size, morphology, structure, energy band gap and surface area of NiO have been investigated by means of powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), ultraviolet visible spectroscopy (UV-vis) and BET surface area studies. X-ray diffraction studies showed the formation of monophasic and highly crystalline cubic NiO. TEM analysis led to decrease the average grain size of NiO nanoparticles from 16.5 nm to 14 nm on increasing the amount of NaOH. FTIR studies also confirm the formation of NiO nanoparticles. It was observed that on increasing the volume of NaOH, the optical band gap energy (2.85 eV to 2.95 eV) and specific surface area (33.1 to 39.8 m2/g) increases, however the average particles size decreases (16.5 nm to 14 nm). This method may be extended to large scale synthesis of other metal oxides nanoparticles and the present study could be used for the potential applications in water treatment and many other fields.

Keywords: BET surface area analysis, electron microscopy, optical properties, X-ray techniques

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

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Authors: Gidado Lawal Likko

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The study examined the relationship of achievement goals, metacognitive awareness and academic success among students of colleges of education in North Western Nigeria. The study was guided by three objectives. The first two were to find out whether students’ achievement goals and metacognitive awareness correlate with their academic success. 358 students comprising 242 males (67.6%) and 116 females (32.4%) were studied. Correlation survey was employed in the conduct of the study. The instruments used to collect data were students’ bio data form, achievement goals inventory (Roedel, Schraw and Plake, 1994), metacognitive awareness inventory (Schraw & Dennison, 1994) and students’ CGPA (NCCE minimum standard, 2013) was used as the index of academic success. Pearson Product Moment and regression analysis were the statistical techniques used to analyze the data. Results of the analysis indicated that students’ achievement goals (r=0.554, p=0.004) and metacognitive awareness (r= 0.67, p=0.001) positively correlated with their academic success. Similarly, significant relationship exists between achievement goals and metacognitive awareness (r=0.77, p=0.000). Part of the recommendations is the need for the management of all colleges of education to have educational interventions aimed at developing students’ metacognitive awareness which will foster purposeful self-regulation of their learning. This could be achieved by periodic assessment of students’ metacognitive awareness which will serve as feedback as they move from one educational level to another.

Keywords: academic success, goal orientation, metacognitive awareness, prospective teachers

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