Search results for: Extended Park´s vector approach

Authors: Moon-Tak Oh, Kyung-Min Park, Tae-Eun Yoon, Hoon Choi, Chil-Woo Lee

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This paper is about middle-ware which enables group-user applications on mobile devices in physical proximity to interact with other devices without intervention of a central server. Requirements of the middle-ware are identified from service usage scenarios, and the functional architecture of the middle-ware is specified. These requirements include group management, synchronization, and resource management. Group Management needs to provide various capabilities to such applications with respect to managing multiple users (e.g., creation of groups, discovery of group or individual users, member join/leave, election of a group manager and service-group association) using D2D communication technology. We designed the middle-ware for the above requirements on the Android platform.

Keywords: group user, middleware, mobile service, physical proximity

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Authors: Lina Pan

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In non-Gaussian clutter of a spherically invariant random vector, in the cases that a certain estimated covariance matrix could become singular, the adaptive target detection of high-range-resolution radar is addressed. Firstly, the restricted maximum likelihood (RML) estimates of unknown covariance matrix and scatterer amplitudes are derived for non-Gaussian clutter. And then the RML estimate of texture is obtained. Finally, a novel detector is devised. It is showed that, without secondary data, the proposed detector outperforms the existing Kelly binary integrator.

Keywords: non-Gaussian clutter, covariance matrix estimation, target detection, maximum likelihood

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Authors: Sihyun Park, Hyunwoo Kim, Wooyoung Jung, Dongwoo You

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Regular maintenance works are very important on the axial forces of the cable-band bolts in suspension bridges. The band bolts show stress reduction for several reasons, including cable wire creep, the bolt relaxation, load fluctuation and cable rearrangements, etc., with time. In this study, with respect to the stress reduction that occurs over time, we carried out the theoretical review of the main cause based on the field measurements. As a result, the main cause of reduction in the cable-band bolt axial force was confirmed by the plastic deformation of the zinc plating layer used in the main cable wire, and thus, the theoretical process was established for the practical use in the field.

Keywords: cable-band Bolts, field test, maintenance, stress reduction

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Authors: Fethi Benyettou, Abdelkader Aissat, M. A. Benammar

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In this work, we use Silvaco TCAD software for modeling and simulations of standard GaAs solar cell, InAs/GaAs and GaSb/GaAs p-i-n quantum dot solar cell. When comparing 20-layer InAs/GaAs, GaSb/GaAs quantum dots solar cells with standard GaAs solar cell, the conversion efficiency in simulation results increased from 16.48 % to 22.6% and 16.48% to 22.42% respectively. Also, the absorption range edge of photons with low energies extended from 900 nm to 1200 nm.

Keywords: SILVACO TCAD, the quantum dot, simulation, materials engineering

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Authors: Asim Abbasi, Muhammad Sufyan, Iqra, Hafiza Javaria Ashraf

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The share of vector-borne diseases (VBDs) in the global burden of infectious diseases is almost 17%. The advent of new drugs and latest research in medical science helped mankind to compete with these lethal diseases but still diseases transmitted by different mosquito species, including filariasis, malaria, viral encephalitis and dengue are serious threats for people living in disease endemic areas. Injudicious and repeated use of pesticides posed selection pressure on mosquitoes leading to development of resistance. Hence biological control agents are under serious consideration of scientific community to be used in vector control programmes. Fish have a history of predating immature stages of different aquatic insects including mosquitoes. The noteworthy examples in Africa and Asia includes, Aphanius discolour and a fish in the Panchax group. Moreover, common mosquito fish, Gambusia affinis predates mostly on temporary water mosquitoes like anopheline as compared to permanent water breeders like culicines. Mosquitoes belonging to genus Toxorhynchites have a worldwide distribution and are mostly associated with the predation of other mosquito larvae habituating with them in natural and artificial water containers. These species are harmless to humans as their adults do not suck human blood but feeds on floral nectar. However, their activity is mostly temperature dependent as Toxorhynchites brevipalpis consume 359 Aedes aegypti larvae at 30-32 ºC in contrast to 154 larvae at 20-26 ºC. Although many bacterial species were isolated from mosquito cadavers but those belonging to genus Bacillus are found highly pathogenic against them. The successful species of this genus include Bacillus thuringiensis and Bacillus sphaericus. The prime targets of B. thuringiensis are mostly the immatures of genus Aedes, Culex, Anopheles and Psorophora while B. sphaericus is specifically toxic against species of Culex, Psorophora and Culiseta. The entomopathogenic nematodes belonging to family, mermithidae are also pathogenic to different mosquito species. Eighty different species of mosquitoes including Anopheles, Aedes and Culex proved to be highly vulnerable to the attack of two mermithid species, Romanomermis culicivorax and R. iyengari. Cytoplasmic polyhedrosis virus was the first described pathogenic virus, isolated from the cadavers of mosquito specie, Culex tarsalis. Other viruses which are pathogenic to culicine includes, iridoviruses, cytopolyhedrosis viruses, entomopoxviruses and parvoviruses. Protozoa species belonging to division microsporidia are the common pathogenic protozoans in mosquito populations which kill their host by the chronic effects of parasitism. Moreover, due to their wide prevalence in anopheline mosquitoes and transversal and horizontal transmission from infected to healthy host, microsporidia of the genera Nosema and Amblyospora have received much attention in various mosquito control programmes. Fungal based mycopesticides are used in biological control of insect pests with 47 species reported virulent against different stages of mosquitoes. These include both aquatic fungi i.e. species of Coelomomyces, Lagenidium giganteum and Culicinomyces clavosporus, and the terrestrial fungi Metarhizium anisopliae and Beauveria bassiana. Hence, it was concluded that the integrated use of all these biological control agents can be a healthy contribution in mosquito control programmes and become a dire need of the time to avoid repeated use of pesticides.

Keywords: entomopathogenic nematodes, protozoa, Toxorhynchites, vector-borne

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank

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Authors: Seunghee Park, Junkyeong Kim, Eun-Seok Shin, Sang-Hun Han

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In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of underwater concrete structures. A new methodology to estimate the underwater concrete strengths more effectively, named “artificial neural network (ANN) – based concrete strength estimation with the combination of rebound hardness and ultrasonic pulse velocity methods” is proposed and verified throughout a series of experimental works.

Keywords: underwater concrete, rebound hardness, Schmidt hammer, ultrasonic pulse velocity, ultrasonic sensor, artificial neural networks, ANN

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Authors: S. Boulenouar, A. Boukli Hacene, S. Brahmi

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Quality is an old concept but which recently became omnipresent in the society. It is a pledge of the well done job and therefore the satisfaction of the customer. Now, dispensing pharmacies seem to be held away from this approach. Officinal staff is called to dispense drugs. However this essential function is rarely studied and taken into account. To contribute to the good use of medicines and to reduce the dangers, it is important to consider the dispensation of drugs practised in the pharmacies. It is a both descriptive and retrospective study .The descriptive part is to conduct a survey near to the dispensary pharmacists. The retrospective section concentrates on the analysis of medicine prescriptions dispensed to patients. Following the survey that we carried out near the pharmacists of dispensary of the town of Oran, it appears that in majority, they are not inclined, by themselves, to take up the challenge of quality at the dispensary. The approach requires time and a motivation that pharmacists do not have for the moment. Efforts are still needed on the part of pharmacists, but also of authorities and organizations in charge of quality in the dispensary. At the end of this work, it seems to us that the implementation of a quality approach is part of our reflection on the added value of the pharmacist of dispensary in the drug chain.

Keywords: customer satisfaction, dispensary, dispensing of the drug, quality approach

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Authors: Bita Mashayekhi, Azadeh Maddahi, Arash Tahriri

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The purpose of this paper is developing a model for audit quality, with regard to the contextual and environmental attributes of the audit profession in Iran. For this purpose, using an exploratory approach, and because of the special attributes of the auditing profession in Iran in terms of the legal environment, regulatory and supervisory mechanisms, audit firms size, and etc., we used grounded theory approach as a qualitative research method. Therefore, we got the opinions of the experts in the auditing and capital market areas through unstructured interviews. As a result, the authors revealed the determinants of audit quality, and by using these determinants, developed an Integrated Audit Quality Model, including causal conditions, intervening conditions, context, as well as action strategies related to AQ and their consequences. In this research, audit quality is studied using a systemic approach. According to this approach, the quality of inputs, processes, and outputs of auditing determines the quality of auditing, therefore, the quality of all different parts of this system is considered.

Keywords: audit quality, integrated audit quality model, demand for audit service, supply of audit, grounded theory

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Authors: Rosidah Rosidah

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The paper aims to identify and examine the effectiveness of social marketing as an approach for conducting anti-corruption campaign. Social marketing has been widely used to promote social change for the benefit of individual and society; such as for promoting healthy foods consumption, encouraging breastfeeding, reducing smoking, solving alcohol problem and drunk driving. Therefore, it is believed that this approach can be promising to be used in anti-corruption campaign. It is because social marketing can be useful of prompting people to act in accordance to the existing norms that denounce corruption, or help to establish new norms that more averse to corruption. It has established into evidence and insight based approaches to social campaign that focus on changing people’s behavior. Qualitative approach will be used in this study, with the using of literature review and secondary data analysis as the research methods. This paper is still on preliminary stage, which its results is expected to provide fundamental basis for designing model of intervention (anti-corruption campaign) using social marketing approaches.

Keywords: anti-corruption campaign, behavioral change, social influence, social marketing

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Authors: Ramish, Farhan Khalique Awan

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Kinematic redundancy within the manipulators presents extended dexterity and manipulability to the manipulators. Redundant serial robotic manipulators are very popular in industries due to its competencies to keep away from singularities during normal operation and fault tolerance because of failure of one or more joints. Such fault tolerant manipulators are extraordinarily beneficial in applications where human interference for repair and overhaul is both impossible or tough; like in case of robotic arms for space programs, nuclear applications and so on. The design of this sort of fault tolerant serial 3 DoF manipulator is presented in this paper. This work was the extension of the author’s previous work of designing the simple 3R serial manipulator. This work is the realization of the previous design with optimizing the link lengths for incorporating the feature of fault tolerance. Various measures have been followed by the researchers to quantify the fault tolerance of such redundant manipulators. The fault tolerance in this work has been described in terms of the worst-case measure of relative manipulability that is, in fact, a local measure of optimization that works properly for certain configuration of the manipulators. An optimum fault tolerant Jacobian matrix has been determined first based on prescribed null space properties after which the link parameters have been described to meet the given Jacobian matrix. A solid model of the manipulator was then developed to realize the mathematically rigorous design. Further work was executed on determining the dynamic properties of the fault tolerant design and simulations of the movement for various trajectories have been carried out to evaluate the joint torques. The mathematical model of the system was derived via the Euler-Lagrange approach after which the same has been tested using the RoboAnalyzer© software. The results have been quite in agreement. From the CAD model and dynamic simulation data, the manipulator was fabricated in the workshop and Advanced Machining lab of NED University of Engineering and Technology.

Keywords: fault tolerant, Graham matrix, Jacobian, kinematics, Lagrange-Euler

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Ahn Christine Myunghee, Sim Wonjin, Cho Kristina, Ahn Mira, Hong Yeju, Kwok Jihae, Lim Sooyeon, Park Hansol

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With a sharp increase in the prevalence rate for mental health issues in Korea, there is a need for specific and effective intervention strategies in counseling and psychotherapy for use with Korean clients. With the cultural emphasis on restraining emotional expression and not disclosing personal and familial problems to outsiders, clients often find it difficult to discuss their emotional issues even to therapists. Exploring a client’s internal psychological processes bypassing this culture-specific mode of therapeutic communication often becomes a challenge in the therapeutic setting. Given this socio-cultural context, the purpose of the current study was to investigate the effectiveness of using dream work to individuals in Korea. The current study conducted one 60-90 minute dream session and analyzed the dream content of 39 Korean young adults to evaluate the effectiveness of the Hill dream model in accessing the intra-psychic materials, determining essential emotional themes, and learning how the individuals interpreted the contents of their dreams. The transcribed data, which included a total of 39 sessions from 39 volunteer university students, were analyzed by the Consensus Qualitative Research (CQR) approach in terms of domains and core ideas. Self-report measures on Dream Salience, Gains from Dream Interpretations and the Session Evaluation Scale were administered before and after each of their dream sessions. The results indicated that dream work appears to be an effective way to understand unconscious motivations, thoughts, and feelings related to a person’s sense of self, and also how these people relate to other people. Current findings need to be replicated with clients referred for counseling and psychotherapy to determine if the dream work is an appropriate and useful intervention in counseling settings. Limitations of the current study and suggestions for future follow-ups are included in the discussion.

Keywords: dream work, dream interpretation, Korean, young adults, CQR

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Authors: H. E. Keshta, A. A. Ali

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Three phase grid-tied inverters are widely employed in micro-grids (MGs) as interphase between DC and AC systems. These inverters are usually controlled through standard decoupled d–q vector control strategy based on proportional integral (PI) controllers. Recently, advanced meta-heuristic optimization techniques have been used instead of deterministic methods to obtain optimum PI controller parameters. This paper provides a comparative study between the performance of the global Porcellio Scaber algorithm (GPSA) based PI controller and Manta Ray foraging optimization (MRFO) based PI controller.

Keywords: micro-grids, optimization techniques, grid-tied inverter control, PI controller

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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Authors: Adrian Sauer, Lorenz Einberger, Florian Hilpert

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The advancements and technical innovations in the field of electric unmanned aviation over the past years opened the third dimension in areas like surveillance, logistics, and mobility for a wide range of private and commercial users. Researchers and companies are faced with the task of integrating their technology into airborne platforms. Especially start-ups and researchers require unmanned aerial vehicles (UAV), which can be quickly developed for specific use cases without spending significant time and money. This paper shows a design approach for the rapid development of a lightweight automatic separate-lift-thrust (SLT) electric vertical take-off and landing (eVTOL) UAV prototype, which is able to fulfill basic transportation as well as surveillance missions. The design approach does not require expensive or time-consuming design loop software. Thereby developers can easily understand, adapt, and adjust the presented method for their own project. The approach is mainly focused on crucial design aspects such as aerofoil, tuning, and powertrain.

Keywords: aerofoil, drones, rapid prototyping, powertrain

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Authors: Younghoon Kim, Seoung Bum Kim

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One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

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Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

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Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation

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Authors: Kristina De Milt, Nicole Huang, Jihye Park

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Opioids have been a mainstay of the treatment of chronic pain, but their overprescription and misuse have led to an opioid epidemic. Recently, as an attempt to decrease the number of opioids prescribed, the use of cannabinoid therapy has become an increasingly popular adjunctive chronic pain management choice among providers. This review of literature investigates the effects of adjunctive cannabinoids to opioids in the management of chronic pain. The nine articles are included in the literature review range from observational studies to meta-analyses published in the year 2016 and after. A majority of the studies showed a decrease in the need for opioids after adjunctive cannabinoids were introduced and, in some instances, the cessation of opioid consumption. More high-quality evidence is needed to further support this stance and providers should weigh the benefits and risks of adjunctive cannabinoids according to the clinical picture.

Keywords: cannabis, chronic pain, opioids, pain management

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Authors: Walid Wahballah, Taher Bazan, Fawzy Eltohamy

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One of the important functions of the satellite attitude control system is to provide the required pointing accuracy and attitude stability for optical remote sensing satellites to achieve good image quality. Although offering noise reduction and increased sensitivity, time delay and integration (TDI) charge coupled devices (CCDs) utilized in high-resolution satellites (HRS) are prone to introduce large amounts of pixel smear due to the instability of the line of sight. During on-orbit imaging, as a result of the Earth’s rotation and the satellite platform instability, the moving direction of the TDI-CCD linear array and the imaging direction of the camera become different. The speed of the image moving on the image plane (focal plane) represents the image motion velocity whereas the angle between the two directions is known as the drift angle (β). The drift angle occurs due to the rotation of the earth around its axis during satellite imaging; affecting the geometric accuracy and, consequently, causing image quality degradation. Therefore, the image motion velocity vector and the drift angle are two important factors used in the assessment of the image quality of TDI-CCD based optical remote sensing satellites. A model for estimating the image motion velocity and the drift angle in HRS is derived. The six satellite attitude control parameters represented in the derived model are the (roll angle φ, pitch angle θ, yaw angle ψ, roll angular velocity φ֗, pitch angular velocity θ֗ and yaw angular velocity ψ֗ ). The influence of these attitude parameters on the image quality is analyzed by establishing a relationship between the image motion velocity vector, drift angle and the six satellite attitude parameters. The influence of the satellite attitude parameters on the image quality is assessed by the presented model in terms of modulation transfer function (MTF) in both cross- and along-track directions. Three different cases representing the effect of pointing accuracy (φ, θ, ψ) bias are considered using four different sets of pointing accuracy typical values, while the satellite attitude stability parameters are ideal. In the same manner, the influence of satellite attitude stability (φ֗, θ֗, ψ֗) on image quality is also analysed for ideal pointing accuracy parameters. The results reveal that cross-track image quality is influenced seriously by the yaw angle bias and the roll angular velocity bias, while along-track image quality is influenced only by the pitch angular velocity bias.

Keywords: high-resolution satellites, pointing accuracy, attitude stability, TDI-CCD, smear, MTF

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Authors: Samah Laalej, Abdelfattah Bouatem

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In the field of wind turbine blades, it is complicated to evaluate the aerodynamic performances through experimental measurements as it requires a lot of computing time and resources. Therefore, in this paper, a hybrid BEM-CFD numerical technique is developed to predict power and aerodynamic forces acting on the blades. Computational fluid dynamics (CFD) simulation was conducted to calculate the drag and lift forces through Ansys software using the K-w model. Then an enhanced BEM code was created to predict the power outputs generated by the wind turbine using the aerodynamic properties extracted from the CFD approach. The numerical approach was compared and validated with experimental data. The power curves calculated from this hybrid method were in good agreement with experimental measurements for all velocity ranges.

Keywords: blade element momentum, aerodynamic forces, wind turbine blades, computational fluid dynamics approach

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Authors: Pınar Yardımcı

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This paper tries to answer to the questions whether or not trade openness cause economic growth and trade policy changes is good for Turkey as a developing country in global economy before and after 1980. We employ Johansen cointegration and Granger causality tests with error correction modelling based on vector autoregressive. Using WDI data from the pre-1980 and the post-1980, we find that trade openness and economic growth are cointegrated in the second term only. Also the results suggest a lack of long-run causality between our two variables. These findings may imply that trade policy of Turkey should concentrate more on extra complementary economic reforms.

Keywords: globalization, trade policy, economic growth, openness, cointegration, Turkey

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Authors: Aladdin Al-Tarawneh

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The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.

Keywords: Quran translation, hybrid approach, domestication, foreignization, hybrid model

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Authors: Taehyun Kim, Taehyun Kim, Hyunjoo Park

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Photovoltaic facility occurs conflicts and disputes over environmental issues such as soil runoff, landscapes damage, and ecosystems damage. Because of these problems, huge social and economic cost occurred. The purpose of this study is to analyze resident‘s acceptability and conflict factors on the location of PV facilities, and suggest ways to promote resident’s acceptability and solutions for conflicts. Literature review, cases analysis, and expert interview on the acceptance and conflict factors related to the location of PV facilities are used to derive results. The results of this study are expected to contribute to the minimization of environmental impact and social conflict due to the development of renewable energy in the future.

Keywords: acceptance factor, conflict factor, factor analysis, photovoltaic facility

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Authors: K. V. F. Fatokun, P. A. Eniayeju

Abstract:

This study concerns the effects of concept mapping-guided discovery integrated teaching approach on the learning style and achievement of chemistry students. The sample comprised 162 senior secondary school (SS 2) students drawn from two science schools in Nasarawa State which have equivalent mean scores of 9.68 and 9.49 in their pre-test. Five instruments were developed and validated while the sixth was purely adopted by the investigator for the study, Four null hypotheses were tested at α = 0.05 level of significance. Chi square analysis showed that there is a significant shift in students’ learning style from accommodating and diverging to converging and assimilating when exposed to concept mapping- guided discovery approach. Also t-test and ANOVA that those in experimental group achieve and retain content learnt better. Results of the Scheffe’s test for multiple comparisons showed that boys in the experimental group performed better than girls. It is therefore concluded that the concept mapping-guided discovery integrated approach should be used in secondary schools to successfully teach electrochemistry. It is strongly recommended that chemistry teachers should be encouraged to adopt this method for teaching difficult concepts.

Keywords: integrated teaching approach, concept mapping-guided discovery, achievement, retention, learning styles and interest

Procedia PDF Downloads 329

Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

Abstract:

In the current paper, a residual generation filter with finite memory structure is proposed for fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

Keywords: residual generation filter, finite memory structure, kalman filter, fast detection

Procedia PDF Downloads 699

Authors: M. Ziółkowska, J. T. Duda, J. Milewska-Duda

Abstract:

This paper describes an approach to the adsorption phenomena modeling aimed at specifying the adsorption mechanisms on localized or nonlocalized adsorbent sites, when applied to the nanocarbons. The concept comes from the fundamental thermodynamic description of adsorption equilibrium and is based on numerical calculations of the hydrogen adsorbed particles volume on the surface of selected nanocarbons: single-walled nanotube and nanocone. This approach enables to obtain information on adsorption mechanism and then as a consequence to take appropriate mathematical adsorption model, thus allowing for a more reliable identification of the material porous structure. Theoretical basis of the approach is discussed and newly derived results of the numerical calculations are presented for the selected nanocarbons.

Keywords: adsorption, mathematical modeling, nanocarbons, numerical analysis

Procedia PDF Downloads 269

Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

Abstract:

New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

Procedia PDF Downloads 140