Search results for: model reference adaptive control

Authors: Mina Kalantarzadeh, Claire Lockie-Williams, Caroline Howard

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DNA barcoding is increasingly used for identification of medicinal plants worldwide. In the last decade, a large number of DNA barcodes have been generated, and their application in species identification explored. The success of DNA barcoding process relies on the accuracy of the results from polymerase chain reaction (PCR) amplification step which could be negatively affected due to a presence of inhibitors or degraded DNA in herbal samples. An established DNA reference material can be used to support molecular characterisation protocols and prove system suitability, for fast and accurate identification of plant species. The present study describes the use of a novel reference material, the trnH-psbA British Pharmacopoeia Nucleic Acid Reference Material (trnH-psbA BPNARM), which was produced to aid in the identification of Ocimum tenuiflorum L., a widely used herb. During DNA barcoding of O. tenuiflorum, PCR amplifications of isolated DNA produced inconsistent results, suggesting an issue with either the method or DNA quality of the tested samples. The trnH-psbA BPNARM was produced and tested to check for the issues caused during PCR amplification. It was added to the plant material as control DNA before extraction and was co-extracted and amplified by PCR. PCR analyses revealed that the amplification was not as successful as expected which suggested that the amplification is affected by presence of inhibitors co-extracted from plant materials. Various potential issues were assessed during DNA extraction and optimisations were made accordingly. A DNA barcoding protocol for O. tenuiflorum was published in the British Pharmacopoeia 2016, which included the reference sequence. The trnH-psbA BPNARM accelerated degradation test which investigates the stability of the reference material over time demonstrated that it has been stable when stored at 56 °C for a year. Using this protocol and trnH-psbA reference material provides a fast and accurate method for identification of O. tenuiflorum. The optimisations of the DNA extraction using the trnH-psbA BPNARM provided a signposting method which can assist in overcoming common problems encountered when using molecular methods with medicinal plants.

Keywords: degradation, DNA extraction, nucleic acid reference material, trnH-psbA

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: Ibrahim M. Mehedi, Uzair Ansari, Ubaid M. Al-Saggaf, Abdulrahman H. Bajodah

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This paper presents a methodology for balancing a rotary inverted pendulum system using Robust Generalized Dynamic Inversion (RGDI) under influence of parametric variations and external disturbances. In GDI control, dynamic constraints are formulated in the form of asymptotically stable differential equation which encapsulates the control objectives. The constraint differential equations are based on the deviation function of the angular position and its rates from their reference values. The constraint dynamics are inverted using Moore-Penrose Generalized Inverse (MPGI) to realize the control expression. The GDI singularity problem is addressed by augmenting a dynamic scale factor in the interpretation of MPGI which guarantee asymptotically stable position tracking. An additional term based on Sliding Mode Control is appended within GDI control to make it robust against parametric variations, disturbances and tracking performance deterioration due to generalized inversion scaling. The stability of the closed loop system is ensured by using positive definite Lyapunov energy function that guarantees semi-global practically stable position tracking. Numerical simulations are conducted on the dynamic model of rotary inverted pendulum system to analyze the efficiency of proposed RGDI control law. The comparative study is also presented, in which the performance of RGDI control is compared with Linear Quadratic Regulator (LQR) and is verified through experiments. Numerical simulations and real-time experiments demonstrate better tracking performance abilities and robustness features of RGDI control in the presence of parametric uncertainties and disturbances.

Keywords: generalized dynamic inversion, lyapunov stability, rotary inverted pendulum system, sliding mode control

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: J. J. Vargas, N. Prieto, L. A. Toro

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Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: Daehyoung Kim, Pervez Khan, Hoon Kim

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Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Keywords: spectrum sharing, adaptive opportunistic transmission, unlicensed bands, heterogeneous networks

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Authors: Ilqar Ramazanli

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The matrix completion problem has been studied broadly under many underlying conditions. The problem has been explored under adaptive or non-adaptive, exact or estimation, single-phase or multi-phase, and many other categories. In most of these cases, the observation cost of each entry is uniform and has the same cost across the columns. However, in many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Keywords: matroid optimization, matrix completion, linear algebra, algorithms

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

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A blind source separation method is proposed; in this method, we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work, the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each subband than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Hang Ju, Changmin Zhu

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The development level of the BeiDou Navigation Satellite System (BDS) can strongly reflect national defense strength as an important spatial information infrastructure. BDS can be not only used for military purposes, such as intelligence gathering, nuclear explosion monitoring, emergency communications, but also for location services, transportation, mapping, precision agriculture. In order to ensure the national defense security and the wide application of BDS in civil and military areas, BDS must be autonomous and controllable. As a complex system of knowledge-intensive, knowledge transformation runs through the whole process of research and development, production, operation, and maintenance of BDS. Based on the perspective of knowledge transformation, this paper expounds on the meaning of socialization, externalization, combination, and internalization of knowledge transformation, and the coupling relationship of autonomy and control on the basis of analyzing the status quo and problems of the autonomy and control of BDS. The autonomous and controllable framework of BDS based on knowledge transformation is constructed from six dimensions of management capability, R&D capability, technical capability, manufacturing capability, service support capability, and application capability. It can provide support for the smooth implementation of information security policy, provide a reference for the autonomy and control of the upstream and downstream industrial chains in Beidou, and provide a reference for the autonomous and controllable research of aerospace components, military measurement test equipment, and other related industries.

Keywords: knowledge transformation, BeiDou Navigation Satellite System, autonomy and control, framework

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Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

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Among all FACTS devices, the unified power flow controller (UPFC) is considered to be the most versatile device. This is due to its capability to control all the transmission system parameters (impedance, voltage magnitude, and phase angle). With the growing interest in UPFC, the attention to develop a mathematical model has increased. Several models were introduced for UPFC in literature for different type of studies in power systems. In this paper a novel comparison study between two dynamic models of UPFC with their proposed control strategies.

Keywords: FACTS, UPFC, dynamic modeling, PWM, fundamental frequency

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Authors: Qinghua Xing, Noha M. Mesbah, Haisheng Wang, Jun Li, Baisuo Zhao

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Droplet digital PCR (ddPCR) is being increasingly adopted for gene detection and quantification because of its higher sensitivity and specificity. According to previous observations and our lab data, it is essential to use endogenous reference genes (RGs) when investigating gene expression at the mRNA level under salt stress. This study aimed to select and validate suitable RGs for gene expression under salt stress using ddPCR. Six candidate RGs were selected based on the tandem mass tag (TMT)-labeled quantitative proteomics of Alkalicoccus halolimnae at four salinities. The expression stability of these candidate genes was evaluated using statistical algorithms (geNorm, NormFinder, BestKeeper and RefFinder). There was a small fluctuation in cycle threshold (Ct) value and copy number of the pdp gene. Its expression stability was ranked in the vanguard of all algorithms, and was the most suitable RG for quantification of expression by both qPCR and ddPCR of A. halolimnae under salt stress. Single RG pdp and RG combinations were used to normalize the expression of ectA, ectB, ectC, and ectD under four salinities. The present study constitutes the first systematic analysis of endogenous RG selection for halophiles responding to salt stress. This work provides a valuable theory and an approach reference of internal control identification for ddPCR-based stress response models.

Keywords: endogenous reference gene, salt stress, ddPCR, RT-qPCR, Alkalicoccus halolimnae

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Authors: Mohamed Amarouayache, Badia Amrouche, Gharbi Akila, Boukadoume Mohamed

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This work is devoted to the modeling of DC-DC converter (boost) used for MPPT applications to set conditions of stability. For this, we establish a linear mathematical model of the DC-DC converter with an average small signal model. This model has allowed us to apply conventional linear methods of automation. A mathematical relationship between the duty cycle and the voltage of the panel has been set up. With this relationship we specify the conditions of the stability in closed-loop depending on the system parameters (the elements of storage capacity and inductance, PWM control).

Keywords: MPPT, PWM, stability, criterion of Routh, average small signal model

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Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

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The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

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Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun

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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Keywords: grey relational degree, multiple linear regression, membership function, nonlinear programming

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Authors: Doğan Yıldız, Aydan Müşerref Erkmen

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The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.

Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

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Authors: P. Nafisi Poor, P. Javid

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Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

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Authors: Getachew Tilahun, Oluwole Makinde, David Malonza

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We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically.

Keywords: cost effectiveness analysis, optimal control, pneumonia dynamics, stability analysis, numerical simulation

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Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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Authors: Fernanda M. Bastos, Teógenes A. da Silva

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Extrapolation chambers were designed to be used as primary standard dosimeter for measuring absorbed dose in a medium in beta radiation and low energy x-rays. The International Organization for Standardization established series of reference x-radiation for calibrating and determining the energy dependence of dosimeters that are to be reproduced in metrology laboratories. Standardization of the low energy x-ray beams with tube potential lower than 30 kV may be affected by the instrument used for dosimetry. In this work, parameters of a 23392 model PTW extrapolation chamber were determined aiming its use in low energy x-ray beams as a reference instrument.

Keywords: extrapolation chamber, low energy x-rays, x-ray dosimetry, X-ray metrology

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Authors: Kaddari Faiza, Mazari Benyounes, Mihoub Youcef, Safa Ahmed

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Active filtering of electric power has now become a mature technology for reactive power and harmonic compensation caused by the proliferation of power electronics devices used for industrial, commercial and residential purposes. The aim of this study is to enhance the power quality by improving the performances of shunt active power filter in harmonic mitigation to obtain sinusoidal source currents with very weak ripples. A power circuit configuration and control scheme for shunt active power filter are described with an improved method for harmonics compensation using self-tuning-filter for harmonics identification and fuzzy logic control to generate reference current. Simulation results (using MATLAB/SIMULINK) illustrates the compensation characteristics of the proposed control strategy. Analysis of these results proves the feasibility and effectiveness of this method to improve the power quality and also show the performances of fuzzy logic control which provides flexibility, high precision and fast response. The total harmonic distortion (THD %) for the simulations found to be within the recommended imposed IEEE 519-1992 harmonic standard.

Keywords: Active Powers Filter (APF), Self-Tuning-Filter (STF), fuzzy logic control, hysteresis-band control

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Authors: Alexander Winkler, Jozef Suchý

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This paper investigates simple implicit force control algorithms realizable with industrial robots. A lot of approaches already published are difficult to implement in commercial robot controllers, because the access to the robot joint torques is necessary or the complete dynamic model of the manipulator is used. In the past we already deal with explicit force control of a position controlled robot. Well known schemes of implicit force control are stiffness control, damping control and impedance control. Using such algorithms the contact force cannot be set directly. It is further the result of controller impedance, environment impedance and the commanded robot motion/position. The relationships of these properties are worked out in this paper in detail for the chosen implicit approaches. They have been adapted to be implementable on a position controlled robot. The behaviors of stiffness control and damping control are verified by practical experiments. For this purpose a suitable test bed was configured. Using the full mechanical impedance within the controller structure will not be practical in the case when the robot is in physical contact with the environment. This fact will be verified by simulation.

Keywords: robot force control, stiffness control, damping control, impedance control, stability

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Authors: Akinola Ikudayisi, Josiah Adeyemo

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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: irrigation, principal component analysis, reference evapotranspiration, Vaalharts

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Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

Abstract:

The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Bit-Na Kwon, Hyun-Jee Yang, Dong-Hyun Ha, Hyoung-Kyu Song

Abstract:

In this paper, an adaptive cooperative scheme in the cell edge is proposed. The proposed scheme considers the location of a user and applies the suitable cooperative scheme. In cellular systems, the performance of communication is degraded if the user is located in the cell edge. In conventional scheme, two base stations are used in order to obtain diversity gain. However, the performance of communication is not sufficiently improved since the distance between each base station and a user is still distant. Therefore, we propose a scheme that the relays are used and the cooperative scheme is adaptively applied according to the user location. Through simulation results, it is confirmed that the proposed scheme has better performance than the conventional scheme.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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