Search results for: adaptive plasticity

Authors: Kharisma Utomo Mulyodinoto, Suwarno, A. Abu-Siada

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Dissolved Gas Analysis is one of impressive technique to detect and predict internal fault of transformers by using gas generated by transformer oil sample. A number of methods are used to interpret the dissolved gas from transformer oil sample: Doernenberg Ratio Method, IEC (International Electrotechnical Commission) Ratio Method, and Duval Triangle Method. While the assessment of dissolved gas within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straight forward as it depends on personnel expertise more than mathematical formulas. To get over this limitation, this paper is aimed at improving the interpretation of Doernenberg Ratio Method, IEC Ratio Method, and Duval Triangle Method using Two Stages Adaptive Neuro-Fuzzy Inference System (ANFIS). Dissolved gas analysis data from 520 faulty transformers was analyzed to establish the proposed ANFIS model. Results show that the developed ANFIS model is accurate and can standardize the dissolved gas interpretation process with accuracy higher than 90%.

Keywords: ANFIS, dissolved gas analysis, Doernenberg ratio method, Duval triangular method, IEC ratio method, transformer

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Sergei Voychuk

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Introduction: Adaptive response (AR) is a manifestation of radiation hormesis, which deal with the radiation resistance that may be increased with the pretreatment with small doses of radiation. In the current study, we evaluated the potency of radiofrequency EMF to induce the AR mechanisms and to increase a resistance to UV light. Methods: Saccharomyces cerevisiae yeast strains, which were created to study induction of mutagenesis and recombination, were used in the study. The strains have mutations in rad2 and rad54 genes, responsible for DNA repair: nucleotide excision repair (PG-61), postreplication repair (PG-80) and mitotic (crossover) recombination (T2). An induction of mutation and recombination are revealed due to the formation of red colonies on agar plates. The PG-61 and T2 are UV sensitive strains, while PG-80 is sensitive to ionizing radiation. Extremely high frequency electromagnetic field (EHF-EMF) was used. The irradiation was performed in floating mode and frequency changed during exposure from 57 GHz to 62 GHz. The power of irradiation was 100 mkW, and duration of exposure was 10 and 30 min. Treatment was performed at RT and then cells were stored at 28° C during 1 h without any exposure but after that they were treated with UV light (254nm) for 20 sec (strain T2) and 120 sec (strain PG-61 and PG-80). Cell viability and quantity of red colonies were determined after 5 days of cultivation on agar plates. Results: It was determined that EHF-EMF caused 10-20% decrease of viability of T2 and PG-61 strains, while UV showed twice stronger effect (30-70%). EHF-EMF pretreatment increased T2 resistance to UV, and decreased it in PG-61. The PG-80 strain was insensitive to EHF-EMF and no AR effect was determined for this strain. It was not marked any induction of red colonies formation in T2 and PG-80 strain after EHF or UV exposure. The quantity of red colonies was 2 times more in PG-61 strain after EHF-EMF treatment and at least 300 times more after UV exposure. The pretreatment of PG-61 with EHF-EMF caused at least twice increase of viability and consequent decrease of amount of red colonies. Conclusion: EHF-EMF may induce AR in yeast cells and increase their viability under UV treatment.

Keywords: Saccharomyces cerevisiae, EHF-EMF, UV light, adaptive response

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Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

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An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

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Authors: Wang Yongdong, Yeneayehu Fenetahun, You Yuan, Ogbue Chukwuka, Yahaya Ibrahim, Xu Xinwen

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This paper explores an innovative Ethiopian approach to combatting desertification, focusing on the semi-arid savanna grasslands in Southern Ethiopia. The study investigates the multifaceted strategies employed by Ethiopian communities, governmental bodies, and non-governmental organizations to address desertification challenges in the region. Through an analysis of legislative frameworks, community engagement, afforestation programs, and sustainable land management techniques, this research highlights the efficacy of Ethiopia's strategy in reducing the effects of desertification. The results emphasize how crucial it is to build effective measures for halting desertification in fragile ecosystems by utilizing local knowledge, community involvement, and adaptive governance. In addition, this study also addresses how the Ethiopian approach may be applied to other areas with comparable environmental problems. In summary, this research adds significant perspectives to the worldwide conversation about desertification and provides useful guidance for sustainable land use.

Keywords: adaptive governance, community engagement, desertification, policy frameworks

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Developing tailored management strategies to ensure the sustainability of groundwater resource under climate and demographic changes is critical for tropical karst island, where relatively small watershed and highly porous soil nature make this natural resource highly susceptible and thus very sensitive to those changes. In this study, long-term impacts of climate variability on groundwater recharge and discharge at the Oemau spring, Rote Island, Indonesia were investigated. Following calibration and validation of groundwater model using MODFLOW code, groundwater flow was simulated for period of 2020-2090 under HadCM3 global model climate (GCM) scenarios, using input data of weather variables downscaled by Statistical Downscaling Model (SDSM). The reported analysis suggests that the sustainability of groundwater resources will be adversely affected by climate change during dry years. The area is projected to variably experience 2.53-22.80% decrease of spring discharge. A subsequent comprehensive set of management strategies as palliative and adaptive efforts was proposed to be implemented by relevant stakeholders to assist the community dealing with water deficit during the dry years. Three main adaptive strategies, namely socio-cultural, technical, and ecological measures, were proposed by incorporating physical and socio-economic characteristics of the area. This study presents a blueprint for assessing groundwater sustainability under climate change scenarios and developing tailored management strategies to cope with adverse impacts of climate change, which may become fundamental necessities across other tropical karst islands in the future.

Keywords: climate change, groundwater, management strategies, tropical karst island, Rote Island, Indonesia

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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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: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique

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Authors: Anisah Ari

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Effects of organized crime permeate all facets of life, including public health, socio-economic endeavors, and human security. If any element of this is affected, it impacts large-scale national and global interest. Seeking to address terrorist networks through technical thinking is like trying to kill a weed by just cutting off its branches. It will re-develop and expand in proportions beyond one’s imagination, even in horrific ways that threaten human security. The continent of Africa has been bedeviled by this menace, with little or no solution to the problem. Nigeria is dealing with a protracted insurgency that is perpetrated by a sect against any form of westernization. Reimagining approaches to dealing with pressing issues like terrorism may require engaging the right set of people in the conversation for any sustainable change. These are people who have lived through the daily effects of the violence that ensues from the activities of terrorist activities. Effective leadership is required for an inclusive process, where spaces are created for diverse voices to be heard, and multiple perspectives are listened to, and not just heard, that supports a determination of the realistic outcome. Addressing insurgency in Nigeria has experienced a lot of disinformation and uncertainty. This may be in part due to poor leadership or an iteration of technical solutions to adaptive challenge peacemaking efforts in Nigeria has focused on behaviors, attitudes and practices that contribute to violence. However, it is important to consider the underlying issues that build-up, ignite and fan the flames of violence—looking at conflict as a complex system, issues like climate change, low employment rates, corruption and the impunity of discrimination due to ethnicity and religion. This article will be looking at an option of the more relational way of addressing insurgency through adaptive approaches that embody engagement and solutions with the people rather than for the people. The construction of a local turn in peacebuilding is informed by the need to create a locally driven and sustained peace process that embodies the culture and practices of the people in enacting an everyday peace beyond just a perennial and universalist outlook. A critical analysis that explores the socially identified individuals and situations will be made, considering the more adaptive approach to a complex existential challenge rather than a universalist frame. Case Study and Ethnographic research approach to understand what other scholars have documented on the matter and also a first-hand understanding of the experiences and viewpoints of the participants.

Keywords: terrorism, adaptive, peace, culture

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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: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Mustafa Sahin, İlkay Yavrucuk

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This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control

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Authors: Kazumoto Tanaka, Takayuki Fujino

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Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image

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Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

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Authors: Masoud Sheidaei, Fahimeh Koohdar

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Date palms are economically important tree plants with high nutrition and medicinal values. More than 400 date palm cultivars are cultivated in many regions of Iran, but no report is available on landscape genetics and species distribution modeling of these trees from the country. Therefore, the present study provides a detailed insight into the genetic diversity and structure of date palm populations in Iran and investigates the effects of geographical and climatic variables on the structuring of genetic diversity in them. We used different computational methods in the study like, spatial principal components analysis (sPCA), redundancy analysis (RDA), latent factor mixed model (LFMM), and Maxent and Dismo models of species distribution modeling. We used a combination of different molecular markers for this study. The results showed that both global and local spatial features play an important role in the genetic structuring of date palms, and the genetic regions associated with local adaptation and climatic variables were identified. The effects of climatic change on the distribution of these taxa and the genetic regions adaptive to these changes will be discussed.

Keywords: adaptive genetic regions, genetic diversity, isolation by distance, populations divergence

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Authors: Biji Jacob

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Vector quantization algorithm which uses minimum distance calculation for codebook generation, a time consuming calculation performed on each pixel values leads to computation complexity. The codebook is updated by comparing the distance of each vector to their centroid vector and measure for their closeness. In this paper vector quantization is modified based on vector difference algorithm for image enhancement purpose. In the proposed scheme, vector differences between the vectors are considered as the new generation vectors or new codebook vectors. The codebook is updated by comparing the new generation vector with a threshold value having minimum error with the parent vector. The minimum error decides the fitness of each newly generated vector. Thus the codebook is generated in an adaptive manner and the fitness value is determined for the suppression of the degraded portion of the image and thereby leads to the enhancement of the image through the adaptive searching capability of the vector quantization through vector difference algorithm. Experimental results shows that the vector difference scheme efficiently modifies the vector quantization algorithm for enhancing the image with peak signal to noise ratio (PSNR), mean square error (MSE), Euclidean distance (E_dist) as the performance parameters.

Keywords: codebook, image enhancement, vector difference, vector quantization

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Authors: Minsu Kim, Hae-Chang Cho, Jae Hoon Chung, Inwook Heo, Kang Su Kim

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For safe design of the UHPC flexural members, accurate estimations of their shear strengths are very important. However, since the shear strengths are significantly affected by various factors such as tensile strength of concrete, shear span to depth ratio, volume ratio of steel fiber, and steel fiber factor, the accurate estimations of their shear strengths are very challenging. In this study, therefore, the Adaptive Neuro-Fuzzy System (ANFIS), which has been widely used to solve many complex problems in engineering fields, was introduced to estimate the shear strengths of UHPC flexural members. A total of 32 experimental results has been collected from previous studies for training of the ANFIS algorithm, and the well-trained ANFIS algorithm provided good estimations on the shear strengths of the UHPC test specimens. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(NRF-2016R1A2B2010277).

Keywords: ultra-high-performance concrete, ANFIS, shear strength, flexural member

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Authors: Karima Djebaili, Lamine Melkemi

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Elgamal encryption is a fundamental public-key encryption in cryptography, which is based on the difficulty of discrete logarithm problem and the Diffie-Hellman problem. Supposing the Diffie–Hellman problem is computationally infeasible then Elgamal is secure under a chosen plaintext attack, where security indicates it is difficult for the attacker, given the ciphertext, to restore the whole of the plaintext. However, although it is secure against chosen plaintext attack, Elgamal is absolutely malleable i.e. is not secure against an adaptive chosen ciphertext attack, where the attacker can recover the plaintext. We present a extension on Elgamal encryption which result in non-malleability against adaptive chosen plaintext attack using concatenation and a cryptographic hash function, our evidence utilizes the device of plaintext aware. The algorithm proposed can be used in cryptography voting protocol given its level security. Our protocol protects the confidentiality of voters because each voter encrypts their choice before casting their vote, offers public verifiability using a signing algorithm, the final result is correctly computed using homomorphic property, and works even in the presence of an adversary due to the propriety of non-malleability. Moreover, the protocol prevents some parties colluding to fix the vote results.

Keywords: Elgamal encryption, non-malleability, plaintext aware, e-voting

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Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed

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The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.

Keywords: bleeding, asphalt film thickness differential, Anfis Modeling

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Authors: Jessica Torres, James W. Sturges

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This correlational study explored the potential relationship between social media use and social connectedness. College students (n = 190) were surveyed using the revised Social Connectedness Scale (SCS-R) and were asked about the number of hours they used social media platforms such as Instagram, TikTok, Twitter, Snapchat, and Facebook. We also developed and administered a 14-item Social Media Use Scale (SMUS) to measure potentially maladaptive social media use, such as use that likely interfered with other activities. The SMUS was found to have good inter-item consistency (Cronbach’s alpha = .92) and was significantly correlated with hours of use, r(182) = .622, p < .001. As expected, we found that the SCS-R scores were inversely related to total hours of social media use, r(182) = -.188 (p < .005). This suggested that lots of time allocated to online interactions is negatively associated with social connectedness in general. Interestingly, however, higher social connectedness scores were associated specifically with Snapchat use, r(28) = .210, p = .004. This may have to do with the specific nature of the Snapchat experience and perhaps its original use for one-to-one communication. The use of other social media platforms (Tiktok, Instagram, Twitter) was not related to better social connectedness scores. Although we failed to find that scores on our measure of problem use (the SMUS) were correlated with social connectedness, we are hopeful that the SMUS will be of use in identifying patterns of maladaptive social media use that may have an impact on other important outcome measures of adaptive functioning and well-being.

Keywords: adaptive functioning, college students, social connectedness, social media use

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: automobile suspension, MATLAB, control system, PID, PSO

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Andreas Hammer

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Six peculiar architecture designs from the Frankfurt University will be discussed within this paper and their future potential of the adaptable and solar thin-film sheets implemented facades will be shown acting and reacting on climate/solar changes of their specific sites. The different aspects, as well as limitations with regard to technical and functional restrictions, will be named. The design process for a “multi-purpose building”, a “high-rise building refurbishment” and a “biker’s lodge” on the river Rheine valley, has been critically outlined and developed step by step from an international studentship towards an overall energy strategy, that firstly had to push the design to a plus-energy building and secondly had to incorporate bionic aspects into the building skins design. Both main parameters needed to be reviewed and refined during the whole design process. Various basic bionic approaches have been given [e.g. solar ivyᵀᴹ, flectofinᵀᴹ or hygroskinᵀᴹ, which were to experiment with, regarding the use of bendable photovoltaic thin film elements being parts of a hybrid, kinetic façade system.

Keywords: bionic and bioclimatic design, climate adaptive building shells [CABS], energy-strategy, harvesting façade, high-efficiency building skin, photovoltaic in building skins, plus-energy-buildings, solar gain, sustainable building concept

Procedia PDF Downloads 430

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

Procedia PDF Downloads 290

Authors: Aditya, Ganapati Joshi, Vinod Kumar

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IN THE MODERN-WARFARE ERA, THE PRIME REQUIREMENT IS A HIGH SPEED AND MACH NUMBER. WHEN THE MISSILES STRIKE IN THE HYPERSONIC REGIME THE OPPONENT CAN DETECT IT WITH THE ANTI-DEFENSE SYSTEM BUT CAN NOT STOP IT FROM CAUSING DAMAGE. SO, TO ACHIEVE THE SPEEDS OF THIS LEVEL THERE ARE TWO ENGINES THAT ARE AVAILABLE WHICH CAN WORK IN THIS REGION ARE RAMJET AND SCRAMJET. THE PROBLEM WITH RAMJET STARTS TO OCCUR WHEN MACH NUMBER EXCEEDS 4 AS THE STATIC PRESSURE AT THE INLET BECOMES EQUAL TO THE EXIT PRESSURE. SO, SCRAMJET ENGINE DEALS WITH THIS PROBLEM AS IT NEARLY HAS THE SAME WORKING BUT HERE THE FLOW IS NOT MUCH SLOWED DOWN AS COMPARED TO RAMJET IN THE DIFFUSER BUT IT SUFFERS FROM THE PROBLEMS SUCH AS INLET BUZZ, THERMAL CHOCKING, MIXING OF FUEL AND OXIDIZER, THERMAL HEATING, AND MANY MORE. HERE THE NEW ENGINE IS DEVELOPED ON THE SAME PRINCIPLE AS THE SCRAMJET ENGINE BUT BURNING HAPPENS DUE TO DETONATION INSTEAD OF DEFLAGRATION. THE PROBLEM WITH THE ENGINE STARTS WHEN THE MACH NUMBER BECOMES VARIABLE AND THE INLET GEOMETRY IS FIXED AND THIS LEADS TO INLET SPILLAGE WHICH WILL AFFECT THE THRUST ADVERSELY. SO, HERE ADAPTIVE INLET IS MADE OF SHAPE MEMORY ALLOYS WHICH WILL ENHANCE THE INLET MASS FLOW RATE AS WELL AS THRUST.

Keywords: detonation, ramjet engine, shape memory alloy, ignition delay, shock-boundary layer interaction, eddy dissipation, asymmetric nozzle

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Authors: Arzu Karahan, Loriano Ballarin, Baruch Rinkevich

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Marine invertebrates, the highly diverse phyla of multicellular organisms, represent phenomena that are either not found or highly restricted in the vertebrates. These include phenomena like budding, fission, a fusion of ramets, and high regeneration power, such as the ability to create whole new organisms from either tiny parental fragment, many of which are controlled by totipotent, pluripotent, and multipotent stem cells. Thus, there is very much that can be learned from these organisms on the practical and evolutionary levels, further resembling Darwin's words, “It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change”. The ‘stem cell’ notion highlights a cell that has the ability to continuously divide and differentiate into various progenitors and daughter cells. In vertebrates, adult stem cells are rare cells defined as lineage-restricted (multipotent at best) with tissue or organ-specific activities that are located in defined niches and further regulate the machinery of homeostasis, repair, and regeneration. They are usually categorized by their morphology, tissue of origin, plasticity, and potency. The above description not always holds when comparing the vertebrates with marine invertebrates’ stem cells that display wider ranges of plasticity and diversity at the taxonomic and the cellular levels. While marine/aquatic invertebrates stem cells (MISC) have recently raised more scientific interest, the know-how is still behind the attraction they deserve. MISC, not only are highly potent but, in many cases, are abundant (e.g., 1/3 of the entire animal cells), do not locate in permanent niches, participates in delayed-aging and whole-body regeneration phenomena, the knowledge of which can be clinically relevant. Moreover, they have massive hidden potential for the discovery of new bioactive molecules that can be used for human health (antitumor, antimicrobial) and biotechnology. The MARISTEM COST action (Stem Cells of Marine/Aquatic Invertebrates: From Basic Research to Innovative Applications) aims to connect the European fragmented MISC community. Under this scientific umbrella, the action conceptualizes the idea for adult stem cells that do not share many properties with the vertebrates’ stem cells, organizes meetings, summer schools, and workshops, stimulating young researchers, supplying technical and adviser support via short-term scientific studies, making new bridges between the MISC community and biomedical disciplines.

Keywords: aquatic/marine invertebrates, adult stem cell, regeneration, cell cultures, bioactive molecules

Procedia PDF Downloads 169

Authors: Mustarakh Gelfi, Poonam Taneja, Tiedo Vellinga, Delon Hamonangan

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The initial masterplan of New Priok in the Port of Tanjung Priok was developed in 2012 is being updated to cater to new developments and new demands. In the new masterplan (2017), Phase II of development will start from 2035-onwards, depending on the future conditions. This study is about creating a robust masterplan for Phase II, which will remain functional under future uncertainties. The methodology applied in this study is scenario-based planning in the framework of Adaptive Port Planning (APP). Scenario-based planning helps to open up the perspective of the future as a horizon of possibilities. The scenarios are built around two major uncertainties in a 2x2 matrix approach. The two major uncertainties for New Priok port are economics and sustainability awareness. The outcome is four plausible scenarios: Green Port, Business As Usual, Moderate Expansion, and No Expansion. Terminal needs in each scenario are analyzed through traffic analysis and identifying the key cargos and commodities. In conclusion, this study gives the wide perspective for Port of Tanjung Priok for the planning Phase II of the development. The port has to realize that uncertainties persevere and are very likely to influence the decision making as to the future layouts. Instead of ignoring uncertainty, the port needs to make the action plans to deal with these uncertainties.

Keywords: Indonesia Port, port's layout, port planning, scenario-based planning

Procedia PDF Downloads 534