Path planning in nuclear facility decommissioning: Research status, challenges, and opportunities

Adibeli, Justina Onyinyechukwu,Liu, Yong-kuo,Ayodeji, Abiodun,Awodi, Ngbede Junior Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.11

During nuclear facility decommissioning, workers are continuously exposed to high-level radiation. Hence, adequate path planning is critical to protect workers from unnecessary radiation exposure. This work discusses recent development in radioactive path planning and the algorithms recommended for the task. Specifically, we review the conventional methods for nuclear decommissioning path planning, analyze the techniques utilized in developing algorithms, and enumerate the decision factors that should be considered to optimize path planning algorithms. As a major contribution, we present the quantitative performance comparison of different algorithms utilized in solving path planning problems in nuclear decommissioning and highlight their merits and drawbacks. Also, we discuss techniques and critical consideration necessary for efficient application of robots and robotic path planning algorithms in nuclear facility decommissioning. Moreover, we analyze the influence of obstacles and the environmental/radioactive source dynamics on algorithms' efficiency. Finally, we recommend future research focus and highlight critical improvements required for the existing approaches towards a safer and cost-effective nuclear-decommissioning project.

Time harmonic analysis of dam-foundation systems by perfectly matched layers

Adib Khazaee,Vahid Lotfi 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.50 No.3

Perfectly matched layers are employed in time harmonic analysis of dam-foundation systems. The Lysmer boundary condition at the truncation boundary of the PML region has been incorporated in the formulation of the dam-foundation FE model (including PML). The PML medium is defined in a way that the formulation of the system can be transformed into time domain. Numerical experiments show that applying Lysmer boundary conditions at the truncation boundary of the PML area reduces the computational cost and make the PML approach a more efficient technique for the analysis of dam-foundation systems.

Real-Time State of Charge estimation of Li-Ion Battery Considering The Effect of State of Health

Adib M. Kamali(아딥),Angela Caliwag(안젤라),Donguk Kwon(권동욱),Wansu Lim(임완수) 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2

Battery health estimation has an important role in safe operation and long-life battery. Battery health estimation can be represented as a battery State of charge (SOC) and state of health (SOH). The existing approach performs SOC without considering SOH effect which assumes that capacity always in the maximum value. This approach is lack of accuracy because capacity of battery degrades with aging not always same. Therefore, we propose SOC estimation considering the effect of SOH. The result shows the SOH adjusted the capacity value to improve SOC estimation accuracy. The experimental result is presented using battery management system C2000 and cloud computing.

Generative Adversarial Network with Face Alignment for Face Generation

Adib Kamali,Udurume Miracle,Udeogu Chigozie Uzochukwu,Angela Caliwag,Wansu Lim 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.11

Face generation is extensively conducted to increase the number of face images dataset. In face generation field, Generative Adversarial Network (GAN) have shown remarkable success in face image generations. However, most of the existing methods only generate face images from random noise, and cannot generate faces according to face alignment. This make GAN produce poor quality face images when using unaligned face image. In this paper, we propose face generation based on GAN with considering the face alignments. In detail, original face images which is not always aligned is fed to the face alignment module. Then the aligned face images is added noises. The aligned images with noise are then used as input for GAN based image generator. Generator and discriminator are trained to optimize the face generation model performance. Based on extensive experimental study, we present the analysis on face alignment and face generation result with and without considering face alignment.

Family of Isolated Zero Current Transition PWM Converters

Adib, Ehsan,Farzanehfard, Hosein The Korean Institute of Power Electronics 2009 JOURNAL OF POWER ELECTRONICS Vol.9 No.2

In this paper a family of zero current transition PWM converters which employs a simple auxiliary circuit is introduced. This soft switched auxiliary circuit is only composed of a switch and a capacitor. The proposed converters are analyzed and various operating modes of the ZCT flyback converter are discussed. Design considerations are presented and the experimental results of the ZCT flyback converter laboratory prototype are illustrated. The experimental results confirm the validity of theoretical analysis.

Bilateral supernumerary maxillary fourth and fifth molars: A clinical case report and literature review

Adib Al-Haj, Husain,Daphne, Schonegg,Fabienne Andrina, Bosshard,Silvio, Valdec Korean Academy of Oral and Maxillofacial Radiology 2022 Imaging Science in Dentistry Vol.52 No.-

Supernumerary teeth that are present in the molar region may be evident based on crowding and impaction, but most cases are asymptomatic and discovered as incidental findings during routine radiological examinations. This article reports the case of a 29-year-old woman who presented with a severe feeling of pressure in the region of the maxillary third molars that had been increasing in intensity for weeks. A clinical examination revealed crowding of the maxillary anterior teeth despite the completion of orthodontic treatment and an erupted third molar with localized gingivitis in the second quadrant. A radiographic examination revealed bilateral supernumerary maxillary fourth and fifth molars, so cone-beam computed tomography was performed to locate the supernumerary teeth precisely for a preoperative diagnosis and comprehensive treatment planning. This report presents the radiological and surgical case management of a rare case of bilateral supernumerary molars and reviews the literature regarding epidemiology and treatment options.

Muslim`s Role in the Opposition to Marcos

( Cesar Adib Majul ) 인하대학교 국제관계연구소 1986 Pacific Focus Vol.1 No.1

Family of Isolated Zero Current Transition PWM Converters

Ehsan Adib,Hosein Farzanehfard 전력전자학회 2009 JOURNAL OF POWER ELECTRONICS Vol.9 No.2

In this paper a family of zero current transition PWM converters which employs a simple auxiliary circuit is introduced. This soft switched auxiliary circuit is only composed of a switch and a capacitor. The proposed converters are analyzed and various operating modes of the ZCT flyback converter are discussed. Design considerations are presented and the experimental results of the ZCT flyback converter laboratory prototype are illustrated. The experimental results confirm the validity of theoretical analysis.

Cholinergic Differentiation of Neural Stem Cells Generated from Cell Aggregates-derived from Human Bone Marrow Stromal Cells

Samane Adib,Taki Tiraihi,Merzieh Darvishi,Taher Taheri,Hadi Kazemi 한국조직공학과 재생의학회 2015 조직공학과 재생의학 Vol.12 No.1

Human Bone marrow stromal cells (hBMSCs) can differentiate under appropriate experimental conditionsinto neuronal and glial-like cells. This study shows a protocol for producing human neural stem cells (hNSCs)from hBMSCs and the subsequent differentiation of hNSCs into cholinergic neurons (CNs), where sequential mediareplaced the culturing media. hBMSCs have been used in generating cell aggregates (CAs) using bFGF, EGF andB27. The hNSCs were isolated from CAs, and the CNs differentiated from the hNSCs using sequential media, wherebFGF, EGF and B27 were gradually replaced with NGF. The hNSC stemness was checked by RT-PCR of SOX2,Oct-4 and Nanog genes. Fibronectin, CD90, CD106, CD31, nestin, neurofilament 68 (NF-68), NF-200 and ChATimmunostaining evaluated the differentiation of the hBMSCs, the hNSCs and the CNs. FM1-43 was used in studyingthe function of the CNs. The hBMSCs were immunoreactive to fibronectin, CD90 and CD106; they werechecked for lipogenic and osteogenic differentiation. The cells of the CAs were immunoreactive to nestin. ThehNSCs were immunoreactive to nestin and NF-68, also, they expressed SOX2, Oct-4 and nanong. Nestin expressiondeclined sharply following NSC differentiation into CNs, while the expression of NF-200, synapsin I, synaptophysin,MAP-2 and ChAT increased. They were stained with FM1-43, where the synaptic vesicles were releasedfollowing stimulation. The present study demonstrates the conversion of hBMSCs into CASs under appropriate conditions. CAs generated hNSCs, which were induced in order to differentiate into CNs using sequential media, wherethe yield was 83%.

A Local-Cloud Edge based Keyword Spotting using Deep Learning

M. Adib Kamali,Paul Angelo Oroceo,Alexander Pascual,Angela Caliwag,Wansu Lim 대한인간공학회 2021 대한인간공학회 학술대회논문집 Vol.2021 No.11

Objective: This study aims to develop a reliable and efficient keyword spotting (KWS) system suitable for a user interface on an edge device application. In addition, this study also aims to implement KWS on both local (to perform low-level tasks and in condition without internet access) and cloud (to perform high-level tasks). Background: KWS plays a significant role in realizing speech-based user interaction with an edge device. Existing KWS system issues include 1) low accuracy, caused by unrecognized noise signals during training and inference process, 2) high computational complexity, caused by the use of deep learning models with complex architecture, 3) internet connection dependency, caused by running main processes into cloud server, and 4) system responsiveness, can be affected by high latency in data transfer over the internet which is affected by external factors. Method: First, to increase the accuracy, crowd-sourcing techniques is used to obtain training sets which includes variety of audio sample with different accents and voice quality. The quality of the training data is improved using signal augmentation and curation methods. Second, to reduce the computational complexity, the trained model is optimized using a quantization method. In case of increasing accuracy, signal augmentation adds background noise to the training dataset and assists the KWS model to recognize the keyword in a variety of environments. Data curation is used is to process augmented signals which include: collecting, organizing, labeling, cleaning, enhancing, and preserving data for the KWS training process. In addition to signal augmentation and curation, a Mel Frequency Cepstral Coefficient (MFCC) is used to extract the features in an audio signal. The extracted features are then restructured to an image and a convolutional neural network (CNN) is used to learn the features and classify the MFCCs in each sample dataset. To further improve the accuracy, the training parameters are adjusted to achieve a validation accuracy of at least 85%. Also, regularization techniques and dropout layers are added to avoid overfitting. In KWS system deployment, the trained model is optimized to reduce memory, computing, and power consumption. Hence, model weights and activations parameters are quantized using 8-bit integers without incurring a significant loss in accuracy. The implementation utilizes the local-cloud server processing, where a local database residing in the edge server works alongside with the cloud server to execute more complex algorithm and processes. Results: The training result shows that our KWS model achieves an average accuracy and loss of 95.9% and 0.18, respectively. The raining result also reveals that the trained KWS model is ready for model testing on the edge. Furthermore, the optimization result shows the inference time, peak random access memory usage, and flash usage are reduced by 21.1%, 32.3%, and 58.5%, respectively. Conclusion: The result of model training and testing shows that the proposed KWS system has high accuracy and resource efficiency. The system also exhibits internet independence as local database is implemented locally. Application: The inference process uses two platforms: edge device and cloud server. The edge device, Arduino BLE sense microcontroller, is used to spot the keywords using optimized CNN that will produce a unique keyword identifier and is sent over to the cloud server. The identifier is used to match the keyword for its corresponding response. The cloud server sends the response of the spotted keyword to the edge device.