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Design and Implementation of IoT based Low cost, Effective Learning Mechanism for Empowering STEM Education in India

  • Simmi Chawla;Parul Tomar;Sapna Gambhir
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.163-169
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    • 2024
  • India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

Seismic Facies Classification of Igneous Bodies in the Gunsan Basin, Yellow Sea, Korea (탄성파 반사상에 따른 서해 군산분지 화성암 분류)

  • Yun-Hui Je;Ha-Young Sim;Hoon-Young Song;Sung-Ho Choi;Gi-Bom Kim
    • Journal of the Korean earth science society
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    • v.45 no.2
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    • pp.136-146
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    • 2024
  • This paper introduces the seismic facies classification and mapping of igneous bodies found in the sedimentary sequences of the Yellow Sea shelf area of Korea. In the research area, six extrusive and three intrusive types of igneous bodies were found in the Late Cretaceous, Eocene, Early Miocene, and Quaternary sedimentary sequences of the northeastern, southwestern and southeastern sags of the Gunsan Basin. Extrusive igneous bodies include the following six facies: (1) monogenetic volcano (E.mono) showing cone-shape external geometry with height less than 200 m, which may have originated from a single monogenetic eruption; (2) complex volcano (E.comp) marked by clustered monogenetic cones with height less than 500 m; (3) stratovolcano (E.strato) referring to internally stratified lofty volcanic edifices with height greater than 1 km and diameter more than 15 km; (4) fissure volcanics (E.fissure) marked by high-amplitude and discontinuous reflectors in association with normal faults that cut the acoustic basement; (5) maar-diatreme (E.maar) referring to gentle-sloped low-profile volcanic edifices with less than 2 km-wide vent-shape zones inside; and (6) hydrothermal vents (E.vent) marked by upright pipe-shape or funnel-shape structures disturbing sedimentary sequence with diameter less than 2 km. Intrusive igneous bodies include the following three facies: (1) dike and sill (I.dike/sill) showing variable horizontal, step-wise, or saucer-shaped intrusive geometries; (2) stock (I.stock) marked by pillar- or horn-shaped bodies with a kilometer-wide intrusion diameter; and (3) batholith and laccoliths (I.batho/lac) which refer to gigantic intrusive bodies that broadly deformed the overlying sedimentary sequence.

Research for Space Activities of Korea Air Force - Political and Legal Perspective (우리나라 공군의 우주력 건설을 위한 정책적.법적고찰)

  • Shin, Sung-Hwan
    • The Korean Journal of Air & Space Law and Policy
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    • v.18
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    • pp.135-183
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    • 2003
  • Aerospace force is a determining factor in a modem war. The combat field is expanding to space. Thus, the legitimacy of establishing aerospace force is no longer an debating issue, but "how should we establish aerospace force" has become an issue to the military. The standard limiting on the military use of space should be non-aggressive use as asserted by the U.S., rather than non-military use as asserted by the former Soviet Union. The former Soviet Union's argument is not even strongly supported by the current Russia government, and realistically is hard to be applied. Thus, the multi-purpose satellite used for military surveillance or a commercial satellite employed for military communication are allowed under the U.S. principle of peaceful use of space. In this regard, Air Force may be free to develop a military surveillance satellite and a communication satellite with civilian research institute. Although MTCR, entered into with the U.S., restricts the development of space-launching vehicle for the export purpose, the development of space-launching vehicle by the Korea Air Force or Korea Aerospace Research Institute is beyond the scope of application of MTCR, and Air Force may just operate a satellite in the orbit for the military purpose. The primary task for multi-purpose satellite is a remote sensing; SAR sensor with high resolution is mainly employed for military use. Therefore, a system that enables Air Force, the Korea Aerospace Research Institute, and Agency for Defense Development to conduct joint-research and development should be instituted. U.S. Air Force has dismantled its own space-launching vehicle step by step, and, instead, has increased using private space launching vehicle. In addition, Military communication has been operated separately from civil communication services or broadcasting services due to the special circumstances unique to the military setting. However, joint-operation of communication facility by the military and civil users is preferred because this reduces financial burden resulting from separate operation of military satellite. During the Gulf War, U.S. armed forces employed commercial satellites for its military communication. Korea's participation in space technology research is a little bit behind in time, considering its economic scale. In terms of budget, Korea is to spend 5 trillion won for 15 years for the space activities. However, Japan has 2 trillion won annul budget for the same activities. Because the development of space industry during initial fostering period does not apply to profit-making business, government supports are inevitable. All space development programs of other foreign countries are entirely supported by each government, and, only recently, private industry started participating in limited area such as a communication satellite and broadcasting satellite, Particularly, Korea's space industry is in an infant stage, which largely demands government supports. Government support should be in the form of investment or financial contribution, rather than in the form of loan or borrowing. Compared to other advanced countries in space industry, Korea needs more budget and professional research staff. Naturally, for the efficient and systemic space development and for the prevention of overlapping and distraction of power, it is necessary to enact space-related statutes, which would provide dear vision for the Korea space development. Furthermore, the fact that a variety of departments are running their own space development program requires a centralized and single space-industry development system. Prior to discussing how to coordinate or integrate space programs between Agency for Defense Development and the Korea Aerospace Research Institute, it is a prerequisite to establish, namely, "Space Operations Center"in the Air Force, which would determine policy and strategy in operating space forces. For the establishment of "Space Operations Center," policy determinations by the Ministry of National Defense and the Joint Chief of Staff are required. Especially, space surveillance system through using a military surveillance satellite and communication satellite, which would lay foundation for independent defense, shall be established with reference to Japan's space force plan. In order to resolve issues related to MTCR, Air Force would use space-launching vehicle of the Korea Aerospace Research Institute. Moreover, defense budge should be appropriated for using multi-purpose satellite and communication satellite. The Ministry of National Defense needs to appropriate 2.5 trillion won budget for space operations, which amounts to Japan's surveillance satellite operating budges.

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Transfer Learning using Multiple ConvNet Layers Activation Features with Principal Component Analysis for Image Classification (전이학습 기반 다중 컨볼류션 신경망 레이어의 활성화 특징과 주성분 분석을 이용한 이미지 분류 방법)

  • Byambajav, Batkhuu;Alikhanov, Jumabek;Fang, Yang;Ko, Seunghyun;Jo, Geun Sik
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.205-225
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    • 2018
  • Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

Risk Factor Analysis and Surgical Indications for Pulmonary Artery Banding (폐동맥 밴딩의 위험인자 분석과 수술적응중)

  • Lee Jeong Ryul;Choi Chang Hyu;Min Sun Kyung;Kim Woong Han;Kim Yong Jin;Rho Joon Ryang;Bae Eun Jung;Noh Chung I1;Yun Yong Soo
    • Journal of Chest Surgery
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    • v.38 no.8 s.253
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    • pp.538-544
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    • 2005
  • Background: Pulmonary artery banding (PAB) is an initial palliative procedure for a diverse group of patients with congenital cardiac anomalies and unrestricted pulmonary blood flow. We proved the usefulness of PAB through retrospective investigation of the surgical indication and risk analysis retrospectively. Material and Method: One hundred and fifty four consecutive patients (99 males and 55 females) who underwent PAB between January 1986 and December 2003 were included. We analysed the risk factors for early mortality and actuarial survival rate. Mean age was $2.5\pm12.8\;(0.2\sim92.7)$ months and mean weight was $4.5\pm2.7\;(0.9\sim18.0)\;kg$. Preoperative diagnosis included functional single ventricle $(88,\;57.1\%)$, double outlet right ventricle $(22,\;14.2\%)$, transposition of the great arteries $(26,\;16.8\%)$, and atrioventricular septal defect $(11,\;7.1\%)$. Coarctation of the aorta or interrupted aortic arch $(32,\;20.7\%)$, subaortic stenosis $(13,\;8.4\%)$ and total anomalous pulmonary venous connection $(13,\;8.4\%)$ were associated. Result: The overall early mortality was $22.1\%\;(34\;of\;154)$, The recent series from 1996 include patients with lower age $(3.8\pm15.9\;vs.\;1.5\pm12.7,\;p=0.04)$ and lower body weight $(4.8\pm3.1\;vs.\;4.0\pm2.7,\;p=0.02)$. The early mortality was lower in the recent group $(17.5\%;\;16/75)$ than the earlier group $(28.5\%;\;18/45)$. Aortic arch anomaly (p=0.004), subaortic stenosis (p=0.004), operation for subaortic stenosis (p=0.007), and cardiopulmonary bypass (p=0.007) were proven to be risk factors for early death in univariate analysis, while time of surgery (<1996) (p=0.026) was the only significant risk factor in multivariate analysis. The mean time interval from PAB to the second-stage operation was $12.8\pm10.9$ months. Among 96 patients who survived PAB, 40 patients completed Fontan operation, 21 patients underwent bidirectional cavopulmonary shunt, and 35 patients underwent biventricular repair including 25 arterial switch operations. Median follow-up was $40.1\pm48.9$ months. Overall survival rates at 1 year, 5 years and 10 years were $81.2\%\;65.0\%,\;and\;63.5\%$ respectively. Conclusion: Although it improved in recent series, early mortality was still high despite the advances in perioperative management. As for conventional indications, early primary repair may be more beneficial. However, PA banding still has a role in the initial palliative step in selective groups.