• Tissue Engineering and Regenerative Medicine
• /
• v.15 no.6
• /
• pp.735-750
• /
• 2018

BACKGROUND: The major challenge of tissue engineering is to develop constructions with suitable properties which would mimic the natural extracellular matrix to induce the proliferation and differentiation of cells. Poly(${\varepsilon}$-caprolactone)-poly(ethylene glycol)-poly(${\varepsilon}$-caprolactone) (PCL-PEG-PCL, PCEC), chitosan (CS), nano-silica ($n-SiO_2$) and nano-hydroxyapatite (n-HA) are biomaterials successfully applied for the preparation of 3D structures appropriate for tissue engineering. METHODS: We evaluated the effect of n-HA and $n-SiO_2$ incorporated PCEC-CS nanofibers on physical properties and osteogenic differentiation of human dental pulp stem cells (hDPSCs). Fourier transform infrared spectroscopy, field emission scanning electron microscope, transmission electron microscope, thermogravimetric analysis, contact angle and mechanical test were applied to evaluate the physicochemical properties of nanofibers. Cell adhesion and proliferation of hDPSCs and their osteoblastic differentiation on nanofibers were assessed using MTT assay, DAPI staining, alizarin red S staining, and QRT-PCR assay. RESULTS: All the samples demonstrated bead-less morphologies with an average diameter in the range of 190-260 nm. The mechanical test studies showed that scaffolds incorporated with n-HA had a higher tensile strength than ones incorporated with $n-SiO_2$. While the hydrophilicity of $n-SiO_2$ incorporated PCEC-CS nanofibers was higher than that of samples enriched with n-HA. Cell adhesion and proliferation studies showed that n-HA incorporated nanofibers were slightly superior to $n-SiO_2$ incorporated ones. Alizarin red S staining and QRT-PCR analysis confirmed the osteogenic differentiation of hDPSCs on PCEC-CS nanofibers incorporated with n-HA and $n-SiO_2$. CONCLUSION: Compared to other groups, PCEC-CS nanofibers incorporated with 15 wt% n-HA were able to support more cell adhesion and differentiation, thus are better candidates for bone tissue engineering applications.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1577-1585
• /
• 2022

As the interest in the 4th industrial revolution and metaverse increases, metaverse with multi edge structure is proposed and noted. Metaverse is a structure that can create digital doctor-like system through a large amount of image processing and data transmission in a multi edge system. Since metaverse application requires calculating performance, which can reconstruct 3-D space, edge hardware's insufficient calculating performance has been a problem. To provide streamable AI software in runtime, image processing, and data transmission, which is edge's loads, needs to be lightweight. Also lightweight at the edge leads to power consumption reduction of the entire metaverse application system. In this paper, we propose collaborative edge-cloud image processing with remote image processing method and Region of Interest (ROI) to overcome edge's power performance and build streamable and runtime executable AI software. The proposed structure was implemented using a PC and an embedded board, and the reduction of time, power, and network communications were verified.

• Microbiology and Biotechnology Letters
• /
• v.40 no.1
• /
• pp.1-9
• /
• 2012

This study's aim was to isolate microorganisms producing agarase with a high activity, with possible applications in improving the performance of the pretreatment processes for bioethanol production. Marine algaes were collected from the south coast of Korea, from which three kinds of microorganisms were isolated. After a 4-day culture of these strains at $25^{\circ}C$, crude enzymes were obtained from culture supernatant or cell-free extract by ammonium sulfate precipitation and membrane dialysis. Agarase activity was observed in these crude enzymes. Notably higher specific activity was observed in the crude enzyme obtained from the culture supernatant rather than that from the cell-free extract. This indicates that a secreted enzyme has a much greater activity than a cellular enzyme. Crude enzymes from the GNUM08122 strain were inferred to have ${\alpha}$-agarase activity because release of p-nitrophenol was observed, possibly due to the cleavage of p-nitrophenyl-${\alpha}$-D-galactopyranoside. The 16S rRNA sequence of GNUM08122 showed a close relationship to Pseudoalteromonas issachenkonii KMM 3549 (99.8%) and Pseudoalteromonas tetraodonis IMA 14160 (99.7%), which led us to assign it to the genus Pseudoalteromonas. Biochemical and physiological study revealed that this strain can grow well at $40^{\circ}C$ under a wide range of pH (pH 4~8) in high-salt conditions (10% NaCl).

• Journal of Korean Neurosurgical Society
• /
• v.30 no.2
• /
• pp.131-136
• /
• 2001

Object : The clinical uses of screws are increasing with broader applications in spinal disorders. When screws are inserted repeatedly to achieve optimal position, tips of screw pitch may become damaged during insertion even though there are significant differences in the moduli of elasticity between bone and titanium. The effect of repeated screw insertion on pullout resistance was investigated. Methods : Three different titanium screws(cortical lateral mass screw, cancellous lateral mass screw and cervical vertebral body screw) were inserted into the synthetic cancellous material and then extracted axially at a rate of 2.4mm/min using Instron(Model TT-D, Canton, MA). Each set of screws was inserted and pulled out three times. There were six screws in each group. The insertional torque was measured with a torque wrench during insertion. Pullout strength was recorded with a digital oscilloscope. Results : The mean pullout force measurements for the cortical lateral mass screws($185.66N{\pm}42.60$, $167.10N{\pm}27.01$ and $162.52 N{\pm}23.83$ for first, second and third pullout respectively : p=0.03) and the cervical vertebral body screws($386.0N{\pm}24.1$, $360.2N{\pm}17.5$ and $330.9N{\pm}16.7$ : p=0.0024) showed consecutive decrease in pullout resistance after each pullout, whereas the cancellous lateral mass screws did not($194.00N{\pm}36.47$, $219.24N{\pm}26.58$ and 199.49N(36.63 : p=0.24). The SEM after insertion and pullout three times showed a blunting in the tip of the screw pitch and a smearing of the screw surface. Conclusions : Repetitive screw insertion and pullout resulted in the decrease of pullout resistance in certain screws possibly caused by blunting the screw tip. This means screw tips suffer deformations during either repeated insertion or pullout. Thus, the screws that have been inserted should not be used for the final construct.

• Journal of Venture Innovation
• /
• v.5 no.1
• /
• pp.107-127
• /
• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1041-1043
• /
• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].

• Journal of Radiation Protection and Research
• /
• v.33 no.3
• /
• pp.105-112
• /
• 2008

To measure the soil-to-plant transfer factors ($TF_a,\;m^2\;kg^{-1}$-fresh) of radionuclides deposited during the growing season of potato, a radioactive solution containing $^{54}Mn,\;^{60}Co,\;^{85}Sr$ and $^{137}Cs$ was applied to the soil surfaces in soil boxes 2 d before seeding and three different times during the plant growth. For the pre-seeding application (PSA), radionuclides were mixed with the topsoil (loamy sand and 5.2 in pH). The plant parts investigated were leaves, stems, tuber skin and tuber flesh. The $TF_a$ values of $^{54}Mn,\;^{60}Co,\;^{85}Sr$ and $^{137}Cs$ from the PSA were in the ranges of $1.9{\times}10^{-4}{\sim}1.5{\times}10^{-2}$, $1.8{\times}10^{-4}{\sim}7.5{\times}10^{-4}$, $4.0{\times}10^{-4}{\sim}1.6{\times}10^{-2}$, $1.5{\times}10^{-4}{\sim}3.9{\times}10^{-4}$ respectively, for different plant parts. The TFa values from the growing-time applications were on the whole a few times lower than those from the PSA. For $^{54}Mn,\;^{85}Sr$ and $^{137}Cs$, the $TF_a$ values from the early- or middle-growth-stage application were higher than those from the late-growth-stage application, whereas the opposite was true for $^{60}Co$. Leaves and tuber flesh had the highest and lowest $TF_a$ values, respectively, in most cases. The total uptake from soil by the four plant parts was in the range of $0.05{\sim}3.16%$. In the third year following the PSA, the $TF_a$ values of $^{54}Mn,\;^{60}Co$ and $^{137}Cs$ were $11{\sim}25%$, $21{\sim}25%$ and $38{\sim}67%$ of those in the first year, respectively, depending on the plant parts. The present results can be used for estimating the radiological impact of an acute radioactive deposition during the growing season of potato and for testing the validity of relevant food-chain models.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.4
• /
• pp.39-58
• /
• 2019

This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R²) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R², and VCI results.

• The Journal of Korean Academy of Prosthodontics
• /
• v.44 no.6
• /
• pp.699-711
• /
• 2006

Statement of problem. Elastomeric impression materials have been widely used to obtain an accurate impression. However there have not been enough studies on the influence of the thickness of the tray adhesives on the bonding strength between the trays and the elastomeric impression materials. Purpose. In order to understand the relationship between the thickness of the tray adhesive and the tensile bond strength and to suggest the thickness at which the bonding strength is strongest, tensile bond strength related to the thickness of adhesives of 3 different elastomeric impression materials were tested. Materials and methods. 3 impression materials, $Permlastic^{(R)}$. Regular Set(Kerr Corp., Romulus, Michigan, U.S.A.), $Impregum^{TM}$ $Penta^{TM}$(3M ESPE, Seefeld, Germany), and Aquasil Ultra Monophase Regular Set Smart Wetting.(Dentsply Caulk, Milford, Delaware, U.S.A.), were used in this study, and tray adhesives from the same manufacturers of the impression materials were used, which were Rubber Base Adhesive, Polyether Adhesive, and Silfix, respectively. The tray specimens were prepared by autopolymerizing the tray material(Instant Tray Mix, Lang, Wheeling, Illinois, U.S.A.), and a PVC pipe was used to house the impression material. In group A, tray adhesives were applied in multiple thin layers of 1 to 5 and in group B, adhesives were applied only once, in the thickness equivalent to several applications. Lightness($L^*$) of the adhesion surface was measured with a spectrophotometer(CM-3500d, Konica Minolta, Sakai, Osaka, Japan). The tensile bond strength of the elastomeric impression material and the tray resin was measured with universal materials testing machines(Instron, Model 3366, Instron Corp, Nowood, Massachusetts, U.S.A.). A formula between the number of adhesive application layers and the lightness of the adhesion surface was deduced in group A, and the number of adhesive layers in group B was estimated by applying the lightness($L^*$) to the deduced formula. Results. 1. In group A, a statistically significant increase in tensile bond strength appeared when the number of application layers increased from 1 to 2 and from 4 to 5, and no significant difference was present between 2, 3, and 4 layers in Permlastic. In Impregum, the tensile bond strength was significantly increased when the number of adhesive layers increased from 1 to 3, but no significant difference after 3 layers. In Aquasil, the tensile bond strength significantly increased as the number of application layers increased up to 4 but showed no significant difference between 4 and 5. 2. In group B, the tensile bond strength was decreased when the thickness of the adhesive increased in Permlastic. Impregum showed an increased tensile bond strength when the thickness of the adhesive was increased. In Aquasil, the tensile bond strength increased as the number of adhesive application layers increased up to approximately 2.5 layers but it sharply decreased after approximately 4.5. Conclusion. From the study, the common idea that it is better to apply a thin and single coat of tray adhesive needs correction in more detailed ways, and instructions on some of the tray adhesives should be reconsidered since there were several cases in which the tensile bond strength increased according to the increase in the thickness of the adhesives.

• Journal of the Korean Magnetics Society
• /
• v.13 no.5
• /
• pp.187-192
• /
• 2003

The magnetic and thermal properties of NiFe/[IrMn-Mn]/CoFe with Mn additions have been studied. As-deposited CoFe pinned layers with [IrMn-Mn]layer had dominantly larger exchange biasing field ( $H_{ex}$) and blocking temperature ( $T_{b}$) than those with pure I $r_{22}$M $n_{78}$ used. The $H_{ex}$ and $T_{b}$ improved with 76.8-78.1 vol% Mn, but those of the NiFe/IrMn/CoFe dropped considerably with more addition of 0.6 vol % Mn. The average x-ray diffraction peak ratios of fcc [(111)CoFe, NiFe]/(111)IrM $n_3$ textures for the Mn inserted total vol of 75.5, 77.5, and 79.3% were about 1.4, 0.8, and 0.6, respectively. For the sample without Mn inserted layer, the $H_{ex}$ between IrMn and CoFe layers was almost zero, but it increased to 100 Oe after annealing of 250 $^{\circ}C$. For as-grown two multilayers samples with ultra-thin Mn layers of 77.5 and 78.7 vol %, the $H_{ex}$s were 259 and 150 Oe, respectively. In case of IrMn with 77.5 vol% Mn, the $H_{ex}$ was increased up to 475 Oe at 350 $^{\circ}C$ but decreased to 200 Oe at 450 $^{\circ}C$, respectively. The magnetic properties and thermal stabilities of NiFe/[IrMn-Mn]/CoFe multilayer were enhanced with Mn additions. In applications where higher $H_{ex}$ and $T_{b}$ are required, proper contents of Mn can be used. be used. used.