• Title/Summary/Keyword: Optimization.

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Optimization of the Extraction of Bioactive Compounds from Chaga Mushroom (Inonotus obliquus) by the Response Surface Methodology (반응표면분석법을 이용한 차가버섯(Inonotus obliquus)의 생리활성물질 최적 추출조건 탐색)

  • Kim, Jaecheol;Yi, Haechang;Lee, Kiuk;Hwang, Keum Taek;Yoo, Gichun
    • Korean Journal of Food Science and Technology
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    • v.47 no.2
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    • pp.233-239
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    • 2015
  • This study determined the optimum extraction conditions based on five response variables (yield, total phenolics, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavanging activity, oxygen radical absorbance capacity (ORAC), and ${\beta}$-1,3-glucan content) in chaga mushroom (Inonotus obliquus) using the response surface methodology, where three independent variables (ethanol concentration, extraction temperature, and extraction time) were optimized using a central composite design. The optimum ethanol concentration, extraction temperature, and extraction time were 50% (w/w), $88.7^{\circ}C$, and 14.5 h; 9.2%, $92.7^{\circ}C$, and 14.5 h; 50.8%, $92.7^{\circ}C$, and 14.5 h; 9.2%, $92.7^{\circ}C$, and 1.5 h; and 90.8%, $92.7^{\circ}C$, and 1.5 h for yield, total phenolics, ABTS, ORAC, and ${\beta}$-1,3-glucan content, respectively. The predicted values of the response variables were compared with those of the extracts under the optimal extraction conditions to verify the models. The optimum extraction condition for the five response variables was predicted to be 81.4% ethanol at $92.7^{\circ}C$ for 14.5 h.

Assessment of the Angstrom-Prescott Coefficients for Estimation of Solar Radiation in Korea (국내 일사량 추정을 위한 Angstrom-Prescott계수의 평가)

  • Hyun, Shinwoo;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.4
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    • pp.221-232
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    • 2016
  • Models to estimate solar radiation have been used because solar radiation is measured at a smaller number of weather stations than other variables including temperature and rainfall. For example, solar radiation has been estimated using the Angstrom-Prescott (AP) model that depends on two coefficients obtained empirically at a specific site ($AP_{Choi}$) or for a climate zone ($AP_{Frere}$). The objective of this study was to identify the coefficients of the AP model for reliable estimation of solar radiation under a wide range of spatial and temporal conditions. A global optimization was performed for a range of AP coefficients to identify the values of $AP_{max}$ that resulted in the greatest degree of agreement at each of 20 sites for a given month during 30 years. The degree of agreement was assessed using the value of Concordance Correlation Coefficient (CCC). When $AP_{Frere}$ was used to estimate solar radiation, the values of CCC were relatively high for conditions under which crop growth simulation would be performed, e.g., at rural sites during summer. The statistics for $AP_{Frere}$ were greater than those for $AP_{Choi}$ although $AP_{Frere}$ had the smaller statistics than $AP_{max}$ did. The variation of CCC values was small over a wide range of AP coefficients when those statistics were summarized by site. $AP_{Frere}$ was included in each range of AP coefficients that resulted in reasonable accuracy of solar radiation estimates by site, year, and month. These results suggested that $AP_{Frere}$ would be useful to provide estimates of solar radiation as an input to crop models in Korea. Further studies would be merited to examine feasibility of using $AP_{Frere}$ to obtain gridded estimates of solar radiation at a high spatial resolution under a complex terrain in Korea.

Quality Characteristics and Optimization of Fish-Meat Noodle Formulation Added with Olive Flounder (Paralichthys olivaceus) Using Response Surface Methodology (반응표면분석법을 이용한 넙치 첨가 어묵면의 품질 특성 및 제조조건 최적화)

  • Oh, Jung Hwan;Kim, Hyung Kwang;Yu, Ga Hyun;Jung, Kyong Im;Kim, Se Jong;Jung, Jun Mo;Cheon, Ji Hyeon;Karadeniz, Fatih;Kong, Chang-Suk
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.46 no.11
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    • pp.1373-1385
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    • 2017
  • The purpose of this study was to optimize the formulation for fish-meat noodles added with farmed olive flounder (Paralichthys olivaceus) using response surface methodology. Fish-meat (surimi) from P. olivaceus was prepared by a traditional washing process. Independent variables were Alaska pollack, fish-meat from P. olivaceus, and starch, whereas dependent variables were whiteness and texture. The results for whiteness and texture produced very significant values for whiteness (P<0.001), strength (P<0.001), hardness (P<0.05), breaking force (P<0.001), chewiness (P<0.001), brittleness (P<0.001), extensibility force (P<0.001), and extensibility distance (P<0.05). The optimal formula for fish-meat noodle was addition of 72.00 g Alaska pollack, 11.59 g P. olivaceus, and 15.86 g starch. Experimental values of whiteness, strength, hardness, breaking force, chewiness, brittleness, extensibility force, and extensibility distance under optimal conditions were $59.01{\pm}0.53$, $708.22{\pm}54.12g/cm^2$, $1,390.07{\pm}67.70g/cm^2$, $3,622.77{\pm}92.52g$, $2,686.94{\pm}103.22g$, $278,578.31{\pm}10,150.22g$, $52.22{\pm}2.97g$, $24.14{\pm}3.55mm$, respectively.

An Efficient Heuristic for Storage Location Assignment and Reallocation for Products of Different Brands at Internet Shopping Malls for Clothing (의류 인터넷 쇼핑몰에서 브랜드를 고려한 상품 입고 및 재배치 방법 연구)

  • Song, Yong-Uk;Ahn, Byung-Hyuk
    • Journal of Intelligence and Information Systems
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    • v.16 no.2
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    • pp.129-141
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    • 2010
  • An Internet shopping mall for clothing operates a warehouse for packing and shipping products to fulfill its orders. All the products in the warehouse are put into the boxes of same brands and the boxes are stored in a row on shelves equiped in the warehouse. To make picking and managing easy, boxes of the same brands are located side by side on the shelves. When new products arrive to the warehouse for storage, the products of a brand are put into boxes and those boxes are located adjacent to the boxes of the same brand. If there is not enough space for the new coming boxes, however, some boxes of other brands should be moved away and then the new coming boxes are located adjacent in the resultant vacant spaces. We want to minimize the movement of the existing boxes of other brands to another places on the shelves during the warehousing of new coming boxes, while all the boxes of the same brand are kept side by side on the shelves. Firstly, we define the adjacency of boxes by looking the shelves as an one dimensional series of spaces to store boxes, i.e. cells, tagging the series of cells by a series of numbers starting from one, and considering any two boxes stored in the cells to be adjacent to each other if their cell numbers are continuous from one number to the other number. After that, we tried to formulate the problem into an integer programming model to obtain an optimal solution. An integer programming formulation and Branch-and-Bound technique for this problem may not be tractable because it would take too long time to solve the problem considering the number of the cells or boxes in the warehouse and the computing power of the Internet shopping mall. As an alternative approach, we designed a fast heuristic method for this reallocation problem by focusing on just the unused spaces-empty cells-on the shelves, which results in an assignment problem model. In this approach, the new coming boxes are assigned to each empty cells and then those boxes are reorganized so that the boxes of a brand are adjacent to each other. The objective of this new approach is to minimize the movement of the boxes during the reorganization process while keeping the boxes of a brand adjacent to each other. The approach, however, does not ensure the optimality of the solution in terms of the original problem, that is, the problem to minimize the movement of existing boxes while keeping boxes of the same brands adjacent to each other. Even though this heuristic method may produce a suboptimal solution, we could obtain a satisfactory solution within a satisfactory time, which are acceptable by real world experts. In order to justify the quality of the solution by the heuristic approach, we generate 100 problems randomly, in which the number of cells spans from 2,000 to 4,000, solve the problems by both of our heuristic approach and the original integer programming approach using a commercial optimization software package, and then compare the heuristic solutions with their corresponding optimal solutions in terms of solution time and the number of movement of boxes. We also implement our heuristic approach into a storage location assignment system for the Internet shopping mall.

Game Theoretic Optimization of Investment Portfolio Considering the Performance of Information Security Countermeasure (정보보호 대책의 성능을 고려한 투자 포트폴리오의 게임 이론적 최적화)

  • Lee, Sang-Hoon;Kim, Tae-Sung
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.37-50
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    • 2020
  • Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

Development and Evaluation of Model-based Predictive Control Algorithm for Effluent $NH_4-N$ in $A^2/O$ Process ($A^2/O$ 공정의 유출수 $NH_4-N$에 대한 모델기반 예측 제어 알고리즘 개발 및 평가)

  • Woo, Dae-Joon;Kim, Hyo-Soo;Kim, Ye-Jin;Cha, Jae-Hwan;Choi, Soo-Jung;Kim, Min-Soo;Kim, Chang-Won
    • Journal of Korean Society of Environmental Engineers
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    • v.33 no.1
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    • pp.25-31
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    • 2011
  • In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.

Photocatalytic Oxidation of Arsenite Using Goethite and UVC-Lamp (침철석과 UVC-Lamp를 이용한 아비산염의 광촉매 산화)

  • Jeon, Ji-Hun;Kim, Seong-Hee;Cho, Hyen-Goo;Kim, Soon-Oh
    • Economic and Environmental Geology
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    • v.50 no.3
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    • pp.215-224
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    • 2017
  • Arsenic (As) is known to be the most toxic element and frequently detected in groundwater environment. Inorganic As exists as arsenite [As(III)] and arsenate [As(V)] in reduced and oxidized environments, respectively. It has been reported that the toxicity of arsenite is much higher than that of arsenate and furthermore arsenite shows relatively higher mobility in aqueous environments. For this reason, there have been numerous researches on the process for oxidation of arsenite to arsenate to reduce the toxicity of arsenic. In particular, photooxidation has been considered to be simple, economical, and efficient to attain such goal. This study was conducted to evaluate the applicability of naturally-occurring goethite as a photocatalyst to substitute for $TiO_2$ which has been mostly used in the photooxidation processes so far. In addition, the effects of several factors on the overall performance of arsenite photocatalytic oxidation process were evaluated. The results show that the efficiency of the process was affected by total concentration of dissolved cations rather than by the kind of those cations and also the relatively higher pH conditions seemed to be more favorable to the process. In the case of coexistence of arsenite and arsenate, the removal tendency by adsorption onto goethite appeared to be different between arsenite and arsenate due to their different affinities with goethite, but any effect on the photocatalytic oxidation of arsenite was not observed. In terms of effect of humic acid on the process, it is likely that the higher concentration of humic acid reduced the overall performance of the arsenite photocatalytic oxidation as a result of competing interaction of activated oxygen species, such as hydroxyl and superoxide radicals, with arsenite and humic acid. In addition, it is revealed that the injection of oxygen gas improved the process because oxygen contributes to arsenite oxidation as an electron acceptor. Based on the results of the study, consequently, the photocatalytic oxidation of aqueous arsenite using goethite seems to be greatly feasible with the optimization of process.

Optimization for the Process of Ethanol of Persimmon Leaf(Diospyros kaki L. folium) using Response Surface Methodology (반응표면분석법을 이용한 감잎(Diospyros kaki L. folium) 에탄올 추출물의 최적화)

  • Bae, Du-Kyung;Choi, Hee-Jin;Son, Jun-Ho;Park, Mu-Hee;Bae, Jong-Ho;An, Bong-Jeon;Bae, Man-Jong;Choi, Cheong
    • Applied Biological Chemistry
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    • v.43 no.3
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    • pp.218-224
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    • 2000
  • The efforts were made to optimite ethanol extraction from persimmon leaf with the time of extraction$(1.5{\sim}2.5\;hrs)$, the temperature of extraction$(70{\sim}90^{\circ}C)$, and the concentration of ethanol$(0{\sim}40%)$ as three primary variables together with several functional characteristics of persimmon leaf as reaction variables. The conditions of extraction was best fitted by using response surface methodology through the center synthesis plan, and the optimal conditions of extraction were established. The contents of soluble solid and soluble tannin went up as the concentration of ethanol went up and the temperature of extraction went down, and the turbidity went down as the concentration of ethanol went down. Electron donation ability was hardly affected by the extraction temperature and had the tendency to go up as the concentration of ethanol went up. The inhibitory activity of xanthine oxidase(XOase) had the tendency to go up as both the concentration of ethanol and the temperature of extraction went up. The inhibitory activity of angiotensin converting enzyme(ACE), the significance of which still was not recognized, showed the maximum when the concentration of ethanol was 27%. In result, the optimal conditions of extraction was the extraction time of two hours, the extraction temperature of $75{\sim}81^{\circ}C$, and the ethanol concentration of $33{\sim}35%$.

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Object Tracking Based on Exactly Reweighted Online Total-Error-Rate Minimization (정확히 재가중되는 온라인 전체 에러율 최소화 기반의 객체 추적)

  • JANG, Se-In;PARK, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.53-65
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    • 2019
  • Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

Optimization of the cryopreserved condition for utilization of GPCR frozen cells (GPCR 냉동보관 세포의 활용을 위한 냉동조건의 최적화 연구)

  • Noh, Hyojin;Lee, Sunghou
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.2
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    • pp.1200-1206
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    • 2015
  • The major target for drug discovery, G-protein coupled receptor (GPCR) is involved in many physiological activities and related to various diseases and disorders. Among experimental techniques relating to the GPCR drug discovery process, various cell-based screening methods are influenced by cell conditions used in the overall process. Recently, the utilization of frozen cells is suggested in terms of reducing data variation and cost-effectiveness. The aim of this study is to evaluate various conditions in cell freezing such as temperature conditions and storage terms. The stable cell lines for calcium sensing receptor and urotensin receptor were established followed by storing cultured cells at $-80^{\circ}C$ up to 4 weeks. To compare with cell stored at liquid nitrogen, agonist and antagonist responses were recorded based on the luminescence detection by the calcium induced photoprotein activation. Cell signals were reduced as the storage period was increased without the changes in $EC_{50}$ and $IC_{50}$ values $EC_{50}:3.46{\pm}1.36mM$, $IC_{50}:0.49{\pm}0.15{\mu}M$). In case of cells stored in liquid nitrogen, cell responses were decreased comparing to those in live cells, however changes by storage periods and significant variations of $EC_{50}/IC_{50}$ values were not detected. The decrease of cell signals in various frozen cells may be due to the increase of cell damages. From these results, the best way for a long-term cryopreservation is the use of liquid nitrogen condition, and for the purpose of short-term storage within a month, $-80^{\circ}C$ storage condition can be possible to adopt. As a conclusion, the active implementation of frozen cells may contribute to decrease variations of experimental data during the initial cell-based screening process.