Recently, researches on light weight of vehicles have been actively carried out to reduce fuel consumption. Researchers have generally attempted to replace metal materials with composites, but these materials do not meet the required strength and rigidity of the vehicle and require a variety of design approaches. In this paper, deck assembly of truck was compared and compared with assembly using existing floor as Apitong, and it was verified by structural analysis and modal analysis. To do this, we measured the mechanical properties of the material through tests and evaluated the safety of the Deck Assembly through maximum equivalent stress, total deformation, and safety factor values. In addition, the fit of the hybrid deck assembly structure was evaluated by measuring the approximation of the analysis by single component assembly test.

대의제는 익히 대화와 토론을 통한 공공의 이익 판단을 위하여 고안된 정치제도이다. 공공의 이익은 ‘결정’ 되거나 ‘발견’ 되어 진다. 결정되는 공익은 가치관의 차이에 의거 극단적인 대립 속에서 다수결의 원칙으로 정해지는 것이고 발견되는 공익은 숙의 없이 공익이 발견되는 경우와 숙의가 반드시 필요한 경우로 나뉜다. AI는 이 세 가지 유형 중에서 숙의가 필요한 경우에 가장 유용하게 사용될 수 있다. 현재에도 대의제의 핵심 요소인 선거를 통하여 선출된 대표자들이 공공의 이익을 판단을 돕기 위한 여러 가지 제도와 장치들이 구성되어 있다. 대통령의 직무를 돕기 위해 대통령의 인사권이 인정되는 ‘임명직’ 공직자나 국회의원의 공공의 이익 판단을 위해 국민 세금으로 운영되는 국회예산정책처, 국회입법조사처 등의 조사기관들이 그것이다. 이와 같이 최종 공익결정 권한이 없는 중간 판단자와 공익 결정의 권한이 있는 결정 주체 모두에게 AI는 유용할 수 있다. 물론, 대표를 선출하지 않는 (직접)민주주의 하에서도 AI는 기능할 수 있다. AI가 제공한 정보로 가부를 묻는 실시간 국민투표를 실시할 수 있는 기술의 발전을 기대할 수 있기 때문이다. 다만, 이와 같은 경우에는 가부를 묻는 의제의 선정을 사람이 아닌 AI가 맡기 때문에 실질적으로는 AI가 사람을 지배하는 상황으로 변질 될 수 있는 위험성도 매우 크다. 한 발 더 나아가 AI가 의제를 결정하고 중간 판단도 하며 최종 공익 결정도 AI가 할 경우 사람은 주권을 포기하거나 강탈당하거나 양자 중에 선택해야 한다. 물론 이와 같은 경우는 헌법적으로 용인되지 않는다. 그러나 이에 앞서 필수적으로 고려해야 하는 인공지능의 특징이 있다. 대부분의 사람들은 사람에 비하여 훨씬 AI가 ‘객관적’이라 믿는다. 하지만, AI는 어떤 알고리즘을 통하여 학습하는가에 따라서 완벽하게 다른 결론을 ‘객관적’으로 보이도록 할 수 있다. AI가 입법과정을 다룸에 있어서 사람만큼이나 편견이 생겨 그 편향성이 강화된다면 AI에게 객관성을 기대하기 어렵다. 편향성을 가진 인공지능이 의제를 결정하고 중간판단에도 개입하고 최종 공익 결정도 누군가에 의해 의도적인 알고리즘 조작을 통해 가능하다면 그것이 우리 인류가 대의제를 고안한 근본 원칙에 맞는 것인가에 대해 동의할 수 없음은 자명하다. 이것이 AI가 발전하면 서도 궁극적으로 공공의 이익의 최종 판단을 합의제 의사결정 기구인 국회에서 ‘사람’으로 구성된 국회의원이 해야만 하는 이유이다. 객관적일 것이라 기대하는 AI도 우리만큼 편향적일 수 있기에 우리가 마지막으로 기댈 수 있는 것은 ‘불완전한 인간’들의 숙의를 통한 공익 추구뿐이다.

To formulate folate receptor (FR)-specific graphene-based electrochemical electrodes, a folic acid (FA) derivative attached with two pyrene molecules on the glutamate tail of FA was synthesized. The resulting pyrene-functionalized FA (FA-Py) presented the spontaneous noncovalent binding on chemically reduced graphene oxides (rGO) through an π-π interaction. Ultrathin morphology, high water-resistance, and preservation of intact FR-specific pteroates from the rGO/FA-Py assembly allow this assembly to be exploited as robust and FR-specific electrochemical electrode materials. The limits of detecting rGO/FA-Py modified electrodes were found to be as low as 3.07 nM in FR concentrations in cyclic voltammetry analysis.

In this study, a membrane electrode assembly(MEA) composed of three electrodes(anode, cathode, and reference electrode) is designed to investigate the effects of methanol concentration on the overpotentials of anode and cathode in direct methanol fuel cells(DMFCs). Using the three-electrode cell, in-situ analyses of the overpotentials are carried out during direct methanol fuel cell operation. It is demonstrated that the three-electrode cell can work effectively in transient state operating condition as well as in steady-state condition, and the anode and cathode exhibit different overpotential curves depending on the concentration of methanol used as fuel. Therefore, from the real-time separation of the anode and cathode overpotentials, it is possible to more clearly prove the methanol crossover effect, and it is expected that in-situ analysis using the three-electrode cell will provide an opportunity to obtain more diverse results in the area of fuel cell research.

In this study, we consider the assembly line balancing (ALB) problem which is known as an very important decision dealing with the optimal design of assembly lines. We consider ALB problems with soft constraints which are expected to be fulfilled, however they are not necessarily to be satisfied always and they are difficult to be presented in exact quantitative forms. In previous studies, most researches have dealt with hard constraints which should be satisfied at all time in ALB problems. In this study, we modify the mixed integer programming model of the problem introduced in the existing study where the problem was first considered. Based on the modified model, we propose a new algorithm using the genetic algorithm (GA). In the algorithm, new features like, a mixed initial population selection method composed of the random selection method and the elite solutions of the simple ALB problem, a fitness evaluation method based on achievement ratio are applied. In addition, we select the genetic operators and parameters which are appropriate for the soft assignment constraints through the preliminary tests. From the results of the computational experiments, it is shown that the proposed algorithm generated the solutions with the high achievement ratio of the soft constraints.

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

Vitamin A is essential for growth and differentiation of a number of cells and tissues, as result the precursor, a carotenoid β-carotene remains their essential source of vitamin A. However, the major problem this carotenoid face, is its susceptible to photodegradation and chemical oxidation, those properties make it difficult to use as an ingredient as functional food product and reduce its bioavailability. This study presents a novel approach to prepare a one-step inclusion complex using amylose microparticles as host molecule using amylosucrase from Deinococcus geothermalis (DGAS) and β-carotene nanoparticles, which were added into the DGAS enzyme reaction solution to entrap them during the synthesis of amylose chains. HRFE-SEM showing a spherical shape and average diameter of 4-8 μm; XRD and DSC showed an amorphous structure as well as less energy required to start the gelatinization process, due to the complexation of amylose chains with the β-carotene nano dispersion. Last but not least Raman spectroscopy was performed in order to confirmed the complex formation between β-carotene and amylose microparticles, showing the characteristic peaks of both compound. The stability test in this study showed the high stability of the complexed microparticles against environmental stresses such as, photodegradation and chemical oxidation. We expect this study contributes to the development of functional food materials to enhance the stability and bioavailability of active compounds.

The modification of Silicotungstic acid (STA) was done by Melamine and Mixed matrix membranes from the Melamine modified Silico tungstic acid (M-STA) particles were prepared for the pervaporation dehydration of Water -Isopropanol (IPA) mixture. The characterization of the membranes were done by FTIR, SEM, EDS AFM XRD, and contact angle measurements. The M-STA loaded composite membranes showed improved pervaporation performance in comparison to the virgin membrane. The 8 wt% M-STA loaded (M8-MSTA) membrane gave an optimum pervaporation performance having flux = 0.36 kg/m2h, separation factor 485.6 for 20 wt% water -isopropanol feed composition at 60 0C was observed.

글로벌 경제 침체 속에서 기업은 날로 높아져 가는 소비자들의 수요를 만족하기 위하여 납기 대응 그리고 LB(Line Balance, 라인편성효율) 향상과 제조원가의 절감을 위한 생산성 향상은 중요한 개선 항목이다. 따라서 본 연구에서는 자동차 물류 중 조달물류를 대상으로 하여 불출자의 로드밸런스율을 증대할 수 있는 휴리스틱 알고리즘 개발에 대하여 연구를 진행함으로써 1차 목표 값을 적용하였을 load balancing율은 45.6%에서 91.7%로 개선 된 것을 확인할 수 있었다.

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization with multiple objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA.

Resveratrol was incorporated into various combinations of single- and double-layer nanoemulsions, prepared by selfassembly emulsification and complex coacervation with chitosan, alginate, and β-cyclodextrin, respectively. Resveratrol nanoemulsions were composed of medium-chain trigacylglycerols (MCTs), Tween ® 80, water, chitosan, alginate, and β-cyclodextrin. The corresponding mixtures were formulated for the purpose of being used as a nutraceutical delivery system. Resveratrol nanoemulsions were obtained with particle sizes of 10-800 nm, with the size variation dependent on the emulsification parameters including the ratio of aqueous phase and surfactant ratio. Resveratrol nanoemulsions were characterized by evaluating particle size, zeta-potential value, stability, and release rate. There were no significant changes in particle size and zeta-potential value of resveratrol nanoemulsions during storage for 28 days at 25°C. The stability of resveratrol in the double-layer nanoemulsions complexed with chitosan or β-cyclodextrin was higher, compared with the single-layer nanoemulsions.