This research investigates the impact of specific emotions in electronic word-of-mouth (eWOM) on the monthly donations received by a non-profit organization (NPO). We employ the empathy-helping (empathy-altruism) hypothesis as a theoretical foundation, proposing that donation motivations should inform eWOM fundraising appeals. To do so, we analyzed 71,462 tweets about a charity from 23,430 users, categorizing them as either marketer-generated content (MGC) or user-generated content (UGC). To automatically detect six distinct emotions in the text, we utilized a transformer-transfer learning approach for emotion detection. This model was trained in a sequential manner, starting with self-reported emotions in over 3.6 million tweets and progressing to socially agreed-upon emotion datasets to mimic social-emotional development stages. Our findings revealed that emotions prompting empathy (such as sadness in MGC) and positive empathy (like joy in UGC) positively influence donation amounts in line with the empathy-helping hypothesis. We offer insights on how social media marketers can leverage these results to create and manage tweets that boost donations. This study contributes to marketing research and practice in three ways: (1) by being the first, to our knowledge, to examine the effect of specific emotions in eWOM on donation decisions, (2) by introducing a novel machine learning model capable of detecting emotions in large-scale eWOM, and (3) by providing actionable recommendations for NPOs to increase donations via emotionally driven social media messaging. As a result, marketing managers can more effectively use social media platforms to foster emotional connections between NPOs and donors.

The inscription of Cheonsang Yeolcha Bunyajido (天象列次分野之圖) has the sun’s locations at the equinoxes, which must have been copied from the astronomical treatises in Chinese historical annals, Songshu (宋書) and Jinshu (晉書). According to the treatises, an astronomer Wang Fan (王蕃, 228–266 CE) referred those values from a calendrical system called Qianxiangli (乾象 曆, 223 CE), from which it is confirmed that it adopted the sun’s location at the winter solstice of the (211 4 )th du of the 8th lunar lodge Dou (斗) as the reference direction for equatorial lodge angles. This indicates that the sun’s locations at equinoxes and solstices in the calendrical system are the same as those in Jingchuli (景初曆, 237 CE). Hence, we propose that the sun’s location at the autumnal equinox in Cheonsang Yeolcha Bunyajido should be corrected from ‘wu du shao ruo’ (五度少弱), meaning the (51 6 )th du, to ‘wu du ruo’ (五度弱), meaning the (411 12 )th du, of the first lunar lodge Jiao (角), as seen in Jingchuli. We reconstruct the polar coordinate system used in circular star charts, assuming that the mean motion rule was applied and its reference direction was the sun’s location at the winter solstice. Considering the precession, we determined the observational epoch of the sun’s location at the winter solstice to be 𝑡o = −18.3 ± 43.0 adopting the observational error of the so-called archaic determinatives (古度). It is noteworthy that the sun’s locations at equinoxes inscribed in Cheonsang Yeolcha Bunyajido originated from Houhan Sifenli (後漢四分曆) of the Latter Han dynasty (85 CE), while the coordinate origin in the star chart is related to Taichuli (太初 曆) of the Former Han dynasty (104 BCE).

Shoushili was the official calendrical method promulgated in 1280 CE by the Yuan dynasty. It contains a list of the angular spans in right ascensions for the 28 lunar lodges. They are known to have been measured by Guo Shoujing with his advanced instruments with an unprecedented precision or reading error of 5′. Such precise data are useful to determine their observational epoch with an error range which is narrow enough to pinpoint on which historical occasion they were observed. Using the precise SIMBAD data based on eDR3 of GAIA and carefully identified determinative stars and considering the precession of equinoxes and proper motions, we apply linear regression methods to those data and obtain the observational epoch of 1271 ± 16 CE and the measurement error of 4.1′. We also have polar distances corresponding to declinations written in another manuscript of the Ming dynasty. Since the two data sets have similar significant digits, they were suggested to have the same origin. However, we obtain their observational epoch of 1364±5 CE and the measurement error of 5.7′. They must have been measured with different instruments and on a different occasion from the observations related to Shoushili. We review the history of the calendrical reform during the 13th century in the Yuan dynasty. We conclude that the observational epoch obtained from lodge spans in Shoushili agrees with the period of observations led by Guo Shoujing or 1276–1279 CE, which is also supported by the fact that the ecliptic lodge span values listed in Shoushili were calculated from the equatorial lodge spans.

Neutron resonance transmission technique was applied for assaying isotopic fissile materials produced in the pyro-process. In each process of the pyro-process, a different composition of the fissile material is produced. Simulation was basically performed on 235U and 239Pu assay for TRU-RE product, hull waste, and uranium addition. The resonance energies were evaluated for uranium and plutonium in the simulation, and the linearity in the detection response was examined on the fissile content variation. The linear resonance energies were determined for the analysis of 235U and 239Pu on the different fissile materials. For enriched TRU-RE assay, the sample condition was suggested; The sample density, content, and thickness are the key factors to obtain accurate fissile content. The detection signal is discriminated for uranium and plutonium in neutron resonance technique. The transmitted signal for fissile resonance has a direct relation with the content of fissile. The simulation results indicated that the neutron resonance technique is promising to analyze 235U and 239Pu for various types of the pyro-process material. An accurate fissile assay will contribute toward safeguarding the pyro-processing system.

VR 및 AR은 대중들이 접근하기 어려운 기술이 아닌, 개인용 스마트 폰 하나로 체험 및 활용 할 수 있는 시 대가 되었다. 최근 이런 개인용 스마트 폰의 다양한 센서를 활용한 AR 콘텐츠가 개발되고 서비스 되고 있다. AR 콘텐츠의 수요가 커지면서Software교육의 수요도 커지게 되었다. 하지만, 비전공자들도 배우기 쉬운 Python 언어를 중심으로 SW 교육이 활발해졌음에도, 아직까지 AR 콘텐츠 개발에서는 Python을 적극적으로 사용할 수 없다. AR 콘텐츠는 기술 분야 뿐 아니라 인터렉티브 아트 분야에서도 활발하게 사용되고 있다. 최근 인터 렉티브 아티스트들은 Python을 이용하여 인공지능을 활용한 작품을 개발 및 전시하고 있다. Python을 통한 SW 교육은 SW 분야의 취업에만 필요한 것이 아니라 아트 분야에서도 필요한 교육이 되었다. 본 논문에서는 AR 콘텐츠 개발 교육을 위한 Python과 Unity 3D Engine을 이용한 네트워크 기반 AR 프레임 워크를 제안한다. 제 안한 AR 프레임 워크는 Web 기반 브라우저에서 개인용 스마트 폰의 카메라에 접근하여 카메라 정보를 Main Server에 전송하고 Python에서 Mark를 분석한다. Mark 정보에 맞춰 Unity 3D Engine에서 3D 오브젝트를 렌더 링하고, 카메라 정보화 합성 후, MJPEG 스트리밍으로 개인용 스마트 폰 화면에 렌더링 된다. 본 논문에서 제 안한 AR 프레임 워크는 SW 교육 플랫폼과 비대면 교육 플랫폼의 요구사항을 반영하며, 인터렉티브 아티스트 들의 다양한 도전에 필요한 기술적 제한을 낮춰 줄 것으로 기대한다.

This study presents a methodology to determine the radionuclides of concern that are expected to be found during the final status survey of Kori Unit 1 decommissioning. The methodology involved reflecting the evaluation results of ORIGEN based on reference documents such as NUREG/CR-3474, NUREG/CR-4289, NUREG/CR-0130, WINCO-1191, and representative fuel loading. A list of potential radionuclides of concern was provided by reflecting the list of radionuclides of concern included in the Kori Unit 1 decommissioning plan. To select the radionuclides of concern, we analyzed the approach of US decommissioning plants based on the recommendations of NUREG-1757 Vol.2 Rev.1 and excluded certain radionuclides from the list. The final list of 23 radionuclides of concern was derived by excluding radionuclides that have a short half-life, low specific activity, analytically difficult to measure, inert gases, or naturally occurring radionuclides. This methodology can be applied to other nuclear power plants, such as the Wolsong Nuclear Power Plant, by reflecting the unique characteristics of the reactor.

As the decommissioning of nuclear power plants progresses, interest in the inevitably generated radioactive waste is also increasing. Especially, because the containers of ILW packages are significantly more expensive than the containers of LLW packages, the special attention should be focused on minimizing the number of the containers of ILW packages. The radiation dose limit for packaging of ILW shall not exceed 2 mSv/h and 0.1 mSv/h on contact and at 2 m, respectively in South Korea. Meanwhile, The DEMplus provides various environmental geometry and all properties such as materials, absorptions, and reflections and the estimation of the radiation dose rates is based on the radiation interactions of the designed 3D geometry model. With the consideration of the radiation dose rate by using DEMplus and its strategy of packaging and cutting plan, the number of containers for ILW packages generated from decommissioning of Reactor Vessel Internal (RVI) of a nuclear power plant that has been in operation for decades was optimized in this paper. The modular shielded containers (MSC) with shielding inserted were used for radioactive wastes that require shielded packaging. In order to verify the accuracy of the estimated radiation dose rate by using DEMplus, the estimated results were compared with those obtained using MicroShield. The trends of the estimated radiation dose rates using DEMplus and the estimation of MicroShield were similar to each other. The results of this study demonstrated the feasibility of using DEMplus as a means of estimating the radiation dose limit in packaging plan of the radioactive waste.

Al-B4C neutron absorbers are currently widely used to maintain the subcriticality of both wet and dry storage facilities of spent nuclear fuel (SNF), thus long-term and high-temperature material integrity of the absorbers has to be guaranteed for the expected operation periods of those facilities. Surface corrosion solely has been the main issue for the absorber performance and safety; however, the possibility of irradiation-assisted degradation has been recently suggested from an investigation on Al-B4C surveillance coupons used in a Korean spent nuclear fuel pool (SFP). Larger radiation damage than expectation was speculated to be induced from 10B(n, α)7Li reactions, which emit about a MeV α-particles and Li ions. In this study, we experimentally emulated the radiation damage accumulated in an Al-B4C neutron absorber utilizing heavy-ion accelerator. The absorber specimens were irradiated with He ions at various estimated system temperatures for a model SNF storage facility (room temperature, 150, 270, and 400°C). Through the in-situ heated ion irradiation, three exponentially increasing level of radiation damages (0.01, 0.1, and 1 dpa or displacement per atom) were achieved to compare differential gas bubble formation at near surface of the absorber, which could cause premature absorber corrosion and subsequential 10B loss in an SNF storage system. An extremely high radiation damage (10 dpa), which is unlikely achievable during a dry storage period, was also emulated through high temperature irradiation (350°C) to further test the radiation resistance of the absorber, conservatively. The irradiated specimens were characterized using HR-TEM and the average size and number density of radiation-induced He bubbles were measured from the obtained bright field (BF) TEM micrographs. Measured helium bubble sizes tend to increase with increasing system (or irradiation) temperature while decrease in their number density. Helium bubbles were found from even the lowest radiation damage specimens (0.01 dpa). Bubble coalescence was significant at grain boundaries and the irradiated specimen morphology was particularly similar with the bubble morphology observed at the interface between aluminum alloy matrix and B4C particle of the surveillance coupons. These characterized irradiated specimens will be used for the corrosion test with high-temperature humid gas to further study the irradiation-assisted degradation mechanism of the absorber in dry SNF storage system.

As the use of nuclear energy has been expanded, issues in a spent nuclear fuel management are raised. Several methods have been proposed and developed to manage spent fuels safely and efficiently. One method is to reduce environmental burden in disposal of spent fuels by decreasing volume of high-level waste. A nuclides management process (NMP) is one example. Through this novel process, it is able to separate highly mobile nuclides (ex. iodine, krypton), high thermal emission nuclides (ex. strontium, barium), and optionally, uranium from spent fuels. Since the NMP is a back-end fuel cycle technology, a reliable safeguards system should be employed in the facility. As international atomic energy agency (IAEA) recommends safeguards-by-design (SBD), it is desirable to investigate an appropriate safeguards approach at a step of technology development. Process monitoring (PM) is a complemental safeguards technology for traditional safeguards technologies which based on mass balance. PM traces nuclear materials indirectly but consecutively by using process parameters such as temperature, pressure, and flow of fluid. These parameters are obtainable by installing appropriate sensors. In a respect of SBD, PM is a promising approach to achieve the safeguards goal, the timely detection of diversion of a nuclear material. However, it is necessary to classify useful process parameters from all available signals which provided from PM in order to properly utilize PM. In this study, we investigated application methods of the PM approach to NMP. NMP consists of several unit processes in series. Firstly, we inspected a principle and a feature of each unit process. Based on the results, we evaluated applicability of the PM approach to each unit process according to effectiveness in enhancing safeguardability. Several unit processes were expected that their safeguards are able to be enhanced by using certain process parameters from PM.

Surveillance plays a crucial role in safeguards. Reviewing surveillance data requires a significant number of inspection manpower. As the number of surveillance cameras increases, the demand for such manpower is expected to grow even more. Recently, in the field of security, there has been a development of deep learning models that automatically detect abnormal events from video images, and their usage is expanding. In this study, we used an AutoEncoder-based semi-supervised learning model, which can detect unexpected abnormal events, to detect anomalies in the UCSDped2 dataset and in simulating safeguards-related event videos taken at Dry Mockup facility of KAERI. To improve the model performance, we transformed the video images into two parts: the appearance part, which are sequences of video image frames, and the motion part, which are the pixel value differences of consecutive video frames. In addition, we added memory module to the bottle neck of the AutoEncoder model, and skip connection to enhance the model performance. To evaluate the model performance, we proposed a new evaluation index, which is adequate to the video images of safeguards surveillance in addition to the widely used AUC (Area Under the ROC Curve).

Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.

For deep geological repository of the spent nuclear fuel, the fuel assemblies loaded in the storage cask are transferred to the disposal cask and the operation is performed in the fuel handling hot cell at the fuel re-packaging facility. As the fuel handling hot cell shielding is accomplished by the concrete wall and the viewing glass window, the required shielding thickness was evaluated for both materials. The ordinary concrete is applied to hot cell wall and two kinds of glasses, i.e., single layer of lead glass and double layer of lead glass and borosilicate glass, are considered for the viewing glass window. A bare spent PWR fuel assembly exposed to the environment in the hot cell was considered as the neutron and gamma radiation sources. The neutron and gamma transport calculations were performed using the MAVRIC program of the SCALE code system for the dose rate evaluation. The dose limit of 10 μSv/h is applied as the target dose to establish the required shielding thickness. The concrete wall of 94 cm thickness reduces the total dose rate to 6.9 μSv/h, which is the sum of neutron dose and gamma dose. Penetrating the concrete wall, both of the neutron dose and the gamma dose decrease constantly with shield thickness and the gamma dose is always dominant through whole penetrating distance. Single layer lead glass of 74 cm thickness reduces total dose rate to 6.2 μSv/h. Applying double layer shield glass combined of lead glass and borosilicate glass, the total dose rate reduces to 3.6 μSv/h at same shield thickness of 74 cm. Through the shield glass, gamma dose decreases rapidly and neutron dose decreases slowly compared with those for concrete wall. In result, neuron dose becomes dominant on the window glass shielding. The more efficient dose reduction of double layer glass is achieved by the borosilicate glass’s superior neutron shielding power. Thus, the use of double layer glass of lead glass and borosilicate glass is recommended for the viewing glass of the fuel handling hot cell. Finally, it is concluded that about 1 m thick concrete wall and 75 cm thick viewing glass window are sufficient for the radiation shielding of the hot cell at the spent fuel repackaging facility.

A simulation model was developed for heavy water pre-enrichment and detritiation by the Combined Electrolysis and Catalytic Exchange (CECE) process. In the CECE process, heavy water enrichment and detritiation are based on the principle that concentrated in to water phase through an isotopic exchange reaction between water vapor and hydrogen gas produced by a water electrolysis. An operational analysis for a liquid phase catalytic exchange column was carried out by the model equations, composed of a material balance and combined equilibrium relationships for a scrubbing and catalyst bed, respectively. As a result of simulation, the optimum flow ratio of water to the rising hydrogen gas in contact with the down-coming water was predicted as the key variables in the separation performance analysis at a given feed flow rate and isotopic composition. From a graphical approach based on this model, the operating conditions can be determined within the range where the operating line does not meet the combined equilibrium line before reaching the specified target concentration.