Search results for: Fuji Foo

Authors: Dong Xie, Jun Zhao, Yiming Weng

Abstract:

One of the challenges in dental cement biomaterials is how to make a restorative with mechanical strengths and wear resistance that are comparable to contemporary dental resin composites. Currently none of the dental cement restoratives has been used in high stress-bearing sites due to their low mechanical strengths and poor wear-resistance. The objective of this study was to synthesize and characterize the poly(alkenoic acid)s with different molecular structures, use these polymers to formulate a dental cement restorative, and study the effect of molecular structures on reaction kinetics, viscosity, and mechanical strengths of the formed polymers and cement restoratives. In this study, poly(alkenoic acid)s with different molecular structures were synthesized. The purified polymers were formulated with commercial Fuji II LC glass fillers to form the experimental cement restoratives. The reaction kinetics was studied via 1HNMR spectroscopy. The formed restoratives were evaluated using compressive strength, diametral tensile strength, flexural strength, hardness and wear-resistance tests. Specimens were conditioned in distilled water at 37 oC for 24 h prior to testing. Fuji II LC restorative was used as control. The results show that the higher the arm number and initiator concentration, the faster the reaction was. It was also found that the higher the arm number and branching that the polymer had, the lower the viscosity of the polymer in water and the lower the mechanical strengths of the formed restorative. The experimental restoratives were 31-53% in compressive strength, 37-55% in compressive modulus, 80-126% in diametral tensile strength, 76-94% in flexural strength, 4-21% in fracture toughness and 53-96% in hardness higher than Fuji II LC. For wear test, the experimental restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional wear depths of Fuji II LC in each wear cycle. The aging study also showed that all the experimental restoratives increased their strength continuously during 30 days, unlike Fuji II LC. It is concluded that polymer molecular structures have significant and positive impact on mechanical properties of dental cement restoratives.

Keywords: dental materials, polymers, strength, biomaterials

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Authors: Dong Xie, Yuling Xu, Leah Howard

Abstract:

Secondary caries is found to be one of the main reasons to the restoration failure of dental restoratives. To prevent secondary caries formation, dental restoratives ought to be made antibacterial. In this study, a natural fruit component furaneol was tethered onto polyacid, the formed polyacid was used to formulate the light-curable glass-ionomer cements, and then the effect of this new antibacterial compound on compressive strength (CS) and antibacterial activity of the formed cement was evaluated. Fuji II LC glass powders were used as fillers. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed cement. The experimental cement showed a significant antibacterial activity, accompanying with an initial CS reduction. Increasing the compound loading significantly decreased the S. mutans viability from 5 to 81% and also reduced the initial CS of the formed cements from 4 to 58%. The cement loading with 7% antibacterial polymer showed 168 MPa, 7.8 GPa, 243 MPa, 46 MPa, and 57 MPa in yield strength, modulus, CS, diametral tensile strength and flexural strength, respectively, as compared to 141, 6.9, 236, 42 and 53 for Fuji II LC. The cement also showed an antibacterial function to other bacteria. No human saliva effect was noticed. It is concluded that the experimental cement may potentially be developed to a permanent antibacterial cement.

Keywords: antibacterial, dental materials, strength, cell viability

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Authors: Fuji Astuti, Helen Onyeaka

Abstract:

The aim of the study was to investigate the combine effects of cinnamaldehyde (0.25 and 0.45% v/v) on thermal resistance of pathogenic Escherichia coli during low temperature long time (LT-LT) cooking below 60℃. Three different static temperatures (48, 53 and 50℃) were performed, and the number of viable cells was studied. The starting concentrations of cells were 10⁸ CFU/ml. In this experiment, heat treatment efficiency for safe reduction indicated by decimal logarithm reduction of viable recovered cells, which was monitored for heating over 6 hours. Thermal inactivation was measured by means of establishing the death curves between the mean log surviving cells (log₁₀ CFU/ml) and designated time points (minutes) for each temperature test. The findings depicted that addition of cinnamaldehyde exhibited to elevate the thermal sensitivity of E. coli. However, the injured cells found to be well-adapted to all temperature tests after certain time point of cooking, in which they grew to more than 10⁵ CFU/ml.

Keywords: cinnamaldehyde, decimal logarithm reduction, Escherichia coli, LT-LT cooking

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Authors: Shunichiro Morishita

Abstract:

This study examines the factors for attracting foreign guests in the Japanese lodging industry and discusses some measures taken for accepting foreign guests. It reviews three different accommodation providers acclaimed highly by foreign guests, Yamashiroya, Sawanoya and Fuji-Hakone Guest House, and identifies their characteristics. The common points for attracting foreign guests were: 1) making the best use of the old facilities, 2) multilingual signs, guidance and websites, 3) necessary and sufficient communication in English, 4) events and opportunities to experience Japanese culture, 5) omotenashi, warm and homely Japanese hospitality. These findings indicate that foreign guests’ dissatisfaction level can be decreased through internationalization utilizing ICT and by offering multilingual support. On the other hand, their satisfaction level can be increased by encouraging interaction with other guests and local Japanese people, providing events and opportunities to experience Japanese culture and omotenashi, home-style Japanese hospitality.

Keywords: hospitality management, foreign guests, Japanese lodging industry, Omotenashi

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

Abstract:

Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

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Authors: Yulinda Rizky Pratiwi, Fuji Anugrah Emily

Abstract:

Management of Occupational Safety and Health (OSH) are appropriately applied properly by all workers and pekarya in the company. K3 management application also has become very important to prevent accidents. Violation of the rules regarding the K3 has often occurred from time to time. By 2015 the number of occurrences of a violation of the K3 or so-called unsafe action tends to increase. Until finally in January 2016, the number increased drastically unsafe action. Trigger increase in the number of unsafe action is a decrease in the quality of management practices K3. While the application of K3 management performed by each individual thought to be influenced by the attitude and observation guide the actions of each of the individual. In addition to the decline in the quality of K3 management application may result in increased likelihood of accidents and losses for the company as well as the local co-workers. The big difference in the number of unsafe action is very significant in the month of January 2016, making the company Pertamina as the national oil company must do a lot of effort to keep track of how the implementation of K3 management on every worker and pekarya, one at PT Pertamina EP Cepu Field Asset IV. To consider the effort to control the implementation of K3 management can be seen from the attitude and observation guide the actions of the workers and pekarya. By using Multiple Linear Regression can be seen the influence of attitude and action observation guide workers and pekarya the K3 management application that has been done. The results showed that scores K3 management application of each worker and pekarya will increase by 0.764 if the score pekarya worker attitudes and increase one unit, whereas if the score Reassurance action guidelines and pekarya workers increased by one unit then the score management application K3 will increase by 0.754.

Keywords: occupational safety and health, management of occupational safety and health, unsafe action, multiple linear regression

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Authors: Farid Yuristiawan, Aulina R. Rahmi, Detty Iryani, Gunawan

Abstract:

Glass ionomer cement is one of the filling material that often used in the field of dentistry because it is relatively less expensive and mostly available. Surface hardness is one of the most important properties of restoration material; it is the ability of material to stand against indentation, which is directly connected to the material compressive strength and its ability to withstand abrasion. The higher surface hardness of a material means it is better to withstand abrasion. The existence of glass ionomer cement in the mouth makes it susceptible to any substance that comes into mouth, one of them is mouthwash which is a solution that used for many purposes such as antiseptic, astringent, to prevent caries, and bad breath. The presence of alcohol in mouthwash could affect the properties of glass ionomer cement, surface hardness. Objective: To determine the comparison of surface hardness of glass ionomer cement which soaked in alcohol containing mouthwash and alcohol-free mouthwash. Methods: This research is a laboratory experimental type study. There were 30 samples made from GC FUJI IX GP EXTRA and then soaked in artificial saliva for the first 24 hours inside incubator which temperature and humidity were controlled. Samples then divided into three groups. The first group will be soaked in alcohol-containing mouthwash; second group will be soaked alcohol-free mouthwash and control group will be soaked in artificial saliva for 6 hours inside incubator. Listerine is the mouthwash that was used on this research and surface hardness was examined using Vickers Hardness Tester. The result of this research shows mean value for surface hardness of the first group is 16.36 VHN, 24.04 VHN for second group, and 43.60 VHN for control group. The result one way ANOVA with post hoc Bonferroni comparing test show significant results p = 0.00. Conclusions: The data showed there were statistically significant differences of surface hardness between each group, which surface hardness of the first group is lower than the second group, and both surface hardness of the first (alcohol mouthwash) and second group (alcohol-free mouthwash) are lowered than control group (p = 0.00).

Keywords: glass ionomer cement, mouthwash, surface hardness, Vickers hardness tester

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

Abstract:

In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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