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Wood Classification of Japanese Fagaceae using Partial Sample Area and Convolutional Neural Networks
( Taufik Fathurahman ),( P. H. Gunawan ),( Esa Prakasa ),( Junji Sugiyama ) 한국목재공학회 2021 목재공학 Vol.49 No.5
Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when identification work is required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program is applied to improve the image classification results. The research focuses on the algorithm accuracy and efficiency in dealing with the dataset limitations. For this, it is proposed to do the sample selection process or only take a small portion of the existing image. Still, it can be expected to represent the overall picture to maintain and improve the generalisation capabilities of the CNN method in the classification stages. The experiments yielded an incredible F1 score average up to 93.4% for medium sample area sizes (200 × 200 pixels) on each CNN architecture (VGG16, ResNet50, MobileNet, DenseNet121, and Xception based). Whereas DenseNet121-based architecture was found to be the best architecture in maintaining the generalisation of its model for each sample area size (100, 200, and 300 pixels). The experimental results showed that the proposed algorithm can be an accurate and reliable solution.
Automatic False-Alarm Labeling for Sensor Data
Taufik Nur Adi,Hyerim Bae(배혜림),Nur Ahmad Wahid 한국컴퓨터정보학회 2019 韓國컴퓨터情報學會論文誌 Vol.24 No.2
A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as “alarm” when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.
Epi Taufik,Irma Isnafia Arief,Cahyo Budiman,Yusuf Wibisono,Alfian Noviyanto 한국축산식품학회 2022 한국축산식품학회지 Vol.42 No.3
The bioactive functions of oligosaccharides from human milk have been reported by many studies. Many of oligosaccharides isolated from colostrum and/or milk of dairy animals have been reported to have similar chemical structures with those in human colostrum and/or milk. It has been proved by several studies that the oligosaccharides with similar chemical structure shared common bioactivities. Among domesticated dairy animals, bovine/cattle, caprine/goat, and ovine/sheep are the most commonly used species to isolate oligosaccharides from their colostrum and/or milk. Several studies on the oligosaccharides from goat colostrum and milk have revealed similar properties to that of human milk and possess the highest content of sialyl oligosaccharides (SOS) as compared to other ruminants. Indonesia ranks first in Association of Southeast Asian Nations (ASEAN) for goat milk production. Therefore, goat milk is the second most consumed milk in the country. The most reared dairy goat breed in Indonesia is Etawah Grade. However, oligosaccharides from Indonesia dairy animals including goat, have not been characterized. This is the first study to characterize oligosaccharides from Indonesia dairy animals. The present study was aimed to isolate and characterize oligosaccharides, specifically SOS from the colostrum of Etawah Grade goats by using proton/1H-nuclear magnetic resonance. The SOS successfully characterized in this study were: Neu5Ac(α2- 3)Gal(β1-4)Glc (3’-N-acetylneuraminyllactose), Neu5Ac(α2-6)Gal(β1-4)Glc (6’-Nacetylneuraminyllactose), Neu5Gc(α2-3)Gal(β1-4)Glc (3’-N-glycolylneuraminyllactose), Neu5Gc(α2-6)Gal(β1-4)Glc (6’-N-glycolylneuraminyllactose), Neu5Ac(α2-6)Gal(β1-4) GlcNAc (6’-N-acetylneuraminyllactosamine) and Neu5Gc(α2-6)Gal(β1-4)GlcNAc (6’- N-glycolylneuraminyllactosamine). This finding shows that Etawah Grade, as a local dairy goat breed in Indonesia, is having significant potential to be natural source of oligosaccharides that can be utilized in the future food and pharmaceutical industries.
Dede Taufik,Mikrajuddin Abdullah,Hernawan,Suhanda Sutardi,Rifki Septawendar 한양대학교 세라믹연구소 2016 Journal of Ceramic Processing Research Vol.17 No.10
Nanocrystallines of calcia-stabilized zirconia are known to reveal excellent mechanical and high ionic conductivity propertieswhose depend on the calcia concentration. In this work, nanocrystallines of calcia-stabilized zirconia were synthesized fromzircon precursor and 7.5 weight % CaO at 1000 oC, 1200 oC, and 1400 oC. Phase transformation and microstructure evolutionwere investigated by an X-ray diffraction and a scanning electron microscopy. Another un-doped zirconia was also synthesizedfrom the local zircon by following the same procedure for comparison. A fully cubic form of the calcia-stabilized zirconia andcalcium zirconate were obtained at 1200°C having the crystallite sizes ranging from 55 to 87 nm and remained stable at1400 oC. Meanwhile, un-doped zirconia consisted of pure the monoclinic zirconia at 1200 oC and 1400 oC. High agglomerationis found in the calcia-stabilized zirconia particles at 1000 oC, whereas grain boundaries and interconnect are observed at1400 oC. The cubic crystal of zirconia has specific and different finger print characteristics in the infra-red spectrum comparedto the monoclinic zirconia.
SMEs Opportunities in Tourism Sector Based on Community Development in Banten
HER Rahmat Taufik,Ismail Lebai Othman 한국문화관광학회 2015 문화관광연구 Vol.17 No.2
The general objective of this paper is to examine how local community would react to entrepreneurial opportunities arising from tourism development in the destination. Without a doubt, that community participation in a destination is imperative in order to achieve a successful tourism development. The study is based on a model of small business opportunities in community-based tourism sector. During the economic crisis of 1998, SMEs in Indonesia were able to sustain resistance and has a chance to grow even more in the growing tourism format of community participation. The research was conducted using quantitative research to provide empirical generalizations, setting objectives, concepts, proving the theory, and developed a theory. The research subjects were 400 entrepreneurs spread across three districts using proportional stratified random sampling technique. Research data obtained using a questionnaire. The study shows that there is a significant relationship to collaboration, substitute products, promotion, acquisition and joint venture opportunities in the community. However, the inclusion of moderating variable has produced a mix results. Research shows that there is also a direct effect of community-based tourism development of SME entrepreneurial opportunities.