Search Results (10)

The oil and gas industry is a high-risk industry because of the work, meaning that employees in this industry to be very prone to work accidents. Employees who work in isolated locations such as offshore platforms in the long term can experience mental and emotional fatigue, resulting in burnout. Therefore, this research was conducted with the aim of analyzing and identifying the influence of mental workload and burnout on safety behavior with different roster systems of 2 weeks and 3 weeks in the oil and gas industry. The researchers used several approaches to analyzing mental workload, burnout, and safety behavior using the PLS-SEM method with SMART PLS software. Based on the results obtained from the comparative analysis of the roster systems, it was concluded that the 2-week roster system is better than the 3-week one. This research can also provide information to companies regarding the level of mental workload, burnout, and their relationship with safety behavior and recommendations programs for companies to minimize the risk of accidents by paying attention to the mental health aspects of their employees. Full article

Introduction: Implant placement in the maxillary anterior area requires sufficient quantity and quality of both soft and hard tissue. In cases where soft and hard tissues are insufficient, additional regeneration using biomaterials is recommended. Treatment using bovine-derived xenograft and acellular dermal matrix (ADM) may increase bone volume and soft tissue thickness. Case and management: A 65-year-old woman sought help for discomfort and aesthetic issues with her denture, reporting missing teeth (11, 12, 13, 14, and 21) and bone volume shrinkage due to disuse atrophy. Intraoral examination revealed 1 mm gingival thickness. CBCT showed labio-palatal bone thickness of 6.0 mm, 5.8 mm, and 4.7 mm for teeth 21, 12 and 14, respectively. Implant planning and surgical guide fabrication were carried out before the surgery. Surgery included the placement of implants 3.3 mm in diameter and 12 mm in length, with the use of xenograft and ADM. Three months post-op, improvements in soft and hard tissues were observed, with a final prosthesis being a long-span implant-supported bridge. Conclusions: Disuse alveolar atrophy causes soft and hard tissue deficiency. The use of xenograft and ADM show favourable results even on a geriatric patient. Full article

This study aims to develop a novel retention method combining the retrievability of the screw retention method with the ideal occlusal table and the aesthetic capability of cement retention. Coping was developed to have lateral screw access, allowing the screw to lock the coping using lateral forces from screw tightening and friction between the tip of the screw and the sandblasted surface of an abutment. Sandblasting parameters varied based on particle size. The results show a positive correlation to surface roughness and indicate a positive correlation to retention force. The highest surface roughness and retention force result was shown by groups that were sandblasted using 686 μm of aluminum oxide. Experiments on the tightening strength of 48 subjects measured in simulated conditions similar to the assembly conditions of lateral screw retention implants resulted in a mean of 69.75 Nmm with the highest and lowest values of 120.67 Nmm and 34.67 Nmm. This result became the basis of tightening torque variation. Each group’s retention capability is measured and compared to cement-retained dental implants. The results show that the tightening torque correlates positively with retention force, with the highest average retention score showed by lateral screws retained under a tightening torque of 200 Nmm—317.87 N higher than cement-retained screws. Full article

Strengthening the learning culture and the safeguards in organizations can enhance safety and performance in preventing incidents. The effective implementation of human performance improvement and operational learning can support the organization in achieving these goals. However, there is no streamlined implementation framework that considers the alignment of strategic and tactical actions in the management system cycle to implement human performance improvement and operational learning. This paper presents an implementation framework that fills the above gaps. It consists of four steps: (1) establish/validate a strategic objective, (2) conduct an assessment, (3) develop a plan, and (4) execute the plan. The proposed framework also includes a site tour phase during operational learning as an alternative to storytelling, which has an inherent bias. This framework was tested in the land transportation system of one of Indonesia’s biggest oil producers. Full article

Icons have been widely utilized to describe and promote COVID-19 prevention measures. The purpose of this study was to analyze the preference and subjective design features of 133 existing icons associated with COVID-19 prevention measures published by the health and medical organizations of different countries. The 133 icons represent nineteen different function names, such as “Wash Hands” and “Wear Face Mask”. A total of 57 participants were recruited to perform two different tests: ranking test and subjective rating test. The ranking test was conducted to elicit the preference ranking of seven icon designs representing each function name. It was followed by a subjective rating test using 13 semantic scales on the two most preferred icons to analyze their perceived quality. Spearmen correlation was applied to derive the possible correlations between users’ rankings and the semantic scales, and Friedman’s test was also performed to determine the true difference between ranking in terms of each semantic scale to provide a fully meaningful interpretation of the data. Generally, findings from the current study showed that the image presented in the icon is the key point that affects the icons’ perceived quality. Interestingly, Spearman’s correlation analysis between preference ranking and semantic scales showed that vague–clear, weak–strong, incompatible–compatible, and ineffective–effective were the four strongest semantic scales that highly correlated with the preference ranking. Considering the significant relationships between the semantic distances and the functions, images depicted in an icon should be realistic and as close as possible to its respected function to cater to users’ preferences. In addition, the results of Spearman’s correlation and Friedman’s test also inferred that compatibility and clarity of icon elements are the main factors determining a particular icon’s preferability. This study is the first comprehensive study to evaluate the icons associated with the COVID-19 prevention measures. The findings of this study can be utilized as the basis for redesigning icons, particularly for icons related to COVID-19 prevention measures. Furthermore, the approach can also be applied and extended for evaluating other medical icons. Full article

The drivers for coastal flooding may vary from extremely high intensity and persistent rainfall, morphological factors of the coastal area, to extreme waves from the ocean. This means that the flood vulnerability of a coastal area does not solely depend on a single driver but can be a combination with others. A national standard for coastal flooding based on rainfall drivers has been developed. As an evaluation, this study aimed to develop a method for coastal flood-prone mapping by combining rainfall with tidal waves. The steps included the assessment of the coastal flood-prone areas driven by rainfall (CFR) and the coastal flood-prone areas by combined drivers (CFC), which was developed by employing the analytic hierarchy process (AHP), spatial-overlaid, weighted-scored, and logical tests. The coastal area of Mataram City on the Island of Lombok in Indonesia was selected as the study area, since it is frequently affected by flooding. The findings determined the essentiality of the CFC method for identifying flood vulnerability areas. Thus, the minimum standard for CFC parameters can be defined with climatic and land characteristic factors. Further, the findings also identified the need for expert judgment in the development of the CFC weighted score-based method. Full article

Local authorities require information on shoreline change for land use decision making. Monitoring shoreline changes is useful for updating shoreline maps used in coastal planning and management. By analysing data over a period of time, where and how fast the coast has changed can be determined. Thereby, we can prevent any development in high risk areas. This study investigated the transferability of a fuzzy classification of shoreline changes and to upscale towards a larger area. Using six sub areas, three strategies were used: (i) Optimizing two FCM (fuzzy c-means) parameters based on the predominant land use/cover of the reference subset, (ii) adopting the class mean and number of classes resulting from the classification of reference subsets to perform FCM on target subsets, and (iii) estimating the optimal level of fuzziness of target subsets. This approach was applied to a series of images to identify shoreline positions in a section of the northern Central Java Province, Indonesia which experienced a severe change of shoreline position over three decades. The extent of shoreline changes was estimated by overlaying shoreline images. Shoreline positions were highlighted to infer the erosion and accretion area along the coast, and the shoreline changes were calculated. From the experimental results, we obtained $m$ (level of fuzziness) values in the range from 1.3 to 1.9 for the seven land use/cover classes that were analysed. Furthermore, for ten images used in this research, we obtained the optimal $m$ = 1.8. For a similar coastal characteristic, this $m$ value can be adopted and the relation between land use/cover and two FCM parameters can shorten the time required to optimise parameters. The proposed method for upscaling and transferring the classification method to a larger, or different, areas is promising showing $\mathsf{\kappa }$ (kappa) values > 0.80. The results also show an agreement of water membership values between the reference and target subsets indicated by $\mathsf{\kappa }$ > 0.82. Over the study period, the area exhibited both erosion and accretion. The erosion was indicated by changes into water and changes from non-water into shoreline were observed for approximately 78 km². Accretion was due to changes into non-water and changes from water into shoreline for 19.5 km². Erosion was severe in the eastern section of the study area, whereas the middle section gained land through reclamation activities. These erosion and accretion processes played an active role in the changes of the shoreline. We conclude that the method is applicable to the current study area. The relation between land use/cover classes and the value of FCM parameters produced in this study can be adopted. Full article

This paper addresses uncertainty modelling of shorelines by comparing fuzzy sets and random sets. Both methods quantify extensional uncertainty of shorelines extracted from remote sensing images. Two datasets were tested: pan-sharpened Pleiades with four bands (Pleiades) and pan-sharpened Pleiades stacked with elevation data as the fifth band (Pleiades + DTM). Both fuzzy sets and random sets model the spatial extent of shoreline including its uncertainty. Fuzzy sets represent shorelines as a margin determined by upper and lower thresholds and their uncertainty as confusion indices. They do not consider randomness. Random sets fit the mixed Gaussian model to the image histogram. It represents shorelines as a transition zone between water and non-water. Their extensional uncertainty is assessed by the covering function. The results show that fuzzy sets and random sets resulted in shorelines that were closely similar. Kappa (κ) values were slightly different and McNemar’s test showed high p-values indicating a similar accuracy. Inclusion of the DTM (digital terrain model) improved the classification results, especially for roofs, inundated houses and inundated land. The shoreline model using Pleiades + DTM performed better than that of using Pleiades only, when using either fuzzy sets or random sets. It achieved κ values above 80%. Full article

Mapping of shorelines and monitoring of their changes is challenging due to the large variation in shoreline position related to seasonal and tidal patterns. This study focused on a flood-prone area in the north of Java. We show the possibility of using fuzzy-crisp objects to derive shoreline positions as the transition zone between the classes water and non-water. Fuzzy c-means classification (FCM) was used to estimate the membership of pixels to these classes. A transition zone between the classes represents the shoreline, and its spatial extent was estimated using fuzzy-crisp objects. In change vector analysis (CVA) applied to water membership of successive shorelines, a change category was defined if the change magnitude between two years, T1 and T2, differed from zero, while zero magnitude corresponded to no-change category. Over several years, overall change magnitude and change directions of the shoreline allowed us to identify the trend of the fluctuating shoreline and the uncertainty distribution. The fuzzy error matrix (FERM) showed overall accuracies between 0.84 and 0.91. Multi-year patterns of water membership changes could indicate coastal processes such as: (a) high change direction and high change magnitude with a consistent positive direction probably corresponding to land subsidence and coastal inundation, while a consistent negative direction probably indicates a success in a shoreline protection scheme; (b) low change direction and high change magnitude indicating an abrupt change which may result from spring tides, extreme waves and winds; (c) high change direction and low change magnitude which could be due to cyclical tides and coastal processes; and (d) low change direction and low change magnitude probably indicating an undisturbed environment, such as changes in water turbidity or changes in soil moisture. The proposed method provided a way to analyze changes of shorelines as fuzzy objects and could be well-suited to apply to coastal areas around the globe. Full article

This study presents an unsupervised fuzzy c-means classification (FCM) to observe the shoreline positions. We combined crisp and fuzzy methods for change detection. We addressed two perspectives of uncertainty: (1) uncertainty that is inherent to shoreline positions as observed from remote sensing images due to its continuous variation over time; and (2) the uncertainty of the change results propagating from object extraction and implementation of shoreline change detection method. Unsupervised FCM achieved the highest kappa (κ) value when threshold (t) was set at 0.5. The highest κ values were 0.96 for the 1994 image. For images in 2013, 2014 and 2015, the κ values were 0.95. Further, images in 2003, 2002 and 2000 obtained 0.93, 0.90 and 0.86, respectively. Gradual and abrupt changes were observed, as well as a measure of change uncertainty for the observed objects at the pixel level. These could be associated with inundations from 1994 to 2015 at the northern coastal area of Java, Indonesia. The largest coastal inundations in terms of area occurred between 1994 and 2000, when 739 ha changed from non-water and shoreline to water and in 2003–2013 for 200 ha. Changes from water and shoreline to non-water occurred between 2000 and 2002 (186 ha) and in 2013–2014 (65 ha). Urban development in flood-prone areas resulted in an increase of flood hazards including inundation and erosion leading to the changes of shoreline position. The proposed methods provided an effective way to present shoreline as a line and as a margin with fuzzy boundary and its associated change uncertainty. Shoreline mapping and monitoring is crucial to understand the spatial distribution of coastal inundation including its trend. Full article