Mount Merapi eruption

Coastal areas are increasingly vulnerable to abrasion, flash floods, and seawater intrusion due to climate change and human activities. Addressing these hazards requires an integrated early warning system that enables timely and adaptive disaster mitigation. This study integrates landscape analysis, Mobile GIS technology, and the Ant algorithm into a unified early warning framework. Landscape analysis identifies geomorphological patterns and coastline changes. Mobile GIS supports real-time spatial data acquisition, while the Ant algorithm optimizes evacuation routes, sensor placement, and hazard prediction through agent-based modeling. The system incorporates spatial, topographic, oceanographic, and socio-economic data processed through spatial and computational methods. Validation using historical records and field data shows enhanced hazard detection, more efficient evacuation planning, and quicker response times. The Ant algorithm adapts routes in real time based on environmental changes. Sensor deployment is optimized for high-risk zones. Mobile GIS ensures continuous updates and spatial visualization. Real-time processing supports rapid decision-making and threat modeling. These integrated components demonstrate a strong potential to build a resilient, data-driven early warning system for coastal communities. In conclusion, the proposed system offers a precise, adaptive, and scalable approach to improve disaster preparedness in vulnerable coastal regions. Keywords: early warning system, Mobile GIS, ant algorithm, landscape analysis, coastal disaster mitigation

Potential solar energy use in the global petroleum sector

In global supply chain, the scheduling problems of large products such as ships, airplanes, space shuttles, assembled constructions, and/or automobiles are complicated by nature. New scheduling systems are often developed in order to reduce inherent computational complexity. As a result, a problem can be decomposed into small sub-problems, problems that contain independently small scheduling systems integrating into the initial problem. As one of the authors experienced, DAS (Daewoo Shipbuilding Scheduling System) has adopted a two-layered hierarchical architecture. In the hierarchical architecture, individual scheduling systems composed of a high-level dock scheduler, DAS-ERECT and low-level assembly plant schedulers, DAS-PBS, DAS-3DS, DAS-NPS, and DAS-A7 try to search the best schedules under their own constraints. Moreover, the steep growth of communication technology and logistics enables it to introduce distributed multi-nation production plants by which different parts are produced by designated plants. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. No standard coordination mechanism of multiple scheduling systems exists, even though there are various scheduling systems existing in the area of scheduling research. Previous research regarding the coordination mechanism has mainly focused on external conversation without capacity model. Prior research has heavily focuses on agent-based coordination in the area of agent research. Yet, no scheduling domain has been developed. Previous research regarding the agent-based scheduling has paid its ample attention to internal coordination of scheduling process, a process that has not been efficient. In this study, we suggest a general framework for agent-based coordination of multiple scheduling systems in global supply chain. The purpose of this study was to design a standard coordination mechanism. To do so, we first define an individual scheduling agent responsible for their own plants and a meta-level coordination agent involved with each individual scheduling agent. We then suggest variables and values describing the individual scheduling agent and meta-level coordination agent. These variables and values are represented by Backus-Naur Form. Second, we suggest scheduling agent communication protocols for each scheduling agent topology classified into the system architectures, existence or nonexistence of coordinator, and directions of coordination. If there was a coordinating agent, an individual scheduling agent could communicate with another individual agent indirectly through the coordinator. On the other hand, if there was not any coordinating agent existing, an individual scheduling agent should communicate with another individual agent directly. To apply agent communication language specifically to the scheduling coordination domain, we had to additionally define an inner language, a language that suitably expresses scheduling coordination. A scheduling agent communication language is devised for the communication among agents independent of domain. We adopt three message layers which are ACL layer, scheduling coordination layer, and industry-specific layer. The ACL layer is a domain independent outer language layer. The scheduling coordination layer has terms necessary for scheduling coordination. The industry-specific layer expresses the industry specification. Third, in order to improve the efficiency of communication among scheduling agents and avoid possible infinite loops, we suggest a look-ahead load balancing model which supports to monitor participating agents and to analyze the status of the agents. To build the look-ahead load balancing model, the status of participating agents should be monitored. Most of all, the amount of sharing information should be considered. If complete information is collected, updating and maintenance cost of sharing information will be increasing although the frequency of communication will be decreasing. Therefore the level of detail and updating period of sharing information should be decided contingently. By means of this standard coordination mechanism, we can easily model coordination processes of multiple scheduling systems into supply chain. Finally, we apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly- plant-scheduling agents, and a meta-level coordination agent. A series of experiments using the real world data are used to empirically examine this mechanism. The results of this study show that the effect of agent-based platform on coordinated scheduling is evident in terms of the number of tardy jobs, tardiness, and makespan.

Agent-based coordination framework for disruption management in a chemical supply chain

PurposeThe current National Early Warning System for Sri Lanka (NEWS: SL) was established after the devastations of the Indian Ocean Tsunami in 2004. Although early warning (EW) systems and evacuation procedures are in place, several areas which need improvements have been emphasized in recent studies carried out in the country. Therefore, this paper aims to outline the gaps in existing EW and EP related to tsunami and other coastal hazards with a special focus on the use of social media for disaster communication based on age groups.Design/methodology/approachThis study has drawn on a review of past studies carried out by the same research team to identify the scope of the study. In addition to that, a conceptual framework was developed for the use of social media in the event of a disaster. Based on this conceptual framework, an online questionnaire was administered to identify the current status of the use of social media in Sri Lanka during a disaster situation. In total, 408 responses were collected and analyzed using the binary logistic regression method to evaluate the variation of different predictors associated with the use of social media for disaster communication.FindingsFindings of the study revealed that the use of social media for disaster communication depends on the previous experience of users and their age. The gender of users does not affect the use of social media for disaster communication. Therefore, the accuracy and timeliness of disaster information distributed via social media should be improved further to enhance the use of social media for disaster communication. Moreover, the findings have highlighted unaddressed issues in areas such as governance; communication of technical agencies; evacuation and shelters; and response of the community.Originality/valueThis paper has identified key areas that need attention in the process of enhancing the use of social media for disaster communication. More use of technological platforms such as social media for receiving disaster-related information can address issues such as bottlenecks in communication, poor awareness and lack of last-mile dissemination. Furthermore, this paper has proposed recommendations for addressing the identified gaps in the overall EW mechanisms and EP pertaining to tsunamis and other coastal hazards to enhance the coastal disaster resilience in Sri Lanka.

PurposeThe study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms.Design/methodology/approachThe ABM model, developed in the Latin American context, specifically focuses on a case study of Colombia. Three coordination mechanisms (centralized, decentralized and cluster-type) have been evaluated using three performance indicators: effectiveness, efficiency and flexibility.FindingsSimulation results show that the decentralized scenario outperforms in terms of efficiency and flexibility. On the contrary, the centralized and cluster-type scenarios demonstrate higher effectiveness, achieving a greater percentage of requirements coverage during the disaster preparedness stage. The ABM approach effectively evaluates strategical coordination mechanisms based on the analyzed performance indicators.Research limitations/implicationsThis study has limitations due to the application of results to a single real case. In addition, the focus of the study is primarily on a specific type of disaster, specifically hydrometeorological events such as flash floods, torrential rains and landslides. Moreover, the scope of decision-making is restricted to key actors involved in local-level disaster management within a municipality.Originality/valueThe proposed ABM model has the potential as a decision-making tool for policies and local coordination schemes for future disasters. The simulation tool could also explore diverse geographical scenarios and disaster types, demonstrating its versatility and broader applicability for further insights and recommendations.

<strong class="journal-contentHeaderColor">Abstract.</strong> Analyses of future agricultural drought impacts require a multidisciplinary approach in which both human and environmental dynamics are studied. In this study, we used the socio-hydrologic, agent-based drought risk adaptation model ADOPT. This model simulates the decisions of smallholder farmers regarding on-farm drought adaptation measures and the resulting dynamics in household vulnerability and drought impact over time. We applied ADOPT to assess the effect of four top-down disaster risk reduction interventions on smallholder farmers' drought risk in the Kenyan drylands: the robustness of additional extension services, lowered credit rates, ex ante rather than ex post cash transfers, and improved early warnings were evaluated under different climate change scenarios. Model results suggest that extension services increase the adoption of newer low-cost drought adaptation measures while credit schemes are useful for measures with a high investment cost, and ex ante cash transfers allow the least wealthy households to adopt low-cost, well-known measures. Early warning systems are shown to be more effective in climate scenarios with less frequent droughts. Combining all four interventions displays a mutually reinforcing effect with a sharp increase in the adoption of on-farm drought adaptation measures, resulting in reduced food insecurity, decreased poverty levels, and drastically lower need for emergency aid, even under hotter and drier climate conditions. These nonlinear synergies indicate that a holistic perspective is needed to support smallholder resilience in the Kenyan drylands.

Processes involved in the palm oil industry can be categorized into three main operations; upstream operation (planting and milling), midstream operation (physical/chemical refining), and downstream operation (palm-based oleochemical processing). For the last few years, some industrial key players have emphasized a change from stand-alone operations towards an integrated manufacturing facility. This has become the basis idea for integration of palm-based production processes. It includes material integration, shared energy and utility resources and waste-to-feed utilization. Integrated process however, involves a complex network; thus, the process has to be simulated to analyze its feasibility in terms of process throughput and material, energy and utility consumption. Hence, this paper addresses the basis to simulate the integrated palm oil process using process simulator Aspen Plus V8.6 for its dynamic capabilities in adjusting process variables to meet the required capacity for a target product. This study is critical in providing a basis and overview of the typical processes in palm oil industry and the possible interrelations associated with the proposed integrated facility for palm oil-based production.

The multilayer overlay lithography process is one of the most important steps in semiconductor manufacturing. It is a multistage manufacturing process in which errors are introduced in each step, and existing errors accumulated in upstream operations cause occurrence of additional errors in downstream operations. Thus, variations in the previously deposited reference layers will also affect the overlay errors in the subsequently deposited layers. Therefore, a systematic method is needed to model the flow of overlay errors from layer to layer and to mitigate this effect using controllable process parameters. In this paper, a stochastic model for the introduction, accumulation and propagation of multilayer overlay errors of the lithography process is proposed. Based on that model, a sequential optimization method is utilized to find the optimal adjustments of controllable process parameters for minimizing the total multilayer overlay errors. A number of simulation case studies are presented to demonstrate the newly introduced model-based approach to controlling the multilayer overlay errors in lithography processes.

Oil &amp; Gas industries are continuously striving to increase production capacities, achieving cost efficiencies, and venturing in technically challenging areas to maintain their respective market shares. Efficiency in Upstream operations with reduction in production costs, with high focus on safety and asset integrity remains a challenge. Similarly stretching the margin of refined barrel of oil, expanding petrochemical production, developing new high value products to meet growing demand and increasing refining capacity drives operation excellence in downstream operations. Operations of aged faculties in harsh environmental conditions creates challenging operating conditions for any Oil &amp; Gas operator. In the Oil and Gas industry, both onshore and offshore, there are large amounts of hazardous chemicals on drilling or production sites and major incidents resulting in loss of primary containments (LoPC) in Oil &amp; Gas industries from both Upstream &amp; Downstream segments has enhanced focus on asset integrity, process safety and operational excellence. Several types of processes, in the oil and gas industry, have the potential for chemical releases and associated fire, safety, and health hazards due to the nature of these releases. These losses may result in asset damage, occupational injuries, environmental impact, and loss of production and or company reputation. Process safety is a combination of engineering and management controls aimed to prevent catastrophic incidents and near misses, such as structural collapse/damage, fire &amp; explosions, releases of energy or hazardous substances such as chemicals and petroleum products. All such failures were subjected to incident investigation process, aimed to identify root causes of the event and recommending corrective actions to prevent recurrence of such events in future. A critical review of over Fifty (50) process safety events (PSE), both in Upstream and Downstream segments, was undertaken and findings &amp; causes of these events were mapped with Center for Chemical Process Safety (CCPS) Process Safety Elements &amp; Pillars to assess the strength of process safety barriers. Data indicates that Inadequate Identification of Worksite/Job Hazards (under category of Management Supervision/ Employee Leadership) was the topmost root cause of process safety incidents representing 26% of all root causes. It represented inadequacies in task risk assessment where a particular risk was not identified or identified risk was not effectively controlled. Approximately half (55%) of incident causes were under themes of Hazard Identification &amp; Risk Analysis, Auditing, Asset Integrity and Reliability. This novel approach to prevent process safety incidents by integrating &amp; strengthening process safety &amp; operation excellence frameworks in Upstream &amp; Downstream segments of Oil &amp; Gas operations will be assist in preventing incidents and is adaptable by other operators and companies.

Though the question of the determinants of workgroup performance is one of the most central in organization science, precise theoretical frameworks and formal demonstrations are still missing. In order to fill in this gap the COD agent-based simulation model is here presented and used to study the effects of task interdependence and bounded rationality on workgroup performance. The first relevant finding is an algorithmic demonstration of the ordering of interdependencies in terms of complexity, showing that the parallel mode is the most simplex, followed by the sequential and then by the reciprocal. This result is far from being new in organization science, but what is remarkable is that now it has the strength of an algorithmic demonstration instead of being based on the authoritativeness of some scholar or on some episodic empirical finding. The second important result is that the progressive introduction of realistic limits to agents’ rationality dramatically reduces workgroup performance and addresses to a rather interesting result: when agents’ rationality is severely bounded simple norms work better than complex norms. The third main finding is that when the complexity of interdependence is high, then the appropriate coordination mechanism is agents’ direct and active collaboration, which means teamwork.

We proposed and experimentally demonstrated a novel point-to-point (P2P) coherent optical link based on optical frequency comb and injection-locking optical process, featuring single wavelength and wavelength division multiplexing (WDM) full-duplex coherent transmission over a fiber link up to 100-km distance. With light sources and local oscillators that are injection locked to an optical frequency comb, simultaneous down-stream and up-stream operations at the same wavelength using full-duplex coherent optical transceivers have been experimentally demonstrated.

Manufacturing lines operating under high demand and constrained resources require systematic load planning to achieve timely delivery and efficient utilization of available capacity. In multi-stage production systems, imbalance between upstream and downstream operations often leads to bottlenecks, excessive Work-in-Process (WIP) inventory, and dependence on overtime. This study presents a computational load planning and capacity analysis of a Two-Wheeler Rocker Arm (TWRA) manufacturing line using actual shop-floor data. Python-based computational programs were developed to evaluate daily and weekly production capacity, identify bottleneck stations, quantify demand gaps, and estimate buffer inventory under different operating scenarios, including normal working hours, demand-gap-based selective overtime, and extended overtime configurations. The results demonstrate that line throughput is governed primarily by downstream bottlenecks rather than total installed capacity and that targeted overtime at critical stations effectively bridges demand gaps. The proposed computational framework provides a transparent and repeatable decision-support tool for capacity planning and continuous improvement in multi-stage manufacturing systems.

Aim: This paper examines the concepts of oil and gas production, effects of the operations on the environment and relevant environmental protection technologies to make the industry a sustainable one. Problem Statement: Reports show environmental pollution and ecosystem disruption emanating from oil and gas operations which are majorly exploration, production and distribution to end-users. This makes the environment to be unhealthy for living and causes breakage in food chain. Significance of Study: High relevance of oil and gas industry to the economic growth of a Nation has made it imperative to critically address the adverse effects attributed to the operations involved. Tackling the accorded problems via current environmental protection technologies will prevent operational accidents and minimize environmental pollution. With this, lives are protected, environment is kept safe, and the industry is enhanced for future sustainability. Discussions: The upstream, midstream and downstream operations that make up the oil and gas value chain were discussed. The philosophy of sustainability and sustainable development as pertained to environmental pollution and disruption of ecosystem by the operations of oil and gas industries were discussed. Reasons why round table talk should be conducted from time to time by all stakeholders as related to environmental sustainability of Oil and Gas industries in years to come were discussed. The adopted technologies to ensure there is safety and environmental protections were stated within. Conclusion: In conclusion, there is need for further research on effective technologies to improve the existing ones in terms of making safety and environmental protection from oil and gas industry a sustainable one.

Application of Hydrophobic Membranes for Hydrogen Sulfide Removal from Sour Water