Identification of Adaptive Capacity Assessments to Improve Collective Adaptation of Farmers to Climate Change

Collective adaptation is a relevant discussion in association with the limited adaptive capacity of farmers to deal with climate change. This study aims to improve the collective adaptation of farmers through the identification of adaptive capacity assessments. A collective adaptation mechanism in the form of planning for rice planting time has succeeded in reducing the vulnerability of farmers. This study was conducted at a rice production center with a collective adaptation mechanism in Indramayu District, West Java Province, Indonesia. The data were collected using a quantitative method through a questionnaire distributed to 296 farmer respondents and a qualitative method through structured interviews. The observations provided an overview for authors to build structured interviews. The results of the study show that the adaptive capacity of farmers is supported by social capital and collective adaptation mechanisms of farmers consisting of trust in the formal leaders, quality of collective decisions, and planning capacity. The results of this study contribute to the implementation of public policies in order to support the successful implementation of adaptation strategies to deal with climate change in accordance with the needs of farmers.

Modular Robotic Limbs for Astronaut Activities Assistance

In order to meet the assist requirements of extravehicular activity (EVA) for astronauts, such as moving outside the international space station (ISS) or performing on-orbit tasks by a single astronaut, this paper proposes an astronaut robotic limbs system (AstroLimbs) for extravehicular activities assistance. This system has two robotic limbs that can be fixed on the backpack of the astronaut. Each limb is composed of several basic module units with identical structure and function, which makes it modularized and reconfigurable. The robotic limbs can work as extra arms of the astronaut to assist them outside the space station cabin. In this paper, the robotic limbs are designed and developed. The reinforcement learning method is introduced to achieve autonomous motion planning capacity for the robot, which makes the robot intelligent enough to assist the astronaut in unstructured environment. In the meantime, the movement of the robot is also planned to make it move smoothly. The structure scene of the ISS for extravehicular activities is modeled in a simulation environment, which verified the effectiveness of the proposed method.

Integrated facility location and capacity planning under uncertainty

We address a multi-period facility location problem with two customer segments having distinct service requirements. While customers in one segment receive preferred service, customers in the other segment accept delayed deliveries as long as lateness does not exceed a pre-specified threshold. The objective is to define a schedule for facility deployment and capacity scalability that satisfies all customer demands at minimum cost. Facilities can have their capacities adjusted over the planning horizon through incrementally increasing or reducing the number of modular units they hold. These two features, capacity expansion and capacity contraction, can help substantially improve the flexibility in responding to demand changes. Future customer demands are assumed to be unknown. We propose two different frameworks for planning capacity decisions and present a two-stage stochastic model for each one of them. While in the first model decisions related to capacity scalability are modeled as first-stage decisions, in the second model, capacity adjustments are deferred to the second stage. We develop the extensive forms of the associated stochastic programs for the case of demand uncertainty being captured by a finite set of scenarios. Additional inequalities are proposed to enhance the original formulations. An extensive computational study with randomly generated instances shows that the proposed enhancements are very useful. Specifically, 97.5% of the instances can be solved to optimality in much shorter computing times. Important insights are also provided into the impact of the two different frameworks for planning capacity adjustments on the facility network configuration and its total cost.

The Aging Workforce Management in Business Sectors

Background: Aging society affects good planning in workforce management for sustainable business running. Workforce management is not only the duty of human resources but also promotes the strategy for effective management. Objectives: The objective of this study is to analyze the aging workforce management in business sectors. Method: The research reviews relevant literature and, based on the evidence of theories about age-diverse management, creates a framework related to antecedent factors and the following factors. The testing applied the CBSEM model with a sample group of 300 respondents. Result: The result found that planning “capacity in the workplace” and “knowledge management” are two factors that affect the potential corporate reputation efficiency of an organization significantly via “cultural value” and “social value” which were completely transformational. Conclusion: The result of the study regarding the theory evidence and support research from overseas has a problem in applying to practice with an empirical result that differs locally. Therefore, the model needs to be verified with the local data, and develop a suitable model.

Pelatihan perencanaan pembangunan bagi aparatur desa di Desa Baumata Utara Kecamatan Taebenu Kabupaten Kupang

The village development planning is a routine activity carried out in order to carry out development. Activities that involve many parties (stakeholders) include all members of the community and village apparatus. One of the demands is that it requires planning skills from village apparatus, their capacity is needed in order to anticipate and interpret various development programs according to the demands and needs of the community by utilizing the potential and resources available in the village. The fact indicate that the planning capacity of the apparatus is still not optimal, the indication is that the Proposed list of village development activity plans (DURK-Desa) does not reflect the potential and needs of the village. Planning training for village apparatus aims to provide planning insights so that in the end they can carry out planning functions effectively. The method used in development planning training for village apparatus is the education method, in which village apparatus are given training to be able to apply village development planning analysis techniques with courses; (1) analysis of village potential; (2) SWOT analysis and; (3) formulation of alternative proposals for village development planning. To determine the success of the training, a success evaluation method was made, namely the method; (1) program evaluation; (2) evaluation of results and; (3) final evaluation of activities. The based on the evaluation of planning training, village apparatus have been able to carry out various activities, including; carry out a simple analysis of the potential for village development; SWOT analysis on village development planning and; able to formulate various alternative proposals for village development programs / projects based on the potential and problems faced by the community. Keywords: Development planning, competence, capacity

Competitive state of movements during planning predicts sequence performance

Sequence planning is an integral part of motor sequence control. Here, we demonstrate that the competitive state of sequential movements during sequence planning can be read out behaviorally through movement probes. We show that position-dependent differences in movement availability during planning reflect sequence preparedness and skill but not the timing of the planned sequence. Behavioral access to the preparatory state of movements may serve as a marker of sequence planning capacity.

Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods

In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources.