Limited Resource Capacity Research Articles

Peran Good Governance dalam Meningkatkan Kualitas Pelayanan Publik: Perspektif Teoretis

This study aims to explore the role of good governance in improving the quality of public services. The quality of public services is highly dependent on the implementation of good governance principles, which include transparency, accountability, public participation, and effectiveness. In this research, the approach used is a qualitative method with a literature study to analyze existing literature regarding the implementation of good governance in public services. The results show that transparency and accountability have a very significant role in improving the quality of public services. Transparency allows the public to monitor and ensure that public policies and resources are managed properly. Accountability encourages the government to be responsible for its decisions and policies, thereby increasing public trust in the government. However, the implementation of good governance also faces a number of challenges such as complex bureaucracy, corruption, and limited human resource capacity. These challenges hinder the effectiveness of public services, even though the principles of good governance have been applied.

White box specification of intervention policies for prescriptive process monitoring

Prescriptive process monitoring methods seek to enhance business process performance by triggering real-time interventions, such as offering discounts to increase the likelihood of a positive outcome (e.g., a purchase). At the core of a prescriptive process monitoring method lies an intervention policy, which determines under which conditions and when to trigger an intervention. While state-of-the-art prescriptive process monitoring approaches rely on black-box intervention policies derived through reinforcement learning, algorithmic decision-making requirements sometimes dictate that the business stakeholders must be able to understand, justify, and adjust these intervention policies manually. To address this requirement, this article proposes WB-PrPM (White-Box Prescriptive Process Monitoring), a framework that enables stakeholders to define intervention policies in business processes. WB-PrPM is a rule-based system that helps decision-makers balance the demand for effective interventions with the imperatives of limited resource capacity. The framework incorporates an automated method for tuning the parameters of the intervention policies to optimize a total gain function. An evaluation is presented using real-life datasets to examine the tradeoffs among various parameters. The evaluation reveals that different variants of the proposed framework outperform existing baselines in terms of total gain, even when default parameter values are used. Additionally, the automated parameter optimization approach further enhances the total gain.

Online Service Function Chain Planning for Satellite-Ground Integrated Networks to Minimize End-to-End (E2E) Delay.

The combination of software-defined networking (SDN) and satellite-ground integrated networks (SGINs) is gaining attention as a key infrastructure for meeting the granular quality-of-service (QoS) demands of next-generation mobile communications. However, due to the unpredictable nature of end-user requests and the limited resource capacity of low Earth orbit (LEO) satellites, improper Virtual Network Function (VNF) deployment can lead to significant increases in end-to-end (E2E) delay. To address this challenge, we propose an online algorithm that jointly deploys VNFs and forms routing paths in an event-driven manner in response to end-user requests. The proposed algorithm selectively deploys only the essential VNFs required for each Service Function Chain (SFC), focusing on minimizing E2E delay-a critical QoS parameter. By defining a minimum-hop region (MHR) based on the geographic coordinates of the routing endpoints, we reduce the search space for candidate base stations, thereby designing paths that minimize propagation delays. VNFs are then deployed along these paths to further reduce E2E delay. Simulations demonstrate that the proposed algorithm closely approximates the global optimum, achieving up to 97% similarity in both E2E delay and CPU power consumption, with an average similarity of approximately 90%.

A two-echelon multi-trip vehicle routing problem with synchronization for an integrated water- and land-based transportation system

This study focuses on two-echelon synchronized logistics problems in the context of integrated water- and land-based transportation (IWLT) systems. The aim is to meet the increasing demand in city logistics as a result of the growth in transport activities, including parcel delivery, food delivery, and waste collection. We propose two models, a novel mixed integer linear joint model, and a logic-based Benders’ decomposition (LBBD) model, for a two-echelon problem under realistic settings such as multi-trips, time windows, and synchronization at the satellites with no storage and limited resource capacities. The objective is to optimize transfers and satellite assignments, thereby reducing overall logistics costs for street vehicles and vessels. Computational experiments demonstrate that the LBBD model is more robust in terms of solution quality and solution time on average while the added value of the LBBD is more evident when solving large-scale instances with 100 customers, reducing the overall costs by 10.6% on average and significantly reducing the fleet costs on both networks. Furthermore, we assess the effect of changing cost parameters and satellite locations in the proposed IWLT system–analyzing system behavior and suggesting potential improvements–and evaluate several system alternatives in city logistics–consisting of different transportation network designs (single- and two-echelon), vehicle types, and operational constraints. On average, the proposed two-echelon IWLT system reduces the number of kilometers traveled by vehicles at street level by ranging from 20% to 30% compared to a typical single-echelon service design that relies solely on trucks.

Minimum Wage Increases And Civil Servants' Welfare In Nigeria’s Fourth Republic: An Examination Of Lagos And Osun States Civil Service

This study examines the impact of minimum wage increases on civil servants' welfare within the context of Nigeria’s Fourth Republic, focusing on Lagos and Osun States. The study employs both quantitative and qualitative methodologies, the research analyses survey data from civil servants to assess the effectiveness of minimum wage policies in addressing welfare issues. A total number of 400 questionnaires were distributed while 347 were validly returned. Findings reveal that while minimum wage increments are intended to enhance workers' living standards, challenges such as budget limitations, inflation, and administrative capacity significantly hinder their effective implementation. In Osun State, economic constraints, including delayed salary payments, were identified as key barriers. Similarly, in Lagos, where internally generated revenue is comparatively higher, responses indicate that while wage implementation is smoother, rising living costs erode purchasing power gains. The study also highlights how limited administrative capacity and inadequate resource allocation exacerbate these challenges, undermining civil servants' access to essential needs like housing, healthcare, and education. The paper concluded that the minimum wage policy in Nigeria faces barriers like inflation, budget limits, and administrative issues, underscoring the need for reforms and adjustments.It was recommended thatthe government should conduct a regular assessment of the economic and social impact of minimum wage adjustments following each five-year review. Datadriven insights into the effectiveness of wage policies that would guide future adjustments

Agile Governance Public Information Management at the Communication, Informatics, and Statistics Service of Riau Province

This study aims to analyze the implementation of agile governance in public information management at the Riau Province Communication, Informatics and Statistics Service (Diskominfotik). Agile governance is a governance approach that emphasizes flexibility, responsiveness, and rapid collaboration in providing public services. The research method used is qualitative descriptive with an explanatory approach. Data collection was carried out through observation, interviews, and document studies analyzed using Nvivo 14 software. The results of the study indicate that the implementation of agile governance at Diskominfotik Riau is still faced with a number of obstacles, including limited knowledge and capacity of human resources (HR) in understanding the concept and a bureaucratic structure that does not fully support flexibility. In addition, performance evaluations that are not yet based on quick wins slow down the adaptation process. Nevertheless, Diskominfotik Riau has utilized various digital platforms to provide access to public information, although improvements need to be made in terms of responsiveness and timeliness of service. Recommendations from this study include increasing training for HR, implementing a more flexible governance model, and periodic evaluations based on short-term results. The implementation of agile governance is expected to improve the quality of public services and strengthen public trust in government transparency.

Federated influencer learning for secure and efficient collaborative learning in realistic medical database environment.

Enhancing deep learning performance requires extensive datasets. Centralized training raises concerns about data ownership and security. Additionally, large models are often unsuitable for hospitals due to their limited resource capacities. Federated learning (FL) has been introduced to address these issues. However, FL faces challenges such as vulnerability to attacks, non-IID data, reliance on a central server, high communication overhead, and suboptimal model aggregation. Furthermore, FL is not optimized for realistic hospital database environments, where data are dynamically accumulated. To overcome these limitations, we propose federated influencer learning (FIL) as a secure and efficient collaborative learning paradigm. Unlike the server-client model of FL, FIL features an equal-status structure among participants, with an administrator overseeing the overall process. FIL comprises four stages: local training, qualification, screening, and influencing. Local training is similar to vanilla FL, except for the optional use of a shared dataset. In the qualification stage, participants are classified as influencers or followers. During the screening stage, the integrity of the logits from the influencer is examined. If the integrity is confirmed, the influencer shares their knowledge with the others. FIL is more secure than FL because it eliminates the need for model-parameter transactions, central servers, and generative models. Additionally, FIL supports model-agnostic training. These features make FIL particularly promising for fields such as healthcare, where maintaining confidentiality is crucial. Our experiments demonstrated the effectiveness of FIL, which outperformed several FL methods on large medical (X-ray, MRI, and PET) and natural (CIFAR-10) image dataset in a dynamically accumulating database environment, with consistently higher precision, recall, Dice score, and lower standard deviation between participants. In particular, in the PET dataset, FIL achieved about a 40% improvement in Dice score and recall.

A Proactive Telephonic Outreach Program to Address Unmet Social Needs of Children in Immigrant and Refugee Families at a Federally Qualified Health Center.

We developed a telephonic outreach and care coordination program for children in immigrant and refugee families (CIRF) at a federally qualified health center (FQHC) in North Carolina to address unmet health-related social needs (HRSN). Participants were recruited between December 2020 and October 2021. Eligible children were ages 0-5, non-English speaking, and were seen at the FQHC in the 2years prior. A bicultural/bilingual case manager completed telephonic outreach to caregivers of participants with HRSN screening. Bilingual patient navigators made follow-up calls to assess connection to resources and to develop strategies for addressing unmet needs. Three hundred forty-two families received outreach; 212 (62.0%) completed the baseline questionnaire. The majority (N = 160, 75.5%) completed at least one follow-up. The majority (N = 186, 88.1%) were Spanish-speaking, and over two-thirds (N = 149, 70.3%) were uninsured. Most participants had between 3-5 HRSNs identified (N = 121, 57.1%); "employment" (n = 158, 74.5%) and "food" (n = 138, 65.1%) were the most common. Despite repeated assistance, the majority of participants struggled to link to a community resource for their highest priority need (N = 123, 78.3%). Proactive phone-based HRSN screening may be a feasible and effective intervention to facilitate the identification of social needs for CIRF. The delivery of the intervention in languages other than English may have further contributed to program acceptability. Despite program feasibility and acceptability, community-level barriers to the resolution of HRSNs persist. While similar care coordination models can be considered to identify the high burden of unmet HRSN among CIRF, addressing the limited capacity of community-based resources for this population will be a critical component to ensuring the sustainability of such programs.

The importance of institutional capacity in drinking water supply system governance: A policy evaluation from border area

In most developing countries, the equal access to clean and potable water is a major challenge faced by many communities. This research aims to evaluate water supply system governance policies as well as potential springs, constraints and problems related to the water needs of border communities. This research is a descriptive study using a qualitative approach. The qualitative approach looks at policies, institutions, conflicts, and problems faced, as well as looking at data on water sources, socio-economic challenges, culture, and local wisdom. The research location was in Belu Regency, on the Indonesia-Leste Timor border. Research informants were representatives of local government, academics and the community. The problems faced are the underdevelopment of piped networks due to budget constraints, low capacity and quality of human resources, and the absence of specific regulations governing the Drinking Water Supply System (SPAM). The study area has springs spread across 11 subdistricts, with raw water potential ranging from 0.5 to 250 liters per second. Most of these water sources are good for community consumption, but some have not been optimally utilized so that they cannot be fully utilized to meet the needs of the population. The results show that SPAM management policies can be implemented to a certain extent, but have not yet run optimally because they still require capacity building and competence of the apparatus and local communities and an increase in the role of local governments to help implement central government policies in relation to assistance tasks and as a tool for deconcentration of the central government. In conclusion, the potential of raw water sources has not been fully utilized due to the challenges of infrastructure development and the limited capacity of human resources and budgets. Without good management and institutional support, communities will continue to face problems related to access to clean water.

Розвиток майнового оподаткування в окремих постсоціалістичних країнах Центральної та Східної Європи

Introduction. According to the National Revenue Strategy until 2030, the development of property taxation in Ukraine should be carried out by switching from property taxation based on the area of real estate to taxation based on its market value in order to increase local budget revenues and improve taxation fairness. Problem Statement. The introduction of taxation of real estate in Ukraine based on its value, which is a difficult task involving painstaking preparatory work and significant financial resources, requires an analysis of the experience of implementing similar transformations in other countries. At the same time, the development of property taxation in the post-socialist countries of Central and Eastern Europe (hereinafter CEE), some of which still tax real estate by area, while others immediately introduced a tax by value, is of greatest interest. The purpose of the article is to determine, based on the analysis of property taxation experience in selected CEE countries, the prerequisites and ways of transition from a tax based on area to a tax based on value. The methods of systemic, structural-functional, comparative analysis, analogies and theoretical generalization are used. Results. The article analyzes the development of property taxation in two CEE countries (Poland and Slovakia), where, like in Ukraine, the basis for recurrent taxes on real estate is its area, and three Baltic countries where ad valorem real estate taxes have been introduced. The author focuses on the prerequisites and features of their introduction, the design of taxes in individual countries, peculiarities of their administration and prospects for reform. The author draws conclusions about the common and specific reasons for delaying the introduction of ad valorem tax in countries where it is based on real estate area. The author identifies the necessary measures and reveals the problems on the way to introduction of the ad valorem real estate tax related to the creation of a sufficiently complete and reliable database on real estate and its market value and keeping it up to date, gradual introduction of mass assessment of land and property, limited administrative capacity, little experience and insufficient resources of local authorities to entrust them with the function of property tax administration.

Strategi Pengelolaan dan Pengembangan Objek Wisata Gunung Pa’baladoan pada Lembang Belau Kecamatan Masanda Kabupaten Tana Toraja

This research aims to analyze and formulate a management and development strategy for Mount Pa'baladoan tourism in Tana Toraja Regency using SWOT analysis. Qualitative research method with data collection through interviews, observation and documentation studies. The results of the SWOT analysis show that Mount Pa'baladoan has strengths in the form of natural beauty, cultural richness, accessibility and local wisdom. However, there are weaknesses such as management that is not optimal, limited human resource capacity, and promotion that is less effective. The opportunities that exist are tourism growth, government support, and ecotourism-oriented community lifestyles. Meanwhile, the threats are competition from other destinations, natural disasters, as well as the impact of globalization and cultural westernization. Based on the SWOT analysis, the Mount Pa'baladoan tourism development strategy includes SO, WO, ST and WT strategies. The implementation of these strategies is expected to increase the competitiveness and sustainability of Mount Pa'baladoan tourism development in Tana Toraja Regency

How to improve efficiency for prefabricated component production scheduling with worker allocation and order outsourcing?

Prefabricated building is an advanced building mode that is actively promoted in China owing to its high-efficiency, energy-saving and labour-saving characteristics. However, because of the limited production capacity and production resources of the final assembly parts production plant, it is usually impossible for a factory to accept all orders. Therefore, the factory will consider outsourcing part of the orders to reduce delay penalties. In addition, the allocation of workers in the production process will significantly affect the processing time of orders. Regarding those two issues, a production scheduling integrated optimization model, considering worker allocation and order outsourcing, is established to maximize net profit. To address the complexity of problem solving caused by the NP-hard nature of this problem, a hybrid improved genetic–accelerated iterative greedy search algorithm is developed. Finally, a numerical example is delivered to verify that the proposed algorithm has improved solution quality and convergence.

Medical occupational check-ups during the COVID-19 pandemic in the European Union.

Given the enormous scale of the COVID-19 pandemic affecting the healthcare sector, limited human resource capacity, and efforts to prevent the spread of COVID-19, occupational health protection could not escape changes. The aim was to identify and compare the regulations regarding the provision of medical occupational check-ups (MOCs) during the pandemic in all European Union member states (EU MS). The study employed the Delphi method, involving experts from EU MS to assess MOC regulations between January 2020 and May 2021. Experts were queried regarding the existence and specifics of MOC regulations, particularly for entrance and periodic MOCs at hazardous and non-hazardous workplaces. Out of the 27 EU MS surveyed, 13 EU MS did not regulate MOCs, while 14 EU MS (51.6%) regulated the provision of MOCs. The regulations were changes in the way MOCs were provided, modifications (postponement in time, alternative provision, e.g. using telemedicine or online connection, or replacing the medical certificate of fitness to work based on the MOC with a declaration by the worker), or interruption without compensation, even for hazardous works. The regulations were in effect for different lengths of time and varied in some countries during the study period. The cumulative duration of MOC interruptions in all EU MS during the study period was 137 months (7.5% of the cumulative study period of 1836 months). Given the different approaches to the provision of MOCs in EU MS, it has proved appropriate to develop an optimal unified framework plan for future similar situations.

Contesting the public works domain: examining the factors affecting presence and success of SMES in public procurement

This study investigates the effects of procurement tools to support small and medium-sized enterprises (SMEs) in public contracts by analysing contract awards for public works published on Tenders Electronic Daily in 2018–2022. Focusing on dividing contracts into smaller lots, a key feature of the 2014 EU modernised procurement framework, this study’s findings reveal that splitting contracts might not necessarily attract SMEs to bid but increases their chances of winning such contracts. Other factors, such as using open and unrestricted bidding procedures and allowing SMEs to showcase their specialisation by awarding contracts based on the best price-quality ratio, positively affect the SMEs’ bidding. The findings of this study emphasise the importance of thoroughly considering individual contract characteristics and overall procurement settings to accommodate SMEs’ limited resource capacities and foster their performance in the public procurement marketplace.

Scheduling optimisation of alcohol test sites

Drink driving is an infamous factor in road crashes and fatalities. Alcohol testing is a major countermeasure, and random breath tests (RBTs) deter tested drivers and passersby (observers who are not tested). We propose a genetic algorithm (GA)-based RBT scheduling optimisation method to achieve maximal deterrence of drink driving. The RBT schedule denotes the daily plan of where, when, and for how long tests should occur in the road network. The test results (positive and negative) and observing drivers are considered in the fitness function. The limited testing resource capacity is modeled by a number of constraints that consider the total duration of tests, the minimum and maximum duration of a single test site, and the total number of test sites during the day. Clustering of the alcohol-related crash data is used to estimate the matrix for drink driving on the scheduled day. The crash data and traffic flow data from Victoria, Australia are analysed and used to describe sober/drink driving. A detailed synthetic example is developed and a significant improvement with 150% more positive results and 59% more overall tests is observed using the proposed scheduling optimisation method.

FedMon: A Federated Learning Monitoring Toolkit

Federated learning (FL) is rapidly shaping into a key enabler for large-scale Artificial Intelligence (AI) where models are trained in a distributed fashion by several clients without sharing local and possibly sensitive data. For edge computing, sharing the computational load across multiple clients is ideal, especially when the underlying IoT and edge nodes encompass limited resource capacity. Despite its wide applicability, monitoring FL deployments comes with significant challenges. AI practitioners are required to invest a vast amount of time (and labor) in manually configuring state-of-the-art monitoring tools. This entails addressing the unique characteristics of the FL training process, including the extraction of FL-specific and system-level metrics, aligning metrics to training rounds, pinpointing performance inefficiencies, and comparing current to previous deployments. This work introduces FedMon, a toolkit designed to ease the burden of monitoring FL deployments by seamlessly integrating the probing interface with the FL deployment, automating the metric extraction, providing a rich set of system, dataset, model, and experiment-level metrics, and providing the analytic means to assess trade-offs and compare different model and training configurations.

Process of Confiscation of Assets Proceeding from Crime of Selling Narcotics Carried Out by the National Narcotics Agency of Aceh Province

The background of this research is that disclosing the source of funds from the sale of narcotics is very important because wealth is the weakest point of crime with the principle of criminology which states that money is the blood of crime or what is more often known as Money is the blood of the crime. Funds from crime, in this case narcotics, are often reused to grow and finance the crime itself so that the crime becomes bigger and better organized, which results in this case being the case that narcotics crime itself becomes an organized crime. The result of this research is the process of confiscation of assets resulting from sales crimes. Narcotics carried out by the Aceh BNNP is carried out through a mapping stage process. The next stage is the confiscation stage after receiving a decision that has permanent legal requirements, where the assets are in the form of cash, which is immediately deposited into the state treasury by the Prosecutor's Office as non-tax state revenue (PNBP). Meanwhile, assets in the form of securities, movable or not, tangible or not, are managed by the Ministry of Finance. Constraints faced by the Aceh BNNP in the process of returning assets from the sale of narcotics are the limited capacity of human resources investigating money laundering at the Aceh BNNP and the limited research and inquiry budget. The crime of money laundering, the implementation of MLA, takes a long time and is not optimal due to clashes between legal systems. Prevention efforts carried out by the Aceh BNNP in dealing with Narcotics Crime are through the Hard Power Approach, Soft Power Approach, Smart Power Approach and Co-Operation.

Establishing Quality and Outcome Measures for Recovery Housing: A Tiered Approach Supporting Service Evolution.

With over one-hundred thousand drug overdose deaths in 2021, substance use disorder (SUD) is a public health crisis in the United States. Medical stabilization has been the predominant focus of SUD interventions despite low levels of retention. Consequently, national quality measures for SUD care outside the clinical continuity of care are limited. The expansion of recovery support services addressing social drivers of health outside clinical settings is needed. The current SUD quality measures are not applicable nor feasible for recovery support service providers with limited resource capacities, like the estimated 17,900 recovery housing providers nationwide. Despite widespread support for recovery housing and its documented effectiveness, no universal set of measures has been developed for widespread adoption. In this brief, a matrix of quality measures are proposed to meet the needs of recovery housing providers with various capacities to support service evolution and improve equitable SUD treatment and recovery care.

Do extreme temperatures affect cognition? A short review of the impact of acute heat stress on cognitive performance of firefighters.

Research shows that exposure to high environmental temperatures can affect task performance. Theoretical explanations outline that heat is a source of stress that competes for limited-capacity resources, therefore if a task is resource-intensive, and/or if heat stress is extreme, performance will suffer. One occupation in which individuals complete demanding tasks and make difficult decisions, often in temperatures exceeding 200°C, is firefighting. Yet very little is currently known about the impact of heat stress on the cognitive functioning of firefighters. This short review summarizes the limited research in this area, focusing on studies that measured cognition of firefighters following a realistic training exercise. The findings are mixed with evidence that heat stress improves, impairs, and has no impact on cognitive functioning. While there are differences in the firefighting activities utilized, and the temperatures that participants were exposed to, it is argued that the varied findings can be attributed to the tasks used to assess cognitive processing, and the cognitive functions being measured. In accordance with the wider field of research, it is concluded that complex functioning, such as sustained attention, vigilance, and working memory is negatively impacted by acute exposure to extreme heat. Greater understanding of factors affecting cognition would inform safety practices and more research is needed to understand how and when heat stress may influence cognition in firefighting scenarios.

A flow formulation for the rolling stock maintenance scheduling problem

Rolling stock maintenance is a key issue for the railway operations. Planning cyclical maintenance activities is a fundamental aspect of maintenance management, requiring a variety of operational choices. We present a novel flow formulation approach to schedule rolling stock maintenance activities optimising both maintenance costs and train availability. The schedule takes into account cyclical maintenance activities and the decoupling between elapsed and operational time. Limited resource and depot capacity are taken into account together with operational constraints to reflect the real operations of the railway system. The proposed formulation is based on an integer linear programming (ILP) approach, which is solved using a commercial solver on randomly generated realistic instances.