Overhead Costs Research Articles

Estimating the cost for obstetric fistula repair in hospitals of Mozambique: a low-income country

BackgroundObstetric fistula is incident and prevalent in low-income countries. Globally, about 100,000 women develop fistula annually. In Mozambique, more than 2,000 fistulas are reported annually. A national strategy to combat obstetric fistula has been implemented in Mozambique from 2012–2020. This strategy is under review, making it opportune to generate evidence that reflects the course of the strategy implemented to subsidize/optimize the definition of priorities of the new strategy to achieve universal health coverage. In Mozambique, information on the costs incurred to treat fistula is scarce. This study aims to estimate the mean unit cost of repair/treatment of simple and complex obstetric fistula in Mozambique.MethodsWe carried out a retrospective evaluation, from the provider’s perspective, using the Ingredient and Stepdown approaches. The mean unit cost was obtained by the sum of individual and shared ingredients to treat fistula. Cost dimensions included Direct Medical Costs (personnel, drugs, and supplies), Overhead and Capital Costs (administration and capital assets’ costs, respectively). The average exchange rate was USD 1 = MZN 61.47. Data were collected in secondary, tertiary, and quaternary hospitals of Zambézia and Nampula provinces in 2021. Costs borne by patients and their families and loss of productivity were not included.ResultsThe mean cost for Simple Obstetric Fistula repair was MZN 14,937.21 (USD 243) and Complex Obstetric Fistula was MZN 21,145.68 (USD 344) per person operated. Regardless of the type of fistula, the repair cost was MZN 18,072.18 (USD 294).ConclusionWithout neglecting that prevention is better than plasty, the results show feasible levels of fistula repair costs for mobilization of funds. For the estimated 2,000 fistulas reported annually, the government needs an average MZN 36,144,360 (USD 588,000).

Analisis Penerapan Metode Activity Based Costing dalam Penentuan Harga Pokok Produksi pada UMKM Nurul Aini Mojokerto Tahun 2024

The purpose of this study was to determine and analyze the calculation of the cost of production at Nurul Aini UMKM in Mojokerto using traditional accounting and determining the cost of production based on the activity-based costing (ABC) method. This study uses a quantitative descriptive approach. Data were collected through documentation and interviews. The analysis used is quantitative descriptive analysis, which is an analysis based on decisions. The results of the study are as follows: 1. By using a traditional approach to calculate the cost of production at Nurul Aini UMKM, it was found that the raw materials used to produce motorcycle seats were 37,253,166,000, labor costs were 2,350,570,000, and factory overhead costs were 339,960,000. Thus, the cost of production of Nurul Aini UMKM in 2023 is IDR 39,943,696,000. 2) The activity-based costing system is used to calculate the COGS of Nurul Aini UMKM. To begin, the costs of activity resources must be examined. It begins by identifying and dividing activities into four levels of activity: unit level, batch-related costs, product enhancement costs, and facility enhancement costs. Next, product costs must be examined. where the cost drivers used by each product are used to limit factory overhead costs.

Penerapan Perhitungan Harga Pokok Produksi Menggunakan Metode Job Order Costing untuk Menentukan Harga Jual pada UD. Jati Makmur di Jombang

The results of the data analysis show that the Cost of Production for the order of 31 units of school desks according to UD's calculations. Jati Makmur is Rp. 4,433,000, while according to the calculation of the job order costing method of Rp. 5,557,234, the Cost of Production for the order of 31 units of school chairs is Rp. 3,002,000, while according to the calculation of the job order costing method is Rp. 4,226,234. The Cost of Production calculated using the job order costing method is higher than according to UD's calculations. Jati Makmur, this is because the job order costing method is more accurate, all costs are clearly detailed, be it direct raw material costs, direct labor costs, and overhead costs, so that there is a difference in the Cost of Production caused by UD. Jati Makmur did not detail and group the components of production costs, namely the cost of raw materials, direct labor costs, and overhead costs. An inaccurate calculation of the Cost of Production will affect the determination of profits to not be in accordance with the company's wishes.

Analisis Penentuan Harga Pokok Produksi Produk Beras dengan Menggunakan Metode Full Costing pada PT. Aldi Tana Walie

This study aims to find out the comparison between the determination of the cost of production of the full costing method and the method of determining the cost of production used by companies. The variable in this study is the cost of production using the full costing method. The population in this study is data on the calculation of the cost of production at PT. Aldi Tana Walie in 2022, while the sample in this study is data on the cost of raw materials, direct labor and factory overhead of PT. Aldi Tana Walie in 2022 which was taken with a purposive sampling technique. Data collection is used by observation and documentation techniques. Data analysis was carried out by qualitative data analysis using a descriptive approach. The results of the study show that there is a difference in the results of the calculation of the cost of production according to the company with the full costing method. The results of the study show that there is a difference in the results of calculating the cost of production according to the company with the full costing method. The cost of production according to the company's method which only calculates direct costs and indirect costs of IDR 366,236,000 while the calculation uses the full costing method of IDR 382,980,992. The difference in the amount of cost of production is because the company has not applied the full costing method in determining its cost of production so that the company is still not suitable in classifying production costs

Levelized Cost and Carbon Intensity of Solar Hydrogen Production from Water Electrolysis Using a Scalable and Intrinsically Safe Photocatalytic Z-Scheme Raceway System

The realization of an environmentally sustainable and widely-adopted hydrogen economy may require lowering hydrogen production costs of production pathways with ultra-low greenhouse gas emissions to $1/kg H2. The allocation of new or existing renewable electricity generation solely to hydrogen production remains contentious due to disputes regarding emissions accounting. Photoelectrochemical (PEC) hydrogen production technologies offer a unique solution, as hydrogen is produced directly from solar energy and water, without the need for electricity generation. However, cost projections for past photoelectrochemical designs have suggested that they are not cost competitive compared to conventional electrolysis systems manufactured at scale. Herein, we offer the first illustrative benchmark of cost and carbon intensity of hydrogen produced in a Type 2 Z-scheme photocatalytic reactor design that employs suspended semiconducting nanoparticles organized in two stacked baggies in a raceway design.To explore the near-term and future cost projection for hydrogen production via Type 2 photocatalytic Z-scheme raceways, the authors developed a bottom-up total installed capital cost model. This project cost model incorporates: 1) raceway reactor cost, derived from a Design for Manufacturing and Assembly (DFMA) process-based cost model, 2) mechanical balance of plant, including process equipment, piping, valves, and instrumentation, derived from equipment quotes, scaling, database values, and Aspen estimates; 3) electrical balance of plant, including wiring, derived from time and material cost correlations; 4) Site Preparation, focused on green field installation; and 5) Construction Overhead, including engineering, procurement, and construction (EPC) costs and project contingency. The capital cost model is fed into a Levelized Cost of Hydrogen (LCOH) discounted cash flow model that accounts for electricity and water consumption, in addition to other operating costs, including labor, maintenance, and raceway replacements.A hybrid life-cycle approach was used to develop an inventory of greenhouse gas emissions from all materials and energy flows associated with the facility life cycle. These flows are converted to emissions based on specific emission factors, or by using physical units-based input–output LCA models associated with the broader economic impacts of fuel and materials production, use, and end use.Estimates for levelized cost of hydrogen suggest that a 50 metric ton H2 per day (MTD) raceway plant can approach $2.50/kg H2 at an 8% solar-to-hydrogen efficiency with further cost improvements possible through increased performance and larger plant scales. Carbon intensity is estimated to be well under clean hydrogen targets for global warming potential of <2-4 kg CO2e/kg H2 produced. The results suggest a highly competitive and scalable technology, that justifies further experimental validation and prototyping in the field. Figure 1

Analisis Biaya Produksi Pada UMKM Kerupuk Putih Parida

Cracker MSMEs, as an important sector in the Indonesian economy, often experience sudden and unpredictable increases in raw material prices. The aim of this research is to analyze production costs with the aim of increasing operating profits in the Parida white cracker business. This research uses descriptive quantitative methods. The research sample in this study was the financial records of the Parida white cracker company. The research results show that the condition of MSMEs facing rising raw material prices is currently not increasing the selling price of raw materials. Despite increases in production costs, owners may choose to absorb some or all of the increased costs to prevent customers from switching to other competitors. All costs involved must be considered, including the costs of raw materials, labor, and factory overhead. The results of this research can be a guide for MSME owners in maintaining stable production costs. Apart from that, owners are expected to have several backup suppliers so that when raw material conditions improve, MSME owners can look for suppliers who sell lower-priced products.

Exploration of PQC-Based Digital Signature Schemes in TLS Certificates

The rapid development in quantum computers brings huge risks to traditional cryptographic systems. This paper talks about the integration of PQC-based digital signature schemes to solve challenges posed on Transport Layer Security certificates. In this paper, we give an analysis of the efficacy, security, and performance implications of various schemes in PQC—particularly lattice-based, hash-based, and multivariate polynomial-based algorithms. We detail more closely the challenges of the real deployment, directly connected with these digital signatures, considering communication overhead and computational costs. Our findings indicate that hybrid certificate chains, which integrate multiple PQC schemes, offer a feasible solution for a seamless transition to quantum-resistant standards with manageable performance trade-offs. Moreover, our study extends to the quantification of security benefits these PQC schemes provide against both quantum and classical computational attacks, underscoring their potential in enhancing the resilience of digital communication systems. This paper aims to contribute valuable insights to ongoing standardization discussions and support the broader adoption of PQC, thereby ensuring robust and future-proof security in digital communications amidst the advancing quantum computing era.

Authentication with privacy-preserving scheme for 5G-enabled vehicular networks

The 5G-enabled vehicular network is an innovative technology that has promise for intelligent transportation systems. It enables the transmitting of messages about traffic that deliver the most recent information on congestion, road conditions, and driving surroundings. The communication channel used by vehicle networks is inherently open, which unfortunately exposes the system to privacy and security concerns. To solve the problems of deploying a safe vehicular network, some academics have put forth plans. However, a number of current methods have significant computational or communication overhead costs. To solve this problem, an efficient and secure authentication with a privacypreserving (ES-APP) scheme established elliptic curve encryption is introduced. With the proposed ES-APP, the data signed and verified for vehicle-to-vehicle and vehicle-to-infrastructure modes in the 5G-based vehicular network are more effective. The ES-APP scheme’s goal is to meet the criteria for the security and privacy of the 5G-enabled automotive network. Ultimately, this work discusses the critical survey of the existing studies and the expected outcome for the ESAPP scheme and further works in the 5G-enabled vehicular network.

Analysis of Determining Cost of Production in the Sangkar Perkutut UD Galery Sangkar Mas in Dawuhan Mangli Village, Sukowono Subdistrict, Jember Regency

A company is an organization that operates with the aim of generating profits, by selling products (goods and/or services) to its customers. The cost of production is all costs related to the product or goods obtained, in which there are elements of product costs in the form of raw material costs, direct labor costs, and factory overhead costs. The selling price is the amount of compensation (money or goods) required to obtain a combination of goods or services. The method used is qualitative data and quantitative data. Calculation of the cost of production using the variable costing method. Calculation of Turtledove Cage Gallery UD. Sangkar Mas is the highest for 250 bird cages are the cost of production in January 2024.

MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks.

Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet's focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.

MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks

Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet’s focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.

SEDCPT: A secure and efficient Dynamic Searchable Encryption scheme with cluster padding assisted by TEE

Dynamic Searchable Symmetric Encryption (DSSE), which enables users to search and update encrypted data on an untrusted server without decryption, is a proven method when dealing with availability issues for outsourced data. However, the existing DSSE schemes suffer from forward and backward privacy problems. Although forward and backward privacy DSSE schemes can prevent these attacks, they still suffer from other challenges, such as count attacks, high communication overhead, and low computing efficiency. To solve the above problems simultaneously, we propose a secure and efficient dynamic searchable encryption scheme, which integrates a clustering algorithm, padding strategy, and trusted execution environments (TEE). The purpose of the scheme is to prevent count attacks while ensuring forward and backward privacy security. Our scheme also reduces the computing overhead and storage cost of the client by using TEE (e.g. Intel Software Guard Extension, Intel SGX) while maximizing the protection of client privacy. Furthermore, the scheme provides a secure hardware isolation environment for the cluster padding and search/update process to prevent malicious attacks from external software or super administrators. Finally, we provide corresponding security proofs and experimental evaluation which demonstrate both the security and efficiency of our scheme, respectively.

FurMoLi: A Future Query Technique for Moving Objects Based on a Learned Index

The future query of moving objects involves predicting their future positions based on their current locations and velocities to determine whether they will appear in a specified area. This technique is crucial for positioning and navigation, and its importance in our daily lives has become increasingly evident in recent years. Nonetheless, the growing volume of data renders traditional index structures for moving objects, such as the time-parameterized R-tree (TPR-tree), inefficient due to their substantial storage overhead and high query costs. Recent advancements in learned indexes have demonstrated a capacity to significantly reduce storage overhead and enhance query efficiency. However, most existing research primarily addresses static data, leaving a gap in the context of future queries for moving objects. We propose a novel future query technique for moving objects based on a learned index (FurMoLi for short). FurMoLi encompasses four key stages: firstly, a data partition through clustering based on velocity and position information; secondly, a dimensionality reduction mapping two-dimensional data to one dimension; thirdly, the construction of a learned index utilizing piecewise regression functions; and finally, the execution of a future range query and future KNN query leveraging the established learned index. The experimental results demonstrate that FurMoLi requires 4 orders of magnitude less storage overhead than TPR-tree and 5 orders of magnitude less than B+-tree for moving objects (Bx-tree). Additionally, the future range query time is reduced to just 41.6% of that for TPR-tree and 34.7% of that for Bx-tree. For future KNN queries, FurMoLi’s query time is only 70.1% of that for TPR-tree and 47.4% of that for Bx-tree.

PENDAMPINGAN LITERASI KEUANGAN UMKM KERANG INDAH BERBASIS ANDROID KECAMATAN SOREANG KOTA PAREPARE

MSMEs are now getting attention from the government and the general public now, because MSMEs can improve the community's economy, such as MSMEs of Kerang Indah Craftsmen in Soreang District which are able to produce various handicraft products from sea shells, but so far there are still many MSMEs that have not been able to make financial reports. able to distinguish or classify production costs such as the cost of Raw Materials, Labor Costs, and Factory Overhead Costs to make financial reports with MSME standards. The method used is Community Service, the first is observation, the second is socialization of MSME financial reports, the third is assistance in preparing financial reports, the fourth is training in preparing financial reports, evaluating whether MSME Shellfish Craftsmen are able to generate profits or losses as a shellfish craftsman business. the. The benefit of this community service is that it will gradually provide knowledge and skills in classifying production costs such as the cost of Raw Materials, Labor Costs, and Overhead Costs to make financial reports with MSME standards.

Mother-leaf-method accelerated parallel-GPU AMR phase-field simulations of dendrite growth

Parallel computing with multiple graphics processing units (GPUs) for adaptive mesh refinement (AMR) is a powerful method that improves the computational efficiency of phase-field (PF) simulations of dendrite growth. Octree-type block-structured AMR is often used in parallel computation because of its good parallelism; however, the process of filling the buffer region with physical data from adjacent blocks constitutes a major overhead cost that reduces computational performance. In this study, the mother-leaf (ML) method, which can reduce this overhead, was applied to accelerate parallel-GPU AMR PF simulations of dendrite growth. To evaluate the computational performance of the ML method, single- and parallel-GPU AMR PF simulations of dendrite growth were performed. The results show that single- and parallel-GPU AMR computations with the ML method accelerate the PF simulations of dendrite growth approximately 1.2–1.6 times and 1.2–1.4 times, respectively, compared to the conventional method without the ML method. In large-scale dendrite-growth PF simulations, such accelerations are significant for investigating various dendrite growth phenomena.

[formula omitted]: Isogeny-based Secret Handshakes with friendly communication costs

Secret handshake schemes allow members from the same organization to authenticate each other anonymously. After its proposal, various schemes have been introduced to achieve advanced privacy protection. Regrettably, all the schemes based on number theoretic assumptions are insecure under quantum computers, and the known post-quantum designs are impractical because of the overhead cost (> 10 MB). To fill the gap, we present the first isogeny-based secret handshake scheme (i.e., ISH) with a friendly communication cost (67 KB). In particular, we apply the CSI-FiSh signature scheme to generate group keys and credentials. For each zero-knowledge transcript in the credential, we generate a signature for handshake via the Fiat–Shamir paradigm, while it fails anonymous authentication. To fix the issue, we modify the Fiat–Shamir-type signature by embedding the CSIDH ephemeral private key into the challenge space. After verifying the modified signatures, two users recover the right ephemeral private key if they are in the same group, then they can negotiate a session key and authenticate each other. Our scheme is proved secure under the Group Action Inverse Problems (GAIP) in the random oracle model, and deniability, as an attractive property, also holds for ISH, enabling user’s ability to deny their interactions in the finished handshakes. Via choosing appropriate parameters, the communication cost surpasses all the existing post-quantum secret handshakes.

Analisis perhitungan harga pokok produksi dengan menggunakan metode full costing pada UKM Nona

Determination of cost of production is a method used in collecting production costs consisting of direct raw materials, direct labor, and factory overhead costs plus product inventory in the initial process and less product inventory in the final process. This study aims to determine the application of determining the cost of production using the full costing method, in UKM Nona. This method determines the cost of products which takes into account all elements of production costs consisting of raw materials, direct labor costs and factory overhead costs, both fixed and variable. The selling price can be obtained from the cost of production plus the expected profit. This research uses descriptive research method. The results of this study indicate that the calculation of the cost of production using the full costing method obtains a higher cost of goods compared to the calculation of UKM.

Are current shipbuilding cost estimation methods ready for a sustainable future? A literature review of cost estimation methods and challenges

In the fiercely competitive shipbuilding industry, precise cost estimates must be considered as they serve as a critical input for determining market prices effectively and ensuring a small profit for the shipyard. In Western Europe, where most projects are Engineering-To-Order (ETO), cost estimations are extra challenging, due to lack of similarity between projects. On top of this, cost estimations are becoming increasingly difficult in a market confronted by mounting challenges related to safety regulations, cost-effectiveness, and the pressing need to address energy conservation and environmental protection. New technologies introduce changes in nearly all aspects of shipbuilding design and construction. This article conducts a literature review, to present the state-of-the-art methods for estimating man-hours, explicitly focusing on man-hours for shipyard production, excluding overhead costs and challenges the suitability of existing systems for ETO and especially for the changes caused to ships by the energy transition. An indication is given of the practicality of each method as outlined in the literature. A solution direction, incorporating the construction process, is proposed to improve cost estimations for ETO projects in pre-contract phase.

The Demand and Drivers for Teleworking Among Back-Office Personnel After the COVID-19 Pandemic in New Zealand

Telework enables employees to work from any location other than their designated work environment with the integration of computing and telecommunication technologies. The advantages of teleworking include improved productivity and job satisfaction for employees, reduced overhead costs for employers, and decreased carbon footprint for the environment. However, the benefits and challenges of telework, especially on back-office employees in their organisations, are still not fully investigated. This project researched the demand for telework from New Zealand back-office personnel after the COVID-19 pandemic and the drivers for this need. The research used a mixed-methods approach with qualitative and quantitative approaches to achieve the research objective. A questionnaire consists of the Likert scale, open-ended, and multiple-choice questions was used to collect quantitative data. In order to get insightful qualitative information about the research question, semi-structured structured interviews were used. The findings of the research revealed that there is a significant demand for telework among the back-office employees in New Zealand, and predominantly they prefer a hybrid telework model.

Study on Leveraging Digital Tools for Enhancing Employee Engagement in Remote Work Settings

The global workforce has witnessed a transformative shift towards remote work arrangements, accelerated by advancements in digital technology and the unprecedented challenges posed by the COVID-19 pandemic. This paradigm shift has necessitated a reevaluation of traditional workplace dynamics and a greater emphasis on leveraging digital tools to facilitate remote work. With the traditional office setting no longer the norm, organizations are increasingly turning to virtual collaboration platforms, communication tools, and digital solutions to enable remote work. The rise of remote work presents both opportunities and challenges for organizations. On one hand, it offers employees greater flexibility, reduces overhead costs associated with maintaining physical office spaces, and enables access to a wider talent pool. On the other hand, remote work can lead to feelings of isolation, communication barriers, and challenges in maintaining employee engagement and productivity. Employee engagement is not just about satisfaction with the job; it's about fostering a deep connection at the emotional between employees and their work and the organization they belong to. It encompasses enthusiasm, dedication, and commitment towards organizational goals, reflecting a sense of purpose and belonging within the company. As the modern workplace undergoes a seismic shift towards remote work arrangements, maintaining and nurturing this emotional connection poses a significant challenge. Remote work offers undeniable benefits, including flexibility and cost advantages, yet it also introduces unique hurdles to sustaining employee engagement. One such challenge is the preservation of a strong team spirit across geographically dispersed members. Without the physical proximity of a traditional office, communication can become fragmented, hindering team cohesion and leaving individuals feeling isolated and uninformed. Moreover, the absence of face-to-face interactions can obscure recognition of accomplishments, leading to diminished morale and motivation among remote workers. However, the digital landscape provides an array of tools to address these challenges and cultivate a thriving remote team environment. Communication platforms, such as chat features, video conferencing, and instant messaging, bridge the geographical divide, facilitating seamless interaction and information sharing among team members. Collaboration tools, including project management software and shared documents, foster transparency and teamwork, enabling remote employees to collaborate effectively despite physical separation.