Efficient Management Research Articles

Penerapan IoT dengan Algoritma Fuzzy dan Mikrokontroler ESP32 dalam Monitoring Penyiraman

Smart farming has become a major focus in the development of modern agricultural technology. In this context, the Internet of Things (IoT) offers innovative solutions to increase productivity and efficiency in crop management. This research introduces an IoT-based plant watering monitoring system that uses a fuzzy algorithm and an ESP32 microcontroller. This system is designed to automatically regulate plant watering based on environmental conditions and plant needs. The ESP32 microcontroller acts as the brain of the system, collecting environmental data such as soil moisture, air temperature, and relative humidity. This data is analyzed using a fuzzy algorithm to determine plant watering needs in real-time. Based on the output of the fuzzy algorithm, the system automatically controls the water pump to water the plants according to the specified needs. The application of fuzzy algorithms allows the system to overcome uncertainty in plant watering decisions, especially in the face of complex variations in environmental conditions. With the adoption of IoT technology, farmers can monitor and control crop watering efficiently through web interfaces or mobile applications, even remotely. This research shows that the integration of IoT with fuzzy algorithms and ESP32 microcontrollers can be an effective solution in managing crop watering, increasing overall agricultural productivity, while reducing water and energy consumption.

Implementasi Sistem Pemberian Pakan Ikan Hias Otomatis Menggunakan Esp32 Berbasis IoT (Internet of Things)

This study aims to design and implement an automatic feeding system for ornamental fish using Internet of Things (IoT) technology, with the ESP32 microcontroller and servo motor. Given Indonesia's extensive water resources and the importance of its fisheries sector, ornamental fish farming has gained significant popularity. Fish owners often struggle with providing timely and consistent feeding. IoT technology offers an effective solution through remote connectivity. The developed system utilizes the Blynk application to schedule and monitor aquarium conditions in real-time. Test results indicate that the integration of ESP32 and the servo motor functions effectively, enabling scheduled automatic feeding. The system was tested and found to operate punctually, supporting a consistent daily feeding cycle. This study contributes to the advancement of innovative solutions in aquaculture, particularly in the application of IoT technology for more efficient and effective aquarium management.

Efficiency evaluation of waste management: A systematic literature review of DEA applications

This paper aims to implement a systematic literature review to survey the Web of Science scientific database and review papers with an emphasis on the application of Data Envelopment Analysis (DEA) in the efficiency evaluation of waste management. This approach includes the identification, screening, eligibility, and inclusion phase of the relevant papers. The article also provides a theoretical overview of waste management and the DEA methodology. Researching the Web of Science scientific database according to the keywords “waste management”, “waste disposal” and “data envelopment analysis” led to 12 full-text published papers written in English. Qualitative analysis of papers was carried out with an emphasis on the analyzed country, i.e. region, time frame, applied DEA model, and included input and output variables in the model. Research of this type complements the scientific literature on the importance of waste management and provides key guidelines to scientists, policymakers, and authorities on efficient waste management as one of the key problems of today's society.

A technical–scientific content management system on water reuse as an environmental education tool: the experience of a Portugal/Brazil partnership

ABSTRACT This study presents the Instituto Reúso de Água (IRdA) as a high-quality environmental education tool. The results measured the reach of IRdA's direct (webinars, learning series, and mentoring) and indirect (technical–scientific repository and the production of more easily assimilated data) educational actions since its conception (Period 01), operation of the platform (Period 02), and operation of IRdA (Period 03), through its digital platform and social media. The direct actions proved to be effective in disseminating knowledge, highlighting a preference for the topic ‘regulation’ and adherence to content produced in different video formats. On the other hand, the indirect actions showed that the scientific approach is less accessed due to its complex language. However, when presented into more accessible data, scientific content gains confidence and can be of great relevance for the transformation of society. The results corroborate the current trend of greater educational reach in a free and digital format to build a society truly committed to water reuse and its more efficient management.

Comparative performance analysis of large language models: ChatGPT-3.5, ChatGPT-4 and Google Gemini in glucocorticoid-induced osteoporosis

BackgroundsThe use of large language models (LLMs) in medicine can help physicians improve the quality and effectiveness of health care by increasing the efficiency of medical information management, patient care, medical research, and clinical decision-making.MethodsWe collected 34 frequently asked questions about glucocorticoid-induced osteoporosis (GIOP), covering topics related to the disease’s clinical manifestations, pathogenesis, diagnosis, treatment, prevention, and risk factors. We also generated 25 questions based on the 2022 American College of Rheumatology Guideline for the Prevention and Treatment of Glucocorticoid-Induced Osteoporosis (2022 ACR-GIOP Guideline). Each question was posed to the LLM (ChatGPT-3.5, ChatGPT-4, and Google Gemini), and three senior orthopedic surgeons independently rated the responses generated by the LLMs. Three senior orthopedic surgeons independently rated the answers based on responses ranging between 1 and 4 points. A total score (TS) > 9 indicated ‘good’ responses, 6 ≤ TS ≤ 9 indicated ‘moderate’ responses, and TS < 6 indicated ‘poor’ responses.ResultsIn response to the general questions related to GIOP and the 2022 ACR-GIOP Guidelines, Google Gemini provided more concise answers than the other LLMs. In terms of pathogenesis, ChatGPT-4 had significantly higher total scores (TSs) than ChatGPT-3.5. The TSs for answering questions related to the 2022 ACR-GIOP Guideline by ChatGPT-4 were significantly higher than those for Google Gemini. ChatGPT-3.5 and ChatGPT-4 had significantly higher self-corrected TSs than pre-corrected TSs, while Google Gemini self-corrected for responses that were not significantly different than before.ConclusionsOur study showed that Google Gemini provides more concise and intuitive responses than ChatGPT-3.5 and ChatGPT-4. ChatGPT-4 performed significantly better than ChatGPT3.5 and Google Gemini in terms of answering general questions about GIOP and the 2022 ACR-GIOP Guidelines. ChatGPT3.5 and ChatGPT-4 self-corrected better than Google Gemini.

Interaction Effects of Nutrient and Water on Crop Production System under Dry and Irrigated Agriculture System

Many areas in India, including dryland areas, are under stress from two main obstacles to agricultural output, namely, inadequate soil nutrients and a scarcity of water. In most rainfed regions, except for a few places that can conduct irrigation, low precipitation levels and their erratic distribution usually result in soil water deficiency which leads to water as well as the instances of nutritional stress. Hence, in sustainable agricultural production systems, soil water and nutrient stress are major concerns. In crop production systems, the interplay between water and nutrients might yield favourable results, contingent on the growth stages, volumes, combinations, and balance of the crops. In irrigated areas, water and nutrients have interdependent effects. Efficient water management can enhance nutrient availability and transformation in soil or fertilizers. Water boosts plant nutrient content, uptake, and overall efficiency. Water scarcity stresses plants, impeding root growth and nutrient absorption. Additionally, it has been discovered that there is typically a strong, nearly linear correlation between crop yield and nutrient and water management techniques. Water availability and nutrient efficiency are therefore intimately related. The water state of the soil should be taken into consideration when applying nutrients in a balanced manner, taking into account their types, ratios, amounts, timing, and methods, in addition to their capacity to give nutrients. Therefore, determining the best time or growth stage to add water and nutrients to various crops, as well as how water and nutrients interact, are essential for a sustainable crop production system.

Arkitekt: streaming analysis and real-time workflows for microscopy.

Quantitative microscopy workflows have evolved dramatically over the past years, progressively becoming more complex with the emergence of deep learning. Long-standing challenges such as three-dimensional segmentation of complex microscopy data can finally be addressed, and new imaging modalities are breaking records in both resolution and acquisition speed, generating gigabytes if not terabytes of data per day. With this shift in bioimage workflows comes an increasing need for efficient orchestration and data management, necessitating multitool interoperability and the ability to span dedicated computing resources. However, existing solutions are still limited in their flexibility and scalability and are usually restricted to offline analysis. Here we introduce Arkitekt, an open-source middleman between users and bioimage apps that enables complex quantitative microscopy workflows in real time. It allows the orchestration of popular bioimage software locally or remotely in a reliable and efficient manner. It includes visualization and analysis modules, but also mechanisms to execute source code and pilot acquisition software, making 'smart microscopy' a reality.

Predicting ICU Readmission from Electronic Health Records via BERTopic with Long Short Term Memory Network Approach

Background: The increasing rate of intensive care unit (ICU) readmissions poses significant challenges in healthcare, impacting both costs and patient outcomes. Predicting patient readmission after discharge is crucial for improving medical quality and reducing expenses. Traditional analyses of electronic health record (EHR) data have primarily focused on numerical data, often neglecting valuable text data. Methods: This study employs a hybrid model combining BERTopic and Long Short-Term Memory (LSTM) networks to predict ICU readmissions. Leveraging the MIMIC-III database, we utilize both quantitative and text data to enhance predictive capabilities. Our approach integrates the strengths of unsupervised topic modeling with supervised deep learning, extracting potential topics from patient records and transforming discharge summaries into topic vectors for more interpretable and personalized predictions. Results: Utilizing a comprehensive dataset of 36,232 ICU patient records, our model achieved an AUROC score of 0.80, thereby surpassing the performance of traditional machine learning models. The implementation of BERTopic facilitated effective utilization of unstructured data, generating themes that effectively guide the selection of relevant predictive factors for patient readmission prognosis. This significantly enhanced the model’s interpretative accuracy and predictive capability. Additionally, the integration of importance ranking methods into our machine learning framework allowed for an in-depth analysis of the significance of various variables. This approach provided crucial insights into how different input variables interact and impact predictions of patient readmission across various clinical contexts. Conclusions: The practical application of BERTopic technology in our hybrid model contributes to more efficient patient management and serves as a valuable tool for developing tailored treatment strategies and resource optimization. This study highlights the significance of integrating unstructured text data with traditional quantitative data to develop more accurate and interpretable predictive models in healthcare, emphasizing the importance of individualized care and cost-effective healthcare paradigms.

Labor-Saving in Order Picking- A Real Time Study Advancing Lean Operations

Purpose: Efficient warehouse operations rely heavily on optimizing order picking processes, which are known to constitute a significant portion of overall operational costs. The aim is to enhance operational efficiency and cost-effectiveness by minimizing non-value-added tasks in warehouse operations. Materials and Methods: This study investigates the transition from an Assisted-Picker model to a Solo-Picker model at a prominent 3PL service provider in India. The analysis compares two approaches for picking orders—pairing laborers versus employing a Solo-Picker—using metrics such as travel time and picking time. Findings: Results reveal that while the Assisted-Picker model may initially show faster completion times for individual orders, the Solo-Picker model proves more efficient overall. This is attributed to the elimination of idle time associated with helpers and enhanced labor utilization efficiency. Real-time productivity data collected during the study period demonstrate a remarkable 44% increase in productivity with the Solo-Picker model, resulting in substantial Labor-Savings and significant reductions in operational costs. Implications to Theory, Practice and Policy: This study highlights the critical importance of reevaluating traditional labor allocation strategies in warehouse environments. By identifying and eliminating non-value-added work, warehouses can move closer to lean and efficient supply chain management practices, ultimately enhancing overall productivity and cost-efficiency.

Nationwide Survey - What is important for a sustainable radiology?

Radiology departments with the large diagnostic devices CT and MRI contribute significantly to the overall energy consumption of health facilities. However, there is a lack of systematic knowledge about the opinions of radiological staff on the most relevant aspects of sustainability. For this reason, we conducted a comprehensive survey for radiology employees on sentiment and experiences regarding sustainability in radiology.In collaboration with the Sustainability Network of the German Roentgen Society (DRG), we developed a questionnaire on various dimensions of sustainability in radiology. We conducted a nationwide online survey of radiology employees between July 1st, 2023 and November 30th, 2023. The absolute and percentage distributions were then determined.From 109 participants, mainly doctors (67/109; 62%) from university hospitals (48/109; 44.0%), 81 out of 109 rated sustainability in professional environment (74.3%) as important or very important. However, only 38 out of 109 (38%) of the respondents were able to name specific sustainable procedures in their institute. The most important topics for a sustainable radiology were waste management (26/109, 22.6%), energy reduction (19/109, 16.5%), conscious behaviour (15/109, 13%) and reduction of obsolete examinations (14/109, 12.2%). In addition, a lack of qualifications (16%), finances (21%) and compliance (21%) were named as challenges for the implementation of sustainable actions in radiology. The perceived importance of specific, sustainable measures in radiology is generally higher than the amount of already established actions.Radiology has significant, yet untapped, potential for sustainable optimization. There is a need for qualified and sensitized health care workers in radiology who are committed to sustainability in everyday clinical practice. Among other things, in this study the respondents demand a more critical indication for diagnostic workup, including avoiding redundant examinations, and a technological progress towards energy-efficient devices, which requires a dynamic exchange between radiology, industry and health care facilities. · Of 109 respondents from radiology departments, 74.3% consider sustainability to be important or very important in a professional context.. · Waste management (22.6%), energy reduction (16.5%), conscious behaviour (13%) and reduction of obsolete or redundant examinations (12.2%) are, according to those surveyed, most important for a more sustainable radiology.. · Sustainability initiatives have been institutionally established among 38% of participants. However, key challenges to the implementation of sustainable practices in radiology include insufficient compliance from staff and patients (21%), limited access to funding (21%), and a lack of necessary qualifications (16%).. · The perceived importance of specific measures for sustainability in radiology is generally higher than the previously established measures.. · Technology & energy efficiency (59.6%), energy contracting (46.8%) and waste management (34.9%) are the areas of interest with the highest priority.. · Palm V, Wucherpfennig L, Do TD et al. Nationwide Survey - What is important for a sustainable radiology?. Fortschr Röntgenstr 2024; DOI 10.1055/a-2378-6366.

Diffraction efficiency management by complex binary gratings

The diffraction efficiencies of a complex binary diffraction grating with a rectangular profile are controlled through the steps’ phases, amplitudes, and duty cycle, based on analytical expressions. It is demonstrated that the zeroth-diffraction order can be canceled for any arbitrary value of the duty cycle, provided that a π-phase difference is imposed, along with a specific ratio of the steps’ amplitudes. This feature is not feasible for separated amplitude-only and phase-only rectangular binary gratings in the context of one-dimensional gratings. In this framework, a key analytic relationship between the duty cycle and the steps’ amplitude ratio is derived, allowing the design of such gratings with this desired feature across a wide range of conditions, not limited to a duty cycle of 0.5. Concerning the higher diffraction orders, it is proved that their intensities cancel or maximize for fixed duty cycle no matter the amplitude and phase values of the steps. The intensity of the m-th diffraction order possesses m maxima and m − 1 zeros on the full range of the duty cycle. All these features were corroborated experimentally. The broad insight of such a grating allows the design of gratings with diffraction efficiencies tailored for specific applications.

Genome-wide survey of the bipartite structure and pathogenesis-related genes of Neostagonosporella sichuanensis, a causal agent of Fishscale bamboo rhombic-spot disease

Bamboo resources have garnered significant global attention due to their excellent capacity for regeneration and high yield. Rhombic-spot disease, a substantial threat to fishscale bamboo (Phyllostachys heteroclada), is primarily caused by Neostagonosporella sichuanensis. This study first reported the genome assemblies and characteristics of two N. sichuanensis isolates using PacBio and Illumina sequencing platforms. The genomes of N. sichuanensis strain SICAUCC 16–0001 and strain SICAUCC 23–0140, with sizes of 48.0 Mb and 48.4 Mb, respectively, revealed 10,289 and 10,313 protein-coding genes. Additionally, they contained 34.99 and 34.46% repetitive sequences within AT-rich regions, with notable repeat-induced point mutation activity. Comparative genome analysis identified 1,049 contracted and 45 expanded gene families in the genome of N. sichuanensis, including several related to pathogenicity. Several gene families involved in mycotoxin metabolism, secondary metabolism, sterol biosynthesis and transport, and cell wall degradation were contracted. Compared to most analyzed necrotrophic, hemibiotrophic, and phaeosphaeriacous pathogens, the genomes of two N. sichuanensis isolates exhibited fewer secondary metabolite enzymes, carbohydrate-active enzymes, plant cell wall degrading enzymes, secreted proteins, and effectors. Comparative genomics analysis suggested that N. sichuanensis shares more similar characteristics with hemibiotrophic pathogens. Based on single carbon source tests, N. sichuanensis strains demonstrated a higher potential for xylan decomposition than pectin and cellulose. The proportion of cell wall-degrading enzyme effectors occupied a high proportion of the total effectors of the N. sichuanensis genomes. These findings provide valuable insights into uncovering the pathogenesis of N. sichuanensis toward the efficient management of rhombic-spot disease of fishscale bamboo.

Comparative effectiveness of combined biologic agents versus standard therapies in the treatment of plaque psoriasis: a retrospective analysis

IntroductionPlaque psoriasis is a persistent skin disorder that necessitates efficient management. This study investigates the therapeutic effectiveness and timeline for skin lesion resolution in plaque psoriasis patients treated with combined biologic agents compared to standard therapies.MethodsConducted retrospectively between March 2020 and March 2023, the study included 162 patients with moderate to severe plaque psoriasis. Participants were divided into two groups: the Control Group, which received standard treatments, and the Combined Biologic Agent Group, which received additional biologic therapy with secukinumab. Participants in the Control Group received standard treatments, while those in the Combined Biologic Agent Group received standard treatments plus secukinumab.ResultsThe results showed that the Combined Biologic Agent Group experienced a significantly faster onset of therapeutic effects, with an average time of 3.04 ± 2.25 days compared to 6.12 ± 2.06 days in the Control Group. Additionally, skin lesion resolution occurred more rapidly in the biologic agent group (7.04 ± 2.13 days) than in the control group (14.56 ± 4.73 days). By week 24, the Psoriasis Area and Severity Index (PASI) scores demonstrated a more substantial reduction in the biologic agent group, decreasing from 26.98 ± 11.28 to 2.48 ± 3.01, whereas the control group showed a reduction from 25.82 ± 10.47 to 10.40 ± 7.63. The overall effectiveness rate was higher in the biologic agent group, with no cases of ineffectiveness, compared to a 20.99% ineffectiveness rate in the control group. Furthermore, there was no recurrence of the disease in the biologic agent group, while the control group experienced an 11.11% recurrence rate. Both groups had a similar incidence of adverse reactions, indicating that the addition of biologic agents does not significantly increase the risk of adverse events.DiscussionThese findings suggest that combined biologic agent therapy offers a more effective and faster treatment option for plaque psoriasis without compromising safety. However, larger-scale clinical trials are necessary to validate these results and establish the long-term benefits and safety of this treatment approach in diverse patient populations.

Research on the Problems and Countermeasures of Using Management Accounting Methods to Promote the Reform of State-owned Enterprises

This paper deeply discusses how to use the power of management accounting to promote the deepening of the reform of state-owned enterprises, and proposes effective solutions to the existing problems. The reform of state-owned enterprises, as an indispensable part of China's economic map, is of great importance. Management accounting, as a mature and efficient management tool, is gradually becoming an indispensable supporting force in the reform of state-owned enterprises. This paper provides an in-depth analysis of the unique role of management accounting in the reform of state-owned enterprises. We find that by introducing management accounting concepts and methods, we can effectively optimize resource allocation, improve decision-making efficiency, and inject new vitality into the reform of state-owned enterprises. The research results of this paper are of great significance for guiding the reform practice of state-owned enterprises and improving the operating performance of state-owned enterprises. We believe that with the help of management accounting, the reform of state-owned enterprises will be able to take more solid steps and contribute more to the sustainable development of China's economy.

A Bulk versus Nanoscale Hydrogen Storage Paradox Revealed by Material‐System Co‐Design

AbstractMetal hydrides are serious contenders for materials‐based hydrogen storage to overcome constraints associated with compressed or liquefied H2. Their ultimate performance is usually evaluated using intrinsic material properties without considering a systems design perspective. An illustrative case with startling implications is (LiNH2+2LiH). Using models that simulate the storage system and associated fuel cell of a light‐duty vehicle (LDV), the performance of the bulk hydrides is compared with a nanoscaled version in porous carbon (PC), (LiNH2+2LiH)@(6‐nm PC). Using experimental material properties, the simulations show that (LiNH2+2LiH)@(6‐nm PC) counterintuitively has higher usable gravimetric and volumetric capacities than the bulk counterpart on a system basis despite having lower capacities on a materials‐only basis. Nanoscaling increases the thermal conductivity and lowers the desorption enthalpy, which consequently increases heat management efficiency. In a simulated drive cycle for fuel cell‐powered LDV, the fuel cell is inoperable using bulk (LiNH2+2LiH) as the storage material but completes the drive cycle using the nanoscale material. These results challenge the notion that nanoscaling incurs mass and volume penalties. Instead, the synergistic nanoporous host‐hydride interaction can favorably modulate chemical and heat transfer properties. Moreover, a co‐design approach considering application‐specific tradeoffs is essential to accurately assess a material's potential for real‐world hydrogen storage.

The Influence of Business Model Canvas on Financial Performance of Micro, Small, and Medium Enterprises (MSMEs)

This research aimed to analyze the influence of the nine components of Business Model Canvas (BMC) on financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Kudus Regency. BMC components included Customer Segments, Value Propositions, Channels, Customer Relationships, Revenue Streams, Key Resources, Key Activities, Key Partnerships, and Cost Structure. In addition, the data was collected from 393 MSMEs selected through purposive sampling using a quantitative method. The analysis was performed using Structural Equation Modeling (SEM) and SmartPLS 3 software. The results showed that Cost Structure had a positive and significant impact on financial performance of MSMEs out of the nine BMC components. In this context, the efficiency in cost management significantly contributed to the improvement of financial performance. Other components such as Channels, Customer Relationships, Customer Segments, Key Activities, Key Partnerships, Key Resources, Revenue Streams, and Value Propositions did not have a significant impact on financial performance. Therefore, MSMEs in Kudus Regency were expected to optimize the implementation of the components to have a greater impact on financial performance. The practical implications were that MSMEs should focus more on efficient Cost Structure management as a primary strategy to enhance financial performance.

The Factors Affecting the Small and Medium Enterprises Management in Shanghai

Administrative aspects are recognized as crucial components for the efficient functioning of the entire enterprise, especially in influencing daily operations. Each administrative link influences regular operations in different ways. At the level of decision-making, the scientific implementation of command and control is highly urgent. The optimum performance of corporate departments relies heavily on the implementation of effective decision-making processes. Although prominent leaders and principals hold significant guiding power over each department, this authority is often misunderstood. The power of leadership should not be overexerted or left unused. Instead, it should be strategically employed to foster and enhance the efficiency and productivity of each department. This study investigates the lasting impact of administrative factors on the efficiency of enterprise management. By promoting efficient administrative practices and well-informed decision-making, leaders can ensure that each department operates at its highest potential. This approach not only streamlines the enterprise's daily operations but also contributes to its long-term success and sustainability. Overall, the study highlights the intricate and essential relationship between administrative factors and enterprise management efficiency.

Investigation of cabin heating in electric vehicles with integrating solar cells and heat storage systems

In recent years, the production and usage of electric vehicles have been encouraged due to zero emissions, efficiency, and economic factors. Efficient cabin heating and thermal management in electric vehicles are crucial for enhancing passenger comfort, extending battery life, and optimizing overall energy usage, thus contributing to the sustainability and practicality of electric transportation. Heating the cabin of electric vehicles in winter has a negative effect on range. Therefore, methods are being researched to use energy efficiently without sacrificing passenger comfort and minimizing the effect on the vehicle's range. This study presents an innovative radiator design specifically crafted for Electric Vehicles (EVs), leveraging solar panels to heat water for the radiator. This system enables the vehicle to harness solar energy for heating a water tank while stationary, effectively serving as an energy storage reservoir. Upon vehicle movement, the radiator system activates to disperse the stored thermal energy throughout the cabin, ensuring superior thermal comfort. Consequently, optimizing battery range is achieved as the heating load typically leads to significant range reductions. From the obtained results in experiment 2, the results indicated that the cabin temperature rose from 3 °C to around 15 °C within a few minutes, reflecting an increase of approximately 12 °C. According to the results, this indicates that there will be a reduction in energy consumption of between 1.9 % and 3 % for a one-hour travel range in this electric vehicle. The findings of this investigation demonstrate that utilizing warm water energy storage effectively enhances cabin thermal management.

Design and Integration of Information Systems for the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta with SiHalal Ministry of Religion of the Republic of Indonesia

In the context of the globalization of the halal industry, the Halal Inspection Institute (LPH) UIN Syarif Hidayatullah Jakarta faces challenges in improving halal certification services. This research develops a web-based information system with the integration of the Indonesian Ministry of Religion's SiHalal using the REST API and Prototype model. The main goal is to increase LPH credibility, integrate the LPH system with SiHalal, and improve LPH operational management performance. The system development method used is the Prototype Model, involving data collection through observation, interviews, and literature study to understand user needs. The first stage focuses on communication to understand needs, followed by rapid planning and prototype design. System implementation using JavaScript, NodeJs, and ReactJs. After a series of tests, the system resulted in effective integration with SiHalal and more efficient operational management. The research results include three prototypes. The first prototype focused on building an LPH profile website to increase credibility and access to information. The second prototype successfully integrated the LPH system with SiHalal, ensuring the efficiency and validity of audit reports. The third prototype adds report management, income/expenditure recording, and information updates, increasing LPH's operational efficiency.

Demand-side management scenario analysis for the energy-efficient future of Pakistan: Bridging the gap between market interests and national priorities

Pakistan is facing the worst level of energy and economic crisis of its history. The underlying reason of the economic crisis is basically due to the energy crisis. Various approaches have been adopted to tackle the energy crises which the country is facing for over 2 decades. Demand-side management (DSM) is the most potent and cost-effective option to redress the energy crisis, which, unfortunately, has been the most neglected strategy in Pakistan. DSM has the potential to save up to 10.0%–15.0% of primary energy to ensure the country’s future energy security. Laws and codes do exist, but ironically, the most vital element of DSM’s policy framework and implementation mechanism is missing. Hence, the main objective of this research is to develop a DSM model for Pakistan and analyze the reference and DSM scenarios. Low-emission analysis platform (LEAP) is used to develop Pakistan’s DSM model for the study period 2021–2050. The three alternative DSM scenarios developed include energy efficiency (EEF), energy conservation (EC), and load management (LOM), and they are all analyzed. The model results estimate the electricity demand forecast of 1009.8 TWh under the reference scenario in 2050, whereas DSM tends to result in a 26.38% decreased electricity demand compared to the reference scenario. The alternative DSM scenarios also outperform the reference scenario. In 2050, the EC scenario reduces consumption by 178.0 TWh and GHG emissions by 19.20 million metric tons, the EEF scenario reduces consumption by 110.30 TWh and GHG emissions by 10.04 million metric tons, and the LOM scenario suggests reduced consumption by 101.0 TWh and GHG emissions by 6.20 million metric tons. This study concluded that the DSM must be institutionalized in Pakistan by building a robust regulatory framework and execution mechanism at the government and utility levels.