Inefficient Practices Research Articles

Explaining the stakeholders’ perspectives about urban regeneration policy: a grounded theory study in downtown Tabriz city, Iran

ABSTRACT In recent decades, urban regeneration has become increasingly important as a policy focusing on inner cities and deteriorated urban areas in the Global South. This policy consists of multiple stakeholders involved in its process, which requires profound research to solve acute problems and modify inefficient practices. Therefore, the current paper’s primary purpose is to explain stakeholders’ attitudes about urban regeneration in downtown Tabriz (Iran) as a second-tier middle eastern city based on grounded theory. Data collection was conducted through semi-structural interviews with 32 key stakeholders in the study area. The coding steps were also categorized using Atlas.ti software. Results indicate that the main forces, sub-factors and contextual conditions have been behind urban regeneration. Furthermore, gentrification and technocracy were recognized as the dominant approach in downtown Tabriz city. Consequently, by interpreting and reflecting on conceptual categories, “rent-oriented, growth-based and unbalanced regeneration” was called a core phenomenon.

Sistem Otomatisasi Pemberian Pakan secara Terjadwal untuk Pembibitan Ikan Lele di Fardu Farm Pekanbaru menggunakan PLC dan IoT

<p><strong>With the increasing global population growth, the demand for fishery products, including catfish, continues to rise. Catfish seed production plays a crucial role in the fisheries production chain, as this stage ensures the availability of high-quality fish seeds. However, fish farmers still face challenges in increasing aquaculture production, especially regarding inefficient manual feeding practices. This research aims to develop an automated catfish feeding system on a schedule at Fardu Farm using a combination of Programmable Logic Controller (PLC) and Internet of Things (IoT) technologies. In this study, the researchers design and implement an automation system that enables scheduled feeding in catfish seedlings. The use of Outseal PLC connected to IoT allows for precise and efficient feeding control. This research conducts testing to verify the system's performance, including measuring the weight of the feed dispensed and testing feeding over specific time periods. The results of the study indicate that this automation system successfully provides timely feeding according to the established schedule. Additionally, manual control using the Blynk platform also yields good responsiveness. Thus, the developed system can enhance efficiency in feeding catfish seedlings at Fardu Farm.</strong></p><p><strong><em>Keywords</em></strong> - <em>Automation, Feeding, Catfish Breeding, PLC, IoT.</em></p>

IMAGE PROCESSING-DRIVEN DEEP LEARNING MODEL FOR PLANT DISEASE DETECTION TO ENHANCE IRRIGATION EFFICIENCY IN SMART AGRICULTURE

In the era of smart agriculture, efficient irrigation management is crucial for optimizing crop yield and resource use. Traditional methods of plant disease detection often rely on manual inspection, which is time-consuming and prone to errors. Smart agriculture leverages technology to improve agricultural practices. Accurate and timely plant disease detection is vital for effective irrigation management and overall crop health. Current methods are limited by their manual nature and inability to process large volumes of data quickly. Manual plant disease detection is labor-intensive and may not provide timely information, leading to inefficient irrigation practices. This inefficiency can result in reduced crop yield and wasted resources. LeNet integrates advanced image processing techniques with a deep learning architecture tailored for plant disease detection. The model utilizes convolutional neural networks (CNNs) to analyze plant leaf images, identifying disease patterns with high precision. LeNet incorporates preprocessing steps such as image normalization and augmentation to enhance model robustness. The network is trained on a comprehensive dataset of plant disease images, employing transfer learning to leverage pre-trained weights for improved accuracy. Evaluation of LeNet on a test dataset comprising 10,000 images demonstrated an impressive accuracy of 92.5%, with a precision of 90.3% and recall of 94.1%. The model significantly outperforms traditional methods, reducing disease detection time by 60% and enhancing irrigation efficiency by 30%. The reduction in water usage and increased crop yield were observed in practical trials.

Secure environmental, social, and governance (ESG) data management for construction projects using blockchain

Environmental, social, and governance (ESG) considerations are increasingly becoming imperative and obligatory across various industries. The ESG performance within the architecture, engineering, and construction (AEC) industry is under heightened market scrutiny. However, current ESG management in construction is still in its infancy due to two limitations: (1) a deficiency in ESG knowledge, such as indicators pertinent to construction activities, and (2) a lack of data security in ESG management, culminating in inefficient and unreliable environmental management practices. Therefore, this paper employs the Design Science Research Method (DSRM) to introduce a Blockchain-ESG Integrated (BESGI) framework, facilitating traceable ESG data management within construction projects. This framework presents three significant contributions. First, it identifies ten AEC-ESG indicators by analyzing ESG methods. Second, it proposes a mapping approach for AEC-ESG indicators to construction projects for key ESG information access and data source identification. Third, it develops a blockchain-based data management mechanism for traceable ESG data management in the BESGI framework. It validates and evaluates the framework in a construction project in Hong Kong. The results show that the framework is usable and can save labor costs by 20.15 % compared to traditional ESG management. This study offers a secure data management solution for ESG analysis of construction projects.

Current paradigms and future challenges in harnessing gut bacterial symbionts of insects for biodegradation of plastic wastes.

The ubiquitous incorporation of plastics into daily life, coupled with inefficient recycling practices, has resulted in the accumulation of millions of metric tons of plastic waste, that poses a serious threat to the Earth's sustainability. Plastic pollution, a global problem, disrupts the ecological balance and endangers various life forms. Efforts to combat plastic pollution are underway, with a promising avenue being biological degradation facilitated by certain insects and their symbiotic gut microorganisms, particularly bacteria. This review consolidates existing knowledge on plastic degradation by insects and their influence on gut microbiota. Additionally, it delves into the potential mechanisms employed by insects in symbiosis with gut bacteria, exploring the bioconversion of waste plastics into value-added biodegradable polymers through mineralization. These insights hold significant promise for the bio-upcycling of plastic waste, opening new horizons for future biomanufacturing of high-value chemicals from plastic-derived compounds. Finally, we weigh the pros and cons of future research endeavors related to the bioprospection of plastic-degrading bacteria from underexplored insect species. We also underscore the importance of bioengineering depolymerases with novel characteristics, aiming for their application in the remediation and valorization of waste plastics.

Workforce nurturing: an approach to improving wellbeing, burnout and professional fulfilment among Australian doctors.

To assess the workplace drivers of professional fulfilment, burnout and perceived impact of workplace issues on wellbeing in doctors working in a regional Australian hospital, following a 6-month period of comprehensive workforce nurturing strategies. An online cross-sectional survey combined both qualitative feedback and quantitative measures of wellbeing including the Stanford Professional Fulfillment Index to assess professional fulfillment and burnout and a workplace issues inventory to assess the relative perceived influence on work-related wellbeing. Survey responses from 124 doctors comprised approximately 60% (n=74) prevocational doctors, 12% (n=15) registrars and 28% (n=35) specialist doctors. Around 63% (n=78) of participants were international medical graduates. Overall, 25% (n=31) reported professional fulfilment and 13% (n=13) reported burnout. The top 6 workplace issues were (i) inefficient work practices and/or processes, (ii) medical officer vacancies in my department, (iii) inadequate support staff and/or excessive admin burden, (iv) inadequate workplace staff amenities, (v) poor access to nutritious onsite food, (vi) inability to access my entitled daily meal break. Factors perceived as having a minimal impact on wellbeing included learning opportunities, rostering, access to leave and support during challenging clinical situations, were directly related to the workforce nurturing strategies implemented. This comprehensive evaluation of wellbeing in a regional healthcare setting provides a novel contribution to the literature by illustrating the transformative potential of workforce nurturing. Notably, the findings reflect the potential impact of workforce nurturing upon professional fulfilment and burnout, in the context of a regional hospital setting.

Codesigning an E-Health Intervention for Surgery Preparation and Recovery.

Surgery is a significant part of healthcare, but its demand is increasing, leading to challenges in managing patient care. Inefficient perioperative practices and traditional linear models contribute to adverse outcomes and patient anxiety. E-health interventions show promise in improving surgical care, but more research is needed. The purpose of this study was to involve patients and healthcare workers during the design phase of an e-health intervention that aims to support the perioperative care of elective surgery preparation and recovery. This study used an Information Systems Research Framework to guide collaborative codesign through semistructured interviews and cocreation workshops. Semistructured interviews collected insights on the perioperative journey and e-health needs from healthcare workers and consumers, resulting in the creation of a patient surgery journey map, experience map, and a stakeholder needs table. Collaborative work between consumers and healthcare workers in the cocreation workshops identified priority perioperative journey issues and proposed solutions, as well as prioritizing application software needs, guiding the development of the wireframe. The development of an e-health application aimed at supporting surgery preparation and recovery is a significant step toward improving patient engagement, satisfaction, and postsurgical health outcomes.

Garbage Monitoring And Management Using Deep Learning

Abstract. Rapid urbanisation and population growth have led to an unprecedented increase in waste generation. In addition to this, increasing tourism has also increased the challenge of maintaining coastal areas. Inefficient and inadequate waste management practices pose significant environmental and health hazards to both humans and wildlife. Through deep learning and computer vision techniques, the garbage can be identified and its location can be extracted directly from the images. Videos are collected using UAVs. Auto generation of waste reports and additional services like chat-bots are also implemented. Furthermore, the system implements OR tools using which the routes of garbage collector vehicles is optimised. By minimising travel distances and maximising cleanup efficiency, the system reduces operational costs and enhances the overall effectiveness of beach cleanup initiatives. Predominant spots of garbage are analysed and the nearest dustbins are mapped along with the route to reach the dustbin. The garbage detection model gave a mAP of 0.845. The silhouette score of clustering was 70.1% for chameleon and 99.02% for k means. All of the above mentioned modules were integrated and presented on the user interface of the application developed.

Tax Administration and Financial Performance of Manufacturing Firms in Kenya: A literature Review

This study explores the impact of tax administration practices on the financial performance of manufacturing firms in Kenya. The manufacturing sector is crucial for economic growth and job creation, making it essential to understand how tax policies affect its performance. Tax administration encompasses procedures and policies governing tax compliance, which have evolved over time. Effective tax administration is vital for economic stability and funding public services. However, inefficient practices can hinder firm productivity and growth. Drawing on tax planning theory and agency theory, this study examines how firms strategically manage tax liabilities and navigate principal-agent relationships to optimize financial performance. The empirical review highlights findings from previous studies on the relationship between tax administration practices and firm performance in Kenya. These studies underscore the importance of tax incentives, compliance costs, and governance mechanisms in shaping firm behavior and economic outcomes. By understanding the nuances of tax administration practices, policymakers and firms can implement strategies to enhance economic stability and growth in the manufacturing sector.

Blooms & Bytes Nurturing Garden with Smart Irrigation – Planning

Blooms and Bytes: Nurturing Garden with Smart Irrigation proposes a cutting-edge solution to address the challenges of water scarcity and inefficient irrigation practices in gardens. The project integrates advanced technology to automate and optimize watering processes, ensuring sustainable plant growth while conserving water resources. Through the implementation of hardware components such as solenoid valves, water filters, and pressure pumps, coupled with automation facilitated by microcontrollers and real-time clock modules, the system offers precise control over irrigation schedules. Additionally, a cloud monitoring system enables remote management and monitoring of the garden layout. The project outlines a comprehensive implementation plan, market research insights, and budget considerations, emphasizing the benefits of water conservation, environmental sustainability, and time efficiency. Collaboration with NGOs and funding agencies is sought to support the project's implementation. Overall, the proposed smart irrigation system presents a promising solution to promote eco-friendly gardening practices and contribute to sustainable development goals. Keywords: Water conservation, Automation, Sustainable Technology, Smart irrigation

A real-time feeding decision method based on density estimation of farmed fish

With the global population growth and increasing demand for high-quality protein, aquaculture has experienced rapid development. Fish culture management and feed supply are crucial components of aquaculture. Traditional baiting management relies on experiential judgment and regular observation, which often leads to inefficient baiting practices and wastage. To address these issues, intelligent bait casting decisions have emerged. Leveraging advanced artificial intelligence algorithms, intelligent bait casting decisions can overcome most drawbacks of traditional bait management and enhance breeding efficiency. However, most of the current intelligent baiting decisions are focused on using methods such as image processing and target detection to identify different feeding actions and patterns. These methods do not discuss based on video streams and do not consider the changes in fish behavior during the baiting process. Therefore, we proposed a real-time analysis method based on the density distribution of fish feeding behavior (FishFeed). Firstly, this method upgrades the input mechanism, not only handling static images but also capable of real-time video stream analysis. Secondly, by evaluating the fish school density distribution through a new intelligent baiting strategy, this method can monitor the feeding behavior of fish school during the baiting process in real time. Finally, we constructed a dataset for fish school density analysis (DlouFishDensity) that includes a wealth of video and image frames, providing a valuable resource for research. Experimental results indicate that our algorithm outperforms MCNN, improving MAE by 1.63 and 1.35, MSE by 1.92 and 1.58, and reducing prediction time by 2.56 seconds on the same dataset. By implementing real-time analysis of fish feeding behavior density distribution, our method offers a more efficient and effective approach to baiting management in aquaculture, contributing to improved breeding efficiency and resource utilization.

Assessing sustainable waste management practices in Rajshahi City Corporation: an analysis for local government enhancement using IoT, AI, and Android technology.

This study addresses the pressing challenge of inefficient waste management practices within the Rajshahi City Corporation (RCC), Bangladesh. Despite rapid urbanization and escalating waste generation rates, RCC struggles with diverse waste disposal practices, limited supervision, irregular waste collection schedules, and inadequate disposal infrastructure. In this context, this study examines the possible improvements that could be made by combining the Internet of Things (IoT), artificial intelligence (AI), and Android application to improve waste management methods in the RCC. The study's foundation is a vast amount of information gathered from residents, with particular attention paid to waste disposal methods, the role of the local government, the frequency of waste collection, and public attitudes toward waste management. The results point to a complicated waste management environment with a range of waste disposal practices, little supervision, irregular waste collection, and insufficient disposal methods. The importance of RCC in waste management is emphasized, highlighting the need for proactive measures including effective monitoring, constant waste collection, and routine drain cleaning. Additionally, it is suggested that combining IoT, AI, and Android technology is a possible way to improve waste management procedures. These technologies have the potential to increase productivity, lessen their negative effects on the environment, and produce cleaner, more sustainable urban environments.

THE QUALITATIVE AND QUANTITATIVE DEVELOPMENT OF EDUCATION IS A CRUCIAL FACTOR IN IMPROVING THE INNOVATION RANKING OF UZBEKISTAN

The qualitative and quantitative development of education is a crucial factor in improving the innovation ranking of Uzbekistan. Obstacles such as corruption, inefficient management, the lack of funds for research, and fund mismanagement hinder progress inthis regard. Corruption within the education sector undermines transparency and trust, necessitating stringent measures to combat this pervasive issue. Inefficient management practices impede the effective utilization of resources and hinder progress towards educational goals. The lack of adequate funding for research and development poses a significant obstacle to innovation, limiting the ability of educational institutions to conduct groundbreaking research and implement innovative projects. Additionally, mismanagement of available funds exacerbates the problem, necessitating a reevaluation of budget allocation mechanisms. To address these challenges, a comprehensive approach is required, including strengthening anti-corruption measures, implementing effective governance and management practices, and prioritizing investment in research and development by allocating sufficient funds and ensuring their judicious use. By overcoming these obstacles, Uzbekistan can foster a conducive environment for education and innovation, empowering the nation to thrive in an increasingly competitive global landscape.

INFLATION IN INDIA: CAUSES AND REMEDIES

This paper delves into the intricate landscape of inflation in India, aiming to dissect its root causes and propose strategic remedies. As a developing economy, India grapples with the complexities of inflation, which significantly impacts economic stability and the standard of living. The causes are multifaceted, including demand-pull factors arising from rapid economic growth, cost-push elements driven by escalating production costs, and structural issues like inefficient agricultural practices. To address these challenges, the paper suggests a multifaceted approach encompassing monetary policy measures, fiscal reforms, and structural changes. By exploring international cooperation and learning from successful strategies in other countries, India can forge a path towards sustained economic growth with controlled inflation, fostering a prosperous and inclusive future.

Memahami Dinamika Administrasi Publik dan Implementasi Kebijakan

Abstract. This study aims to explore and analyze the factors that lead to the persistent discrepancy between policy formulation and effective implementation in public administration.
 By utilizing secondary data obtained from various scientific sources, this study uses qualitative research methods to provide insight into the complex dynamics that influence the outcome of policy implementation.
 The findings of this study emphasize several key factors influencing policy implementation. First, bureaucratic structure and organizational processes are identified as elements that significantly affect implementation results. This study reveals that inefficient bureaucratic practices and systemic barriers often hinder effective policy translation into practice. Moreover, the role of leadership in ensuring the successful implementation of policies in public administration emerges as another important factor. Effective leadership, with its ability to mobilize resources and inspire commitment, plays a critical role in driving successful policy implementation. Furthermore, political factors were found to greatly influence the dynamics of policy implementation. Research shows that political instability, self-interest, and ideological conflict can hinder effective policy implementation, leading to sub-optimal outcomes. To bridge the gap between policy formulation and implementation, this study outlines the main strategies. This strategy includes improving communication channels, stakeholder engagement, capacity building, and cultivating a culture of accountability and transparency within the administrative system.
 In conclusion, this research sheds light on the complexities surrounding policy implementation in public administration. By understanding the multifaceted nature of the problem and adopting strategic interventions, policymakers can work towards achieving a more effective and efficient policy implementation process.
 Keywords: Bureaucratic structure; Organizational processes; Policy implementation; Political factors, Public administration

Estimating Yield Response Functions to Nitrogen for Annual Crops in Iran

Nitrate is a crucial element for crop growth, and its optimal application is essential for maximizing agricultural yield. In Iranian agriculture, there is a substantial gap between recommended nitrate usage and what farmers actually apply. In this study, our primary objective is to determine the most effective utilization of nitrate for crop cultivation. Simultaneously, we aim to analyze the factors that contribute to the disparity between optimal and current nitrate application practices. Furthermore, our research explores the impact of these differences on regional variations in crop yields. This is achieved using a quadratic yield response function model based on unbalanced panel data spanning the years 2000 to 2016, which includes a total of 14 crop activities and encompasses 31 administrative regions. The results show that rice exhibits the highest nitrogen usage, while rain-fed wheat demonstrates the lowest utilization at the optimal point. Depending on whether random- or fixed-effects estimation is found to be the most suitable specification, average yields corresponding to the optimal level of nitrogen use are calculated by region, or the average across all regions. In Iran, the top-performing regions for cereals like rain-fed wheat and irrigated barley can achieve yields of 1.33 and 3 t/ha, respectively. These yields represent a 31% and a 9% increase from the levels observed in 2016. The outcomes derived from the estimated yield response function will be integrated into comprehensive agricultural, economic, and environmental optimization models. These integrated models will facilitate the assessment of various fertilizer policies on fertilizer use, land allocation, farm-household incomes, and environmental externalities, such as nitrate leaching and nitrate balance. This study holds substantial scientific promise, given its exploration of the policy implications surrounding fertilizer usage, making it crucial not only for Iran, but also for many developing nations grappling with inefficient and unsustainable agricultural practices. It represents the first of its kind in the literature, providing estimations of optimal nitrogen use and crop yield points across all regions in Iran. This is achieved through advanced visualization using GIS maps.

Prioritizing factors for the adoption of IoT-based smart irrigation in Saudi Arabia: a GRA/AHP approach

The irrigation sector in the Kingdom of Saudi Arabia (KSA) confronts a range of obstacles, such as scarce water resources, the elevated salinity and alkalinity of irrigation water, inefficient irrigation practices, and inter-sectoral competition for water resources. These challenges have led to diminishing agricultural yields and abandonment of arable lands. Internet of Things (IoT)-based irrigation systems present a promising remedy for these issues. By curbing water wastage and ensuring precise water delivery to crops, IoT-based irrigation systems offer a viable solution to the challenges entrenched in traditional irrigation methodologies in KSA. However, the widespread implementation of an IoT-based Smart Irrigation System (I-SIMS) poses a multifaceted and intricate challenge in KSA. This study is focused on the identification of the factors and challenges through a systematic review and ranking of the challenges/factors that exert a significant influence on the adoption of I-SIMS. Ranking aids in determining the importance of various alternatives. It enables locating the best options that support the required objectives in complex decision situations. The study employs both Grey Relational Analysis (GRA) and Analytical Hierarchical Process (AHP) methodologies to prioritize these factors. The study’s conclusive findings indicate that among the challenges, technical expertise and security measures emerge as the foremost concerns that demand attention.

Determinación de la actividad antimicótica de los aceites esenciales de eucalipto, molle y romero sobre (Fusarium sp; Pythium sp; Rhizoctonia sp), agentes causales del mal de almacigo en condiciones de laboratorio

Introduction: The proliferation of a large number of fungi, diseases, and pests, due to the imbalance of soil mycostasis, is due to the irrational use of pesticides, fungicides, and the use of inefficient agronomic practices, such as monoculture, traditional sowing, and deforestation. Factors that have caused serious problems in environmental balance and human health. One of the possible alternatives to regulate this imbalance is the application of extracts of plant origin to control fungi, pests, and diseases in crops. Objectives: “The objective of this research was to determine the antifungal activity and the inhibition capacity of the extraction process of the essential oils of Eucalyptus, molle and rosemary, on fungi (Fusarium sp. Pythium sp. Rhizoctonia sp. and Sclerotium sp.), causal agents of almacigo disease Damping off. Applying the Methodology: isolation, analysis of variance, Completely Randomized Design (DCA),” separation of means and 5% Tukey test, Determination of effective dose 50, Inhibition capacity, Linear regression analysis; obtaining the following. Results: “The fungi under study are slow growing, no pathogen was able to populate the surface of the Petri dish from 24 to 120 hours, the radial growth rate being presented in the following order: Pythium sp. with 32mm, Rhizoctonia sp. with 30.82 mm, Fusarium sp. with 23.42mm and finally Sclerotium sp with 19 mm. The best treatments were the distillates of Eucalyptus, Molle and Rosemary and the wastewater fraction of Rosemary, which managed to inhibit 91.46%; 93.48% and 94.26% on Fusarium Sp., Phytium Sp., Rhizoctonia sp. and Sclerotium sp. respectively. Conclusions: “The use of essential oils is efficient for pest control, so making a comparison with the Benomyl fungicide by determining the effective dose of 50%, it is advisable to use extracts and distillates to avoid causing health problems. and environmental effects. General study area: Phytopathology. Specific study area: Antifungal Activity.

Microbial and Parasitic Infection in Fish

Major concerns in the fisheries business are parasitic fish and bacterial infections. When it comes to aquatic life microbes are a regular occurrence. The majority of microbes are naturally occurring in water. Because of poor environmental conditions, limited nutrition, and inefficient fish husbandry practices, they only cause diseases. Some microbial infections occur in fresh water fish (Pseudomonas infection, Acinetobacter infections, bacterial gill diseases), in marine water (Vibriosis, Tenacibaculosis, streptococcal infections, bacterial skin diseases) and in brackish water (Red sea bream iridoviral disease (RSID, Lymphocystis disease (LCD). All these infections affect fish differently. Parasitic illnesses can cause epidemics in fish that are overcrowded or under other unnatural situations. A large number of fish species have been severely impacted by parasite and bacterial species. Some parasitic infections of fresh water are Renal Sphaerosporosis, due to leeches and nematodes, isopods and Gill Monogeneans; in amarine water are Microsporidiosis, Cryptocaryonosis and Brooklynelliosis and in brackish water are Diplostomum spathaceum metacercarial infections. Some preventive actions are done to control this problem. In this review there is a complete detail about parasite and bacterial infections and how they can be prevented.

A large-scale empirical study on mobile performance: energy, run-time and memory

Software performance concerns have been attracting research interest at an increasing rate, especially regarding energy performance in non-wired computing devices. In the context of mobile devices, several research works have been devoted to assessing the performance of software and its underlying code. One important contribution of such research efforts is sets of programming guidelines aiming at identifying efficient and inefficient programming practices, and consequently to steer software developers to write performance-friendly code.Despite recent efforts in this direction, it is still almost unfeasible to obtain universal and up-to-date knowledge regarding software and respective source code performance. Namely regarding energy performance, where there has been growing interest in optimizing software energy consumption due to the power restrictions of such devices. There are still many difficulties reported by the community in measuring performance, namely in large-scale validation and replication. The Android ecosystem is a particular example, where the great fragmentation of the platform, the constant evolution of the hardware, the software platform, the development libraries themselves, and the fact that most of the platform tools are integrated into the IDE’s GUI, makes it extremely difficult to perform performance studies based on large sets of data/applications. In this paper, we analyze the execution of a diversified corpus of applications of significant magnitude. We analyze the source-code performance of 1322 versions of 215 different Android applications, dynamically executed with over than 27900 tested scenarios, using state-of-the-art black-box testing frameworks with different combinations of GUI inputs. Our empirical analysis allowed to observe that semantic program changes such as adding functionality and repairing bugfixes are the changes more associated with relevant impact on energy performance. Furthermore, we also demonstrate that several coding practices previously identified as energy-greedy do not replicate such behavior in our execution context and can have distinct impacts across several performance indicators: runtime, memory and energy consumption. Some of these practices include some performance issues reported by the Android Lint and Android SDK APIs. We also provide evidence that the evaluated performance indicators have little to no correlation with the performance issues’ priority detected by Android Lint. Finally, our results allowed us to demonstrate that there are significant differences in terms of performance between the most used libraries suited for implementing common programming tasks, such as HTTP communication, JSON manipulation, image loading/rendering, among others, providing a set of recommendations to select the most efficient library for each performance indicator. Based on the conclusions drawn and in the extension of the developed work, we also synthesized a set of guidelines that can be used by practitioners to replicate energy studies and build more efficient mobile software.