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نتیجه جستجو - synergy

تعداد مقالات یافته شده: 34
ردیف عنوان نوع
1 Barriers to computer vision applications in pig production facilities
موانع برنامه های بینایی کامپیوتری در تاسیسات تولید خوک-2022
Surveillance and analysis of behavior can be used to detect and characterize health disruption and welfare status in animals. The accurate identification of changes in behavior is a time-consuming task for caretakers in large, commercial pig production systems and requires strong observational skills and a working knowledge of animal husbandry and livestock systems operations. In recent years, many studies have explored the use of various technologies and sensors to assist animal caretakers in monitoring animal activity and behavior. Of these technologies, computer vision offers the most consistent promise as an effective aid in animal care, and yet, a systematic review of the state of application of this technology indicates that there are many significant barriers to its widespread adoption and successful utilization in commercial production system settings. One of the most important of these barriers is the recognition of the sources of errors from objective behavior labeling that are not measurable by current algorithm performance evaluations. Additionally, there is a significant disconnect between the remarkable advances in computer vision research interests and the integration of advances and practical needs being instituted by scientific experts working in commercial animal production partnerships. This lack of synergy between experts in the computer vision and animal health and production sectors means that existing and emerging datasets tend to have a very particular focus that cannot be easily pivoted or extended for use in other contexts, resulting in a generality versus particularity conundrum. This goal of this paper is to help catalogue and consider the major obstacles and impediments to the effective use of computer vision associated technologies in the swine industry by offering a systematic analysis of computer vision applications specific to commercial pig management by reviewing and summarizing the following: (i) the purpose and associated challenges of computer vision applications in pig behavior analysis; (ii) the use of computer vision algorithms and datasets for pig husbandry and management tasks; (iii) the process of dataset construction for computer vision algorithm development. In this appraisal, we outline common difficulties and challenges associated with each of these themes and suggest possible solutions. Finally, we highlight the opportunities for future research in computer vision applications that can build upon existing knowledge of pig management by extending our capability to interpret pig behaviors and thereby overcome the current barriers to applying computer vision technologies to pig production systems. In conclusion, we believe productive collaboration between animal-based scientists and computer-based scientists may accelerate animal behavior studies and lead the computer vision technologies to commercial applications in pig production facilities.
keywords: بینایی کامپیوتر | دامپروری دقیق | رفتار - اخلاق | یادگیری عمیق | مجموعه داده | گراز | Computer vision | Precision livestock farming | Behavior | Deep learning | Dataset | Swine
مقاله انگلیسی
2 Ontology-augmented Prognostics and Health Management for shopfloor-synchronised joint maintenance and production management decisions
پیش آگهی و مدیریت سلامت با هستی شناسی تقویت شده برای تصمیمات مدیریت تولید و نگهداری مشترک هماهنگ شده با کف مغازه-2021
In smart factories, guaranteeing shopfloor-synchronised and real-time decision-making is essential to be responsive to the ever-changing internal environment, namely the shopfloor of the production system and assets. At operational level, decisions should balance counter acting objectives of maintenance and production; there- fore, their decision-making processes should be joint and coordinated, to fulfil production requirements considering the health state of the assets. The knowledge of the current state is promoted by the application of Prognostics and Health Management (PHM) as an aid to support informed decision-making. Nevertheless, PHM- purposed information is usually not complete in terms of production requirements. To support joint maintenance and production management decisions, an ontological approach is proposed. The ontology, called ORMA (Ontology for Reliability-centred MAintenance), has a modular structure, including formalisation of asset, pro- cess, and product knowledge. Via suitable relationships, rules, and axioms, ORMA can infer product feasibility based on the current health state of the assets and their functional units. ORMA is implemented in a Flexible Manufacturing Line at a laboratory scale. Therein, an integrated solution, involving a health state detection algorithm that interacts with the ontology, supports human decision-making via a web-based dashboard; joint maintenance and production management decisions can be then taken, relying on diversified information pro- vided by the PHM algorithm as well as the augmentation via ontology reasoning. The proposed ontology-based solution represents a step towards reconfigurability of smart factories where human and automated decision- making processes work in synergy.
keywords: هستی شناسی | استدلال | پیشگویی و مدیریت بهداشت | phm | نگهداری | تولید | Ontology | Reasoning | Prognostics and health management | PHM | maintenance | production
مقاله انگلیسی
3 Framework of Data Analytics and Integrating Knowledge Management
چارچوب تجزیه و تحلیل داده ها و ادغام مدیریت دانش-2021
Big data is significantly dependent on technologies such as cloud computing, machine learning and statistical models. However, its significance is becoming more dependent on human qualities e.g. judgment, value, intuition and experience. Therefore, the human knowledge presents a basis for knowledge management and big data, which are a major element of data analytics. This research contribution applies the process of Data, Information, Knowledge and Perception hierarchy as a structure to evaluate the end-users’ process. The framework in incorporating data analytics and display a conceptual data analytics process (with three phases) evaluated as knowledge management, including the creation, discovery and application of knowledge. Knowledge conversion theories are applicable in data analytics to emphasize on the typically overlooked organizational and human aspects, which are critical to the efficiency of data analytics. The synergy and alignment between knowledge management and data analytics is fundamental in fostering innovations and collaboration.
keywords: تحلیل داده ها | مدیریت دانش | داده های بزرگ | هوش تجاری | کشف داده ها | Data analytics | Knowledge management | Big data | Business intelligence | Data discovery
مقاله انگلیسی
4 Voices from ‘Igbo Bunks’: A qualitative study of the complicity of law-enforcement agents in marijuana use in a Nigerian community
صداهایی از Igbo Bunks : یک مطالعه کیفی از همدستی ماموران اجرای قانون در مصرف ماری جوانا در یک جامعه نیجریه-2020
There exists observable complicity by law enforcement agents in illicit drug networks for financial gain and yet the problem remains under-researched. Thus, this study explored the connection between cannabis use/users and the connivance of narcotic agents in Afikpo North LGA of Ebonyi State, Nigeria. Purposive and snowballing sampling techniques were employed in selecting a sample of 21, comprising 18 regular ‘Igbo Bunks’ (specially designed marijuana-smoking joints) patronisers and three dealers (Bunk owners/managers). Qualitative thematic method was adopted in analysing the data generated from in-depth oral interviews. Findings revealed that three popular Bunks operate unhidden and were well-known to the National Drug Law Enforcement Agency (NDLEA) and Nigeria Police Force (NPF), but little or no action has been taken to close them down. Although the outcome of the connivance has led to an increase in the price of cannabis due to illegal monetary compensation given to law enforcers to secure their approval, recurring use has also been recorded due to the ostensible comfort and protection these joints offer to customers. Organised marijuana smoking is a fast growing but underexplored ‘lawenforcement problem’ to watch and therefore further empirical studies on the phenomenon is suggested to further direct policy and action. There is urgent need for community responses and partnership with law enforcement agents. Since the most visible part of drug issue takes place in our neighbourhoods, this security synergy is necessary and timely for effective prevention and control of the phenomenon.
Keywords: Complicity | Igbo Bunks | Marijuana use | Law-enforcement agents | Qualitative study
مقاله انگلیسی
5 Smart charging of electric vehicles considering photovoltaic power production and electricity consumption: A review
شارژ هوشمند وسایل نقلیه برقی با توجه به تولید انرژی فتوولتائیک و مصرف برق: بررسی-2020
Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potentially impact the overall energy performance of the buildings. Thus, a high penetration of both PV and EVs poses new challenges. Understanding of the synergies between PV, EVs and existing electricity consumption is therefore required. Recent research has shown that smart charging of EVs could improve the synergy between PV, EVs and electricity consumption, leading to both technical and economic advantages. Considering the growing interest in this field, this review paper summarizes state-of-the-art studies of smart charging considering PV power production and electricity consumption. The main aspects of smart charging reviewed are objectives, configurations, algorithms and mathematical models. Various charging objectives, such as increasing PV utilization and reducing peak loads and charging cost, are reviewed in this paper. The different charging control configurations, i.e., centralized and distributed, along with various spatial configurations, e.g., houses and workplaces, are also discussed. After that, the commonly employed optimization techniques and rulebased algorithms for smart charging are reviewed. Further research should focus on finding optimal trade-offs between simplicity and performance of smart charging schemes in terms of control configuration, charging algorithms, as well as the inclusion of PV power and load forecast in order to make the schemes suitable for practical implementations.
Keywords: Photovoltaics | Electric vehicles | Electricity consumption | Smart charging | Energy management system | Charging optimization
مقاله انگلیسی
6 The synergy between human factors and risk attitudes of Malaysian contractors’: Moderating effect of government policy
هم افزایی بین عوامل انسانی و نگرش ریسک از پیمانکاران مالزی: اثر تعدیل کننده سیاست دولت-2020
Many critical factors influence the effectiveness of risk management. There is unanimity among project and risk practitioners about the most significant factor responsible for risk management: “human factors”. As human attitude is always reflected in behaviour, there is a high possibility that a contractors behaviour will be by the attitude. Therefore, this study aims to identify the factors affecting contractors risk attitudes and then determine the relationship with government policy. A total of 100 copies of questionnaire were randomly distributed to the construction companies in Kuantan Malaysia. Out of the 100 copies of the questionnaire distributed, 69 copies were received indicating 72.6% response rate. Thirteen (13) copies of the questionnaire were found to be unusable due to missing data or errors in the responses to all the questions. Thus, 56 copies of the questionnaire, indicating 58.9% response rate, were usable. Moreover, with quantitative research design following the positivist research paradigm, the methodology was designed to focus on the research questions and the objectives. Organizational Control Theory was used to develop the theoretical framework that investigated G-7 contractors in the Kuantan Pahang, Malaysian construction companies. SPSS 20.0 & SmartPLS 3 for structural equation modelling was utilized in testing the hypotheses developed for the study. Government policy moderates the relationships between the internal factors and contractors risk attitudes among the construction companies operating in Kuantan, Malaysia. This implies that the findings of the study provides more understanding of the personal factors that affect contractors risk attitudes to facilitate contractors decision-making process. It also serves as a useful reference for further studies in the field of construction project management.
Keywords: Contractors risk attitude | Risk attitude | Organizational control theory | Government policies | Personal factors | PLS-SEM
مقاله انگلیسی
7 Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities
سیستم مبتنی بر یادگیری ماشین برای مدیریت بهره وری انرژی بخش دولتی به عنوان رویکردی به شهرهای هوشمند-2020
Energy efficiency of public sector is an important issue in the context of smart cities due to the fact that buildings are the largest energy consumers, especially public buildings such as educational, health, government and other public institutions that have a large usage frequency. However, recent developments of machine learning within Big Data environment have not been exploited enough in this domain. This paper aims to answer the question of how to incorporate Big Data platform and machine learning into an intelligent system for managing energy efficiency of public sector as a substantial part of the smart city concept. Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings. The most accurate model was produced by Random forest method, and a comparison of important predictors extracted by all three methods has been conducted. The models could be implemented in the suggested intelligent system named MERIDA which integrates Big Data collection and predictive models of energy consumption for each energy source in public buildings, and enables their synergy into a managing platform for improving energy efficiency of the public sector within Big Data environment. The paper also discusses technological requirements for developing such a platform that could be used by public administration to plan reconstruction measures of public buildings, to reduce energy consumption and cost, as well as to connect such smart public buildings as part of smart cities. Such digital transformation of energy management can increase energy efficiency of public administration, its higher quality of service and healthier environment.
Keywords: Planning models | Energy efficiency | Machine learning | Public sector | Smart cities
مقاله انگلیسی
8 A review on heat enhancement in thermal energy conversion and management using Field Synergy Principle
مروری بر افزایش گرما در تبدیل انرژی و مدیریت انرژی حرارتی با استفاده از اصل فیلد سینرژی-2020
How to improve the efficiency of heat transport, conversion and management has been the research focus of thermal energy application and related disciplines. Since the Field Synergy Principle theory was put forward, it has been further studied and developed in a wider scope which is an effective research method for enhancing convective heat transfer and other heat transfer processes. This paper investigated the optimization applications in thermal transfer such as heat exchangers, fuel cell, porous medium, solar energy receiver vortex generators and diesel particulate filter, which can improve the heat transfer performance significantly. The field synergy direct application can improve the heat transfer capacity of the finned heat exchanger remarkably with a 7% increase of heat transfer capability and about 14.4% less aluminum for the fin. The heat transfers efficient of the wave fin with elliptic improved 30% with the larger averaged intersection angle compared to wavy fin after field synergy optimized. Better use effects have emphasized the utilization of the synergy approaches to enhance the heat transfer combined with other theories, the total time rates of entropy generation are 7.3×10−2 W·K−1 and that is 8.2×10−2 W·K−1 after field synergy and minimum entropy generation principle majorization with the same viscous dissipation of 2.4×10−8 W. The research results explore extensions of the field synergy theory highly desirable attributes to more diverse and broader applications, which provide a way of thinking and research method for the further thermal energy conversion and management development as far as possible.
Keywords: Field Synergy Principle | Convective heat transfer | Heat transfer | Energy conversion and management | Heat enhancement
مقاله انگلیسی
9 Micro-cogeneration based on solid oxide fuel cells: Market opportunities in the agriculture/livestock sector
تولید همزمان خرد بر اساس پیل های سوختی اکسید جامد: فرصت های بازار در بخش کشاورزی / دام-2020
Bio-waste embeds an extraordinary renewable potential, and it becomes a source of energy savings when transformed into a valuable resource, like biogas. Cogeneration (CHP) from biogas employing high-temperature Solid Oxide Fuel Cells (SOFCs) scores a high sustain- ability level, thanks to improved environmental and energy performances. The synergy between the niche market of small/micro biogas producers and SOFCs might act as a springboard to open market opportunities for both SOFC commercialization and business upgrade of small farms. However, local regulations, waste management, renewable energy subsidies and, above all, availability of eligible sites, determine real chances for on-the- ground implementation.Through a detailed analysis of the application scenario, this research aims at investi- gating opportunities for the experimentation of SOFCeCHP in small biogas plants and identifying the possible bottlenecks for future deployment. When it becomes relevant, energy conversion of livestock (especially cattle and swine) and agriculture waste requires SOFC modules from 10 kWe to 35 kWe. This is in line with the current status of SOFC suppliers. Moreover, considering the fuel cell market roll-out, the average levelized cost of electricity is expected to decrease from 0.387 V/kWh to 0.115 V/kWh, when electricity is produced from livestock waste available on-site.© 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved
Keywords: Energy efficiency | Biogas | SOFC | Circular economy | Livestock waste | Micro-CHP
مقاله انگلیسی
10 Deep learning for continuous manufacturing of pharmaceutical solid dosage form
یادگیری عمیق برای تولید مداوم فرم دوز جامد دارویی-2020
Continuous Manufacturing (CM) of pharmaceutical drug products is a new approach within the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line for production of solid dosage forms was investigated. The line was composed of the subsequent continuous unit: operations feeding – twin-screw wet-granulation – fluid-bed drying – sieving and tableting. The formulation of a commercial entity was selected for this study. Several critical process parameters were evaluated in order to probe the process and to characterize the impact on quality attributes. Seven critical process parameters have been selected after a risk analysis: API and excipient mass flows of the two feeders, liquid feed rate and rotation speed of the extruder and rotation speed, temperature and airflow of the dryer. Eight quality attributes were controlled in real time by Process Analytical Technologies (PAT): API content after blender, after dryer, in tablet press feed frame and of tablet, LOD after dryer and PSD after dryer (three PSD parameters: x10 x50 x90). The process parameter values were changed during production in order to detect the impact on the quality of the final product. The deep learning techniques have been used in order to predict the quality attribute (output) with the process parameters (input). The use of deep learning reduces the noise and simplify the data interpretation for a better process understanding. After optimization, three hidden layers neural network were selected with 6 hidden neurons. The activation function ReLU (Rectified Linear Unit) and the ADAM optimizer were used with 2500 epochs (number of learning cycle). API contents, PSD values and LOD values were estimated with an error of calibration lower than 10%. The level of error allow an adequate process monitoring by DNN and we have proven that the main critical process parameters can be identified at a higher levelof process understanding. The synergy between PAT and process data science creates a superior monitoring framework of the continuous manufacturing line and increase the knowledge of this innovative production line and the products that it makes.
Keywords: Continuous manufacturing | Solid dosage form | Process monitoring | Process analytical technology | Deep learning | Process data science | Process data analytics
مقاله انگلیسی
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