Performance Evaluation Of Techniques Research Articles

A Succinct Review on the Numerical and Experimental Performance Evaluation Techniques for Composite Marine Propellers

A Succinct Review on the Numerical and Experimental Performance Evaluation Techniques for Composite Marine Propellers

Development of numerical and experimental performance evaluation techniques for high-reliability turbine flow meters of ice-making water-dispenser

A turbine flowmeter for sensing the water supply in an ice-making system of a refrigerator requires high sensitivity to the flow rate. This research aims to develop a comprehensive performance evaluation technique by constructing an experimental setup and establishing a numerical technique to simulate the rotational motion of the impeller in response to the injection of water into the flowmeter. An experimental rig was built to secure the measurement accuracy according to the fluid temperature and pressure changes and verify the reliability under various flow conditions from low to high. A numerical method based on the six-degree of freedom method was used to confirm its validity, which is different from a moving reference frame, which numerically analyzes the rotational speed of the turbine by backtracking the rotational speed to correspond to the flow conditions by giving it a constant rotational speed. By simulating water injection into the flowmeter, generating kinetic energy in the impeller according to the flow rate, and subsequently rotating the impeller due to the generated torque, the numerical analysis cost was reduced, allowing direct numerical analysis of the impeller’s acceleration motion. The results were evaluated in terms of angular velocity and pulse signal, and the applicability and reliability of the numerical technique were verified by comparing the numerical results with experimental results. The aerodynamic performance of the impeller was analyzed to understand the phenomena as the impeller rotates. The results of this study can be utilized to conduct future research to improve the performance of flow meters, thus proving its value as a preliminary study.

The Effect of Effort and Result-Oriented Contracts on Human Resource Productivity: An Important Component of Sustainable Development Study of Dairy Farm in Iran

Human resource productivity is one of the essential components of the sustainable development of human resources. Human resource efficiency means the optimal use of people's capabilities, skills, knowledge, and experiences in society or organization. The sustainable development of human resources can be aided by raising productivity levels. The management of human resources systems and performance evaluation techniques may need help in evaluating the performance of employees under the influence of its complexities, which can cause inaccurate evaluation results. As a result, the organization will need help achieving the predetermined goals with proper productivity. Therefore, The present study examines the effect of effort and result-oriented contracts on the productivity of human resources in a 20,000-head state cattle farm in Iran. A comparative approach was used to investigate the effect of effort-based and result-based payments on human resource productivity. It analyzed ten projects in a set, where five were used for effort-based contracts and five similar projects used for results-based contracts. The findings of the study show that result-based contracts have a substantial impact on the productivity of labor in terms of effectiveness and efficiency. The study likewise discussed the implications of its results.

Technical analysis and performance evaluation of retrofitted electric Auto Rickshaws (E-TAR) in rural India

India needs to electrify rickshaws because of the emissions produced by modern cars running on fossil fuels like gasoline and diesel. There are incentives, discounts, and exemptions available for the use of e-auto rickshaws. The production of electric vehicles has also been given a target by the Indian government. The Indian government has taken a number of steps to increase the availability of charging stations and a steady supply of electric cars (EVs). Even after taking all of these measures, there has been little adoption. For Indian auto drivers, the capital cost of purchasing an e-auto is expensive. To attain ideal performance, it is important to modify the present generation of traditional auto rickshaws using low-cost retrofitting. Retro-kit is created and evaluated for performance in this study by changing parameters.

Optimizing spatial survey administration adopting RT-GSCS: A statistical perspective on performance metrics

The Real-Time Geo-Spatial Consensus System (RT-GSCS) is a web-based open-source tool designed for the administration of real-time spatial surveys. One distinguishing feature of this system lies in the adoption of the Real-Time Spatial Delphi logic as the main computational algorithm to achieve a convergence of opinions within a group of individuals. The system is available at http://rtgscs.com/ and is particularly instrumental in supporting the decision-making process when spatial data is absent or when user judgments are solicited for territorial actions. Since the release of the beta version, the system has undergone multiple iterations and significant changes, and for this reason, an updated assessment should be conducted. In this paper, we present an in-depth exploration of the latest version of RT-GSCS (v3.0), which includes novel algorithms, statistical analysis, and spatial techniques, optimized for survey administration. The analysis is meticulously conducted by evaluating a comprehensive array of parameters, encompassing performance metrics, spatial elements, security, updates, and privacy assessments. Moreover, a thorough examination of user feedback is presented, enriching the depth of our investigation. This mixed-method approach ensures a robust and updated investigation of the system, facilitating a nuanced comprehension of the process and the attainment of spatial consensus.•Existing spatial survey administration systems cannot facilitate group collaboration for achieving a spatial consensus on the territory in real-time.•The RT-GSCS experienced substantial modifications, necessitating a revised technical evaluation from the initial beta version to its current version.•The proposed method fills the gaps of a technical performance evaluation of the latest version of RT-GSCS, useful for achieving a spatial consensus among a group of individuals with an assessment of the overall performances.

TODIM-GRA technique for performance evaluation of financial management in provincial colleges under 2-tuple linguistic Pythagorean fuzzy sets

Higher provincial education is a very important component of higher education, and it will become a key focus of the higher education development in the future. The purpose of performance evaluation of financial management in provincial colleges is to assess and evaluate the current situation of financial management in provincial colleges based on cost-effectiveness principles, with a performance-oriented approach. A specific, standardized, easy to quantify, and operable evaluation system is designed for its fund operation and financial management. By evaluating the financial management performance of provincial colleges, a new assessment standard can be provided for the “input-output result” of public education, providing an important basis for achieving a performance allocation mechanism. The performance evaluation of financial management in provincial colleges is MAGDM. In recent years, the TODIM and grey relational analysis (GRA) technique was employed to deal with MAGDM. The 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) are employed as an effective tool for expressing uncertain decision information during the performance evaluation of financial management in provincial colleges. In this paper, the 2-tuple linguistic Pythagorean fuzzy number TODIM-GRA (2TLPFN-TODIM-GRA) technique is constructed to deal with MAGDM under 2TLPFNs. Finally, a numerical example for performance evaluation of provincial colleges financial management is constructed to verify the proposed technique.

Division Pattern and Evaluation of Technical Performance of Bio-volume Measurements of Divided and Un-divided Cells in Ulva ohnoi for Determining Growth

Division Pattern and Evaluation of Technical Performance of Bio-volume Measurements of Divided and Un-divided Cells in Ulva ohnoi for Determining Growth

Aspects of Personnel Management of the Probation Service in Albania: Under the Perspective of the Tokyo Rules

The Probation Service is a crucial component of state organization and operation, as this institution\'s purpose is to oversee alternative sentencing, thereby ensuring the rehabilitation of individuals subject to such sanctions. For the successful realization of this goal—namely, the assistance in reintegration and resocialization of law offenders into the community through contemporary methods and tools of alternative punishments—the staff of the Probation Service must be qualified. This entails that the selected personnel not only possess the requisite professional training to handle supervised individuals but also continuously undergo various processes and techniques for motivation, professional development, and performance evaluation. Consequently, and due to the scant scientific research in this field in Albania and beyond, our aim is to highlight the most crucial element of such an institution—the personnel, specifically, the so-called probation service specialists (PSS).We have examined whether the management of PSS in Albania adheres to international standards, or the so-called Tokyo Rules, concerning personnel, starting from the selection process, motivation, performance evaluation, and professional development. To achieve this objective, firstly, it was determined whether the Albanian legal framework on the organization and functioning of the Probation Service specifies these international standards, or the Tokyo Rules, regarding personnel. Secondly, it was verified whether these international standards on personnel are applied in the management practices of PSS in Albania. Thirdly, it was ascertained that managing PSS according to international standards guarantees the effective execution of alternative sentences. In this manner, we have demonstrated the role and impact that well-managed personnel have on achieving the purpose and mission of the Probation Service, namely, the rehabilitation and reintegration of the supervised individual.This study, from the perspective of the Tokyo Rules, has first revealed that the legal framework in Albania for managing the personnel of the Probation Service adheres to international standards, or the so-called Tokyo Rules; secondly, that the management in practice of PSS does not occur according to this legal framework and international standards. Furthermore, it has been shown that the management in practice of PSS not according to international standards has not ensured the effective execution of alternative sentences. Thus, we have identified the direct impact that well-managed personnel have on realizing the goal and mission of the Probation Service, i.e., the supervision of alternative sentences and the rehabilitation/reintegration of the supervised person.

New Characterizations for PEFC Under Sub-Zero Temperature

The operation of fuel cells at sub-zero temperature results in direct deposition of ice or production of supercooled water that freezes upon interacting with nucleation seeds. Ice formation can lead to irreversible mechanical damages in membrane electrode assembly (MEA), particularly at interfaces, which is detrimental to the performance and safety of fuel cells. The mitigation strategies are focused on temperature elevation, including assisted heating, catalytic heating, and starvation (low potential) heating; however, these are associated with parasitic loss that reduces overall efficiency of the system. An alternative method is to develop porous media that are capable of ensuring oxygen transport pathways in the presence of ice or retaining supercooled water without phase transition until the cell reaches above 0ºC.The development of ice-resistant porous media for sub-zero operation is hindered by limitations on material characterization and performance evaluation techniques. The most common characterization technique is differential scanning calorimetry (DSC), by which water-saturated porous media is subjected to rapid temperature cycles to measure melting and freezing peaks. The DSC is a well-established and convenient technique that is suitable for statistical analysis; however, the sample size is limited to the mm-scale, and water must be injected in hydrophobic media prior to the DSC measurement where water saturation level and morphology are unpredictable. In situ testing of novel materials are performed on single cell hardware, in which the temperature is controlled by circulating a coolant through endplates or cooling channels that are placed several mm to cm away from an MEA. Such pseudo-active cooling system results in a significant difference (and delay) between the coolant and cell temperatures, influenced by heat production due to cell operation as well as freezing/melting. On the other hand, free heating operation starting from sub-zero is not desirable, since product heat is dissipated to current collectors and endplates that have much greater mass per active area in comparison to stack. As a result, most of sub-zero tests are performed on isothermal condition.Our previous works [1,2] introduced a unique single fuel cell hardware featuring temperature control and heat flux measurement (TCHM) system. Thermoelectric coolers and tangential gradient heat flux sensors enable a precise control of temperature in the MEA and detection of freezing and melting events during the cell operation. We have advanced the TCHM controlling software and integrated them on the custom fuel cell test bench. In this work, two novel techniques are introduced for sub-zero application for fuel cell porous media: (1) advanced calorimetry and (2) non-isothermal cold start.The advantages of our advanced calorimetry include testing of a large sample area up to 12cm2 and control of water quantity in a gas diffusion layer (GDL). Through neutron imaging, we validated capillary water injection method in the GDL and reduced saturation level with drying gas purging. Using techniques, we analyzed the effect of GDL structures and hydrophobicity on repeated freezing-thaw cycle to assist design of ice-resistant material. Additionally, we successfully implemented non-isothermal cold-start at -20 ºC in addition to isothermal condition, as seen in Figure 1. After the calibration of the TCHM units, the heating load was emulated to match that of the stack, corresponding to the heating rate between 10-15 K/min.The methods introduced in this study are expected to make a significant contribution towards the development of GDLs and catalyst layers that suppress ice formation and related mechanical damages. In particular, the non-isothermal cold-start provides a flexible, precise temperature control in the MEA, which can bridge the gap between the single cell and stack testing. Reference [1] J. Lee, E.R. Carreon-Ruiz, M. Siegwart, P. Boillat, Segmentation for Preventing Ice Propagation in Operating Fuel Cells, Meet. Abstr. MA2021-02 (2021) 1066. https://doi.org/10.1149/MA2021-02361066mtgabs.[2] M. Siegwart, F. Huang, M. Cochet, T.J. Schmidt, J. Zhang, P. Boillat, Spatially Resolved Analysis of Freezing during Isothermal PEFC Cold Starts with Time-of-Flight Neutron Imaging, Journal of The Electrochemical Society. 167 (2020) 064510. https://doi.org/10.1149/1945-7111/ab7d91. Figure 1

NextGen Training for Medical First Responders: Advancing Mass-Casualty Incident Preparedness through Mixed Reality Technology

Mixed reality (MR) technology has the potential to enhance the disaster preparedness of medical first responders in mass-casualty incidents through new training methods. In this manuscript, we present an MR training solution based on requirements collected from experienced medical first responders and technical experts, regular end-user feedback received through the iterative design process used to develop a prototype and feedback from two initial field trials. We discuss key features essential for an effective MR training system, including flexible scenario design, added realism through patient simulator manikins and objective performance assessment. Current technological challenges such as the responsiveness of avatars and the complexity of smart scenario control are also addressed, along with the future potential for integrating artificial intelligence. Furthermore, an advanced analytics and statistics tool that incorporates complex data integration, machine learning for data analysis and visualization techniques for performance evaluation is presented.

Analytical Techniques for Performance Evaluation of Fountain-Coded File Distribution in Packet Radio Networks

Convenient analytical techniques are developed for use in preliminary design of systems and protocols for the delivery of fountain-coded files from a source node to a destination node with the assistance of a relay node. Each node has a half-duplex packet radio, and the time-varying disturbance on each link is represented by a lumpable finite-state Markov chain. The analytical techniques include the use of first passage times and recurrence times in the derivation of an exact expression for the completion time of file transfer over a radio link and the application of results on Markov-correlated Bernoulli trials to obtain exact expressions for completion times of relay-aided file transfer in wireless networks. In the development of analytical techniques, we employ capacity-achieving channel codes and ideal fountain codes; however, we present simulation results for packet radios that employ practical channel codes and for which the fountain code is a standard systematic raptor code.

Design and Optimization of Smart Campus Framework Based on Artificial Intelligence22

In this study, an artificial intelligence (AI)--based smart campus framework is built and optimized with the aim of improving user happiness, raising AI model performance, maximizing resource utilization, and promoting smart campus adoption. The study technique employs a mixed-methods approach that combines quantitative data analysis and qualitative user feedback in order to completely evaluate the effectiveness of the framework. Literature reviews, Questionnaires of 544, interviews of 56 persons, and observations are used to collect data on user satisfaction, AI model performance, optimization strategies, and adoption of smart campuses AI models are built using statistical methodology and AI techniques for performance evaluation. In the Smart Campus Framework based on Artificial Intelligence, we gathered the data by constructing IoT sensor networks for real-time monitoring and merging student data to provide insights into academic performance and student engagement. The findings indicate that, on average, users are satisfied, and the performance ratings for the AI models vary from 7.25 to 8.25. The smart campus framework is effective, as evidenced by the optimization metric's 7.53 average score. A score of 7.4 for smart campus adoption combines user knowledge, perceived utility, and perceived ease of use. The practical implications include better user experience, cost optimization, and smart campus architecture. Theoretical implications include the verification of the mixed-methods strategy and the creation of a framework for AI model optimization. The study's findings act as a model for upcoming smart campus research, spurring creativity and change in institutions of higher learning. The study’s limitations suggest that results can be generalized with minor contextual change and this is the biggest challenge for researchers and policy makers.

Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems

In the current energy usage scenario, the demands on energy load and the tariffs on the usage of electricity are two main areas that require a lot of attention. Energy forecasting is an ideal solution that would help us to better understand future needs and formulate solutions accordingly. Some important factors to investigate are the quantity and quality of smart grids as they are significantly influenced by the transportation, storage, and load management of energy. This research work is a review of various machine learning algorithms for energy grid applications like energy consumption, production, energy management, design, vehicle-to-grid transfers, and demand response. Ranking is performed with the help of key parameters and is evaluated using the Rapid Miner tool. The proposed manuscript uses various machine learning techniques for the evaluation of power quality performance to validate an efficient algorithm ranking in a grid-connected system for energy management applications. The use of renewable energy resources in grid-connected systems is more common in modern power systems. Universally, the energy usage sector (commercial and non-commercial) is undergoing an increase in demand for energy utilization that has substantial economic and ecological consequences. To overcome these issues, an integrated, ecofriendly, and smart system that meets the high energy demands is implemented in various buildings and other grid-connected applications. Among various machine learning techniques, an evaluation of seven algorithms—Naïve Bayes, artificial neural networks, linear regression, support vector machine, Q-learning, Gaussian mixture model, and principle component analysis—was conducted to determine which algorithm is the most effective in predicting energy balance. Among these algorithms, the decision tree, linear regression, and neural networks had more accurate results than the other algorithms used. As a result of this research, a proposal for energy forecast, energy balance, and management was compiled. A comparative statement of various algorithms concludes with results which suit energy management applications with high accuracy and low error rates.

Performance Evaluation of an Occupancy-Based HVAC Control System in an Office Building

As new algorithms incorporate occupancy count information into more sophisticated HVAC control, these technologies offer great potential for reductions in energy costs while enhancing flexibility. This study presents results from a two-year field evaluation of an occupancy-based HVAC control system installed in an office building. Two wings on each of the building’s 2–11 floors were equipped with occupancy counters to learn occupancy patterns. In combination with proprietary machine learning algorithms and thermal modeling, the occupancy data were leveraged to implement optimized start, early closure, and adjustments to fan operation at the air handling unit (AHU) level. This study conducted a holistic evaluation of technical performance, cost-effectiveness analysis, and user satisfaction. Results show the platform reduced weekday AHU run times by 2 h and 35 min per AHU per day during the pandemic time period. Simulation shows that 6.1% annual whole-building savings can be achieved when the building is fully occupied. The results are compared with prior studies, and potential drivers are discussed for future opportunities. The assessment results shed light on the expected in-the-field performance for researchers and industry stakeholders and enabled practical considerations as the technology strives to move beyond research-grade pilot trials into product-grade deployment.

Categorization of Select Cockpit Performance Evaluation Techniques.

INTRODUCTION: The modern aircraft cockpit has evolved into a complex system of systems. Numerous performance evaluation metrics and techniques exist that can measure the effectiveness of cockpit components in terms of how they influence the human operator's ability to perform tasks relevant to mission success. As no prior review of these metrics has been found in the literature, this effort attempts to do so, albeit without applying the metrics to a novel cockpit evaluation.METHODS: These metrics and techniques are discussed and presented in five defined categories as they relate to evaluating cockpit subsystems: ergonomics and anthropometrics; human-computer interaction; data management and presentation; crew resource management and operations; and ingress and egress.DISCUSSION: While this effort is significant and novel, it is not necessarily comprehensive. In conclusion, it is noted that no single holistic quantitative metric to evaluate cockpit design and performance yet exists. Utilizing some of the preexisting metrics presented to develop such a metric would be beneficial in efforts to evaluate aircraft cockpit designs and performance, as well as aiding future cockpit designs.Brighton EM, Klaus DM. Categorization of select cockpit performance evaluation techniques. Aerosp Med Hum Perform. 2023; 94(9):696-704.

Experimental evaluation of three different dehumidifiers for greenhouses in cold regions

Selecting a dehumidifier is not easy for greenhouse growers because of its high capital and operation cost and new emerging technologies, besides selection variations with crop species, local weather climate, and greenhouse sizes. The technical performance evaluation of various dehumidification technologies in commercial-scale greenhouse settings and their comparative results can give growers the new information needed to select the best dehumidifier. In this study, the field performance of a newly developed state point liquid desiccant (SPLD) dehumidifier is compared with two other commercial dehumidification technologies; direct contact liquid desiccant (DCLD) dehumidifier, and heat recovery ventilator (HRV), in ornamental (rose) and tomato greenhouses. Under the test condition, among the three dehumidifiers, the HRV unit had the highest calculated moisture removal rate (MRR) of 189.1 kg hr-1, the lowest moisture removal cost of 0.022 $ kg−1, and the lowest electricity consumption (0.02 kWh kg−1 of moisture removal). The highest electrical consumption was found in the SPLD unit under the wet mode, with an average of 0.44 kWh kg−1. However, the SPLD-wet mode was the most efficient regarding net energy consumption (0.53 kWh kg−1). The DCLD showed a moderate performance on electrical energy (0.15 kWh kg−1) and net energy consumption (0.775 kWh kg−1) with good indoor humidity control. The SPLD unit under dry mode was similar to the HRV unit regarding moisture removal cost (0.026 $ kg−1) and electricity consumption (0.046 kWh kg−1). The comparative results of this study indicate that a single dehumidification technique cannot be both technically effective and economically cost-saving year-round. Thus, combining a low-cost technology, such as ventilation or a heat exchanger, and an internal dehumidification technology will be the most practical and feasible in cold regions.

Application of Acoustic Emission as Damage Assessment Technique for Performance Evaluation of Concrete Structures: A Review

A significant increase in existing inspection efforts and the creation of more resilient structures using built-in sensors and systems is essential for accurate and reliable assessment and monitoring of structural conditions in order to minimize the risk of catastrophic failure. The acoustic emission (AE) technique could immensely benefit the damage assessment, real-time checking of structural integrity under operating conditions, and identification of the operational risk factors along with the causes of initiation and development of flaws. Therefore, this article presents a comprehensive overview of AE as a potential damage assessment and localization technique to determine the performance and behavior of reinforced concrete (RC) members along with an overview of the latest research in computational AE damage modeling and machine learning tools to optimize the accurate interpretation of voluminous AE data. The primary aim of this review is to identify specific gaps in the literature pertaining to concrete structures that need immediate attention of the researchers working in this domain. The identification of damage mechanisms based on AE events and parameters covered in this review would enable researchers to identify damage sources nondestructively in situ and produce large data sets for detailed statistical analyses of the effects of small-scale local damages in large-scale concrete structures. This review will also be helpful for practicing engineers to choose between different available AE parameters based on the limitations and advantages of these parameters for specific inspection and maintenance requirements of various types of RC structural elements, loading conditions, and failure.

Performance evaluation technique for screen‐to‐camera‐based optical camera communications

AbstractThe increasing development and utilisation of optical camera communications offer an excellent opportunity for the implementation of the smartphone‐to‐smartphone‐based visible light communications (S2SVLC) system. In this study, the authors experimentally demonstrate that the S2SVLC system can support high‐quality multimedia transmissions by the investigation of the mean square error estimation, peak signal‐to‐noise (PSNR) degradation, bit error rate (BER), and data rate achieved. The experimental analysis has been carried out for different typical practical background illuminations (i.e., normal illumination and dark condition), distances, tilting, and rotation angles. The PSNR and BER are determined for different frame sizes in the S2SVLC system to provide an insight of system performance. Those results indicate that the data transmission at different conditions significantly impacts the system's performance.

A Rigorous and Integrated On-Water Monitoring System for Performance and Technique Improvement in Rowing.

This paper presents a prototype, on-water rowing monitoring system and its testing results for a single scull boat. The proposed system aims at recording critical kinetic (athlete biomechanics and oar/seat movements) and kinematic (boat position, velocity, acceleration, and attitude) parameters for sport performance evaluation and rowing technique improvement. The data acquisition unit is organized in two parts: the first part aims at logging boat kinematics based on GNSS/INS filtering, while the second one facilitates kinetics data recording using a series of analog sensors (potentiometers, strain gauges) installed on the athlete's body and the boat seat and oars. Both parts are connected to a central unit featuring analog voltage digitizers and a micro-PC for device handling and data storing. In order to test the performance of the system a series of field trials were undertaken featuring different observation scenarios as well as intentionally induced errors in the rowing technique. Analysis revealed the high performance of the system in terms of sensor completeness and setup procedures as well as operational efficiency. Moreover, system performance evaluation exercised through studying raw data recordings and resultant parameters at stroke cycle and average (standardized) stroke cycle level confirmed the fruitfulness of the proposed approach and system and its potential for implementation on a broad scale. Finally, the data acquired from the proposed system were used to compute the adopted input parameters and performance indicators to characterize the system in terms of functionality and operational efficiency.

A Dynamic and Adaptive Cybersecurity Governance Framework

Cybersecurity protects cyberspace from a wide range of cyber threats to reduce overall business risk, ensure business continuity, and maximize business opportunities and return on investments. Cybersecurity is well achieved by using appropriate sets of security governance frameworks. To this end, various Information Technology (IT) and cybersecurity governance frameworks have been reviewed along with their benefits and limitations. The major limitations of the reviewed frameworks are; they are complex and have complicated structures to implement, they are expensive and require high skill IT and security professionals. Moreover, the frameworks require many requirement checklists for implementation and auditing purposes and a lot of time and resources. To fill the limitations mentioned above, a simple, dynamic, and adaptive cybersecurity governance framework is proposed that provides security related strategic direction, ensures that security risks are managed appropriately, and ensures that organizations’ resources are utilized optimally. The framework incorporated different components not considered in the existing frameworks, such as research and development, public-private collaboration framework, regional and international cooperation framework, incident management, business continuity, disaster recovery frameworks, and compliance with laws and regulations. Moreover, the proposed framework identifies and includes some of the existing frameworks’ missed and overlapped components, processes, and activities. It has nine components, five activities, four outcomes, and seven processes. Performance metrics, evaluation, and monitoring techniques are also proposed. Moreover, it follows a risk based approach to address the current and future technology and threat landscapes. The design science research method was used in this research study to solve the problem mentioned. Using the design science research method, the problem was identified. Based on the problem, research objectives were articulated; the objective of this research was solved by developing a security governance framework considering different factors which were not addressed in the current works. Finally, performance metrics were proposed to evaluate the implementation of the governance framework.