Abbas Najjar-Khodabakhsh and Jafar Soltani
In this paper an adaptive nonlinear control scheme has been proposed for direct torque and flux control of interior permanent magnet synchronous motor (IPMSM) without using…
Abstract
Purpose
In this paper an adaptive nonlinear control scheme has been proposed for direct torque and flux control of interior permanent magnet synchronous motor (IPMSM) without using mechanical sensor.
Design/methodology/approach
In this control method the stator resistance is online estimated by adaptive input-output state feedback linearization (AIOFL) controller. Based on proposed control scheme, the strategies of the maximum torque per ampere (MTPA) and maximum power factor (MPF) have been tested using a so-called stator flux search method.
Findings
The motor equations are transferred from the stationary reference frame to the (SX-SY) two-axis frame of the current by the stator current angle. In this frame, the Y component of the motor current is set to zero and the implementation of the nonlinear controller is independent of the two-axis inductances, the rotor magnetic flux, and position.
Practical implications
The effectiveness and capability of the proposed control method has been verified by simulation and experimental results. The proposed control scheme can be used for the sensorless control of IPMSM drive in industrial applications such as electric vehicle, traction system, and air conditioner.
Originality/value
The proposed controller is developed in a special axis (X-Y) rotating reference frame with the X-axis in coincide with the machine current space vector so that there is no need to use and know the machine inductances and rotor position.
Niloufar Ghafari Someh, Mir Saman Pishvaee, Seyed Jafar Sadjadi and Roya Soltani
Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory…
Abstract
Purpose
Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.
Design/methodology/approach
In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.
Findings
The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.
Originality/value
The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.
Details
Keywords
A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and…
Abstract
A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.
Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.
Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.
Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.
Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.
Details
Keywords
Sayed Arash Hosseini Sabzevari, Zoheir Mottaki, Atoosa Hassani, Somayeh Zandiyeh and Fereshteh Aslani
Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it…
Abstract
Purpose
Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it is necessary to create pre-disaster location plans for the homeless population. This study aims to systematically find safe places and select suitable sites according to influential factors.
Design/methodology/approach
The research methodology used is a descriptive–analytical method. A field survey with a quantitative–qualitative approach is applied to recognize physical vulnerabilities and select suitable sites for temporary settlements. Due to the occurrence of several earthquakes in recent decades around the city of Isfahan, Iran, this area has been studied. Fuzzy analytic hierarchy process, geographic information system and rapid visual screening have been used for data analysis.
Findings
According to the site selection and vulnerability criteria and their prioritization, the findings indicate that 60% of the study area is vulnerable. Moreover, vacant lots, stadiums and public green spaces that can be used as multi-purpose sites are the most appropriate options for the temporary settlement.
Practical implications
The research criteria are generalizable and can be used for decision-making, concerning urban fabric vulnerability and site selection of temporary housing in cities exposed to earthquake risk.
Originality/value
Cultural features, accessibility, land conditions, the slope and type of land, availability and construction materials were addressed in locating temporary settlements. In addition to vacant lots and open spaces, safe buildings were also identified for temporary housing, and religious minorities and similar communities were considered.
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Ali Yousefi, Saeed Amir Aslanzadeh and Jafar Akbari
The purpose of this paper is to investigate the surface properties, particle sizes and corrosion inhibition performance of sodium dodecyl sulfate (SDS) in the presence of…
Abstract
Purpose
The purpose of this paper is to investigate the surface properties, particle sizes and corrosion inhibition performance of sodium dodecyl sulfate (SDS) in the presence of imidazolium-based ionic liquid as an additive. Up to now, different properties of alone surfactants and ionic liquids have been studied. However, few studies have been devoted to mixed ionic liquid and surfactant. The significance and novelty of this research is the investigation of 1-methylimidazolium trinitrophenoxide ([MIm][TNP]) as ionic liquid effects on SDS corrosion behavior.
Design/methodology/approach
The inhibition effect of [MIm][TNP], SDS and their mixtures on mild steel surface in 2 M hydrochloric acid (HCl) solution was examined by electrochemical impedance spectroscopy, potentiodynamic polarization (PDP), scanning electron microscopy (SEM), atomic force microscopy and quantum chemical calculations as well as dynamic light scattering (DLS) and surface tension measurements to discuss surface properties of studied solutions.
Findings
Based on the results, ionic liquid/SDS mixtures significantly indicated better inhibition properties than pure surfactant solution. PDP curves indicated that the studied compounds act as mixed-type of inhibitors. The critical micelle concentration, surface properties and particle sizes were investigated from the surface tension measurements and DLS results.
Originality/value
Adsorption of the inhibitors on the steel surface obeyed the Villamil adsorption model. SEM was used for surface analysis and verified the inhibition efficiency of mixed IL/SDS system. Quantum chemical calculations were performed using density functional theory, and a good relationship between experimental and theoretical data has been obtained.
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Behnam Malmir and Christopher W. Zobel
When a large-scale outbreak such as the COVID-19 pandemic happens, organizations that are responsible for delivering relief may face a lack of both provisions and human resources…
Abstract
Purpose
When a large-scale outbreak such as the COVID-19 pandemic happens, organizations that are responsible for delivering relief may face a lack of both provisions and human resources. Governments are the primary source for the humanitarian supplies required during such a crisis; however, coordination with humanitarian NGOs in handling such pandemics is a vital form of public-private partnership (PPP). Aid organizations have to consider not only the total degree of demand satisfaction in such cases but also the obligation that relief goods such as medicine and foods should be distributed as equitably as possible within the affected areas (AAs).
Design/methodology/approach
Given the challenges of acquiring real data associated with procuring relief items during the COVID-19 outbreak, a comprehensive simulation-based plan is used to generate 243 small, medium and large-sized problems with uncertain demand, and these problems are solved to optimality using GAMS. Finally, post-optimality analyses are conducted, and some useful managerial insights are presented.
Findings
The results imply that given a reasonable measure of deprivation costs, it can be important for managers to focus less on the logistical costs of delivering resources and more on the value associated with quickly and effectively reducing the overall suffering of the affected individuals. It is also important for managers to recognize that even though deprivation costs and transportation costs are both increasing as the time horizon increases, the actual growth rate of the deprivation costs decreases over time.
Originality/value
In this paper, a novel mathematical model is presented to minimize the total costs of delivering humanitarian aid for pandemic relief. With a focus on sustainability of operations, the model incorporates total transportation and delivery costs, the cost of utilizing the transportation fleet (transportation mode cost), and equity and deprivation costs. Taking social costs such as deprivation and equity costs into account, in addition to other important classic cost terms, enables managers to organize the best possible response when such outbreaks happen.