Search results for: Farbod Behnaminia

Authors: Farbod Behnaminia, Saeed Samet

Abstract:

The COVID-19 pandemic has paralyzed many lives until a vaccine was available, which caused the so-called “new normal.” According to the World Health Organization (WHO), COVID-19 is an infectious disease. It can cause significant illness or death in anyone. Governments and health officials tried to impose rules and regulations to avoid and slow down transmission. Therefore, software engineers worldwide developed applications to trace and track patients’ movements and notify others, mainly using Bluetooth. In this way, everyone could be informed whether they come in close contact with someone who has COVID-19 and takes proper safety precautions. Because most of the applications use technologies that can potentially reveal the user’s identity and location, researchers have debated privacy preservation and how to improve user privacy during such pandemics. Thanks to Distributed Ledger Technology (DLT), there have been some proposed methods to develop privacy-preserving Patient Tracking Systems in the last two years. As an instance of the DLT, Blockchain is like a decentralized peer-to-peer database that maintains a record of transactions. Transactions are immutable, transparent, and anonymous in this system. We conducted a comprehensive evaluation of the literature by looking for papers in the relevant field and dividing them into pre- and post-pandemic systems. Additionally, we discussed the many uses of blockchain technology in pandemic control. We found that two major obstacles facing blockchain implementation across many healthcare systems are scalability and privacy. The Polkadot platform is presented, along with a review of its efficacy in tackling current concerns. A more scalable healthcare system is achievable in the near future using Polkadot as well as a much more privacy-preserving environment.

Keywords: blockchain, electronic record management, EHR, privacy-preserving, patient tracking, COVID-19, trust and confidence, Polkadot

Procedia PDF Downloads 101

Authors: Farbod Rohani, Elyar Ghafoori, Matin Saeedkondori

Abstract:

Impulse noise is electromagnetic emission which generated by many house hold appliances that are attached to the electrical network. The main difficulty of impulsive noise (IN) elimination process from communication channels is to distinguish it from the transmitted signal and more importantly choosing the proper threshold bandwidth in order to eliminate the signal. Because of wide band property of impulsive noise, we present a novel method for setting the detection threshold, by taking advantage of the fact that impulsive noise bandwidth is usually wider than that of typical communication channels and specifically OFDM channel. After IN detection procedure, we apply simple windowing mechanisms to eliminate them from the communication channel.

Keywords: impulsive noise, OFDM channel, threshold detecting, windowing mechanisms

Procedia PDF Downloads 341

Authors: Mahla Zabet, Navid Zanganeh, Hafez Balavi, Farbod Sharif

Abstract:

Electrodeposition is a method for applying coatings with uniform thickness on complex objects. A conductive surface can be produced using the electrical current in this method. Carbon nanotubes are known to have high electrical conductivity and mechanical properties. In this report, NH2-multiwalled carbon nanotubes (MWCNTs) were used in epoxy resin with different weight percent. The weight percent of incorporated MWCNTS into the matrix was changed in the range of 0.6-3.6 wt% to obtain a series of electrocoatings. The electrocoats were then applied on steel substrates by a cathodic electrodeposition technique. Scanning electron microscopy (SEM) and optical microscopy were used to characterize the electrocoated films. The results illustrated the increase in conductivity by increasing of MWCNT load. However, at the percolation threshold, throwing power was dropped with increase in recoating ability.

Keywords: electrodeposition, carbon nanotube, electrical conductivity, throwing power

Procedia PDF Downloads 414

Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach

Procedia PDF Downloads 277

Authors: Navid Zanganeh, Hafez Balavi, Farbod Sharif, Mahla Zabet, Marzieh Bakhtiary Noodeh

Abstract:

Cerium oxide (CeO2) also known as cerium dioxide or ceria is a pale yellow-white powder with various applications in the industry from wood coating to cosmetics, filtration, fuel cell electrolytes, gas sensors, hybrid solar cells and catalysts. In this research, attempts were made to synthesize and characterization of CeO2 nano-particles via sol-gel method. In addition, the effect of aging time on the size of particles was investigated. For this purpose, the aging times adjusted 48, 56, 64, and 72 min. The obtained particles were characterized by x-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), transmitted electron microscopy (TEM), and Brunauer–Emmett–Teller (BET). As a result, XRD patterns confirmed the formation of CeO2 nanoparticles. SEM and TEM images illustrated the nano-particles with cluster shape, spherical and a nano-size range which was in agreement with XRD results. The finest particles (7.3 nm) was obtained at the optimum condition which was aging time of 48 min, calcination temperature at 400 ⁰C, and cerium concentration of 0.004 mol. Average specific surface area of the particles at optimum condition was measured by BET analysis and recorded as 47.57 m2/g.

Keywords: aging time, CeO2 nanoparticles, size distribution, sol-gel

Procedia PDF Downloads 456

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

Abstract:

Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

Procedia PDF Downloads 211