Search results for: Seddighi Amir Saeed

Authors: M. D. Saeed, S. O. Oladeji

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The level of cobalt was determined in wastewater and vegetable (carrot, lettuce, onion, spinach, cabbage, tomato and okro) samples collected on seasonal basis from December, 2012 to September 2014 along Kubanni stream channels in Zaria. The results showed cobalt concentrations in wastewater were in the range of 3.77 – 15.20 mg/L for the year 2013 and 4.74 – 15.20 mg/L in 2014 while the vegetable had concentrations in the range of 1.25 – 8.75 mg/Kg for the year 2013 and 2.76 – 12.45 mg/Kg in 2014. Statistical analysis revealed a significant difference in cobalt levels across the locations for wastewater and vegetables whereas seasons (harmattan, dry and rainy) showed no significant difference in wastewater and vegetables analyzed. Pearson correlation revealed substantial (r = 0.726) relationship between cobalt levels in wastewater for the year 2013 and 2014 likewise, substantial (r = 0.750) relationship was also obtained for vegetables cultivated in 2013 and 2014 respectively. Cobalt concentrations obtained in this study was higher than Maximum Contaminant Levels set by Standard Organization such as W.H.O. and F.A.O. for wastewater; however, vegetables indicated no contamination with cobalt metal.

Keywords: cobalt, concentration, wastewater, vegetable

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Amir Reza Radmanesh, Sina Farajzadeh Khosroshahi, Hani Sadr

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The transient catalytic converter performance is governed by complex interactions between exhaust gas flow and the monolithic structure of the catalytic converter. Stringent emission regulations around the world necessitate the use of highly-efficient catalytic converters in vehicle exhaust systems. Computational fluid dynamics (CFD) is a powerful tool for calculating the flow field inside the catalytic converter. Radial velocity profiles, obtained by a commercial CFD code, present very good agreement with respective experimental results published in the literature. However the applicability of CFD for transient simulations is limited by the high CPU demands. In the present work, Geometric modeling ceramic monolith substrate is done with square shaped channel type of Catalytic converter and it is coated platinum and palladium. This example illustrates the effect of flow distribution on thermal response of a catalytic converter and different gas flow velocities, during the critical phase of catalytic converter warm up.

Keywords: catalytic converter, computational fluid dynamic, porous media, velocity distribution

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Authors: Bruno Henrique Rocha Fernandes, Amir Rezaee, Jucelia Appio

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The relation between Human Resource Management (HRM) practices and organizational performance remains the subject of substantial literature. Though many studies demonstrated positive relationship, still major influencing variables are not yet clear. This study considers the Person-Environment Fit (PE Fit) and its components, Person-Supervisor (PS), Person-Group (PG), Person-Organization (PO) and Person-Job (PJ) Fit, as possible explanatory variables. We analyzed PE Fit as a moderator between HRM practices and financial performance in the “best companies to work” in Brazil. Data from HRM practices were classified through the High Performance Working Systems (HPWS) construct and data on PE-Fit were obtained through surveys among employees. Financial data, consisting of return on invested capital (ROIC) and price earnings ratio (PER) were collected for publicly traded best companies to work. Findings show that PO Fit and PJ Fit play a significant moderator role for PER but not for ROIC.

Keywords: financial performance, human resource management, high performance working systems, person-environment fit

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Authors: Nassibeh Hosseini-Vasoukolaei, Amir Ahmad Akhavan, Mahmood Jeddi-Tehrani, Ali Khamesipour, Mohammad Reza Yaghoobi Ershadi, Kamhawi Shaden, Valenzuela Jesus, Hossein Mirhendi, Mohammad Hossein Arandian

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Zoonotic cutaneous leishmaniasis (ZCL) is an endemic disease in many rural areas of Iran. Sand flies were collected from rural areas of Esfahan province and were identified using valid identification keys. DNA was extracted from sand flies and Nested PCRs were done using specific primers. In this study, 44 out of 152 (28.9 %) sand flies were infected with L. majoralone. Eight sand flies showed mixed infection: four sand flies (2.6 %) were infected with L. major, L. turanicaand L. gerbili, one sand fly (0.7 %) was infected with L. major and L. turanica and three sand flies (2 %) were infected with L. turanicaand L. gerbili. Our results demonstrate the natural infection of P. papatasi sand fly with three species of L. major, L. turanica and L. gerbili which are circulating among R. opimusreservoir host and P. papatasi sand fly vector in central Iran.

Keywords: Phlebotomus papatasi, Leishmania major, Leishmania turanica, Leishmania gerbili, mixed infection, Iran

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Authors: Nagat M. Saeed, Mabruka S. Elashheb, Fatma M. Ben Rabaha, Aisha M Edrah

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The aim of the study was to determine the type and pattern of antibiotic susceptibility of the pathogenic microorganisms causing chronic suppurative otitis media (CSOM), which could lead to better therapeutic decisions and consequently avoidance of appearance of resistance to specific antibiotics. Most frequently isolated agents were Pseudomonas aeruginosa 28.5%; followed by Staphylococcus aureus 18.2%; proteus mirabilis 13.9%; Providencia stuartti 6.7%; Bacteroides melaninogenicus, Aspergillus sp., candida sp., 4.2% each; and other microorganisms were represented in 3-0.2%. Drug sensitivities pattern of Pseudomonas aeruginosa showed that ciprofloxacin was active against the majority of isolates (93.9%) followed by ceftazidime 86.2%, amikacin 76.2% and gentamicin 40.8%. However, Staphylococcus aureus isolates were resistant to penicillin 72.7%, erythromycin 28.6%, cephalothin 18.2%, cloxacillin 8.3% and ciprofloxacin was active against 96.2% of isolates. The resistance pattern of proteus mirabilis was 55.6% to ampicillin, 47.1% to carbencillin, 29.4% to cephalothin, 14.3% to gentamicin and 4.8% to amikacin while 100% were sensitive to ciprofloxacin. We conclude that ciprofloxacin is the best drug of choice in the treatment of CSOM caused by the common microorganisms.

Keywords: otitis media, chronic suppurative otitis media (CSOM), microorganisms, drug sensitivity

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Authors: Rabia Shabbir, Sheikh Saeed Ahmad, Amna Butt

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Rapid land use changes have taken place in Islamabad, the capital city of Pakistan, over the past decades due to accelerated urbanization and industrialization. In this study, land use changes in the metropolitan area of Islamabad was observed by the combined use of GIS and satellite remote sensing for a time period of 15 years. High-resolution Google Earth images were downloaded from 2000-2015, and object-based classification method was used for accurate classification using eCognition software. The information regarding urban settlements, industrial area, barren land, agricultural area, vegetation, water, and transportation infrastructure was extracted. The results showed that the city experienced a spatial expansion, rapid urban growth, land use change and expanding transportation infrastructure. The study concluded the integration of GIS and remote sensing as an effective approach for analyzing the spatial pattern of urban growth and land use change.

Keywords: land use change, urban growth, Islamabad, object-based classification, Google Earth, remote sensing, GIS

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis

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Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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Authors: Iqra Khan, Ghousia Saeed, Salman Jamil

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Fashion is the soul of styles. People of all times want to look trendy, eye catching and unique among all. For this reason, people always adopt different flairs in their outfits including their clothes, shoes, bags and other accessories. However, unfortunately, there is lack of opportunity for accommodating the fashion exposure activities expressed with the folk dances of different regions so as to exhibit the fashion of Pakistan to the world. The paper focuses on the vibrant setting of the whole building according to the social patterns, folk and local trends and existing environment of Lahore. This is done by studying each of the aspect obtained from objectives through research questions evolved from the objectives. The answers to these questions are found through case studies and the existing theories in the world in relevance to the topic. The paper finds out how the geometry of dance works with design principles to create transparent geometry of fashion building. This all creates the fiesta environment taken from the locality of the region from the local and cultural lifestyles of the locals and then assembling it together to create a full festivity experience throughout the building.

Keywords: fashion, folk dance, geometry, local trends, social patterns, transparent

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Authors: G. Fatima, R. Bashir, M. Saeed Akhtar, M. Malik, M. Safder, D. Nayab

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The main purpose of this quantitative study was to investigate challenges and difficulties being encountered by physically challenged students in inclusive settings at higher education level. A self-developed and validated questionnaire (Cronbach alpha: 0.879) was employed for data collected from a sample of fifty six (56) graduate and continuing students with physical disabilities (males:46, females:10) selected through snow ball sampling technique from colleges and universities of Pakistan. The participants were required to respond on three point criteria (no, to some extent, yes). Data were analyzed by using SPSS. Independent sample t-test and One Way Analysis of Variance (ANOVA) was run to compare mean scores of responses of physically challenged students on the basis of their gender, education, types of physical disability, types of institutions, provinces, and status. Frequencies were run to have an overall picture of challenges faced by physically challenged students. Major findings reflected that physically challenged students were encountering problems in transportation, accessibility, and financial support, etc. Conclusions were drawn and recommendations were made.

Keywords: physically challenged students, inclusive setting, higher education, accessibility

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Abasali Amini, Alireza Mirbagheri, Amir Homayoun Jafari

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In this paper, a new structure for teleoperation systems with time varying delay has been modeled and proposed. A random time varying the delay of up to 150 msec is simulated in teleoperation channel of both masters to slave and vice versa. The system stability and transparency have been investigated, comparing the result of a PID controller and an optimal controller on each master and slave sub-systems separately. The controllers have been designed in slave subsystem for reducing position errors between master and slave, and another controller has been designed in the master subsystem to establish stability, transparency and force tracking. Results have been compared together. The results showed PID controller is appropriate in position tracking, but force response oscillates in contact with the environment. We showed the optimal control established position tracking properly. Also, force tracking is achieved in this controller appropriately.

Keywords: optimal control, time varying delay, teleoperation systems, stability and transparency

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Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

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Authors: Amir Mukhtar, Dr. Likun Xia

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An improved, robust and efficient visual target tracking algorithm using particle filtering is proposed. Particle filtering has been proven very successful in estimating non-Gaussian and non-linear problems. In this paper, the particle filter is used with color feature to estimate the target state with time. Color distributions are applied as this feature is scale and rotational invariant, shows robustness to partial occlusion and computationally efficient. The performance is made more robust by choosing the different (YIQ) color scheme. Tracking is performed by comparison of chrominance histograms of target and candidate positions (particles). Color based particle filter tracking often leads to inaccurate results when light intensity changes during a video stream. Furthermore, background subtraction technique is used for size estimation of the target. The qualitative evaluation of proposed algorithm is performed on several real-world videos. The experimental results demonstrate that the improved algorithm can track the moving objects very well under illumination changes, occlusion and moving background.

Keywords: tracking, particle filter, histogram, corner points, occlusion, illumination

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Authors: Masood Roohi, Amir Taghavipour

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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: Iram Batool, Aamer Saeed, Irfan Zia Qureshi, Ayesha Razzaq, Saima Kalsoom

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Heterocyclic compounds analogues and their derivatives have attracted strong interest in medicinal chemistry due to their biological and pharmacological properties. A series of new thiazolopyrimidine carboxylates were conveniently synthesized by one-pot three-component reaction of ethyl acetoacetate, 2-aminothiazole and benzaldehyde substituted with electron-donating and electron-withdrawing groups in order to find some more potent antidiabetic and antibacterial drugs. The structures of synthesized compounds were characterized by elemental analysis, IR, 1H NMR, 13C NMR spectroscopy. An in vitro antidiabetic effect was evaluated in adult male BALB/c mice and antibacterial activities were tested against Micrococcus luteus, Salmonella typhimurium, Bacillus subtilis, Bordetella bronchiseptica and Escherichia coli. Some of the tested compounds proved to possess good to excellent activities more than the reference drugs. An in silico molecular docking was also performed on synthesized compounds. The current study is expected to provide useful insights into the design of antidiabetic and antibacterial drugs and understanding the mechanism by which such drugs interact with RNA and diabetes target and exert their biochemical action.

Keywords: antidiabetic, antibacterial, MOE docking, thiazolopyrimidine

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Authors: Muhammad Asif Qayyoum, Bilal Saeed Khan

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Poultry red mites (Dermanyssus gallinae De Geer) are economically deleterious parasite of hens in poultry industry in all over the world. Due to lack of proper control managements and result of poor application of commercial products, D. gallinae get resistance and severe infestation in poultry birds. Laboratory experiment was planned for the control of D. gallinae by using different mushroom and plant extracts. We used control treatment (100 ml distilled water) and nine treatments (10 gr Lentinula adobas, Ganoderma lucidum and Pleurotus aryngii with 100 ml methanol, 1% and 2% Neemazal, 1.5% Gamma-T-ol, Echinacea Leaf , 1.5% Fungatol with neem spray and Methanol) with five replication having five mites each. Data collected after 12 and 24 hours every day till mites found dead in every treatment. The significant differences among the mean values were compared with the DUNCAN multiple range test. The efficacy (%) of each treatment was determined with the Abbott formula. All statistical analyses were conducted with the SPSS Version 12 program. Lentinula edodes (80%), Ganoderma lucidum (76%) and Fungatol+Neem spray (1.5%) (80%) were significant against D. gallinae within 3 days.

Keywords: mushroom extracts, plant extracts, D. gallinae, control

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Authors: Milad Keshvardoost, Amir Khanlari, Nader Khalesi

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Background: Any firm in the pharmaceutical industry requires efficient and effective management information systems (MIS) to support managerial functions. Purpose: The aim of this study is to investigate the impact of Task-Technology Fit on user effectiveness, efficiency, and creativity in Iranian pharmaceutical companies. Methodology: 345 reliable and validate questionnaires were distributed among selected samples, through the cluster method, to Information system users of eight leading Iranian pharmaceutical companies, based on the likert scale. The proposed model of the article is based on a model with Task technology fit, on user performance with the definition of efficiency, effectiveness, and creativity through mediation effects of perceived usefulness and ease of use. Results: This study confirmed that TTF with definitions of adequacy and compatibility has positive impacts on user performance Conclusion: We concluded that pharmaceutical users of IS, utilizing a system with a precise and intense observation of users' demands, may make facilitation for them to design an exclusive IS framework.

Keywords: information systems, user performance, pharmaceuticals, task technology fit

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Faramarz Khoshnoudian, Saeed Vosoughiyan

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The main goal of this article is to clarify the soil-structure interaction (SSI) effects on the seismic performance of steel moment resisting frame buildings which are rested on soft soil and equipped with viscous fluid dampers (VFDs). For this purpose, detailed structural models of a ten-story SMRF with VFDs excluding and including the SSI are constructed first. In order to simulate the dynamic response of the foundation, in this paper, the simple cone model is applied. Then, the nonlinear time-history analysis of the models is conducted using three kinds of earthquake excitations with different intensities. The analysis results have demonstrated that the SSI effects on the seismic performance of a structure equipped with VFDs and supported by rigid foundation on soft soil need to be considered. Also VFDs designed based on rigid foundation hypothesis fail to achieve the expected seismic objective while SSI goes into effect.

Keywords: nonlinear time-history analysis, soil-structure interaction, steel moment resisting frame building, viscous fluid dampers

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Authors: Bernhard Bauer, Thomas Meixner, Amir Dini, Detlef Heck

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The inner city building stock is characterized by different types of buildings of different decades and centuries and different types of historical constructions. Depending on the natural growth of a city, those types are often located in downtown areas and the surrounding suburbs. Since the population is becoming older and the variation of the different social requirements spread with the so-called 'Silver Society', city quarters have to be seen alternatively. If an area is very attractive for young students to live there because of the busy nightlife, it might not be suitable for the older society. To identify 'Location Types A, B, C' for different user groups, qualitative interviews with 24 citizens of the city of Graz (Austria) have been carried out, in order to identify the most important values for making a location or city quarter 'A', 'B', or 'C'. Furthermore these acknowledgements have been put into a softwaretool for predicting locations that are the most suitable for certain user groups. On the other hands side, investors or owners of buildings can use the tool for determining the most suitable user group for the location of their building or construction project in order to adapt the project or building stock to the requirements of the users.

Keywords: building stock, location parameters, inner city population, built environment

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using questionnaire of stated preference models users’ departure time choice affected by congestion pricing plan in downtown Tehran. Experimental results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: modeling, departure time, travel timing, time of the day, congestion pricing, transportation planning

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir

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The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.

Keywords: exchange rate, ARIMA, GARCH, PAK/USD

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Authors: Nader Pourmahmoud, Amir Hassanzadeh

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This article investigates the effects of inlet pressure in a newly introduced vortex tube which has been equipped with an additional vortex chamber. A 3-D compressible turbulent flow computation has been carried out toward analysis of complex flow field in this apparatus. Numerical results of flows are derived by utilizing the standard k-ε turbulence model for analyzing high rotating complex flow field. The present research has focused on cooling effect and given a characteristics curve for minimum cool temperature. In addition, the effect of inlet pressure for both chambers has been studied in details. To be presented numerical results show that the effect of inlet pressure in second chamber has more important role in improving the performance of the vortex tube than first one. By increasing the pressure in the second chamber, cold outlet temperature reaches a higher decrease. When both chambers are fed with high pressure fluid, best operation condition of vortex tube occurs. However, it is not possible to feed both chambers with high pressure due to the conditions of working environment.

Keywords: energy separation, inlet pressure, numerical simulation, vortex chamber, vortex tube

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Authors: Saeed M. Al Qahtani, Alaa Eldin A. Ayoub

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The study aimed to develop a battery of measures to assessment gifted initiatives in Saudi Arabia. The battery consisted of 17 measures developed in light of Saudi Arabia's future vision objectives for gifted education. A battery was applied to 193 gifted students who benefit from gifted initiatives and programs, 42 teachers of gifted as well as, 40 experts of gifted. Samples were taken from three main regions: Riyadh, Sharqia, Gharbia in Saudi Arabia. The results indicated that battery measures have a reliability and stability index ranging from 0.6 to 0.87. Besides that, results showed that the educational environment lacks many basic components such as facilities, laboratories, and activities that may stimulate creativity and innovation. Furthermore, results showed that there is a weakness in private sector involvement in the construction of educational buildings, special centers for gifted people and the provision of certain facilities that support talented programs. The recommendations of the study indicate the need for the private sector participation in the provision of services and projects for the care of gifted students in Saudi Arabia.

Keywords: battery of measures, gifted care initiatives, Saudi future vision, gifted student

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Authors: Malik Shahzad Shabbir, Muhammad Saarim Ghazi, Amir Khalil ur Rehman

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This study examines the factors which influence and contribute towards the financial viability of Islamic finance and its impact on global financial stability. However, the purpose of this paper is to differentiate the practical implications of both Islamic and conventional finance on global financial stability. The Islamic finance is asset backed financing which creates wealth through trade, commerce and believes in risk and return sharing. Islamic banking is asset driven as against to conventional banking which is liability driven. In order to introduce new financial products for market, financial innovation in Islamic finance must be within the Shari’ah parameters that are tested against the ‘Maqasid al-Shari’ah’. Interest-based system leads to income and wealth inequalities and mis-allocation of resources. Moreover, this system has absence of just and equitable aspect of distribution that may exploit either the debt holder or the financier. Such implications are reached to a tipping point that leaves only one choice: change or face continued decline and misery.

Keywords: viability, global financial stability, practical implications, asset driven, tipping point

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