Seyed Farhad Saberhoseini; Seyyed Ahmad Edalatpanah; Ali Sorourkhah
Abstract
Public-Private Partnership (PPP) refers to a partnership between a government and a private sector to provide public infrastructure projects, services, etc. These projects have been associated with numerous problems, many of which failed. A critical issue in PPP projects is choosing the right private-sector ...
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Public-Private Partnership (PPP) refers to a partnership between a government and a private sector to provide public infrastructure projects, services, etc. These projects have been associated with numerous problems, many of which failed. A critical issue in PPP projects is choosing the right private-sector partner. Considering various criteria, the public sector has to select the best alternative concerning uncertainty. There needs to be a focus on well-structured, feasible decision approaches necessary to improve the performance of PPPs. In the MCDM context, the ratings of the alternatives provided by decision-makers can be expressed with the Fuzzy Set theory. Single-valued neutrosophic sets SVNSs are well suited for handling ambiguous, incomplete, and imprecise information. Moreover, some information measures for the SVNS model have been proposed, such as similarity measures. As selecting the suitable private-sector partner problem is an MCDM one, including various risk factors and uncertainty, this article has addressed choosing that by considering the risk factors as the problem criteria in a neutrosophic environment. We proposed a simple, practical approach to solve the problem of selecting the best private-sector partner. This approach considers the most critical risk factors affecting the infrastructure PPP project and copes with uncertainty using SVNSs.
Zhi Zhou
Abstract
Wearable technology, wearables, fashion technology, smart wear, skin electronics, or fashion electronics are smart electronic devices. Wearable technology has various applications that grow as the field expands. It appears prominently in consumer electronics with the popularization of the smartwatch ...
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Wearable technology, wearables, fashion technology, smart wear, skin electronics, or fashion electronics are smart electronic devices. Wearable technology has various applications that grow as the field expands. It appears prominently in consumer electronics with the popularization of the smartwatch and activity tracker. A popular activity tracker called the fit bit is widely used in the fitness industry to track calories and health-related goals. A popular smartwatch in the market is the Apple Watch. Apart from commercial uses, wearable technology is incorporated into navigation systems, advanced textiles, and healthcare. As wearable technology is being proposed for critical applications, it must be vetted for its reliability and security properties. Applications based on Wireless Sensor Networks (WSN) for Internet of Things (IoTs) scenarios are rising. The multiple possibilities they offer have spread towards previously hard-to-imagine fields, like e-health or human physiological monitoring. An application has been developed for its usage in scenarios where data collection is applied to smart spaces, aiming at its usage in firefighting and sports. This application has been tested in a gymnasium with real, non-simulated nodes and devices. A graphic user interface has been implemented to suggest a series of exercises to improve a sportsman/woman s condition, depending on the context and their profile. This system can be adapted to a wide variety of e-health applications with minimum changes, and the user will interact using different devices, like smartphones, smartwatches, and/or tablets.
Seyyed Esmaeil Najafi; Soheil Salahshour; Bijan Rahmani Parchikolaei
Abstract
Supplier selection is the practice of evaluating and selecting the best or most suitable supplier for the organization based on the candidates' qualities and qualifications. In large construction projects, supplier selection strongly impacts the quality of materials as well as the cash-flow and logistical ...
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Supplier selection is the practice of evaluating and selecting the best or most suitable supplier for the organization based on the candidates' qualities and qualifications. In large construction projects, supplier selection strongly impacts the quality of materials as well as the cash-flow and logistical support of the project. The issue becomes particularly important when a high number and volume of orders and a varied set of items are involved. If the procurement process is organized into several periods, the impact of Net Present Value (NPV) on the project's overall profit or loss becomes significant, as well. In this study, the solution to a multi-product multi-period supplier selection optimization problem is evaluated using a hybrid metaheuristic algorithm and considering the cash flow. Our analysis of the results shows that the algorithm is able to obtain the intended outcome within an appropriate timeframe and with high precision.
Ibrahim Mekawy
Abstract
Nowadays, we know that Wireless Sensor Networks (WSNs) are being widely applied in many fields of human life such as civil and military applications. WSNs are broadly applied for various applications in tracking and surveillance due to their ease of use and other distinctive characteristics compelled ...
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Nowadays, we know that Wireless Sensor Networks (WSNs) are being widely applied in many fields of human life such as civil and military applications. WSNs are broadly applied for various applications in tracking and surveillance due to their ease of use and other distinctive characteristics compelled by real-time cooperation among the Sensor Nodes (SNs). When applying the WSN in the real world we have to face many challenges such as security, and storage due to its centralized server/client models. Although WSNs can bring a lot of benefits and conveniences. This paper discusses an in-depth survey of a blockchain-based approach for malicious node detection, an exhaustive examination of the integration of blockchain techniques with WSNs (BWSN), and insights into this novel concept.
Agyan Panda; Seyed Ahmad Edalatpanah; Ramin Godarzi Karim
Abstract
The goal is to build and create an agricultural monitoring system that uses a wireless sensor network to boost farming production and quality without having to manually monitor it all of the time. In agriculture, temperature, humidity, and carbon dioxide levels are the most critical elements affecting ...
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The goal is to build and create an agricultural monitoring system that uses a wireless sensor network to boost farming production and quality without having to manually monitor it all of the time. In agriculture, temperature, humidity, and carbon dioxide levels are the most critical elements affecting plant productivity, growth, and quality. As a result, this system measures these characteristics in the fields on a regular basis, allowing farmers or agriculture specialists to view the readings on the web at the same time. Furthermore, if a crucial change in one of the metrics occurs, an agriculture specialist will notify the farmer through mobile text message and e-mail. The farmer can study the best environmental conditions for maximum crop productivity, greater productivity, and significant energy savings by continuously monitoring several environmental data.
Rita de Fátima Muniz; Antônio Clécio Fontelles Thomaz
Abstract
In today's fiercely competitive industrial landscape, companies are under mounting pressure to improve process efficiencies, adhere to stringent environmental regulations, and meet their financial objectives. Given the aging infrastructure of many industrial systems and the ever-changing dynamics of ...
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In today's fiercely competitive industrial landscape, companies are under mounting pressure to improve process efficiencies, adhere to stringent environmental regulations, and meet their financial objectives. Given the aging infrastructure of many industrial systems and the ever-changing dynamics of the manufacturing market, there is an urgent requirement for intelligent and cost-effective industrial automation systems that can enhance productivity and efficiency. In this regard, Wireless Sensor Networks (WSNs) present a compelling alternative to traditional wired monitoring and control systems, offering numerous advantages.
Farid Pourofoghi
Abstract
In most real-world issues, we are dealing with situations where accurate data and complete information are not available. One way to deal with these uncertainties in real life is to use Grey System Theory (GST). In this paper, a linear programing problem in a grey environment with interval Grey Numbers ...
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In most real-world issues, we are dealing with situations where accurate data and complete information are not available. One way to deal with these uncertainties in real life is to use Grey System Theory (GST). In this paper, a linear programing problem in a grey environment with interval Grey Numbers (GN) is considered. Most of the proposed methods for solving grey linear programing problems are done by using GN whitening and turning the problem into a common linear programing problem. However, in this paper we seek to solve the grey linear programing problem directly without turning it into a regular linear programing problem in order to maintain uncertainty in the original problem data in the final answer. For this purpose, by proving the desired theorems, we propose a method based on the initial simplex algorithm to solve grey linear programing problems. This method is simpler than the previous methods. We emphasize that the proposed concept is useful for real and practical situations. To illustrate the efficiency of the method, we solve an example of Grey Linear Programming (GLP).
Ebrahim Ganjalipour; Khadijeh Nemati; Amir Hosein Refahi Sheikhani; Hashem Saberi Najafi
Abstract
In this paper we proposed a new neurodynamic model with recurrent learning process for solving ill-condition Generalized eigenvalue problem (GEP) Ax = lambda Bx. our method is based on recurrent neural networks with customized energy function for finding smallest (largest) or all eigenpairs. We evaluate ...
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In this paper we proposed a new neurodynamic model with recurrent learning process for solving ill-condition Generalized eigenvalue problem (GEP) Ax = lambda Bx. our method is based on recurrent neural networks with customized energy function for finding smallest (largest) or all eigenpairs. We evaluate our method on collected structural engineering data from Harwell Boeing collection with high dimensional parameter space and ill-conditioned sparse matrices. The experiments demonstrate that our algorithm using Adam optimizer, in comparison with other stochastic optimization methods like gradient descent works well in practice and improves complexity and accuracy of convergence.
Ibrahim Mekawy; Alhanouf Alburaikan; Iman Atighi
Abstract
The current landscape of Cloud Computing predominantly relies on closed data centers, housing a multitude of dedicated servers that cater to cloud services. However, an immense number of underutilized Personal Computers (PCs) are owned by individuals and organizations globally. These dormant resources ...
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The current landscape of Cloud Computing predominantly relies on closed data centers, housing a multitude of dedicated servers that cater to cloud services. However, an immense number of underutilized Personal Computers (PCs) are owned by individuals and organizations globally. These dormant resources can be harnessed to form an alternative cloud infrastructure, offering a wide array of cloud services, particularly focusing on infrastructure as a service. This innovative strategy, the "no data center" approach, complements the conventional data center-centric cloud provisioning model. In a research paper, the authors introduce their opportunistic Cloud Computing framework called cuCloud, which effectively utilizes the idle resources of underutilized PCs within a given organization or community. The success of their system serves as tangible evidence that the "no data center" concept is indeed feasible. Beyond conceptualization and philosophy, the authors' experimental findings strongly validate their approach.
Salwa El-Morsy
Abstract
Wireless sensor networks are fast process of connection in part such as agriculture, healthcare, environmental monitoring, security, and manufacturing and also it thesaurus and measure physical signals and it also have wireless communication. Wireless sensors also can track the appliances; it is an automatic ...
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Wireless sensor networks are fast process of connection in part such as agriculture, healthcare, environmental monitoring, security, and manufacturing and also it thesaurus and measure physical signals and it also have wireless communication. Wireless sensors also can track the appliances; it is an automatic control of devices. It works as an investigation of types and application of wireless sensors in the ground and home. In this paper we have presented sort study on WSN applications.
Adil Baig
Abstract
Video Quality Assessment (VQA) is a critical component of various technologies, including automated video broadcasting through displaying technologies. Moreover, determining visual quality necessitates a balanced examination of visual features and functionality. Previous research has also shown that ...
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Video Quality Assessment (VQA) is a critical component of various technologies, including automated video broadcasting through displaying technologies. Moreover, determining visual quality necessitates a balanced examination of visual features and functionality. Previous research has also shown that features derived from pre-trained models of Convolutional Neural Networks (CNNs) are extremely useful in various image analysis and computer vision activities. Based on characteristics collected from pre-trained models of deep neural networks, transfer learning, periodic pooling, and regression, we created a unique architecture for No Reference Video Quality Assessment (NR-VQA) in this research. We were able to get results by solely employing dynamically pooled deep features and avoiding the use of manually produced features. This study describes a novel, deep learning-based strategy for NR-VQA that uses several pre-trained deep neural networks to characterize probable image and video distortions across parallel. A set of pre-trained CNNs extract spatially pooling and intensity-adjusted video-level feature representations, which are then individually mapped onto subjective peer assessments. Ultimately, the perceived quality of a video series is calculated by combining the quality standards from the various regressors. Numerous researches demonstrate that the suggested approach on two large baseline video quality analysis datasets with realistic aberrations sets a new state-of-the-art. Furthermore, the findings show that combining the decisions of different deep networks can greatly improve NR-VQA.
Haifa Alqahtani
Abstract
Parking and transportation becoming crucial from decades, the accidents per day around the world are increasing, so with sensors we can drastically decrease the death rate and accident rate around the world. In this paper I suppose to present you the sensors-based cloud smart parking and sensors-based ...
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Parking and transportation becoming crucial from decades, the accidents per day around the world are increasing, so with sensors we can drastically decrease the death rate and accident rate around the world. In this paper I suppose to present you the sensors-based cloud smart parking and sensors-based AI and ML smart transportation.
Sadegh Eskandari
Abstract
The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough sets ...
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The rough sets theory is a mathematical tool to express vagueness by means of boundary region of a set. The main advantage of this implementation of vagueness is that it requires no human input or domain knowledge other than the given data set. Several efforts have been made to make close the rough sets theory and machine learning tasks. In this regard several extensions and modifications of the original theory are proposed. This paper provides the basic concepts of the theory as well as its well-known extensions and modifications.
Mahnaz Maghbouli; Azam Pourhabib Yekta
Abstract
The traditional Data Envelopment Analysis (DEA) model on network-structured performance analysis normally considers desirable intermediate measures. In many real cases, the intermediate measures consist of both desirable and undesirable factors. The motivation of this paper is employing “Natural ...
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The traditional Data Envelopment Analysis (DEA) model on network-structured performance analysis normally considers desirable intermediate measures. In many real cases, the intermediate measures consist of both desirable and undesirable factors. The motivation of this paper is employing “Natural and managerial disposability” in two-stage network structures with undesirable intermediate measure. The non-cooperative game theory is proposed to study the two-stage structure. A real case of 34 OECD countries in 2012 has been illustrated to shed a light on applicability of the proposed methodology.
Lu Fan
Abstract
Wireless Sensor Networks (WSNs) consist of small nodes with identifying component by sensing, computation, and wireless communications infrastructure capabilities. The path searching means routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy ...
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Wireless Sensor Networks (WSNs) consist of small nodes with identifying component by sensing, computation, and wireless communications infrastructure capabilities. The path searching means routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. WSN provide several types of applications providing comfortable and smart-economic life. The easy molding, fault tolerance, high sensing fidelity, low price, and rapid deployment features of sensor networks create various new and thrilling application areas for remote sensing. In future, this wide range of application areas will make sensor networks an important part of our lives. However, understanding of sensor networks needs to satisfy the constraints presented by factors such as fault tolerance, scalability, cost, hardware, dynamic topology, environment, and power consumption.
Han-Kwang Chen
Abstract
The study aimed to examine difficulties encountered by higher education agencies through action research and to integrate "Online Activity" into an after-school english program at a university to optimize their teaching strategy. The study was conducted between October and December 2022. "Online Activity" ...
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The study aimed to examine difficulties encountered by higher education agencies through action research and to integrate "Online Activity" into an after-school english program at a university to optimize their teaching strategy. The study was conducted between October and December 2022. "Online Activity" was chosen as a possible optimization strategy because it assisted teachers in applying online activities to current course materials, improving students' learning motivations and learning outcomes. The results showed that online activity was a practical strategy for improving foreign language learning. Meanwhile, collaboration, discussions, and reflections among the action research team assisted professional development in teaching. The researchers recommend that educators choose appropriate action strategies to adapt to various learning situations, which may create opportunities for innovation in the current rigid education and learning environment.
Mingyue Wang
Abstract
Wireless sensor network technologies normally deploy a large number of small, low cost sensors, fairly densely that can observe and influence the physical world around them by gathering physical information, transform it into electrical signals, send it to a remote location to do some analysis and deploy ...
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Wireless sensor network technologies normally deploy a large number of small, low cost sensors, fairly densely that can observe and influence the physical world around them by gathering physical information, transform it into electrical signals, send it to a remote location to do some analysis and deploy the results in different applications. This means there is no need to build towers or set up complicated communication links such as; microwave and satellite. It can be deployed anywhere, even in inaccessible places. This technology can provide a real time monitoring for forest fire, where it can provide information at the ignition instance or at very small delay, depends on the node used wake up/sleep schedule. It’s more reliable because it can influence the world in the surrounded area, if it is used in appropriate methods, rather than expecting events over large distances and long delay like other satellite and camera towers techniques. In this work, all nodes only use temperature sensors and they are programmed on a certain threshold temperature, above it the node will send an alarm message to the sink. This concept relies solely on the node behavior to alert of crises possibility using simple node components to provide detection and information on whether this is a peaceful fire, or the beginning of wild fire. The key in this method is to make decisions by tracking the fire propagation and check the logic behind it.
Masoumeh Moterased; Seyed Mojtaba Sajadi; Ali Davari; Mohammad Reza Zali
Abstract
This study discusses the prediction model of Entrepreneurial Exit from Entrepreneurial Perceptions, acquired the data from the Global Entrepreneurship Monitor's (GEM) database in 2008-2019. Some essential indicators include Opportunity Perception, Fear of Failure, Capability Perception, Role Model, and ...
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This study discusses the prediction model of Entrepreneurial Exit from Entrepreneurial Perceptions, acquired the data from the Global Entrepreneurship Monitor's (GEM) database in 2008-2019. Some essential indicators include Opportunity Perception, Fear of Failure, Capability Perception, Role Model, and Entrepreneurial Intention. Data mining results show that the exit reasons and entrepreneurial intention have a more significant impact on entrepreneurial exit than other variables. This research applies the Random Forest Algorithm to get a prediction model that shows the entrepreneurial exit. According to the Random Forest Algorithm results, accuracy, ROC-AUC score, AUC curve, precision, recall, and F1 score validate the classification method. The prediction model shows that the best accuracy predictor of entrepreneurial exit is 99 percent, and another criteria ROC_AUC score 96%. Consistent results demonstrate that the proposed method can consider a promisingly successful predictive model of entrepreneurial exit with excellent predictive performance. These results can predict the individuals' entrepreneurial exit possibility before the psychological and financial impact and loss of capital and failure.
Seyed Esmaeil Najafi; Mir Bahador Aryanezhad; Farhad Hosseinzadeh Lotfi; Seyyed Asghar Ebnerasoul
Abstract
Measuring the performance of a production system has been an important task in management for control, planning, etc. The Balanced Scorecard (BSC) allows us to do just that. BSC is widely used in government and industry because of the clear representation of the relationship and logic between the Key ...
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Measuring the performance of a production system has been an important task in management for control, planning, etc. The Balanced Scorecard (BSC) allows us to do just that. BSC is widely used in government and industry because of the clear representation of the relationship and logic between the Key Performance Indicators (KPIs) of 4 perspectives-financial, customer, internal process, and learning and growth. Conversely, traditional studies in Data Envelopment Analysis (DEA) view systems as a whole when measuring efficiency, ignoring the operation of individual processes within a system. We present and demonstrate a multi-criteria approach for evaluating every project in different stages. Our approach integrates the BSC and DEA and develops an extended DEA model. The input and output measures for the integrated DEA-BSC model are grouped in “cards,” which are associated with "BSC". With efficiency decomposition, the process that causes the inefficient operation of the system can be identified for future improvement. Finally, we illustrate the proposed approach with a case study involving six banking branches.
Khatereh Bagherzadeh Asl; Alhanouf Alburaikan
Abstract
Wireless Sensor Network (WSN) are in incredible request from the new year’s, as these days we have seen wide development of remote gadgets including cell telephones, workstations, mobiles, PDA's and so forth remote sensor networks comprises of thousands of minuscule sensor hubs. In a remote sensors ...
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Wireless Sensor Network (WSN) are in incredible request from the new year’s, as these days we have seen wide development of remote gadgets including cell telephones, workstations, mobiles, PDA's and so forth remote sensor networks comprises of thousands of minuscule sensor hubs. In a remote sensors network a hub is as of now not valuable when its battery passes on, so to stay away from this issue numerous conventions were presented, yet much of the position is given to progressive directing conventions. In this paper, we break down LEACH convention, its stages, benefits and hindrances and additionally different sorts of assaults on this directing convention.
Rita de Fátima Muniz
Abstract
Wireless Sensor Network (WSN) are in great demand from the recent years, as nowadays we have seen a wide growth of wireless devices including cellular phones, laptops, mobiles, PDA’s etc. WSNs consists of thousands of tiny sensor nodes. In a WSN a node is no longer useful when its battery dies, ...
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Wireless Sensor Network (WSN) are in great demand from the recent years, as nowadays we have seen a wide growth of wireless devices including cellular phones, laptops, mobiles, PDA’s etc. WSNs consists of thousands of tiny sensor nodes. In a WSN a node is no longer useful when its battery dies, so to avoid this problem many protocols were introduced, but most of the rank is given to hierarchical routing protocols. In this paper, we analyze LEACH protocol, its phases, advantages and disadvantages and various kinds of attacks on this routing protocol.
Dmitriy S Vladislav
Abstract
Water is individual of the maximum essential beginnings for all consisting beings in the soil. In a rustic like India accompanying excellent society, categorization and control of water is established wonted harsh. The forever increasing entail for water stresses projects had relation accompanying water ...
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Water is individual of the maximum essential beginnings for all consisting beings in the soil. In a rustic like India accompanying excellent society, categorization and control of water is established wonted harsh. The forever increasing entail for water stresses projects had relation accompanying water control, making sure the sensible outdoing and utilization of water origins. It further requires the bettering of main novelty and networks to advance the practice of water and proves calm ingesting water. An attempt is made in this place studies illustrations to justify water encumber customers; facts losses, able to be contracted helping cure selections and moreover to build a clean, reliable and unfamiliar water transfer finish. Clean organized is decided following four customers, individual essential disposal box and Arduino boss for protest of the control scheme.
Reza Rasinojehdehi; Soheil Azizi
Abstract
The escalating annual insurance costs nationwide have sparked a growing interest among insurance industry managers and policymakers in analyzing insurance data to forecast future costs. Accurately predicting the number of claims and implementing appropriate policies can help mitigate potential losses ...
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The escalating annual insurance costs nationwide have sparked a growing interest among insurance industry managers and policymakers in analyzing insurance data to forecast future costs. Accurately predicting the number of claims and implementing appropriate policies can help mitigate potential losses for insurance companies and customers. This study focuses on predicting the amount of customer claims and utilizes data from 128 individuals insured by Iran insurance company. The dataset includes various attributes such as the age of the vehicle owner, type of car, age of the car itself, number of claims, and the corresponding claim amounts (measured in 10,000 Tomans) recorded in the year 1400. All features, except the claim amount (the target variable), were discretized into ordinal variables to ensure accurate analysis and address any outliers or data inconsistencies. Multiple linear regression was employed to predict the target variable, enabling an investigation into the influence of each feature on estimating the claim amount. The data analysis was conducted using IBM SPSS MODELER software, allowing for a comprehensive examination of the assumptions associated with the regression model. By leveraging this approach, insurance industry stakeholders can gain valuable insights into predicting claim amounts and make informed decisions to optimize their operations and minimize potential financial risks.
Fatemeh Mohades Deilami; Hossein Sadr; Mozhdeh Nazari
Abstract
Personality can be defined as the combination of behavior, emotion, motivation, and thoughts that aim at describing various aspects of human behavior based on a few stable and measurable characteristics. Considering the fact that our personality has a remarkable influence in our daily life, automatic ...
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Personality can be defined as the combination of behavior, emotion, motivation, and thoughts that aim at describing various aspects of human behavior based on a few stable and measurable characteristics. Considering the fact that our personality has a remarkable influence in our daily life, automatic recognition of a person's personality attributes can provide many essential practical applications in various aspects of cognitive science. Although various methods have been recently proposed for the task of personality recognition, most of them have mainly focused on human-designed statistical features and they did not make use of rich semantic information existing in users' generated texts while not only these contents can demonstrate its writer's internal thought and emotion but also can be assumed as the most direct way for people to state their feeling and opinion in an understandable form. In order to make use of this valuable semantic information as well as overcoming the complexity and handcraft feature requirement of previous methods, a deep learning based method for the task of personality recognition from text is proposed in this paper. Among various deep neural networks, Convolutional Neural Networks (CNN) have demonstrated profound efficiency in natural language processing and especially personality detection. Owing to the fact that various filter sizes in CNN may influence its performance, we decided to combine CNN with AdaBoost, a classical ensemble algorithm, to consider the possibility of using the contribution of various filter lengths and gasp their potential in the final classification via combining various classifiers with respective filter size using AdaBoost. Our proposed method was validated on the Essay dataset by conducting a series of experiments and the empirical results demonstrated the superiority of our proposed method compared to both machine learning and deep learning methods for the task of personality recognition.
Victoria Nozick
Abstract
In any other place in the world, people crave for protection during dark times (Night). Either it is man or women. Everyone is scared of being alone where dark looks like a haunting one to everyone. Where people are going MAD towards women during at that point. So, I am contributing this project to all ...
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In any other place in the world, people crave for protection during dark times (Night). Either it is man or women. Everyone is scared of being alone where dark looks like a haunting one to everyone. Where people are going MAD towards women during at that point. So, I am contributing this project to all the women who are hustling hard to get their independence and freedom. These DRONES helps them to keep secure and do all the patrol or Police work during nights.
