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Papers by Saad T A L I B Hasson

Vehicular Ad hoc Network (VANET) is a specific type of Mobile Ad Hoc Network (MANET), which repre... more Vehicular Ad hoc Network (VANET) is a specific type of Mobile Ad Hoc Network (MANET), which represents the main component of the Intelligent Transportation System (ITS). Sharing data and information among vehicles is an essential issue in VANET to cover all the possible events and accidents that can threaten human lives. This process is called Data Dissemination in communication. The VANET's applications require frequent floods of messages to improve the road's and passengers' safety. These messages are usually warning messages, which are forwarded to all or some vehicles according to the data dissemination models to warn the drivers about the expected disasters, accidents, and weather conditions. Data Dissemination represents a real challenge in VANET because of the frequent changes in topology and frequent fragmentation. Many protocols and techniques deal with data dissemination. This paper presents an approach that achieves data dissemination based on clustering and avoids a broadcast storm. A developed clustering approach is dependent on forwarded messages among vehicles. The proposed schema achieved good performance metrics.

One of the significant problems in Social Net-works (SN) analysis is how to find the best influen... more One of the significant problems in Social Net-works (SN) analysis is how to find the best influential members. This problem was proved to be non-deterministic polynomial (NP-hard). The influence maximization (IM) problem in SNs aims to maximize the spread of influence in the network. It represents an optimization problem. IM is a fundamental research problem in social networks. Influence maximization problem is the problem of assigning a subset of k users as (seed nodes) in a graph that could maximize the spread of influence by maximizing the expected number of influenced users. It represents a key algorithmic problem in social influence analysis. In this study, centrality-based methods are utilized to select top k nodes of high centrality values. The degree centrality is used to select the opinion leaders, while the between-ness and Eigenvector centrality is used to select the early adopters. The degree discount (as a heuristic approach) is proposed to replace the Greedy algorithms applied in other studies to avoid the time complexity. A mixed diffusion model (replacing the linear threshold and independent cascade) is utilized to be main diffusion model in this study.

Waste management is one of the fundamental services untaken by municipalities to retain cities cl... more Waste management is one of the fundamental services untaken by municipalities to retain cities clean and healthy. It represents a high priority and urgent issue for many communities around the world. Rapid progress in the economy and urbanization has had a significant impact on the increase in waste disposal volumes. In this study, Geographical information system GIS was suggested and implemented for optimizing the waste collection (WC) routes in Al Hillah city. The ArcGIS Network Analyst model was developed to improve the efficiency of WC in the Municipality of Hillah (MoH), through the redistribution of waste collection bins and improved trucks routing in terms of distance and time. Sixty routes are resulted and optimized to minimize the total distances of the current route. Simultaneously, it helps in reducing the time required for each route to complete the waste collection process. The final result shows about 30% of the aggregated route distances are minimized in addition to the resulted duration times. The optimal scenario suggested in this study is found to be more efficient in terms of assembly time and distance traveled by waste trucks.

A recommendation model is important in the trust environment when the trust between some nodes wa... more A recommendation model is important in the trust environment when the trust between some nodes was lacked or incomplete. Thus the trust evaluation before and after any interaction or recommendation becomes a very important issue to overcome distrust and fake recommendation challenges and help in making decisions. The recommendations are one of the most widespread tools to improve trust, where they can be used for developing a trust model when the performance of the trust model depended on the quality and type of the relations. This paper presents a trust evaluation model based on some statistic tests, which aims to compute the ratio between recommendation to trust, and hence filter out noise recommendation and obtain more accurate and trust values.

In the era of Internet and advancing in communication and computing technology, the social networ... more In the era of Internet and advancing in communication and computing technology, the social networks have caught wide applications in real life's. Influence Maximization (IM) in social networks is intended to find a small group (sub set) of specific users as seeds (influencers). These seeds have an ability to activate maximum possible neighbors in the network. IM is usually categorized as NP-hard problem. Different alternatives were proposed to develop approaches to resolve it. Most of the available approaches are considering the centrality metrics to categorize the seed nodes (initial influencer node / early adopters). The essential problem in this study is how to discover the significant players (a subset of seed nodes) in social networks in an efficient manner. Those players must have an ability to affect the maximum probable neighbors by encouraging them to adopt the diffused idea. Best selection will lead to maximize the influence propagation in the network. Information is spreading stochastically in such networks. All These steps are to maximize the information dissemination in social networks. A new proposed approach to find the minimum number of nodes that can maximize information diffusion most effectively is introduced and named as (BetClose) in this study. BetClose has an ability to assign set of nodes with highest betweenness and closeness values in the same time. A developed diffusion model (depend on ICM and LTM simultaneously) is implemented. Certain approaches are used to develop probabilities to improve the diffusion process and a mathematical model is suggested to estimate the threshold values based on the network structure. The results of this study offers indications about the structure of network that having a probable effect on the information diffusion in social networks. The suggested approach outcomes indicate high adoption compared with the traditional approaches which are depending on one metric only. The average adoption size resulted from BetClose is found to be better than the average adoption size resulted from implementing each of the three essential traditional centrality metrics (i.e. betweenness, closeness, and Eigen vector).

Linear programming is one of the most useful techniques used to solve complicated practical probl... more Linear programming is one of the most useful techniques used to solve complicated practical problems nowadays in accordance with its capability to formulate many real-life problems as mathematical models to obtain an optimal solution. The process of re-infrastructure innovation and development is one of the critical issues of planning and managing in each country. In this study, we proposed a mathematical model allocates services for scarce resources in an optimal manner to ensure the provision of accepted services to all these sectors. A large virtual area is divided into many sectors used as an illustrative example to evaluate the performance of the proposed model. The results obtained show that the proposed model is efficient to achieve the optimal solution, and it can be efficiently used to other real-life problems.

Journal of University of Babylon, 2013

Data summarization is a data mining technique to summarize huge data in few understandable knowle... more Data summarization is a data mining technique to summarize huge data in few understandable knowledge. Attribute - Oriented Induction(AOI) is a data summarization algorithm, it suffer from overgeneralization problem. In this paper, we use an entropy measu re to enhance generalization process, feature selection, and stop condition. Experimental results show that the proposed technique will reduce the effect of overgeneralization problem.

Wireless sensor networks (WSNs) usually build from huge number of randomly deployed sensor nodes ... more Wireless sensor networks (WSNs) usually build from huge number of randomly deployed sensor nodes in certain area. The sensors are mainly utilized to monitor physical and environmental conditions, gather information, process this data locally and transfer the sensed data back to the Base Station (BS). The main objective of this paper is to simulate, evaluate and observe the behavior of developed clustering approaches and compare their performance metrics. In this study all the cluster nodes must sensing certain data and transmit it to its cluster head (CH). These data will be collected at particular nodes known as cluster heads that is previously assigned for each cluster. The CH aggregates the data and forwards it to the base station or a node sink. In this study two developed clustering approaches are suggested and created using Net Logo (5.2.1 version 2015). These approaches are Extreme node and double Extreme nodes. In addition to these two approaches, the DB-Scan clustering approach is also suggested to be used as a reference to compare its results with these two suggested algorithms. Results show certain improvement in these suggested algorithms. Many performance metrics can be used to Measure the performance of the suggested WSN such as NRL, PDF, End-to-end and throughput.

Journal of Computational and Theoretical Nanoscience, Mar 1, 2019

Oriental journal of computer science and technology, Jul 1, 2014

Computer Simulation and Modeling techniques were used successfully to represent and propose an Op... more Computer Simulation and Modeling techniques were used successfully to represent and propose an Optimum resource allocation problem in many field and applications. In wireless communication networks these techniques can be applied in the field of developing and controlling the available paths, power control, coverage area, delay, and delivery guarantee. In this study the main objective function is to indicate the optimum location of the wireless network stations to maximize the throughput, minimize delay, reduce path loss information, increase the coverage area and minimize the total network costs. The network performance must not exceed the limitation constraints under the required feasible standard quality of service. The modeling results showed good indications and gave a suitable guide to build, extend or develop such networks.

The International Arab Journal of Information Technology, 2018

The new type of the mobile Ad-hoc network, which is called Vehicular Ad-hoc Network (VANET) is cr... more The new type of the mobile Ad-hoc network, which is called Vehicular Ad-hoc Network (VANET) is creating a rich environment for research. It considered being one of the projects of the Internet of Things (IoT). IoT can be utilized in employing VANET technology to alleviate roads congestion in real time. It has a great impact on the society in general such as to reduce travel time, minimize the fuel consumption, keep passenger's life and to save money. The smart transportation and smart cities represent one of the most important application of IoT. In this paper, a clustering approach is proposed with several road models that represent the environment of VANETs. The proposed system was designed, built, run out and evaluated using Netlogo simulator version (5.2.1). Performance metrics involve: throughput, end to end delay, and count of receiving messages were evaluated in this paper. Useful results were obtained after different simulation runs. The results shows an improvement and give good indications to apply such developed models.

Communications in computer and information science, 2023

مجلة سامراء للعلوم الصرفة والتطبيقية, Mar 30, 2023

This paper examines the challenge of accurately computing highway performance measures by estimat... more This paper examines the challenge of accurately computing highway performance measures by estimating traffic-flow between traffic sensors that are geographically dispersed. Consequently, predicting flows vehicle values is one of the most difficult issues in the field of traffic flow prediction. Therefore, there has been a rise in interest in combining machine learning (ML) methods with indicators from technical analysis. In this paper, we suggest a hybrid strategy for generating traffic to help with this issue. Our proposed method utilizes a technical indicator and an ANN technique to predict future flows. That this method can be applied to other technical indicators while still maintaining its simplicity and effectiveness thanks to the hybrid rules is what makes it novel. The performance of the proposed artificial neural network (ANN) was evaluated with a number of other machine learning techniques to help us choose the optimal ML approach. Daily traffic data from the Motorway Incident Detection and Automatic Signalling (MIDAS) system on the M25 highway was used to test the proposed method. The achieved results demonstrate that the predictive power of ML models is augmented when ML techniques are applied to technical analysis indicators.

Vehicular Ad hoc Network (VANET) is a specific type of Mobile Ad Hoc Network (MANET), which repre... more Vehicular Ad hoc Network (VANET) is a specific type of Mobile Ad Hoc Network (MANET), which represents the main component of the Intelligent Transportation System (ITS). Sharing data and information among vehicles is an essential issue in VANET to cover all the possible events and accidents that can threaten human lives. This process is called Data Dissemination in communication. The VANET's applications require frequent floods of messages to improve the road's and passengers' safety. These messages are usually warning messages, which are forwarded to all or some vehicles according to the data dissemination models to warn the drivers about the expected disasters, accidents, and weather conditions. Data Dissemination represents a real challenge in VANET because of the frequent changes in topology and frequent fragmentation. Many protocols and techniques deal with data dissemination. This paper presents an approach that achieves data dissemination based on clustering and avoids a broadcast storm. A developed clustering approach is dependent on forwarded messages among vehicles. The proposed schema achieved good performance metrics.

One of the significant problems in Social Net-works (SN) analysis is how to find the best influen... more One of the significant problems in Social Net-works (SN) analysis is how to find the best influential members. This problem was proved to be non-deterministic polynomial (NP-hard). The influence maximization (IM) problem in SNs aims to maximize the spread of influence in the network. It represents an optimization problem. IM is a fundamental research problem in social networks. Influence maximization problem is the problem of assigning a subset of k users as (seed nodes) in a graph that could maximize the spread of influence by maximizing the expected number of influenced users. It represents a key algorithmic problem in social influence analysis. In this study, centrality-based methods are utilized to select top k nodes of high centrality values. The degree centrality is used to select the opinion leaders, while the between-ness and Eigenvector centrality is used to select the early adopters. The degree discount (as a heuristic approach) is proposed to replace the Greedy algorithms applied in other studies to avoid the time complexity. A mixed diffusion model (replacing the linear threshold and independent cascade) is utilized to be main diffusion model in this study.

Waste management is one of the fundamental services untaken by municipalities to retain cities cl... more Waste management is one of the fundamental services untaken by municipalities to retain cities clean and healthy. It represents a high priority and urgent issue for many communities around the world. Rapid progress in the economy and urbanization has had a significant impact on the increase in waste disposal volumes. In this study, Geographical information system GIS was suggested and implemented for optimizing the waste collection (WC) routes in Al Hillah city. The ArcGIS Network Analyst model was developed to improve the efficiency of WC in the Municipality of Hillah (MoH), through the redistribution of waste collection bins and improved trucks routing in terms of distance and time. Sixty routes are resulted and optimized to minimize the total distances of the current route. Simultaneously, it helps in reducing the time required for each route to complete the waste collection process. The final result shows about 30% of the aggregated route distances are minimized in addition to the resulted duration times. The optimal scenario suggested in this study is found to be more efficient in terms of assembly time and distance traveled by waste trucks.

A recommendation model is important in the trust environment when the trust between some nodes wa... more A recommendation model is important in the trust environment when the trust between some nodes was lacked or incomplete. Thus the trust evaluation before and after any interaction or recommendation becomes a very important issue to overcome distrust and fake recommendation challenges and help in making decisions. The recommendations are one of the most widespread tools to improve trust, where they can be used for developing a trust model when the performance of the trust model depended on the quality and type of the relations. This paper presents a trust evaluation model based on some statistic tests, which aims to compute the ratio between recommendation to trust, and hence filter out noise recommendation and obtain more accurate and trust values.

In the era of Internet and advancing in communication and computing technology, the social networ... more In the era of Internet and advancing in communication and computing technology, the social networks have caught wide applications in real life's. Influence Maximization (IM) in social networks is intended to find a small group (sub set) of specific users as seeds (influencers). These seeds have an ability to activate maximum possible neighbors in the network. IM is usually categorized as NP-hard problem. Different alternatives were proposed to develop approaches to resolve it. Most of the available approaches are considering the centrality metrics to categorize the seed nodes (initial influencer node / early adopters). The essential problem in this study is how to discover the significant players (a subset of seed nodes) in social networks in an efficient manner. Those players must have an ability to affect the maximum probable neighbors by encouraging them to adopt the diffused idea. Best selection will lead to maximize the influence propagation in the network. Information is spreading stochastically in such networks. All These steps are to maximize the information dissemination in social networks. A new proposed approach to find the minimum number of nodes that can maximize information diffusion most effectively is introduced and named as (BetClose) in this study. BetClose has an ability to assign set of nodes with highest betweenness and closeness values in the same time. A developed diffusion model (depend on ICM and LTM simultaneously) is implemented. Certain approaches are used to develop probabilities to improve the diffusion process and a mathematical model is suggested to estimate the threshold values based on the network structure. The results of this study offers indications about the structure of network that having a probable effect on the information diffusion in social networks. The suggested approach outcomes indicate high adoption compared with the traditional approaches which are depending on one metric only. The average adoption size resulted from BetClose is found to be better than the average adoption size resulted from implementing each of the three essential traditional centrality metrics (i.e. betweenness, closeness, and Eigen vector).

Linear programming is one of the most useful techniques used to solve complicated practical probl... more Linear programming is one of the most useful techniques used to solve complicated practical problems nowadays in accordance with its capability to formulate many real-life problems as mathematical models to obtain an optimal solution. The process of re-infrastructure innovation and development is one of the critical issues of planning and managing in each country. In this study, we proposed a mathematical model allocates services for scarce resources in an optimal manner to ensure the provision of accepted services to all these sectors. A large virtual area is divided into many sectors used as an illustrative example to evaluate the performance of the proposed model. The results obtained show that the proposed model is efficient to achieve the optimal solution, and it can be efficiently used to other real-life problems.

Journal of University of Babylon, 2013

Data summarization is a data mining technique to summarize huge data in few understandable knowle... more Data summarization is a data mining technique to summarize huge data in few understandable knowledge. Attribute - Oriented Induction(AOI) is a data summarization algorithm, it suffer from overgeneralization problem. In this paper, we use an entropy measu re to enhance generalization process, feature selection, and stop condition. Experimental results show that the proposed technique will reduce the effect of overgeneralization problem.

Wireless sensor networks (WSNs) usually build from huge number of randomly deployed sensor nodes ... more Wireless sensor networks (WSNs) usually build from huge number of randomly deployed sensor nodes in certain area. The sensors are mainly utilized to monitor physical and environmental conditions, gather information, process this data locally and transfer the sensed data back to the Base Station (BS). The main objective of this paper is to simulate, evaluate and observe the behavior of developed clustering approaches and compare their performance metrics. In this study all the cluster nodes must sensing certain data and transmit it to its cluster head (CH). These data will be collected at particular nodes known as cluster heads that is previously assigned for each cluster. The CH aggregates the data and forwards it to the base station or a node sink. In this study two developed clustering approaches are suggested and created using Net Logo (5.2.1 version 2015). These approaches are Extreme node and double Extreme nodes. In addition to these two approaches, the DB-Scan clustering approach is also suggested to be used as a reference to compare its results with these two suggested algorithms. Results show certain improvement in these suggested algorithms. Many performance metrics can be used to Measure the performance of the suggested WSN such as NRL, PDF, End-to-end and throughput.

Journal of Computational and Theoretical Nanoscience, Mar 1, 2019

Oriental journal of computer science and technology, Jul 1, 2014

Computer Simulation and Modeling techniques were used successfully to represent and propose an Op... more Computer Simulation and Modeling techniques were used successfully to represent and propose an Optimum resource allocation problem in many field and applications. In wireless communication networks these techniques can be applied in the field of developing and controlling the available paths, power control, coverage area, delay, and delivery guarantee. In this study the main objective function is to indicate the optimum location of the wireless network stations to maximize the throughput, minimize delay, reduce path loss information, increase the coverage area and minimize the total network costs. The network performance must not exceed the limitation constraints under the required feasible standard quality of service. The modeling results showed good indications and gave a suitable guide to build, extend or develop such networks.

The International Arab Journal of Information Technology, 2018

The new type of the mobile Ad-hoc network, which is called Vehicular Ad-hoc Network (VANET) is cr... more The new type of the mobile Ad-hoc network, which is called Vehicular Ad-hoc Network (VANET) is creating a rich environment for research. It considered being one of the projects of the Internet of Things (IoT). IoT can be utilized in employing VANET technology to alleviate roads congestion in real time. It has a great impact on the society in general such as to reduce travel time, minimize the fuel consumption, keep passenger's life and to save money. The smart transportation and smart cities represent one of the most important application of IoT. In this paper, a clustering approach is proposed with several road models that represent the environment of VANETs. The proposed system was designed, built, run out and evaluated using Netlogo simulator version (5.2.1). Performance metrics involve: throughput, end to end delay, and count of receiving messages were evaluated in this paper. Useful results were obtained after different simulation runs. The results shows an improvement and give good indications to apply such developed models.

Communications in computer and information science, 2023

مجلة سامراء للعلوم الصرفة والتطبيقية, Mar 30, 2023

This paper examines the challenge of accurately computing highway performance measures by estimat... more This paper examines the challenge of accurately computing highway performance measures by estimating traffic-flow between traffic sensors that are geographically dispersed. Consequently, predicting flows vehicle values is one of the most difficult issues in the field of traffic flow prediction. Therefore, there has been a rise in interest in combining machine learning (ML) methods with indicators from technical analysis. In this paper, we suggest a hybrid strategy for generating traffic to help with this issue. Our proposed method utilizes a technical indicator and an ANN technique to predict future flows. That this method can be applied to other technical indicators while still maintaining its simplicity and effectiveness thanks to the hybrid rules is what makes it novel. The performance of the proposed artificial neural network (ANN) was evaluated with a number of other machine learning techniques to help us choose the optimal ML approach. Daily traffic data from the Motorway Incident Detection and Automatic Signalling (MIDAS) system on the M25 highway was used to test the proposed method. The achieved results demonstrate that the predictive power of ML models is augmented when ML techniques are applied to technical analysis indicators.