Understanding how the traffic regulation knowledge, awareness and driving ethics help in reducing road traffic accident, this study was carried out to analyse the traffic accident, safety and awareness among the road users of Ras al Khaimah, United Arab Emirates. To achieve the objectives, a survey was developed and distributed among road users in the emirate of Ras al Khaimah. The main findings showed that a high percentage of participants did not wear seatbelt while driving, more than half sometimes used mobile phones, and high percentage responded that they always follow the traffic light and speed limit. Interestingly, some of participants lacked the knowledge of common traffic signs. The violations of traffic regulations are on the rise quite significantly, whereas accidents were on the rise up until 2017 but since have reduced. Based on the findings of this study, more awareness campaigns among the youth need to take place. Utilization of social media and other technologies for the awareness campaigns is needed. Furthermore, encouraging the public to be vigilantes and report serious traffic violations to the police can be a step in the right direction. And the authorities should enforce traffic regulations more often and be more strict in enforcement.

Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar objects into different groups, or more precisely, the partitioning of a data set into subsets, so that the data in each subset according to some defined distance measure. Due to their importance in today’s machine learning applications, our work presents a review on the clustering algorithms, benefits and applications and concludes with a comparison between these techniques giving the reader the possibility to choose easily with technique is more suitable for her application.

In today’s world, e-commerce stores are taking over traditional retail. online shopping is becoming the favorite choice for many people due to its convenience, where customers can shop at any time from any place and find endless variations of brands and prices. The increase in variations that online shopping offer leaves the customers against a wide range of possibilities and they might waste a lot of time in hope to find what they want. Approaches to solving the recommendation problem are influenced by three methods, the collaborative filtering, the search-based, and hybrid method.

Our work focused on surveying the existing recommendation approaches, identifying their limitations and proposing an improved algorithm. The proposed algorithm targets the customer individually since it aims to provide recommendations for shopping centers, where customers purchases are likely to not be related to each other but shares specific properties and based on the item’s properties and fixed parameters the algorithm gives the recommendations. Currently, we are working on developing the prototype that will allow us to test the platform.

Energy efficiency has become a hot topic of discussion in the modern world, where people have become more aware of their energy consumption and are taking more conscious measures to regulate it. In this day and age, especially in a world where climate change is directly attributed to human activity, it is important for people all over the globe to make more conscious decisions regarding not only their energy consumption, but also their carbon footprint and overall impact on the environment. One such way to integrate such changes into daily life will be through the use of a simple energy-saving app.

The overarching idea of the app we are creating is an energy-efficient scheduler app for Android users. In simplest terms, this app will generate a schedule on how to minimize overall costs while maximizing household appliance usage. Household appliances can range from: washer and dryer machines, heaters, A/C, and even small things such as hair straighteners or irons. The app will aim to minimize the costs of using all of these household appliances, simultaneously helping the user reduce their carbon footprint in the long run.

A rather advanced programming concept will be explored to implement in this algorithm: Mixed Integer Linear Programming (MILP). We picked this approach because generating such a cost-efficiency schedule while accounting for various variables (e.g. user constraints, time intervals, user preferences) requires the prospective algorithm to juggle multiple things at once, and MILP just so happened to be the perfect fit for such implementation.

In this paper, the current and voltage output of the photovoltaic panel was predicted using Support Vector Machine. Investigation on renewable energy, Leeds to seek for its efficiency improvement and hence solar. It is important to utilize the maximum power possible to produce without wasting any and there comes the role of efficiency techniques. This paper introduces a unique method to improve the efficiency of the PV panel using Support Vector Machine (SVM). Used learning data were temperature and irradiation of one-year duration. The obtained results show that the system is completely capable of predicting the future power from the PV panel once the temperature and irradiation values are given.

Keywords: PV,SVM, effecency,Mppt;

Life-safety, ventilation, lighting, health and comfort. Security comes from the need to protect property, content and personnel. Examples of security requirements are identification of vehicles entering and exiting a car park, controlling access to sensitive or secured areas, and precautions against terrorist bomb threats, robberies and burglaries. Security has become a high profile global issue in the aftermath of the September 11 2001 terrorist attacks and the ongoing terrorist threat.

The functions implemented by security systems include the following: Surveillance CCTV ( Analog and Digital), Detection, Alarms, Access control, and Communication and information management. Several of these functions are usually integrated with those of other systems. For example, in case of a fire, all doors must be unlocked. In this research, we are going to introduce several techniques of video compression employed in a CCTV system.

The majority of UAE cities are located close to the sea and it is more economical to obtain the sand from the seashore which contains a large amount of sea shells. This study experimentally investigates the effect of crushed sea shells that exists in the sand used in the construction work in UAE on the mechanical properties of concrete in terms of compressive strength and flexural strength. Four different percentages of sea shells have been investigated by using sieve analysis of the raw sand (29%, 14%, 4%, 0%) and then used to prepare the standard mortar and concrete cubes and beams. 48 concrete cubes, 24 concrete beams, 48 mortar cubes and 48 mortar beams have been prepared for testing purposes.

Results revealed that there was a slight decrement in the compressive strength of standard concrete and mortar cubes prepared using raw sand containing 29% sea shells comparing to cubes made with sand removing all exists sea shells 0%. On the other hand, the flexural strength of concrete and mortar beams was slightly higher for beams made with sand containing 29% crushed sea shells comparing to beams made using 0% sea shells in the sand.  All recorded results are for samples loaded until failure after curing 3, 7, 14 and 28 days. The only exception was for the concrete beams as results are for samples loaded until failure after curing 3, 7 and 28 days. This research work recommends using the marine sand in UAE without any considerations of having the crushed sea shells; since the existence of the sea shells has no significant effect on compressive the strength of concrete and it can slightly improve the flexural strength of mortar and concrete.

Understanding how the traffic regulation knowledge, awareness and driving ethics help in reducing road traffic accident, this study was carried out to analyse the traffic accident, safety and awareness among the road users of Ras al Khaimah, United Arab Emirates. To achieve the objectives, a survey was developed and distributed among road users in the emirate of Ras al Khaimah. The main findings showed that a high percentage of participants did not wear seatbelt while driving, more than half sometimes used mobile phones, and high percentage responded that they always follow the traffic light and speed limit. Interestingly, some of participants lacked the knowledge of common traffic signs. The violations of traffic regulations are on the rise quite significantly, whereas accidents were on the rise up until 2017 but since have reduced. Based on the findings of this study, more awareness campaigns among the youth need to take place. Utilization of social media and other technologies for the awareness campaigns is needed. Furthermore, encouraging the public to be vigilantes and report serious traffic violations to the police can be a step in the right direction. And the authorities should enforce traffic regulations more often and be more strict in enforcement.

Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar objects into different groups, or more precisely, the partitioning of a data set into subsets, so that the data in each subset according to some defined distance measure. Due to their importance in today’s machine learning applications, our work presents a review on the clustering algorithms, benefits and applications and concludes with a comparison between these techniques giving the reader the possibility to choose easily with technique is more suitable for her application.

In today’s world, e-commerce stores are taking over traditional retail. online shopping is becoming the favorite choice for many people due to its convenience, where customers can shop at any time from any place and find endless variations of brands and prices. The increase in variations that online shopping offer leaves the customers against a wide range of possibilities and they might waste a lot of time in hope to find what they want. Approaches to solving the recommendation problem are influenced by three methods, the collaborative filtering, the search-based, and hybrid method.

Our work focused on surveying the existing recommendation approaches, identifying their limitations and proposing an improved algorithm. The proposed algorithm targets the customer individually since it aims to provide recommendations for shopping centers, where customers purchases are likely to not be related to each other but shares specific properties and based on the item’s properties and fixed parameters the algorithm gives the recommendations. Currently, we are working on developing the prototype that will allow us to test the platform.

Energy efficiency has become a hot topic of discussion in the modern world, where people have become more aware of their energy consumption and are taking more conscious measures to regulate it. In this day and age, especially in a world where climate change is directly attributed to human activity, it is important for people all over the globe to make more conscious decisions regarding not only their energy consumption, but also their carbon footprint and overall impact on the environment. One such way to integrate such changes into daily life will be through the use of a simple energy-saving app.

The overarching idea of the app we are creating is an energy-efficient scheduler app for Android users. In simplest terms, this app will generate a schedule on how to minimize overall costs while maximizing household appliance usage. Household appliances can range from: washer and dryer machines, heaters, A/C, and even small things such as hair straighteners or irons. The app will aim to minimize the costs of using all of these household appliances, simultaneously helping the user reduce their carbon footprint in the long run.

A rather advanced programming concept will be explored to implement in this algorithm: Mixed Integer Linear Programming (MILP). We picked this approach because generating such a cost-efficiency schedule while accounting for various variables (e.g. user constraints, time intervals, user preferences) requires the prospective algorithm to juggle multiple things at once, and MILP just so happened to be the perfect fit for such implementation.

In this paper, the current and voltage output of the photovoltaic panel was predicted using Support Vector Machine. Investigation on renewable energy, Leeds to seek for its efficiency improvement and hence solar. It is important to utilize the maximum power possible to produce without wasting any and there comes the role of efficiency techniques. This paper introduces a unique method to improve the efficiency of the PV panel using Support Vector Machine (SVM). Used learning data were temperature and irradiation of one-year duration. The obtained results show that the system is completely capable of predicting the future power from the PV panel once the temperature and irradiation values are given.

Keywords: PV,SVM, effecency,Mppt;

Life-safety, ventilation, lighting, health and comfort. Security comes from the need to protect property, content and personnel. Examples of security requirements are identification of vehicles entering and exiting a car park, controlling access to sensitive or secured areas, and precautions against terrorist bomb threats, robberies and burglaries. Security has become a high profile global issue in the aftermath of the September 11 2001 terrorist attacks and the ongoing terrorist threat.

The functions implemented by security systems include the following: Surveillance CCTV ( Analog and Digital), Detection, Alarms, Access control, and Communication and information management. Several of these functions are usually integrated with those of other systems. For example, in case of a fire, all doors must be unlocked. In this research, we are going to introduce several techniques of video compression employed in a CCTV system.

The majority of UAE cities are located close to the sea and it is more economical to obtain the sand from the seashore which contains a large amount of sea shells. This study experimentally investigates the effect of crushed sea shells that exists in the sand used in the construction work in UAE on the mechanical properties of concrete in terms of compressive strength and flexural strength. Four different percentages of sea shells have been investigated by using sieve analysis of the raw sand (29%, 14%, 4%, 0%) and then used to prepare the standard mortar and concrete cubes and beams. 48 concrete cubes, 24 concrete beams, 48 mortar cubes and 48 mortar beams have been prepared for testing purposes.

Results revealed that there was a slight decrement in the compressive strength of standard concrete and mortar cubes prepared using raw sand containing 29% sea shells comparing to cubes made with sand removing all exists sea shells 0%. On the other hand, the flexural strength of concrete and mortar beams was slightly higher for beams made with sand containing 29% crushed sea shells comparing to beams made using 0% sea shells in the sand.  All recorded results are for samples loaded until failure after curing 3, 7, 14 and 28 days. The only exception was for the concrete beams as results are for samples loaded until failure after curing 3, 7 and 28 days. This research work recommends using the marine sand in UAE without any considerations of having the crushed sea shells; since the existence of the sea shells has no significant effect on compressive the strength of concrete and it can slightly improve the flexural strength of mortar and concrete.