r-TOLA: an architecture for real time open learning application for universities

Obtaining degree from university requires rigorous findings and research. Some subjects/courses are very challenging that made it essential to form study groups among students. Besides attending regular lectures, it is demanding to manage time for study groups. As a result, most of the time, students perform below expectation in their academic activities. meanwhile, managing a central real time open learning application will help in maintaining group study easily as well as improve students’ academic performance. Hence, this paper proposes a Real Time Open Learning Application for University (r-TOLA) which consists of huge academic study group’s history that will, help students to dig into archives, search case studies, questions, projects and answers. This will also benefit lecturer to know the trend in students’ performance

Prediction of optimal adsorption of aqueous phenol removal with oil palm empty fruit bunch activated carbon using Artificial Neural Network (ANN)

Adsorption process has an edge in wastewater treatment over other techniques due to low initial cost, sludge free, ease of operation and insensitivity to toxic substance. It is a very essential part in the wastewater treatment process chain. It involves both physical and chemical phenomena and hence susceptible to high percentage of errors due to human factor, variation in the quality as well as chemical/physical characteristics of raw materials used. In order to reduce this percentage error and obtain optimal treatment efficiency, an intelligent method of predicting optimal adsorption capacity based on Artificial Neural Network (ANN) was proposed. Production of Powdered Activation Carbon PAC from processed oil palm empty fruit bunches, EFB was used as adsorbent. Since production of PAC is affected by many parameters, such as CO2 gas flow rate, activation time and activation temperature. Adsorption design was carried out using all these parameters, production results were analyzed. ANN was used to forecast optimal adsorption capacity for aqueous phenol removal. Such ANN based system will be a useful method to address most errors common in wastewater treatment cause by human factors. Experimental results on real data show that the newly developed system is able to accurately predict the optimal adsorption capacity needed in wastewater treatment plant. The Regression and correlation between of optimal adsorption capacity for experimental result and ANN estimation model is 0.9999 of 1.000. This high Correlation of coefficient indicates that the ANN model is a perfect match

Smart parking guidance system using 360o camera and haar-cascade classifier on IoT system

Nowadays, smart parking guidance system is a crucial research for people’s convenience. The main objective of this research is to develop and analyze on a smart parking guidance system where current available system was compared to this new proposed system. Limited parking space has become serious issue since the number of Malaysia’s populations who are using car keep increasing. Some of the big companies, shopping malls and other public facilities already deployed a smart parking system on their building. However, there are still a lot of buildings that do not own it because the system required a lot of investment, where the huge parking areas need higher cost to install sensors on each parking lot available. The proposed smart parking guidance system in this research was depending on a 360° camera that was modified on raspberry pi camera module and 360o lens and Haar-Cascade classifier. The image and video processing was by Open CV and python program to detect the available parking space and cloud firebase was used to update data where users can access the parking space availability by android mobile phone specifically at a closed parking space. A single 360°camera was replaced several sensors and camera which was implemented on traditional smart parking system. An analysis was done on the performance of the system where it can detect the parking availability with 99.74% accuracy and which is far better than conventional system including reliability and cost for the parking space guidance system. © BEIESP

Contemplation of tone mapping operators in high dynamic range imaging

The technique of tone mapping has found widespread popularity in the modern era owing to its applications in the digital world. There are a considerable number of tone mapping techniques that have been developed so far. One method may be better than the other in some cases which is determined by the requirement of the user. In this paper, some of the techniques for tone mapping/tone reproduction of high dynamic range images have been contemplated. The classification of tone mapping operators has also been given. However, it has been found that these techniques lack in providing quality of service visualization of high dynamic range images. This paper has tried to highlight the drawbacks in the existing traditional methods so that the tone-mapped techniques can be enhanced

An empirical study of the evolution of PHP MVC framework

Commercial, social and educational importance of web technology has tremendously increased research activities in web programming/scripting. Several methods for writing PHP codes such as Object Oriented Programming (OOP), Procedural PHP coding and Model View Controller (MVC) pattern have been proposed. Model View Controller (MVC) which is one of the most powerful method for developing PHP application has many variant such Laravel, Symfony, CodeIgniter, CakePHP etc. However, selection of best MVC framework among the variants is of concern to the programmers as well as project managers, especially when managing big applications. Hence, performance evaluation criterions are required. This paper discusses the MVC based most famous PHP frameworks, evaluate their performance and it was found that Laravel outperforms other MVC framework, hence Laravel is proposed as the most suitable PHP framework for future web technology

Bandwith conservation framework for mobile cloud computing: challenges and solutions

Mobile devices are rapidly transforming the computing industry. It is emerging to be the super future computers. Challenges including network bandwidth limitation, availability and storage are among the limitations facing MCC as the number of mobile devices accessing the cloud services are rapidly growing. This paper reviews the state of art of mobile cloud computing as well as it summarizes the latest MCC challenges and solutions. We will also propose a bandwidth conservation framework that will help the bandwidth constrained users to reschedule bandwidth allocatio

STRATEGIC PROFILING & ANALYTIC MODELLING OF NODE MISBEHAVIOR IN MANET BASED IOT PARADIGM THEORY

Ubiquitous Computing and Internet of Things (IoT) are extremely popular in recent age and therefore imparting high level security mechanism is highly indispensable for such advanced technical systems. Game Theory acts as a suitable tool offering promising solutions to securityrelated concerns in Mobile Ad-Hoc Networks (i.e., MANETs). In MANETs, security forms a prominent concern as it includes nodes which are usually portable and require significant coordination between them. Further, the absence of physical organisation makes such networks susceptible to security breaches, hindering secure routing and execution among nodes. Coordination among nodes during communication and working without control of any central manager truly ensembles them to be applied in IoT. However, the identification and later mitigation of malicious nodes becomes an immensely difficult task especially when Selfish/Erroneous nodes exist along with normal Collaborative nodes in the Regular camp. Game Theory approach has been manipulated in the current study to achieve an analytical view while addressing the security concerns in MANETs. This study considers selfish nodes in the regular node camp while modelling the Regular versus Malicious node game and thereby enhancing the prior mathematical schema of strategical decision making to accommodate for the same. The proposed study performs statistical analysis and presents a mathematical model to mimic the multi-stage game between regular and malicious node using Game Theory. The simulation of the model has proved that the Perfect Bayesian Equilibrium outshines other approaches used in this study, specifically pure strategy and mixed strategy. The utility of both regular and malicious node has improved noticeably when nodes adopt PBE strategy. The framework tries to effectively represent the various unpredictable actions of node cooperation, node declination, node attacks as well as node reporting that can model the strategic profiling of various mobile nodes. Understanding the patterns and then deploying the algorithms in security products can reduce intrusion to a greater extent

An application of biometric technology : Iris recognition

Human identification has always been an imerest continuously explored by human. 1lIe need for identification comes from the need to detect and to recognize people for security. verification, validation and recognition and many other reasons. One method of identification that attracts among the greatest interest is biometric identification. Biometric identification deals with 11M: identification of various Iraits of our body. Biometric identification relies on the unique traits and p;lllem COIISiSI of voice. face. body, bi1'ihmark, iris, palm-print, finger-prim and many Olhers. AmOilg tho5e. iris recognition generates the greatest anemion in the last 20 )"<,ars due to lhe accuracy and the reliability of the recognilion. Iris recognition is arguably lhe most reliable biomelric identificalion currently available. Iris ties in,ide the the sclera, which is Ihe whiTe part of our eye. Inside the iris lies the pupil. The .haracterisTic of iris is unique for every individual. It also differs between idemical Twins. The characTeristic is even differem belween the left and right eyes. The iri, consists of limitless palleros that made itvery reliable in deteetion and recognition when compare to other biometrics such as thumb-print and facial recognitio

A cloud-based bus tracking system based on internet-of-things technology

The technological rise in public transportation is on the horizon, but the bus network structure and intelligent bus tracking system should first be in place. Bus transport service is on the edge of digital revolution, generating real-time tracking information about the bus service using smartphones. In this paper, a cloud-based bus tracking system based on IoT is proposed to reduce human intervention, waiting time and energy. The exact location and arrival time of the bus can be tracked dynamically by using a mobile application to provide better and efficient bus service. Furthermore, passengers can buy tickets without queueing and book the available seats by making online payments. The proposed scheme allows more flexibility and user satisfactory service to the rider in terms of time loss and encourages more people to ride by providing real-time bus tracking information to improve passenger satisfaction. The main objective is to minimize the unnecessary waiting and queueing time uncertainty of passengers. Riders can utilize their waiting time more productively by choosing the nearest route and alternative transportation. The sustainability of public transport service can be maintained by providing noteworthy benefits to the passengers using the proposed IoT-based bus tracking system

A proposed architecture for generic and scalable CDR analytics platform utilizing big data technology

Telecom Call Details Record (CDR) data-set is considered a rich source of valuable information that will bring new big revenues to Communication Service providers (CSP) as well as it will empower many out-telco services such as transportation, education, health programs, and business analysis in resource management and planning, decision making, and processes optimization. However, extracting these valuable information from raw CDRs with the classical SQL and BI systems is very costly and has poor performance measures. This is due to the big volume of CDR data-set, the high and growing data rate and the large number of fields it contains. Many CDR analytics systems were built using Big Data technology, to overcome the scalability problem of the centralized computing, but the heterogeneity usage of CDR analytics have not been considered; they were built for specific and predetermined use cases. This paper presents a proposed platform architecture for real, near-real time and batch CDR analysis to provide analytics for heterogeneous applications, through designing a high generic and scalable platform. This paper illustrates the platform design consideration along with how the proposed architecture was built. Moreover, it gives a brief functional description and implementation suggestions for each component in the architecture