A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

Adding Energy Star Rating Schema to Android Applications on Google Play Store an Example of a Preventive Power Saving Model

info:eu-repo/semantics/publishedVersio

Comparison of Game Theoretical Strategy and Reinforcement Learning in Traffic Light Control

Many traffic models and control methods have already been utilized in the public transportation system due to the increasing traffic congestion. Thus, an intelligent traffic model is formalized and presented to control multiple traffic light simultaneously and efficiently according to the distribution of vehicles from each incoming link (i.e. sections) in this paper. Compared with constant strategy, two methods are proposed for traffic light control, i.e., game theoretical strategy and reinforcement learning methods. Game theoretical strategy is generated in a game theoretical framework where incoming links are regarded as players and the combination of the status of traffic lights can be regarded as decisions made by these players. The cost function is evaluated and the strategy is produced with Nash equilibrium for passing maximum vehicles in an intersection. The other one is Single-Agent Reinforcement Learning (SARL), specifically with the Q-learning algorithm in this case, which is usually used in such a dynamic environment to control traffic flow so the traffic problem could be improved. Generally, the intersection is regarded as the centralized agent and controlling signal status is considered as the actions of the agent. The performance of these two methods is compared after simulated and implemented in a junction

Sistem Penghitung dan Pengklasifikasi Jenis Kendaraan Secara Real Time Menggunakan Pengolahan Citra pada Komputer Papan Tunggal Nvidia Jetson Nano

Untuk mendukung terwujudnya smart city, interkoneksi antar bidang menjadi sangat penting, tak terkecuali bidang transportasi. Bidang transportasi berperan sangat besar untuk mendukung kemajuan daerah. Perbandingan jumlah kedaraan dan kapasitas jalan raya yang sesuai sangat penting untuk diperhatikan. Apabila kapasitas jalan kurang, maka akan menimbulkan kemacetan. Kemacetan ini bisa menaikkan tingkat kecelakaan, efek pada pertumbuhan ekonomi, dan kenaikan emisi gas buang. Arus kendaraan merupakan suatu hal yang penting dalam pengoperasian dan perencanaan pada ruas jalan yang baru dan melakukan modifikasi  ruas jalan yang ada untuk dapat memenuhi dan mengantisipasi perubahan yang terjadi pada kondisi lalu-lintas.Untuk mendapatkan informasi karakteristik lalu-lintas ,diperlukan berbagai informasi sarana lalu-lintas yang bergerak, serta perilaku penggunanya. Dari informasi yang diperoleh kemudian dianalisa untuk didapatkan hasil dampak kerja lalu-lintas, apabila hasil dari dampak kerja berada kurang dari  standar pelayanan minimal, maka perlu diusulkan untuk perbaikan geometrik atau pengaturan kembali penggunaan pada ruang jalan. Penghitungan jumlah kendaraan dan pengklasifikasian selama ini dilakukan dengan cara penghitungan secara konvensional  pada titik waktu yang ditentukan. Penggunaan teknik ini  memiliki kekurangan yaitu memerlukan sumber daya manusia yang banyak dan tidak bisa dilakukan secara terus menerus. Dengan mengetahui kondisi tersebut, maka  dalam penelitian ini akan dibuat sistem penghitung dan melakukan klasifikasi  jenis kendaraan secara real time dan terus menerus menggunakan teknik pengolahan citra. Komputer papan tunggal nVidia Jetson Nano digunakan karena didesain melakukan proses kecerdasan buatan yang tertanam dan dengan harga yang relatif terjangkau. Berdasarkan percobaan didapatkan hasil Sistem Pendeteksian yang digunakan mobienet-SSD v2 hasil training mendapatkan akurasi perhitungan kendaraan sepeda motor 50 %, kendaraan ringan yang terdiri dari mobil dan pickup sejumlah 65 %, Truk sejumlah 83 % dan Bus sejumlah 33 %. Kecepatan pemrosesan metode pada Jetson Nano dengan tensor RT, mobilenet SSD v2 dan tensorflow didapatkan kecepatan proses realtime 24 fps.Untuk mendukung terwujudnya smart city, interkoneksi antar bidang menjadi sangat penting, tak terkecuali bidang transportasi. Bidang transportasi berperan sangat besar untuk mendukung kemajuan daerah. Perbandingan jumlah kedaraan dan kapasitas jalan raya yang sesuai sangat penting untuk diperhatikan. Apabila kapasitas jalan kurang, maka akan menimbulkan kemacetan. Kemacetan ini bisa menaikkan tingkat kecelakaan, efek pada pertumbuhan ekonomi, dan kenaikan emisi gas buang. Arus kendaraan merupakan suatu hal yang penting dalam perencanaan dan pengoperasian untuk jalan-jalan yang baru dan memodifikasi dari jalan-jalan yang ada untuk dapat memenuhi dan mengatasi perubahan yang terjadi pada kondisi lalu-lintas.Untuk mendapatkan informasi mengenai karakteristik lalu-lintas maka diperlukan berbagai informasi mengenai prasarana lalu-lintas yang bergerak, serta perilaku penggunanya. Informasi yang diperoleh kemudian dianalisa untuk memperoleh hasil dampak kerja lalu-lintas, bila hasil dampak kerja berada dibawah standar pelayanan minimal, maka selanjutnya diusulkan untuk perubahan geometrik atau pengaturan penggunaan ruang jalan. Penghitungan jumlah kendaraan dan pengklasifikasian selama ini dilakukan secara manual pada waktu-waktu tertentu. Hal ini memiliki kekurangan yaitu memerlukan sumber daya manusia yang banyak dan kurang efisien. Oleh karena itu dalam penelitian ini akan dibuat sistem penghitung dan pengklasifikasi jenis kendaraan secara real time menggunakan pengolahan citra. Komputer papan tunggal nVidia Jetson Nano digunakan karena didesain melakukan proses kecerdasan buatan yang tertanam dan dengan harga yang relatif terjangkau. Berdasarkan percobaan didapatkan hasil Sistem Pendeteksian yang digunakan mobienet-SSD v2 hasil training mendapatkan akurasi perhitungan kendaraan sepeda motor 50 %, kendaraan ringan yang terdiri dari mobil dan pickup sejumlah 65 %, Truk sejumlah 83 % dan Bus sejumlah 33 %. Kecepatan pemrosesan metode pada Jetson Nano dengan tensor RT, mobilenet SSD v2 dan tensorflow didapatkan kecepatan proses realtime 24 fps

ComplexWorld Position Paper

The Complex ATM Position Paper is the common research vehicle that defines the high-level, strategic scientific vision for the ComplexWorld Network. The purpose of this document is to provide an orderly and consistent scientific framework for the WP-E complexity theme. The specific objectives of the position paper are to: - analyse the state of the art within the different research areas relevant to the network, identifying the major accomplishments and providing a comprehensive set of references, including the main publications and research projects; - include a complete list of , a list of application topics, and an analysis of which techniques are best suited to each one of those applications; - identify and perform an in-depth analysis of the most promising research avenues and the major research challenges lying at the junction of ATM and complex systems domains, with particular attention to their impact and potential benefits for the ATM community; - identify areas of common interest and synergies with other SESAR activities, with special attention to the research topics covered by other WP-E networks. An additional goal for future versions of this position paper is to develop an indicative roadmap on how these research challenges should be accomplished, providing a guide on how to leverage on different aspects of the complexity research in Air Transport

Cloud computing and context-awareness: A study of the adapted user experience

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Today, mobile technology is part of everyday life and activities and the mobile ecosystems are blossoming, with smartphones and tablets being the major growth drivers. The mobile phones are no longer just another device, we rely on their capabilities in work and in private. We look to our mobile phones for timely and updated information and we rely on this being provided any time of any day at any place. Nevertheless, no matter how much you trust and love your mobile phone the quality of the information and the user experience is directly associated with the sources and presentation of information. In this perspective, our activities, interactions and preferences help shape the quality of service, content and products we use. Context-aware systems use such information about end-users as input mechanisms for producing applications based on mobile, location, social, cloud and customized content services. This represents new possibilities for extracting aggregated user-centric information and includes novel sources for context-aware applications. Accordingly, a Design Research based approach has been taken to further investigate the creation, presentation and tailoring of user-centric information. Through user evaluated experiments findings show how multi-dimensional context-aware information can be used to create adaptive solutions tailoring the user experience to the users’ needs. Research findings in this work; highlight possible architectures for integration of cloud computing services in a heterogeneous mobile environment in future context-aware solutions. When it comes to combining context-aware results from local computations with those of cloud based services, the results provide findings that give users tailored and adapted experiences based on the collective efforts of the two

Quality assessment technique for ubiquitous software and middleware

The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future

Electrification of Smart Cities

Electrification plays a key role in decarbonizing energy consumption for various sectors, including transportation, heating, and cooling. There are several essential infrastructures for a smart city, including smart grids and transportation networks. These infrastructures are the complementary solutions to successfully developing novel services, with enhanced energy efficiency and energy security. Five papers are published in this Special Issue that cover various key areas expanding the state-of-the-art in smart cities’ electrification, including transportation, healthcare, and advanced closed-circuit televisions for smart city surveillance

Travel Demand Growth: Research on Longer-Term Issues. The Potential Contribution of Trip Planning Systems

INTRODUCTION 1.1 The growth in demand for travel Over the 20 years hm 1965, National Travel Survey (NTS) data shows a 61% growth in total person - km of travel. More detailed analysis suggests that this is made up roughly as follows:- due to increased population 4% due to more journeys 22% due to longer journeys 35% This implies that around 60% of the growth in travel has been due to people travelling further, rather than making more journeys. It is interesting to note, too, that the same phenomenon occurs even in the most congested areas. Between 1975 and 1985, NTS shows an 11% growth in person -km by London residents, at a time when population fell by 5%. In this case, the growth is made up roughly as follows:- due to lost population -5% due to more journeys 4% due to longer journeys 12% It is of course difficult to estimate the extent to which future growth in travel will be generated by longer journeys. The NRTF, which predicts a growth in car-km of between 120% and 180% between 1985 and 2025, is not based on a procedure which enables the effects of journey making and journey length to be separated. However, it is worth noting that if the same pattern were to exist at a national level in future, the predicted growth in car travel due to longer journeys could be equivalent to between 75% and 100% of today's car travel. It seems appropriate to ask whether it is a wise use of scarce resources to provide the infrastructure and energy needed to enable people to carry out their activities further from home. (Continues...