The Dilemma of Private Justice Systems: Big Data Sources, the Cloud and Predictive Analytics

Abstract: In the age of big data, demanding customer expectations, and increasingly limited access to justice for small claims arising from online sales, business organizations are moving to enhanced online customer complaint platforms and insisting upon increased online justice resolution systems. At the same time, online businesses, even websites you fail to think of as a business, are moving from traditional analytics that provide a snapshot of the past, to solutions that provide an accurate picture of the present and a prediction of future trends. For many, predictive analytics is the wave of the future. In many ways, the use of predictive analytics is a wonderful occurrence, as our packages will arrive in a more timely manner, our advertising will be more personal and our online and physical lives will be tailored, monitored and adjusted to our interests, life styles and immediate needs without so much as a hiccup. However, what will happen when the current push for private online dispute resolution systems meets the current big data gathering of a private market? Will the private online dispute resolution providers use the information gathered for good, or as a means to quickly resolve disputes without notice of the law, personal rights and/or ethical outcomes? Worse yet, what will happen when the private market of online dispute resolution faces the demands of a business environment that would prefer analytic outcomes to be skewed to favor the business? Bear in mind, these issues do not arise in a prediction, these private online dispute resolution mechanisms already exist and are growing in support and use on a daily basis. This paper will explore the emerging issue that occurs when private online dispute resolution providers are allowed, without transparency, oversight, or regulation, to create a justice system that knows a lot of personal information about you but is required to follow no legal standard or regulation to resolve your dispute with a merchant

Impacts of Energy Development on Utah Water Resources

Introduction: Choosing a theme for a conference especially one for a group of diverse disciplines such as the American Water Resources Association encompasses, is always a challenge. you find yourself torn between thigns you\u27d really like to talk and hear about, and topics you think will draw attendance. It was most fortunate when somebody came up with the idea of Water for Energy, becasue to my way of thinking, it met both of these ends. There is no denying that starting in late 1973, energy has been the catchword, and the energy crisis has been the bandwagon to leap upon. But in Utah, energy is more than potent ad copy. Development of the coal, oil, oil shale, bituminous sands, and geothermal resources within the State can, and perhaps will, turn the state unside down. Whether or not anyone at any level of government will be able to exercise control over evnergy-related events remains to be seen. It is no surprise that energy-development in Utah will be governed by the availability of water. What may be more important is the growing evidence that if the laws and policies of the state regarding allocation of water are not changed, energy development will get all the water it needs (through the free market system(, and agriculture will be the loser. So the energy crisis will become in effect a rural life crisis. Nearly everybody wants to have conomic growth; nearly everybody wants to maintain the environmentl and aesthetics that have made Utah a pleasant place to live. But can we have both? Water is but one aspect of this question, but in Utah it is a cruicial one. The papers that follow discuess technical, economic, social, legal, and political factors associated with water development for evergy in Utah. Hopefully, this material will provide new insights and result in more informed and rational decision-making

The doctoral research abstracts. Vol:11 2017 / Institute of Graduate Studies, UiTM

Foreword: Congratulation to IGS on the continuous effort to publish the 11th issue of the Doctoral Research Abstracts which highlights the research in various disciplines from science and technology, business and administration to social science and humanities. This research abstract issue features the abstracts from 91 PhD doctorates who will receive their scrolls in this 86th UiTM momentous convocation ceremony. This is a special year for the Institute of Graduate Studies where we are celebrating our 20th anniversary. The 20th anniversary is celebrated with pride with an increase in the number of PhD graduates. In this 86th convocation, the number of PhD graduates has increased by 30% compared to the previous convocation. Each research produces an innovation and this year, 91 research innovations have been successfully recognized to have made contributions to the body of knowledge. This is in line with this year UiTM theme that is “Inovasi Melonjak Persaingan Global (Innovation Soars Global Competition)”. Embarking on PhD research may not have been an easy decision for many of you. It often comes at a point in life when the decision to further one’s studies is challenged by the comfort of status quo. I would like it to be known that you have most certainly done UiTM proud by journeying through the scholarly world with its endless challenges and obstacles, and by persevering right till the very end. Again, congratulations to all PhD graduates. As you leave the university as alumni we hope a new relationship will be fostered between you and UiTM to ensure UiTM soars to greater heights. I wish you all the best in your future endeavor. Keep UiTM close to your heart and be our ambassadors wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Ambulance Emergency Response Optimization in Developing Countries

The lack of emergency medical transportation is viewed as the main barrier to the access of emergency medical care in low and middle-income countries (LMICs). In this paper, we present a robust optimization approach to optimize both the location and routing of emergency response vehicles, accounting for uncertainty in travel times and spatial demand characteristic of LMICs. We traveled to Dhaka, Bangladesh, the sixth largest and third most densely populated city in the world, to conduct field research resulting in the collection of two unique datasets that inform our approach. This data is leveraged to develop machine learning methodologies to estimate demand for emergency medical services in a LMIC setting and to predict the travel time between any two locations in the road network for different times of day and days of the week. We combine our robust optimization and machine learning frameworks with real data to provide an in-depth investigation into three policy-related questions. First, we demonstrate that outpost locations optimized for weekday rush hour lead to good performance for all times of day and days of the week. Second, we find that significant improvements in emergency response times can be achieved by re-locating a small number of outposts and that the performance of the current system could be replicated using only 30% of the resources. Lastly, we show that a fleet of small motorcycle-based ambulances has the potential to significantly outperform traditional ambulance vans. In particular, they are able to capture three times more demand while reducing the median response time by 42% due to increased routing flexibility offered by nimble vehicles on a larger road network. Our results provide practical insights for emergency response optimization that can be leveraged by hospital-based and private ambulance providers in Dhaka and other urban centers in LMICs

Factors influencing learner driver experiences [Road Safety Grant Report 2009-003]

When compared with more experienced drivers, new drivers have a higher crash risk. This study examined the experiences of learner drivers in Queensland and New South Wales in order to develop an understanding of the factors that influenced them while learning to drive. This will enable the development of more effective licensing systems. The research was informed by a number of heoretical perspectives, particularly social learning theory. Participants were recruited from driver licensing centres as soon as they passed their practical driving test to attain a provisional licence. Of those approached, 392 new drivers from capital cities and regional locations in Queensland and New South Wales completed a 35 minute telephone interview that collected information on a range of personal, social, environmental and socio-demographic factors. Participants were obtaining their licence before several changes to the licensing systems in both Queensland and New South Wales were made in 2007. Several implications for countermeasure development resulted from this research. These included ensuring licensing authorities carefully consider mandating a minimum number of hour of practice as it may inadvertently suppress the amount of practice that some learners obtain. Licensing authorities should consider the use of logbooks for learner drivers, even if there is no minimum amount of supervised practice required as it may assist learners and their supervisors structure their practice more effectively. This research also found that the confidence of learner drivers increases between when they first obtain their learner licence and when they obtain their provisional licence. This is an important issue requiring further attention by licensing authorities

Personalized Ambience: An Integration of Learning Model and Intelligent Lighting Control

The number of households and offices adopting automation system is on the rise. Although devices and actuators can be controlled through wireless transmission, they are mostly static with preset schedules, or at different times it requires human intervention. This paper presents a smart ambience system that analyzes the user’s lighting habits, taking into account different environmental context variables and user needs in order to automatically learn about the user’s preferences and automate the room ambience dynamically. Context information is obtained from Yahoo Weather and environmental data pertaining to the room is collected via Cubesensors to study the user’s lighting habits. We employs a learning model known as the Reduced Error Prune Tree (REPTree) to analyze the users’ preferences, and subsequently predicts the preferred lighting condition to be actuated in real time through Philips Hue. The system is able to ensure the user’s comfort at all time by performing a closed feedback control loop which checks and maintains a suitable lighting ambience at optimal level

Computer generated and photographic images

ThesisPhotography is undergoing a revolution, as profound as when glass plates were replaced by acetate film. No longer are photographers reliant on darkrooms, and often poisonous chemicals to process their films. Images can now be recorded in digital form using conventional cameras fitted with special backs containing electronic form, loaded into a computer where they can be enhanced, manipulated or analysed, and the output directly to printing plates, or high quality paper printer. There is no fundamental change in the way pictures are taken - photographers still need the skills of lighting and composition, but now have far greater control over the image. By the same token their role is changing, no longer are they just photographers, they require to transmit the image via a computer, and a result on paper. The barriers between printer, photographer and designer are becoming blurred. This script explains the new technologies of electronic imaging. It looks at the past, future, predictions and the advantages and disadvantages between traditional and digital photography. A range of cameras and printers are also mentioned. It also shows how I went about getting to my final images. There are also a variety of images included to show you, the reader, what results can be achieved. Although the traditional skills of the photographer will not change, anyone working in the field of imageing needs to change their working methods if they are to survive in this rapid expanding field of technology