Syntactic approach to electric mobility in metropolitian areas: NE 1 district core, segment map

Capturing vehicular travel behavior is one of the most popular models that deal with relevant aspects of urban regions and communities. Since 1960s, it has been matured and evolved to cover all aspects of travel demand applications. Different theories are employed to predict the movement of trip makers' likewise metric method and the estimation of origin-destination matrixes, intervening opportunities method which counts more on probabilities, and finally the spatial configuration modeling. The latter is to apply topo-geometrical analysis to arrive at configurational measures that can optimally approximate movement patterns in the urban network. Space syntax is an alternative approach to estimate conventional vehicular travel demand without using O-D matrix trip data, which is difficult to be obtained. Space Syntax is an alternative approach to predict the vehicular movement in urban systems using the concept of accessibility measures (syntactic measures and maps) which reflects the complexity of routes from a road segment to all the others within the system. The syntactic approach is employed in this study to simulate a particular mobility system; electric vehicles (EVs) cluster. Simulating EVs'-systems is a subset of the conventional traffic modeling entire group. In particular, EV modeling environment set-up and configurations differ due to the special paradigms and behavioral characteristic aspects the system has. EV market is a niche market though it is expanding. This paper maps the current EV systems and focuses on one of which that needs prompt actions to be taken to have a mainstream supported and reliable market of EVs. Charging service is a thorny problem annoys the current users and hinders potential users to switch to low carbon emission vehicle purchase option. The study area located in the North East region of United Kingdom is investigated in detail. Spatial configuratioal analysis of the inner urban core of the metropolitan area, Newcastle-Gateshead, NE1 is undertaken. This paper presents a methodology to integrate configuratiomal modeling of NE1 to simulate the mobility mode within the context. Spatial analysis and segment maps have been generated via the use of Depthmap research software. Real information about users was collected from the service providers to employ some the simulation assumptions. A multi model simulation modeling is developed while incorporating configurational modeling to build the urban layer of an EV simulation environment. Space syntax analysis is conducted by using the open source application, Depthmap. Simulation is developed via a commercial tool, Anylogic. The paper views the necessary steps of forming and analyzing the urban system facilitating the integration of EV system to run the simulation

Eras of electric vehicles: electric mobility on the Verge. Focus Attention Scale

Daily or casual passenger vehicles in cities have negative burden on our finite world. Transport sector has been one of the main contributors to air pollution and energy depletion. Providing alternative means of transport is a promising strategy perceived by motor manufacturers and researchers. The paper presents the battery electric vehicles-BEVs bibliography that starts with the early eras of invention up till 2015 outlook. It gives a broad overview of BEV market and its technology in a chronological classification while sheds light on the stakeholders’ focus attentions in each stage, the so called, Focus-Attention-Scale-FAS. The attention given in each era is projected and parsed in a scale graph, which varies between micro, meso, and macro-scale. BEV-system is on the verge of experiencing massive growth; however, the system entails a variety of substantial challenges. Observations show the main issues of BEVsystem that require more attention followed by the authors’ recommendations towards an emerging market

Shocks Pass-Through to Prices in U.S. and Canada: Evidence from Oil and Exchange Rate Markets

This paper investigates the degree of exchange rate and oil prices pass-through to import prices, producer prices, and consumer prices in Canada and United States over the period from 1980 to 2017 using a Structural Vector Auto-Regression (SVAR) model. The results indicate a robust evidence of a positive long-run correlation between exchange rate & oil prices and aggregate price levels. Impulse response function reveals a persistent and incomplete pass-through for both exchange rates and oil prices i.e. 0.20 and 0.04 for Canada and 0.27 and 0.25 for the U.S. That is, greater pass-through exist in an economy which has a more oil import share, more volatile monetary policy, and higher inflation rate. Consistent with impulse response function, variance decomposition reveals that oil price shocks in the United States are the major cause of the variation in the import prices and producer prices, while exchange rate fluctuations explain more of the variation in consumer prices. However, in Canada, import prices are mainly explained by exchange rate fluctuations, while oil price shocks explain the variation in producer and consumer prices

STREAM-EVOLVING BOT DETECTION FRAMEWORK USING GRAPH-BASED AND FEATURE-BASED APPROACHES FOR IDENTIFYING SOCIAL BOTS ON TWITTER

This dissertation focuses on the problem of evolving social bots in online social networks, particularly Twitter. Such accounts spread misinformation and inflate social network content to mislead the masses. The main objective of this dissertation is to propose a stream-based evolving bot detection framework (SEBD), which was constructed using both graph- and feature-based models. It was built using Python, a real-time streaming engine (Apache Kafka version 3.2), and our pretrained model (bot multi-view graph attention network (Bot-MGAT)). The feature-based model was used to identify predictive features for bot detection and evaluate the SEBD predictions. The graph-based model was used to facilitate multiview graph attention networks (GATs) with fellowship links to build our framework for predicting account labels from streams. A probably approximately correct learning framework was applied to confirm the accuracy and confidence levels of SEBD.The results showed that the SEBD can effectively identify bots from streams and profile features are sufficient for detecting social bots. The pretrained Bot-MGAT model uses fellowship links to reveal hidden information that can aid in identifying bot accounts. The significant contributions of this study are the development of a stream based bot detection framework for detecting social bots based on a given hashtag and the proposal of a hybrid approach for feature selection to identify predictive features for identifying bot accounts. Our findings indicate that Twitter has a higher percentage of active bots than humans in hashtags. The results indicated that stream-based detection is more effective than offline detection by achieving accuracy score 96.9%. Finally, semi supervised learning (SSL) can solve the issue of labeled data in bot detection tasks

Rethinking adequate housing for low-income women of the Global South : reflections on women initiated housing transformations to Masese Women Slum-Upgrading Housing Project, Jinja, Uganda

The global discourse on low-income housing promotes participation to provide slum dwellers of the Global South with adequate housing. Despite acknowledged women’s extra vulnerability to the substandard housing of slums, how their participation, or what design considerations support their housing adequacy, remains ambiguous. Case study methodology was used for the exploration of the research presented in this PhD thesis. Targeting women as its main beneficiaries, Masese Women Slum-Upgrading Housing Project (MWSUHP) was selected as the case for the research explorations at it represents the state of the art in providing adequate housing to women living in Ugandan slums. The research aims at describing, exploring and developing an understanding of the contribution of women’s participation in MWSUHP housing processes, as well as identifying design considerations to support their adequate housing provision. Empirical evidence was gathered using combined methods of documents and drawings analysis, walk-throughs, interviews and focus group discussions. The research identified the domination of the colonial ideologies, men’s over representation, ad the gender blindness of the Ugandan low-income housing discourse. These factors contributed to the production of housing designs that promote gender stratification, segregation and subordination. The research results acknowledged Ugandan low-income women’s substantial design knowledge to their housing adequacy and highlights the importance of interpreting housing designs in gender-related terms. To attain housing adequacy to the Ugandan low-income women, the research advocates for; i) including low-income women in their housing design processes, ii) increase women’s representation in the Ugandan housing design discourses, iii) developing housing design ideologies that understand housing in gender related terms iv) developing housing designs that appreciate the Ugandan low-income women’s socio-cultural contexts and lifestyles, respond to their productive, reproductive and community integration roles v) embracing women’s intersectionality vi) considering flexibility, spontaneity, improvisation and incremental development in their housing designs. This research contributes in filling the knowledge gap in the low-income housing discourse, with a focus on providing women living in the Ugandan slums with adequate housing

Safe Space: To Help Minimize Cyberbullying and Support Social Well-being

The perverseness of cyberbullying as a growing and serious form of abuse with the potential for harm among children and youth needs to be recognized. In a resource-limited setting such as South Asia where youth have very little access to counseling within schools, the implications for mental health should be recognized. This research study explores whether our youth is capable of using technology in the right way to minimize cyberbullying and support social well-being. Index Terms - Cyberbullying, Social Well-being, User Experience Design, and Usability Study