Crisis Communication Patterns in Social Media during Hurricane Sandy

Hurricane Sandy was one of the deadliest and costliest of hurricanes over the past few decades. Many states experienced significant power outage, however many people used social media to communicate while having limited or no access to traditional information sources. In this study, we explored the evolution of various communication patterns using machine learning techniques and determined user concerns that emerged over the course of Hurricane Sandy. The original data included ~52M tweets coming from ~13M users between October 14, 2012 and November 12, 2012. We run topic model on ~763K tweets from top 4,029 most frequent users who tweeted about Sandy at least 100 times. We identified 250 well-defined communication patterns based on perplexity. Conversations of most frequent and relevant users indicate the evolution of numerous storm-phase (warning, response, and recovery) specific topics. People were also concerned about storm location and time, media coverage, and activities of political leaders and celebrities. We also present each relevant keyword that contributed to one particular pattern of user concerns. Such keywords would be particularly meaningful in targeted information spreading and effective crisis communication in similar major disasters. Each of these words can also be helpful for efficient hash-tagging to reach target audience as needed via social media. The pattern recognition approach of this study can be used in identifying real time user needs in future crises

Propagation of New Innovations: An Approach to Classify Human Behavior and Movement from Available Social Network Data

It is interesting to observe new innovations, products, or ideas propagating into the society. One important factor of this propagation is the role of individual's social network; while another factor is individual's activities. In this paper, an approach will be made to analyze the propagation of different ideas in a popular social network. Individuals' responses to different activities in the network will be analyzed. The properties of network will also be investigated for successful propagation of innovations

Emerging Next Generation Solar Cells Route to High Efficiency and Low Cost

Generation of clean energy is one of the main challenges of the 21st century. Solar energy is the most abundantly available renewable energy source which would be supplying more than 50 of the global electricity demand in 2100. Solar cells are used to convert light energy into electrical energy directly with an appeal that it does not generate any harmful bi products, like greenhouse gasses. The manufacturing of solar cells is actually based on the types of semiconducting or non semiconducting materials used and commercial maturity. From the very beginning of the terrestrial use of Solar Cells, efficiency and costs are the main focusing areas of research. The definition of so called emerging technologies sometimes described as including any technology capable of overcoming the Shockley-Queisser limit of power conversion efficiency 33.7 percent for a single junction device. In this paper, few promising materials for solar cells are discussed including their structural morphology, electrical and optical properties. The excellent state of the art technology, advantages and potential research issues yet to be explored are also pointed out. Md. Samiul Islam Sadek | Dr. M Junaebur Rashid | Dr. Zahid Hasan Mahmood "Emerging Next Generation Solar Cells: Route to High Efficiency and Low Cost" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 201

Spatiotemporal Patterns of Urban Human Mobility

The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples’ visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility

A Study of Manganese and Cobalt Incorporated Nickel Oxide Based Core-Shell Magnetic Nanoparticles

The synthesis along with the structural and magnetic properties of manganese (Mn) and cobalt (Co) -incorporated nickel oxide (NiO) inverted core-shell nanoparticles (CSNs) were investigated. The primary objective of this study was to determine the effect of substitution of nickel (Ni) by transition metal ions (Mn2+/Co2+) in affecting the magnetic properties of the resultant CSNs. The core of the CSNs is comprised of NiO and the shell constitutes a Nix(Mn/Co)1-xO phase. The synthesis of the CSNs was accomplished in two steps: first, NiO nanoparticles were synthesized using a thermal decomposition method. In the second step, our hydrothermal nanophase epitaxy method was used to create the core-shell structure. Rietveld refinement of X-ray diffraction (XRD) data show rock salt structure throughout in the Mn/Co incorporated CSNs. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images show a combination of pseudo-spherical and faceted shapes of CSNs whereas energy dispersive spectroscopy (EDS) indicates transition metal incorporation in the CSNs. The high-resolution (HR) TEM images confirmed the formation of distinct core and shell regions. Magnetic characterization shows that the Mn- and Co-substituted nickel oxide-based CSNs possess an inverted magnetic structure, with an antiferromagnetic core and a ferro- or ferrimagnetic shell. The coercivity and exchange bias properties are of larger magnitude in Mn-incorporated than in Co-incorporated CSNs

Business sustainability and the UN Global Compact: A “public interest” analysis for Muslim majority countries

Since 2000, different types of organisations have registered for the UN Global Compact (UNGC), an essential guide for undertaking socially and environmentally responsible business. As revealed by the UNGC data, enthusiasm in Muslim majority countries (MMCs) for subscribing to the Compact is comparatively much less than in any other parts of the world. Analysing the phenomenon and the possible reasons thereof, this article examines individuals’ economic responsibility in these MMCs in adhering to the principles of the UN Global Compact. The work shows that regime types, economic conditions, economic structures (with agriculture sector primacy informally employing the largest percentage of the labour force), and civil society conditions seem to have contributed significantly in the UN Global Compact participation by organisations in MMCs. The paper argues that Muslims should fulfil their individual religious obligation by valuing, upholding, and applying the principles of “public interest” (maṣāliḥ al-mursalah) in all commercial dealings not awaiting national consent or the organisations’ conformity to the Global Compact

Tradition and modernity in Islam: A reading through power, property and philanthropy

This study analyses some basic Islamic political, economic, and social traditions under three headings – power, property and philanthropy – to show that the Islamic tradition has embedded principles and concepts thought to be “modern” by many in the present world. It claims that the social responsibility principle of Islamic tradition that promotes devolution and good governance seems to be modern, and thus has survived for the last 1400 years. Thus, in fulfilling individual responsibility (as goods and service regulators, creators, and consumers), Muslims need to serve the interests of the nation, irrespective of business entities (or employees), and the community by following the traditions in Islam. In order to do that, Muslims need to comprehend and adhere to the comprehensive principles of Islam including its guidance for political, property, and social relationships, to become “modern.

Uformer: A UNet-Transformer fused robust end-to-end deep learning framework for real-time denoising of lung sounds

Objective: Lung auscultation is a valuable tool in diagnosing and monitoring various respiratory diseases. However, lung sounds (LS) are significantly affected by numerous sources of contamination, especially when recorded in real-world clinical settings. Conventional denoising models prove impractical for LS denoising, primarily owing to spectral overlap complexities arising from diverse noise sources. To address this issue, we propose a specialized deep-learning model (Uformer) for lung sound denoising. Methods: The proposed Uformer model is constituted of three modules: a Convolutional Neural Network (CNN) encoder module, dedicated to extracting latent features; a Transformer encoder module, employed to further enhance the encoding of unique LS features and effectively capture intricate long-range dependencies; and a CNN decoder module, employed to generate the denoised signals. An ablation study was performed in order to find the most optimal architecture. Results: The performance of the proposed Uformer model was evaluated on lung sounds induced with different types of synthetic and real-world noises. Lung sound signals of -12 dB to 15 dB signal-to-noise ratio (SNR) were considered in testing experiments. The proposed model showed an average SNR improvement of 16.51 dB when evaluated with -12 dB LS signals. Our end-to-end model, with an average SNR improvement of 19.31 dB, outperforms the existing model when evaluated with ambient noise and fewer parameters. Conclusion: Based on the qualitative and quantitative findings in this study, it can be stated that Uformer is robust and generalized to be used in assisting the monitoring of respiratory conditions

Understanding the Loss in Community Resilience due to Hurricanes using Facebook Data

Significant negative impacts are observed in productivity, economy, and social wellbeing because of the reduced human activity due to extreme events. Community resilience is an important and widely used concept to understand the impacts of an extreme event to population activity. Resilience is generally defined as the ability of a system to manage shocks and return to a steady state in response to an extreme event. In this study, aggregate location data from Facebook in response to Hurricane Ida are analyzed. Using changes in the number of Facebook users before, during, and after the disaster, community resilience is quantified as a function of the magnitude of impact and the time to recover from the extreme situation. Based on the resilience function, the transient loss of resilience in population activity is measured for the affected communities in Louisiana. The loss in resilience of the affected communities are explained by three types of factors, including disruption in physical infrastructures, disaster conditions due to hurricanes, and socio-economic characteristics. A greater loss in community resilience is associated with factors such as disruptions in power and transportation services and disaster conditions. Socioeconomic disparities in loss of resilience are found with respect to median income of a community. Understanding community resilience using decreased population activity levels due to a disaster and the factors associated with losses in resilience will enable us improve hazard preparedness, enhance disaster management practices, and create better recovery policies towards strengthening infrastructure and community resilience

Novel Approach To In-situ Mocvd Oxide/dielectric Deposition For Iii-nitride-based Heterojunction Field Effect Transistors

III-Nitride-based compound semiconductors have unique properties such as high bandgap and high breakdown field, which make them attractive for a variety of applications, including high-power and high-frequency electronics and optoelectronics. The most common types of III-Nitride-based field effect transistors (FETs) are aluminum gallium nitride (AlGaN)/gallium nitride (GaN) based, which suffer from some inherent problems such as virtual gate effect, current collapse, gate leakage, etc. The solution to this problem can be the inclusion of a dielectric passivation layer under the gate. However, the addition of the dielectric layer impacts one of the most critical device-controlling parameters, “threshold voltage”, which suffers significantly due to the shift to a higher value. In this dissertation, we have developed a new approach to improve the threshold voltage of the metal oxide semiconductor heterostructure field effect transistor (MOSHFET) structure by in-situ deposition of oxide (e.g., gallium oxide (Ga2O3)) dielectric starting from the sapphire substrate in one step without breaking the vacuum inside the deposition chamber. The overall process shows ~75%-88% improvement of interfacial trap density between the oxide and the AlGaN barrier layer, which ultimately helped to reduce the threshold voltage shift. Integration of oxide precursors in the III-Nitride growth reactor is challenging as the precursors may react, leading to catastrophic damage to the metal-organic chemical vapor deposition (MOCVD) system. However, a systemic approach was used to avoid this problem by mainly using nitrogen as the carrier gas instead of using the most common, hydrogen gas. Switching the growth method to nitrogen carrier gas changes the growth dynamics; hence few of the epilayers’ processes require optimization. In this regard, first, a high-quality aluminum nitride (AlN) epitaxial growth process was developed in the nitrogen environment. The epilayer showed low X-ray diffraction (10¯12) rocking curve FWHM of 289 arcsecs with E2 (high) phonon peak linewidth of 3.4 cm-1 at around 659 cm-1 and low compressive stress of 0.59 GPa. To further understand the differences between the AlN layers developed using these two types of carrier gases, a point defect study was done of the same. The Al0.3Ga0.7N/GaN heterostructure field effect transistor (HFET) structures with a Ga2O3 passivation layer were developed in two ways, which include ex-situ and in-situ oxide deposition processes. X-ray diffraction (XRD) showed the crystalline (¯201) orientation peaks of -Ga2O3 in the device structure. The van der Pauw and Hall measurements yield the electron density of ~ 4 x1018 cm-3 and mobility of ~770 cm2V-1s-1 in the 2-dimensional electron gas (2DEG) channel at room temperature. Capacitance-voltage measurement for the on-state 2DEG density for the MOSHFET structure was found to be of the order of ~1.5 x1013 cm-2. While the leakage current for the ex-situ and in-situ remained similar, it was a 2-order improvement compared to the HFET structure. The interface charge density between the -Ga2O3 and Al0.3Ga0.7N barrier layer in the in-situ process was found to be ~75%-88% lower than in the ex-situ process. The annealing experiment showed that, compared to atomic layer deposited oxides, the MOCVD-grown dielectric oxide Ga2O3 is thermally stable, leading to its use for extreme environment applications. Overall, this dissertation work leads to the in-situ MOCVD oxide dielectric deposition, which tremendously reduces the density of interface states and improves the threshold voltage performance of the MOSHFET structures