Deep learning in medical image registration: introduction and survey

Image registration (IR) is a process that deforms images to align them with respect to a reference space, making it easier for medical practitioners to examine various medical images in a standardized reference frame, such as having the same rotation and scale. This document introduces image registration using a simple numeric example. It provides a definition of image registration along with a space-oriented symbolic representation. This review covers various aspects of image transformations, including affine, deformable, invertible, and bidirectional transformations, as well as medical image registration algorithms such as Voxelmorph, Demons, SyN, Iterative Closest Point, and SynthMorph. It also explores atlas-based registration and multistage image registration techniques, including coarse-fine and pyramid approaches. Furthermore, this survey paper discusses medical image registration taxonomies, datasets, evaluation measures, such as correlation-based metrics, segmentation-based metrics, processing time, and model size. It also explores applications in image-guided surgery, motion tracking, and tumor diagnosis. Finally, the document addresses future research directions, including the further development of transformers

Standard Elevator Information Schema: Its Origins, Features and Example Applications

A generational change is taking place in building transportation systems as manufacturers and maintenance companies begin to integrate their products and services with the technologies of smart buildings and smart cities. Frequently this integration relies on the Internet of Things and cloud services. The diverse and heterogeneous nature of such collaborations requires a common shared semantic understanding of the complex and dense information that may be generated by transportation systems in buildings. The Standard Elevator Information Schema (SEIS) provides this in a format which is both machine and human readable. The role of the schema is to provide the ‘vocabulary’ for these collaborations. At the same time the schema specifies the properties, relationships and validation rules that define the information model, which could form the foundation upon which all elements of building transportation control and monitoring functions are constructed. SEIS is published under the Collective Commons licence and is free to download and incorporate into any product with the objective of reaching the broadest audience. This chapter discusses the origins and features of SEIS and provides a varied set of example applications. Consideration is also given to the issues of cyber security and data protection

Taxing impact of terrorism on global economic openness of developed and developing countries

This study examines the relationship between terrorism and economic openness that takes into account both the number and intensity of terrorist incidents and the impact of government military expenditures on trade-GDP and foreign direct investment-GDP ratios for both developed and developing countries. It uses the dynamic GMM method to account for endogeneity in the variables. Deaths caused by terrorism have a significant negative impact on FDI flows, and the number of terrorist attacks is also found to be significant in hampering the countries’ ability to trade with other nations. The study also demonstrates that the developing countries exhibit almost similar results to our main analysis. The developed countries exhibit a negative impact of terrorism, but the regression results are not significant

Forecasting photovoltaic power generation with a stacking ensemble model

Nowadays, photovoltaics (PV) has gained popularity among other renewable energy sources because of its excellent features. However, the instability of the system’s output has become a critical problem due to the high PV penetration into the existing distribution system. Hence, it is essential to have an accurate PV power output forecast to integrate more PV systems into the grid and to facilitate energy management further. In this regard, this paper proposes a stacked ensemble algorithm (Stack-ETR) to forecast PV output power one day ahead, utilizing three machine learning (ML) algorithms, namely, random forest regressor (RFR), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost), as base models. In addition, an extra trees regressor (ETR) was used as a meta learner to integrate the predictions from the base models to improve the accuracy of the PV power output forecast. The proposed model was validated on three practical PV systems utilizing four years of meteorological data to provide a comprehensive evaluation. The performance of the proposed model was compared with other ensemble models, where RMSE and MAE are considered the performance metrics. The proposed Stack-ETR model surpassed the other models and reduced the RMSE by 24.49%, 40.2%, and 27.95% and MAE by 28.88%, 47.2%, and 40.88% compared to the base model ETR for thin-film (TF), monocrystalline (MC), and polycrystalline (PC) PV systems, respectively

“Less Give More”: Evaluate and zoning Android applications

The Android security mechanism is the first approach to protect data, system resource as well as reduce the impact of malware. Past malware studies tend to investigate the novel approaches of preventing, detecting and responding to malware threats but little attention has been given to the area of risk assessment. This paper aims to fill that gap by presenting a risk assessment approach that evaluate the risk zone for an application. The permission-based approach is presented for evaluating and zoning the Android applications (EZADroid), based on risk assessment. The EZADroid applies the Analytic Hierarchy Process (AHP) as a decision factor to calculate the risk value. A total of 5000 benign and 5000 malware applications were drawn from the AndroZoo and Drebin datasets for evaluation. Results showed that the EZADroid had achieved 89.82% accuracy rate in classifying the application into a different level of risk zones (i.e. very low, low, medium, and high

Do Islamic indices provide diversification to bitcoin? A time-varying copulas and value at risk application

This is an accepted manuscript of an article published by Elsevier in Pacific-Basin Finance Journal on 08/04/2020, available online: https://doi.org/10.1016/j.pacfin.2020.101326 The accepted version of the publication may differ from the final published version.© 2020 The emergence of new asset classes offers avenues to international investment community however understanding relationship between any two assets in a single portfolio is important. We investigate the risk dependence between daily Bitcoin and major Islamic equity markets spanning over from July 2010 to March 2018. We start by examining long memory properties of Bitcoin and sampled Islamic indices and report significant results. The residuals from fractionally integrated models are then used in bivariate time invariant and time varying copulas to investigate dependence structure. Among all Islamic indices, DJIUK, DJIJP and DJICA exhibit time varying dependence with Bitcoin. In addition, we apply VaR, CoVaR and ΔCoVaR as risk measure to examine spillover between Bitcoin and Islamic equity markets. VaR of Bitcoin exceeds from VaR of Islamic indices and CoVaR of both Islamic and Bitcoin exceeds their respective VaR, suggesting presence of risk spillover between each other. Our results also report asymmetry between downside and upside ΔCoVaR suggesting implications for investors with different risk preferences. Finally, the diversification benefits indicate that Islamic equity market serves as an effective hedge in a portfolio along with Bitcoin.Accepted versio

Taxing impact of terrorism on global economic openness of developed and developing countries

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Unmanned Ground Vehicle with Virtual Reality Vision

The paper aims to describe the design and implementation of a smart phone virtual reality (VR) head mounted display (HMD) for search and rescue (SAR) robots which enables visual situation awareness by giving the operator the feel of ''head on rover" while sending the video feeds to separate operator computer for object detection and 3-D model creation of the robot surrounding objects. A smart phone based HMD captures head movements in real time using its inertial measurement unit (IMU) and transmits it to three motors mounted on a rover to provide the movement about three axes (pitch, yaw, and roll). The operator controls the motors via the HMD or a gamepad. Three on-board cameras provide video feeds which are transmitted to the HMD and operator computer. A software performs object detection and builds a 3-D model from the captured 2-D images. The realistic design constraints were identified, then the hardware/software functions that meet the constraints were listed. The robot was designed and implemented in a laboratory environment, it was tested over soft and rough terrain. Results showed that the robot has higher visual-inspection capabilities compared to other existing SAR robots, furthermore, it was found that the maximum speed of 3.3 m/s, six-wheel differential-drive chassis, and spiked air-filled rubber tires of the rover gave it high manoeuvrability in open rough terrain compared to other SAR robots found in literature. The high visual inspection capabilities and relatively high speed of the robot make it a good choice for planetary exploration and military reconnaissance. The three-motors and stereoscopic camera can be easily mounted as a separate unit on a chassis that uses different locomotion mechanism (e.g. leg type or tracked type) to extend the functionality of a SAR robot. The design can be used in building disparity maps and in constructing 3-D models, or in real time face recognition, real time object detection, and autonomous driving based on disparity maps

Statin Eligibility according to 2013 ACC/AHA and USPSTF Guidelines among Jordanian Patients with Acute Myocardial Infarction: The Impact of Gender

The objectives of this study were to evaluate statin eligibility among Middle Eastern patients admitted with acute myocardial infarction (AMI) who had no prior use of statin therapy, according to 2013 ACC/AHA and 2016 USPSTF guidelines, and to compare statin eligibility between men and women. This was a retrospective multicenter observational study of all adult patients admitted to five tertiary care centers in Jordan with a first-time AMI, no prior cardiovascular disease, and no prior statin use between April 2018 and June 2019. Ten-year atherosclerotic cardiovascular disease (ASCVD) risk score was estimated based on ACC/AHA risk score. A total of 774 patients met the inclusion criteria. The mean age was 55 years (SD±11.3), 120 (15.5%) were women, and 688 (88.9%) had at least one risk factor of cardiovascular disease. Compared to men, women were more likely to be older; had a history of diabetes, hypertension, and hypercholesterolemia; and had higher body mass index, systolic blood pressure, total cholesterol, and high-density lipoproteins. Compared to women, men were more likely to have a higher 10-year ASCVD risk score (14.0% vs. 17.8%, p=0.005), and more men had a 10-year ASCVD risk score of ≥7.5% and ≥10%. The proportion of patients eligible for statin therapy was 80.2% based on the 2013 ACC/AHA guidelines and 59.5% based on the USPSTF guidelines. A higher proportion of men were eligible for statin therapy compared to women, based on both the 2013 ACC/AHA (81.4% vs. 73.5%, p=0.050) and USPSTF guidelines (62.0% vs. 45.2%, p=0.001). Among Middle Easterners, over half of patients with AMI would have been eligible for statin therapy prior to admission based on the 2013 ACC/AHA and USPSTF guidelines, with the presence of gender gap. Adopting these guidelines in clinical practice might positively impact primary cardiovascular preventive strategies in this region