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Due to the high availability of location-based sensors like GPS, it has been possible to collect large amounts of spatio-temporal data in the form of trajectories, each of which is a sequence of spatial locations that a moving object occupies in space as time progresses. Many applications, such as intelligent transportation systems and urban planning, can benefit from clustering the trajectories of cars in each locality of a city in order to learn about traffic behavior in each neighborhood. However, the immense and ever-increasing volume of trajectory data and the concept drift present in city traffic constitute scalability challenges that have not been addressed. In order to fill this gap, we propose the first GPU algorithm for local trajectory clustering, called GTraclus. We present a parallelized trajectory partitioning algorithm which simplifies trajectories into line segments using the Minimum Description Length (MDL) principle. We evaluated our proposed algorithm using two large real-life trajectory datasets and compared it against a multicore CPU version, which we call MC-Traclus, of the popular trajectory clustering algorithm, Traclus; our experiments showed that GTraclus had on average up to 24X faster execution time when compared against MC-Traclus.

In recent years, deep learning (DL)-based techniques have achieved significant improvements over image fusion applications. Yet, current DL-based approaches raise formidable feature extraction, computational and statistical challenges in image fusion models. To overcome these challenges, we proposed an end-to-end DL-based architecture for infrared (IR) and visible (VIS) image fusion. We introduce multi-scale feature extraction and self-attention-based new feature fusion strategy to generate a high-quality fused image having balance details of IR and VIS modalities. Specifically, instead of using normal convolutions, we introduce dilated convolutions in the encoders to extract multi-scale features of IR and VIS images. Additionally, we introduce self-attention mechanism to refine and adaptively fuse multi-contextual features of IR and VIS images. Fused image is generated via decoder of the network. Extensive qualitative and quantitative evaluations on a benchmark dataset illustrate that our proposed method achieves reasonable performance over other state-of-the-art and current CNN-based image fusion methods.

Fistulas are defined as abnormal connections between 2 organ, vessels, or structures. They can often present in the genitourinary tract as a result of iatrogenic injury during pelvic surgery. A 46-year-old female presents many years after a hysterectomy for persistent vaginal leakage with concern for a vesicovaginal fistula. Computed tomography urogram, intravenous retrograde pyelogram, and cystoscopy were negative for vesicovaginal fistula; however, a vaginal sinus tract was noted and further explored. This case report will describe the use of both laparoscopy and concomitant vaginoscopy to diagnose and, ultimately, surgically excise a salpingovaginal fistula.

The International Standards for the Neurological Classification of Spinal Cord Injury (ISNCSCI) is a measure for motor-sensory dysfunction following spinal cord injury (SCI) but does not assess the autonomic nervous system dysfunction. The International Standards to document remaining Autonomic Dysfunction after Spinal Cord Injury (ISAFSCI) has been recommended to study autonomic dysfunction in such patients. We present a case presentation to demonstrate how to use the ISAFSCI and ISCoS urodynamics data set in persons with SCIs. A 24-year-old caucasian male presents with T4 ASIA SCI. We followed the patient over the course of 18 months. We present his clinical picture at different stages and how to apply ISAFSCI and ISCoS urodynamic data set to this patient The ISAFSCI and ISCoS urodynamics data sets are important tools in the repertoire of the clinician assessing autonomic dysfunction in persons with SCIs. They allow efficient clinical assessment of patients and standard communication between clinical care providers.

Software developers strive to make mobile applications energy efficient because applications that consume high energy are unpopular among mobile users. Unfortunately, software developers lack knowledge and tools which would help them make their applications efficient in terms of energy. To facilitate them in this regard, we introduce EnSights, a tool that provides critical energy change information to the developer using structural properties of the software application. We test EnSights tool on different versions of three open-source android applications namely BeHe ExploreR, PDFCreator, and QKSMS. Our tool successfully estimates change in energy consumption across versions of these applications with F-scores of up to 86%.

BACKGROUND National Early Warning Score has been studied well in indoor settings of developed countries but hasn’t been tested before in the Emergency Department of developing countries with fewer resources. Our objective was to determine whether the emergency department (ED) NEWS can be associated with Triage, admission, disposition, length of emergency/hospital stay, reappearance and mortality. METHODOLOGY A random sample of 1000 patients’ first encounter in the ED was extracted in the study period (between November 2018 and April 2019). Statistical analysis was done to analyze whether ED NEWS severity category can be associated with Triage, admission, disposition, length of emergency stay, length of hospital stay, reappearance in two weeks and mortality. RESULTS ED NEWS Score is associated with triage as shown by mean 2.68 (SD ± 0.6, p=0.01). Also, a high NEWS score also had impact on admission including 75 (66.4%) patients in severe and 55(74.3%) in moderate NEWS severity category respectively. NEWS score is also associated with Critical care admission and length of Emergency stay likely hood ratio of 26.0(p=0.038). Reappearance in emergency within next two weeks of discharge had no relation to NEWS severity. On the other hand both ED mortality and Hospital mortality were related to High NEWS. It correlates weakly with Length of Stay in emergency or with Length of Stay in Hospital. CONCLUSION NEWS Score can be used in the emergency department to identify and predict adverse outcome of patients presenting to ED. NEWS can be used as a triage tool when deciding whether and where patients should be admitted.

The centenary of the publication of Velten's collection of Swahili folktales invites a reconsideration of out perception of some of the tales: the folktale transcends ethnic boundaries, a particular folktale may be ‘older’ than it seems, and may lend itself to multiple layers of interpretation. The paper then discusses the use of irony in three tales. Irony conditions much of the aesthetic effect of the tales, rendering them more subtle in their entertainment and instruments in the elaboration of the society's moral code.

The growing demands on the Arabic language analysis in the computing field highlights the importance of Arabic information retrieval systems in particular, such as search engines, and it's gaining more interest. One way of enhancing the effectiveness of any information retrieval system is adopted via incorporating query expansion techniques. In this paper, Arabic query expansion is performed by using Arabic WordNet Ontology, and the whole work is evaluated to expose how beneficial is it comparing to the English WordNet Ontology. In fact the medicinal corpus doesn't show much benefit in the Arabic expansion in any of evaluation measures implemented, which are system's precision and recall.