Islamic Banking - Value Added Intellectual Coeficient (IB-VAIC) as an Intellectual Capital Proxy Indonesian Islamic Banking

The main idea of this research is to make the concept of intellectual capital as the most valuable intangible assets for the company. Basically, tangible assets which is owned by the company is also controlled by humans. This study offers Islamic Banking-Value Added Intellectual Coefficient (IB-VAICTM) modified the model pulic by Ulum (2013) as a performance measurement of intellectual capital of Islamic banking in Indonesia. This study also makes Islamic banks rank in term of Best Performance Index (BPI) which is measured using IB-VAIC™. The data used are annual reports, particularly financial performance and balance sheet, obtained either through the official website of each bank as well as from BI website. This study finds that during the study period (2010-2014), the overall performance of Islamic banking in Indonesia in the category of "good performers" with a score of VAIC 2.57. The results also indicates that individual banks that including into the category of "top performers" are three (3) banks, "good performers" 4 (four) Bank and "common performers" 4 (four) Bank. The limitations of this study is that the data used only 11 (eleven) Commercial Bank (BUS) in Indonesia, while the overall number of banks per January 2015 was 197

The future of software engineering: Visions of 2025 and beyond

In the current technological scenario of the industry and businesses, there has been increasing need of software within systems and also an increasing demand being put onto software-intensive systems. This in effect will lead to a significant evolution of software engineering processes over the next twenty years. This is due to the fact of emerging technological advancements like Industry 4.0 and Internet of Things in the IT field, among other new developments. This paper addresses and tries to analyses the key research challenges being faced by the software engineering field and articulates information that is derived from the key research specializations within software engineering. The paper analyses the past and current trends in software engineering. The future of software engineering is also looked with respect to Industry 4.0 which including emerging technological platforms like Internet of Things. The societal impact aspect of future trends in software engineering is also addressed in this paper

Automatic detection of tuberculosis using VGG19 with seagull-algorithm.

Due to various reasons, the incidence rate of communicable diseases in humans is steadily rising, and timely detection and handling will reduce the disease distribution speed. Tuberculosis (TB) is a severe communicable illness caused by the bacterium Mycobacterium-Tuberculosis (M. tuberculosis), which predominantly affects the lungs and causes severe respiratory problems. Due to its significance, several clinical level detections of TB are suggested, including lung diagnosis with chest X-ray images. The proposed work aims to develop an automatic TB detection system to assist the pulmonologist in confirming the severity of the disease, decision-making, and treatment execution. The proposed system employs a pre-trained VGG19 with the following phases: (i) image pre-processing, (ii) mining of deep features, (iii) enhancing the X-ray images with chosen procedures and mining of the handcrafted features, (iv) feature optimization using Seagull-Algorithm and serial concatenation, and (v) binary classification and validation. The classification is executed with 10-fold cross-validation in this work, and the proposed work is investigated using MATLAB® software. The proposed research work was executed using the concatenated deep and handcrafted features, which provided a classification accuracy of 98.6190% with the SVM-Medium Gaussian (SVM-MG) classifier

Cyber physical systems: A smart city perspective

Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed

Autonomous vehicles: A study of implementation and security

Autonomous vehicles have been invented to increase the safety of transportation users. These vehicles can sense their environment and make decisions without any external aid to produce an optimal route to reach a destination. Even though the idea sounds futuristic and if implemented successfully, many current issues related to transportation will be solved, care needs to be taken before implementing the solution. This paper will look at the pros and cons of implementation of autonomous vehicles. The vehicles depend highly on the sensors present on the vehicles and any tampering or manipulation of the data generated and transmitted by these can have disastrous consequences, as human lives are at stake here. Various attacks against the different type of sensors on-board an autonomous vehicle are covered

Classification of electroencephalography using cooperative learning based on participating client balancing

Modern technologies are widely used today to diagnose epilepsy, neurological disorders, and brain tumors. Meanwhile, it is not cost-effective in terms of time and money to use a large amount of electroencephalography (EEG) data from different centers and collect them in a central server for processing and analysis. Collecting this data correctly is challenging, and organizations avoid sharing their and client information with others due to data privacy protection. It is difficult to collect these data correctly and it is challenging to transfer them to research centers due to the privacy of the data. In this regard, collaborative learning as an extraordinary approach in this field paves the way for the use of information repositories in research matters without transferring the original data to the centers. This study focuses on the use of a heterogeneous client balancing technique with an interval selection approach and classification of EEG signals with ResNet50 deep architecture. The test results achieved an accuracy of 99.14 compared to similar methods

Hybrid Reality-Based Education Expansion System for Non-Traditional Learning

Many educators utilize conventional coaching methods to coach and study behaviors in a classroom with face-to-face, verbal contact. But, the coaching with learning atmosphere has developed further than the classroom. The incorporation of technology at the coaching with learning procedure is the novel tendency at teaching, by a favorable result. Technologies present surroundings for learning behaviors to happen anytime also everywhere to advantages instructors with students universal. One of the skills to have been demonstrating feasibilities of the appliance at learning surroundings is Hybrid Reality (HR), which includes together Virtual Reality (VR) with Augmented Reality (AR). This work attempts to construct ahead the recent condition of hybrid reality also its appliance at learning. The initial section depicts the fundamental formation of hybrid reality also its various divisions. The subsequent sections provide the superior construction of a few innovative appliances that are implemented for the hybrid reality. Lastly, the paper shows the benefits of those applications over the traditional teaching methods and the essential user reactions. The outcomes have highly in assistance of taking mobile applications based on Hybrid Reality into a contemporary teaching scheme

An energy-efficient cluster head selection in wireless sensor network using grey wolf optimization algorithm

Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms

F-18-Fluorodeoxyglucose (FDG) Positron-Emission Tomography of Echinococcus multilocularis Liver Lesions: Prospective Evaluation of its Value for Diagnosis and Follow-up during Benzimidazole Therapy

Background:: Long-term benzimidazole therapy benefits patients with non-resectable alveolar echinococcosis (AE). Methods to assess early therapeutic efficacy are lacking. Recently, AE liver lesions were reported to exhibit increased F-18-fluorodeoxyglucose (FDG) uptake in positron emission tomography (PET). To assess the value of FDG-PET for diagnosis and follow-up of AE patients. Patients/Methods:: Twenty-six consecutive patients with newly diagnosed AE were enrolled. Baseline evaluation included CT and FDG-PET. Thirteen patients (11 women; median age 50 years, range 40-76) were resected, the remaining 13 (8 women; median age 60 years, range 39-72) had non-resectable disease, were started on benzimidazoles, and CT and FDG-PET were repeated at 6, 12 and 24 months of therapy. Twelve consecutive patients with newly diagnosed cystic echinococcosis (CE) of the liver were also subjected to baseline FDG-PET. Results:: In 21/26 AE patients, baseline PET scans showed multifocally increased FDG uptake in the hepatic lesions' periphery, while liver lesions were FDG negative in 11/12 CE patients. Thus, sensitivity and specificity of FDG-PET for AE vs. CE were 81% and 92%, respectively. In 5 of 10 non-resectable patients with increased baseline FDG uptake, the intensity of uptake decreased (or disappeared) during benzimidazole therapy, in 3 by ≥2 grades within the initial 6 months. Conclusions:: FDG-PET is a sensitive and specific adjunct in the diagnosis of suspected AE and can help in differentiating AE from CE. The rapid improvement of positive PET scans with benzimidazole therapy in some patients indicates that absent FDG uptake does not necessarily reflect parasite viabilit