An approach to partial occlusion using deep metric learning

<span>The human face can be used as an identification and authentication tool in biometric systems. Face recognition in forensics is a challenging task due to the presence of partial occlusion features like wearing a hat, sunglasses, scarf, and beard. In forensics, criminal identification having partial occlusion features is the most difficult task to perform. In this paper, a combination of the histogram of gradients (HOG) with Euclidean distance is proposed. Deep metric learning is the process of measuring the similarity between the samples using optimal distance metrics for learning tasks. In the proposed system, a deep metric learning technique like HOG is used to generate a 128d real feature vector. Euclidean distance is then applied between the feature vectors and a tolerance threshold is set to decide whether it is a match or mismatch. Experiments are carried out on disguised faces in the wild (DFW) dataset collected from IIIT Delhi which consists of 1000 subjects in which 600 subjects were used for testing and the remaining 400 subjects were used for training purposes. The proposed system provides a recognition accuracy of 89.8% and it outperforms compared with other existing methods.</span>

Heart disease prediction model with k-nearest neighbor algorithm

<span>In this study, the author proposed k-nearest neighbor (KNN) based heart disease prediction model. The author conducted an experiment to evaluate the performance of the proposed model. Moreover, the result of the experimental evaluation of the predictive performance of the proposed model is analyzed. To conduct the study, the author obtained heart disease data from Kaggle machine learning data repository. The dataset consists of 1025 observations of which 499 or 48.68% is heart disease negative and 526 or 51.32% is heart disease positive. Finally, the performance of KNN algorithm is analyzed on the test set. The result of performance analysis on the experimental results on the Kaggle heart disease data repository shows that the accuracy of the KNN is 91.99%</span>

Forensic steganalysis for identification of steganography software tools using multiple format image

<p>Today many steganographic software tools are freely available on the Internet, which helps even callow users to have covert communication through digital images. Targeted structural image steganalysers identify only a particular steganographic software tool by tracing the unique fingerprint left in the stego images by the steganographic process. Image steganalysis proves to be a tough challenging task if the process is blind and universal, the secret payload is very less and the cover image is in lossless compression format. A payload independent universal steganalyser which identifies the steganographic software tools by exploiting the traces of artefacts left in the image and in its metadata for five different image formats is proposed. First, the artefacts in image metadata are identified and clustered to form distinct groups by extended K-means clustering. The group that is identical to the cover is further processed by extracting the artefacts in the image data. This is done by developing a signature of the steganographic software tool from its stego images. They are then matched for steganographic software tool identification. Thus, the steganalyser successfully identifies the stego images in five different image formats, out of which four are lossless, even for a payload of 1 byte. Its performance is also compared with the existing steganalyser software tool.</p>

Electronic health record to predict a heart attack used data mining with Naïve Bayes method

<span>A heart attack is a medical emergency. A heart attack usually occurs when a blood clot blocks the flow of blood to the heart. Cardiovascular disease is a variety of diseases that attack the body's cardiovascular system including the heart and blood vessels. Cardiovascular diseases (CVD) include angina, arrhythmia, heart attack, heart failure, atherosclerosis, stroke, and so on. To resolving (CVD) is to evaluate large scores of datasets, to compare for any information that can be used to forecast, to take care of organize. The method used Naïve Bayes classification because that method can determine target which can be used to answer some questions like whether the patient has the potential for heart disease. After data analyst, authors can use data to electronic health records (EHR).</span>

An Efficent Coverage and Maximization of Network Lifetime in WSN Through Metaheuristics

<span>In wireless sensor networks (WSNs), energy, connectivity, and coverage are the three most important constraints for guaranteed data forwarding from every sensor node to the base station. Due to continuous sensing and transmission tasks, the sensor nodes deplete more quickly and hence they seek the help of data forwarding nodes, called relay nodes. However, for a given set of sensor nodes, finding optimal locations to place relay nodes is a very challenging problem. Moreover, from the earlier studies, the relay node placement is defined as a non-deterministic polynomial tree hard (NP-Hard) problem. To solve this problem, we propose a multi-objective firefly algorithm-based relay node placement (MOFF-RNP) to deploy an optimal number of relay nodes while considering connectivity, coverage, and energy constraints. To achieve network lifetime, this work adopted energy harvesting capabilities to the sensor nodes and backup relay strategy such that every sensor node is always connected to at least one relay to forward the data. The optimal relay placement is formulated as an objective function and MOFF is applied to achieve a better solution. Extensive Simulations are carried out over the proposed model to validate the performance and the obtained results are compared with state-of-art methods)</span>

Narrow-band filter for satellite communication systems

Design narrow-band compact filters, based on high-quality waveguide-dielectric resonators with anisotropic materials is the subject of this paper. Filter represents a segment of a rectangular waveguide rotated around the longitudinal axis of the waveguide 90 degrees and containing one or more dielectric inserts that completely fill the resonator along the narrow wall of the waveguide and partially along the wide one. A distinctive feature of the proposed filter is higher slope steepness of the amplitude-frequency characteristic, and high manufacturability in the centimeter range. The designed narrow-band filter satisfies contradictory requirements: it combines narrow bandwidth (≈ 0.1% of center frequency <em>f</em>₀) with low passband insertion loss (≤ 1 dB).

Knowledge and Utilization of Health Informatics among Medical Doctors in Ahmadu Bello University Teaching Hospital, Shika-Zaria

The strategic visions in the health care system now underpin application of Information Communication Technology for effective care delivery. Recognising the potentials of ICT for Health, the Nigerian government as part of its policy derive towards achieving effective health care delivery by the year 2020, adopted use of ICT for effective healthcare delivery. Part of the target was establishment of ICT/Health informatics units in teaching hospitals in the country. This study assessed level of knowledge and utilization of health informatics among medical doctors in Ahmadu Bello University, Shika-Zaria. Premised on the Unified Theory of Acceptance and Use of Technology, this study adopted descriptive survey method and structured questionnaire as its instrument of data collection. Findings revealed that 91.4% (n=201) of the 220 sampled medical doctors in ABUTH are aware of health informatics and that 68.2% (n=150) have knowledge of how to use it. The most prominent areas of health informatics among the medical doctors are ‘Management Information System’, ‘Electronic Health Record System’ and ‘Electronic Medical Record’. However, only 58.6% (n=129) of the medical doctors in BUTH Shika- Zaria are actually utilizing health informatics. Internet (n=133, 60.5%) and interpersonal sources (n= 71, 32.3%) were found to be the major sources of information of knowledge and utilization of health informatics among the medical doctors. The study therefore recommends that ABUTH, Shika-Zaria should put in place more mechanism for creating awareness on use of health informatics varieties and a strong need for time-series research to examine future development in respect to knowledge and utilization of health informatics in Nigerian health institutions.

ZigBee based data collection in wireless sensor networks

<p>Wireless sensor networks (WSN), referring to groups of technologies wirelessly controlled, are widely used in many different fields, agriculture, medical, military, etc. These technologies are mainly used for monitoring physical or environmental conditions, such as temperatures, sound, pressure, and so on. In WSN fields, there are technologies as Wi-Fi, radio frequency (RF), Bluetooth, ZigBee, Z-Wave, and so on. Furthermore, there is one of this technology that offers more outstanding futures to provide more energy-saving and long distances of transmissions compared to other technologies, and that is Zigbee technology, and this had become for many applications, the first high-quality to use and consequently the most used in WSNs. In Zigbee aided WSNs, are included three main devices used to communicate data, that is a Zig-Bee coordinator (network coordinator), ZigBee router, and ZigBee end-devices. The data sensed is transmitted from sensor nodes through coordinators to a base-station (BS), this device (coordinator), collects the data, stores it in a memory, processes, and finally forward to the next suitable nodes or the BS. This research presents the concepts and discussions of Zigbee technologies used in WSNs. Utmost ZigBee communication technologies are revised and analyzed, as well as simulation results with different scenarios are addressed comprehensively. Proposals for advance applications in WSNs are presented. Suggestions for future developments are provided</p>

X-law detection scheme for monobit transmitted-reference ultra wideband receivers

<p>In ultra-wideband (UWB) communications, monobit receivers offer a low complexity implementation but at the same time exhibit a great performance loss. In this paper, a novel detection scheme, denoted as <em>x</em>-law detection (XLD), is proposed to diminish the performance loss caused by employing monobit analog-to-digital converters in transmitted-reference (TR) UWB receivers. Simulation results show that if the optimal value is employed for <em>x</em>, the XLD-based monobit weighted TR (MWTR) receiver can achieve 14.2~15.5 dB and 8~9.2 dB performance gain over the conventional MWTR receiver in LOS and NLOS scenarios, respectively. Moreover, the XLD-based MWTR receiver performance with the optimal value of <em>x</em> is only 1.6~3 dB away from the optimum MWTR receiver performance in intra-vehicle UWB channels. Additionally, the XLD-based MWTR receiver is not sensitive to the summation interval. This feature decreases the receiver complexity and guarantees a robust performance over different multipath channels. The significant performance improvement of the XLD scheme comes at a limited complexity increase. Thus, the XLD approach is a good candidate for TR-based and other training-based monobit receivers requiring low complexity, high performance, and low power consumption.</p>

Service-aware LSP selection with fuzzy based packet scheduling scheme for non-real time traffics

An essential solution is available in Multi-protocol label switching (MPLS), which solve the problems faced by present-day networks: speed, scalability, quality-of-service (QoS) management, and traffic engineering. This paper is an extension of work on Fuzzy based Packet Scheduling Algorithm (FPSA) combined with Packets Processing Algorithm (PPA) in an Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) networks. This will make provision for an intelligent service to the Label Switched Path (LSP) in MPLS networks. Several research work have been proposed on the MPLS Traffic Engineering. However, it is still imperative to further research on the effect of bandwidth increment on the core network using different mechanisms such as the analytical model of MPLS, expert-based packet scheduling algorithm for MPLS QoS support. Since MPLS is not able to provide intelligent routing, it is necessary to propose an intelligent expert system of FPSA combined with PPA. And analytical model of packet forwarding in the MPLS network would be given to provide suitable solution to traffic congestion and reliable services. Furthermore, the network model created using Network Simulator (NS 2), which carries non-real time application such as File Transfer Protocol (FTP) with bandwidth variations. The results obtained from trace files are interpreted by AWK script and used for the further analysis.