Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal location Planning of EV Charging Station in Existing Distribution Network with stability condition

In this paper, a methodology is presented to determine the optimal location and size of charging station in Distribution network by maintaining stability condition. This paper also investigates that how electric vehicle charging station could impact the electric distribution network by analyzing active loss, reactive loss, power flow through transmission line and voltage deviation. The methodology used in this paper evaluates the maximum utilization of primary energy resources, considering all the operating constraints and stability of Distribution network. The optimal location and capacity of charging stations are investigated in different case studies in which we analyze impact of single charging station and three charging station with different capacities in distribution network. In case studies, an IEEE 33 Node Distribution network is used to verify the effectiveness of the proposed model.
Cyber Threats and Policies for Industrial Control Systems

Modern Industrial Control Systems (ICS) are very important in our life as we use information and communication technology (ICT) to manage, monitor and improve ICS usage. This continually exposes it to new threats due to the vulnerabilities and architectural weaknesses introduced by the extensive use of ICT. Different types of ICSs have common attacks in which these attacks are very sophisticated and have a great impact. This paper presents the results of our research on the impact of ICT attacks. Besides, it discusses how to protect ICS from attacks and policies/standards that each nation implements to protect its critical infrastructure.
A Secure Blockchain-based Prescription Drug Supply in Health-care Systems

Due to existing issues (e.g., complexity/ invisibility on share data for multiple parties, patient's privacy's leak) in the pharmaceutical supply in health-care systems, we proposed the architecture for a prescription drug supply using blockchain. This architecture could provide an efficient authentication among un-trusted parties to prevent an illegal agent from knowing sensitive drug transactions. Besides, dynamic identity is employed to protect users' anonymity and privacy. What's more, secure drug transactions are designed to guarantee share data to be confidentiality, integrity, and non-repudiation by using blockchain. Security analysis shows that our protocol successfully mutually authenticates in addition to being resistant to user impersonation attacks, smart card loss attacks, denial of attacks, database compromised attacks. Furthermore, our protocol can provide reliable service as well as protecting patient's privacy. Performance analysis illustrates our scheme to be competitive in comparison to existing schemes relative to the added security benefits it provides
Design and Analysis of Area and Power Optimised SRAM Cell for High-speed Processor

The basic 6T Static random access memory (SRAM) cell experience from relatively high static and total power loss problem, to solve this 8T, NC cells were designed. But this all consume more area as well as delay. Hence in this paper, 5T SRAM cell proposed and checked by Monte Carlo Simulation. The area reduced by 20.3%, 20.42%, and 7.82% compared to NC, 8T, and 6T cell respectively. The total power is reduced by 95.05%, 94.2%, and 96.6% compared to NC,8T, and 6T. Similarly, static power is diminished by 57.8%,75.8%, and 79.9% compared to NC, 8T, and 6T. Speed of proposed cell improved by 52.3%, 47.6%, and 53.9% compared to NC, 8T, and 6T respectively with acceptable stability. Finally, all the cells are also checked by Monte Carlo Simulation under 45 nm CMOS Technology.
Maximum Power Point Tracking for Photovoltaic-Fed Multi-Source Switched Capacitor Based Multilevel Inverter

In this paper, a shifting carrier based maximum power point tracking (MPPT) algorithm for multisource converters is proposed. This MPPT algorithm is explained for both low frequency (constant carrier) and high frequency (triangular) carrier signals. The proposed algorithm is applied for a single stage multisource switched capacitor based multilevel inverter for grid connected and stand-alone photovoltaic applications. This converter features high gain, less component count, self capacitor charge balancing, better dispersed value of sources and increased source utilization. The importance of selecting an appropriate pulse width modulation technique for switched capacitor based inverters in order to maintain the capacitor charging time is explained. The proposed technique is able to track the maximum power under varying irradiance levels. The experimental results of the proposed algorithm is presented. The MPPT technique is analyzed and verified in simulation for stand-alone and grid connected applications using MATLAB/Simulink platform.
Extended Location-Based Ad-Hoc Routing with Erroneous/Malicious Intermediate Node Detection

In wireless multihop transmissions of data messages in wireless adhoc networks, it is surely assumed that both of a routing protocol and a data message transmission protocol work correctly in each intermediate wireless node. Until now, for flooding based ad-hoc routing protocols such as AODV in which routing and data message transmission functions are separately implemented, various methods for detection of malfunctioning intermediate nodes have been proposed. However, for most of location-based ad-hoc routing protocols such as GEDIR and GPSR in which routing and data message transmission functions are tightly combined, it is impossible for the proposed methods to be applied. This paper proposes a novel method for detection of malfunctioning intermediate nodes. Here, verification of location information advertised by 1-hop neighbor nodes and verification of data message transmissions by 1-hop neighbor nodes by cooperation among neighbor nodes sharing location information of their 2-hop neighbor wireless nodes are introduced.
Glottal Source Information for Pathological Voice Detection

Automatic methods for the detection of pathological voice from healthy speech can be considered as potential clinical tools for medical treatment. This study investigates the effectiveness of glottal source information in the detection of pathological voice by comparing the classical pipeline approach to the end-to-end approach. The traditional pipeline approach consists of a feature extractor and a separate classifier. In the former, two sets of glottal features (computed using the quasi-closed phase glottal inverse filtering method) are used together with the widely used openSMILE features. Using both the glottal and openSMILE features extracted from voice utterances and the corresponding healthy/pathology labels, support vector machine (SVM) classifiers are trained. In building end-to-end systems, both raw speech signals and raw glottal flow waveforms are used to train two deep learning architectures: (1) a combination of convolutional neural network (CNN) and multilayer perceptron (MLP), and (2) a combination of CNN and long short-term memory (LSTM) network. Experiments were carried out using three publicly available databases, including dysarthric (the UA-Speech database and the TORGO database) and dysphonic voices (the UPM database). The performance analysis of the detection system based on the traditional pipeline approach showed best results when the glottal features were combined with the baseline openSMILE features. The results of the end-to-end approach indicated higher accuracies (about 2-3 % improvement in all three databases) when glottal flow was used as the raw time-domain input (87.93 % for UA-Speech, 81.12 % for TORGO and 76.66 % for UPM) compared to using raw speech waveform (85.12 % for UA-Speech, 78.83 % for TORGO and 73.71 % for UPM). The evaluation of both approaches demonstrate that automatic detection of pathological voice from healthy speech benefits from using glottal source information.
Data Loss Mitigation Mechanism using Compressive Sensing for Smart Grids

For the stability and maintenance of Smart Grids, a vast amount of power system data like synchrophasor data need to be collected and processed. Loss of power system data poses severe problems in operation and control of Smart Grids. Data loss may occur due to the transmission medium, congestion, sensor faults, etc. To tackle the data loss, a Compressive Sensing (CS) based data loss mitigation mechanism is proposed in this paper. In this mechanism, redundant data is transmitted to tackle the losses, and it consists of two techniques, feedback based technique and non-feedback technique. Feedback based technique primarily depends upon the data loss rate. In non-feedback based technique irrespective of data loss rate fixed redundancy is maintained. In the present work, an extensive simulated analysis is performed using synchrophasor data obtained from a Phasor Measurement Unit (PMU) for different data loss pattern (random, continuous) and rate (0 to 40%). It is observed that using the proposed mechanism; higher data loss rates are tackled with minimal degradation in reconstruction quality.
Millimeter-Wave Antenna-in-Package Applications Based on D263T Glass Substrate

SCHOTT D263T glass substrate is investigated for millimeter-wave (mm-wave) antenna-in-package applications using integrated passive device (IPD) technology. For comparison, the ring-resonator method and transmission-line method are used to extract the dielectric constant (<inline-formula> <tex-math notation="LaTeX">$\varepsilon \text{r}$ </tex-math></inline-formula>) of the glass substrate up to 67 GHz. The extracted results show good correlation between the two methods. Compared with the ring-resonator method, the transmission-line method requires higher measurement and simulation accuracies as the frequency decreases. Based on the extracted substrate data, a miniaturized Yagi-Uda dipole antenna operating at 60 GHz is designed, fabricated and measured. The measured results show that the antenna achieves a fractional impedance bandwidth (<inline-formula> <tex-math notation="LaTeX">$|S11| < -10$ </tex-math></inline-formula> dB) of 57.1% (<italic>i.e</italic>. 36.4 to 65.5 GHz), and stable gains of 5.5± 0.5 dBi from 40 to 67 GHz with the dimension of <inline-formula> <tex-math notation="LaTeX">$3.4\times 4$ </tex-math></inline-formula> mm<sup>2</sup>. The simulated radiation efficiency is >90% from 45 to 67 GHz, and the measured results agree well with the simulations.
Application of Internet of Things: Last meter smart grid and smart energy efficient system

Internet of things is one of the rapidly growing innovations in the field of telecommunication. The main purpose of the correspondence and collaboration among things, mans and objects is to fulfill the objective set to them as an amalgamated entity. Nowadays, electricity is the Minimum requirement of a community for a decent standard of life. Consumption of energy is increasing exponentially paving the manner for energy effective technologies and revealing limited renewable energy sources. To overcome these problems, bi-functional system is proposed in which last meter smart grid and energy efficient system in-home prototype is recommended. Traditional power grid are being revolutionized to smart grid in order to overcome obstacles such as uni-directional flow of energy and information, wastage of energy, authenticity and security. The classical grid model is mainly “distributedcentric” rather than “consumer centric”. To deal with these problems this paper proposes a comprehensive architecture and implementation of “last meter smart grid”-a part of smart grid situated at end user premises-embedded in iot platform and also proposes a system for continuous monitoring of electrical appliances. The proposed system can also provide provision of decreasing the energy wastage by incessantly observing the electrical appliances based on completely different sensors input.
Convergence Behaviour of Newton-Raphson Method in Node- and Loop-Based Non-linear Magnetic Equivalent Circuit Analysis

In this paper, the non-linear magnetic system equations are derived. The Newton-Raphson method is used to solve the system of non-linear equations. A simplified Jacobian is derived for both node- and loop-based magnetic equivalent circuit analysis. The partial derivative term is eliminated in this simplified Jacobian using differential relative permeability. The convergence behaviour of the Newton-Raphson method is studied. The loop analysis exhibits more stable convergence than that of the node analysis while solving non-linear magnetic equivalent circuit using the Newton-Raphson method.
Control Structure for Bidirectional Battery Charger Integrating 3φ PFC AC/DC and CLLC DC/DC Converters

This paper proposes a control structure for a bidirectional battery charger using a three-phase PWM ac/dc converter and a resonant CLLC dc/dc converter. The proposed control system with a staged architecture focuses on improving the power quality and minimizing total harmonic distortion of the system. A variable frequency hysteresis control system along with a current control loop is employed for the ac/dc converter for the fast charging phase of the battery. For optimal performance, the CLLC converter is designed to operate at the resonant frequency. Simulation results obtained using PLECS simulation software are presented to validate the performance of the proposed control system.
RobcWalk: Conceptual and Optimal Design

In this paper, the design procedure of the RoboWalk as a lower limb rehabilitation assisting robot is presented. First, a brief introduction of the robot is presented. There is a horizontal force component that is inevitably generated by the robot, and user may suffer from this. In order to overcome this problem, a dimensional optimization is performed to minimize this component, besides the required torque to be exerted by user at knee joint. To this end, a conceptual design of RoboWalk is described using the dimensions obtained by the aforementioned optimization. The detailed design is performed afterwards, and reasons for designing of each major element are discussed in detail. Finally, it is shown that this design is capable of fulfilling our goals and requirements using actuators with lower torque-speed specification.
Phase Locked Loop based Commutation Procedure for Sensorless Operation of a Brushless DC Motor

In this paper, we present the theory and implementation of a novel sensorless control strategy for BLDC motors. The proposed control technique overcomes drawbacks of filter-based methods and improves upon existing filterless methods. In order to overcome a frequency dependent phase delay induced in the back-EMF signal when using low-pass filters, a PWM based synchronous sampling technique is used to extract the zero-crossing points. An XOR gate is used in place of a digital multiplexer to combine the three zero-crossing signals so as to capture all logical transitions, while eliminating the need for digital select lines. This facilitates a deterministic transition from open-loop to closed-loop state. A square-wave phase-locked loop is used to provide accurate and timely commutations, while also suppressing RMS-jitter by nearly 75 %, thereby improving efficiency and lowering noise. Analytical and experimental results are also presented to show how the method works while potentially offering an efficiency upto 97.5 %.
RoboGlove: Design of a Tendon-Driven Robotic Glove with Differential Mechanisms

Stroke and spinal cord injury (SCI) are two main causes of human upper-limb movement impairments. In this paper, the design of a soft robotic glove with tendon actuation for rehabilitation purposes of the human hand is presented. This robotic glove called KNTU RoboGlove is designed based on differential mechanisms. To help patients, the glove makes grasping objects with different geometries be possible using a single DC motor. To this end, the differential mechanisms are first presented, which are used in two parts of the system. The actuation unit actuates all fingers with a motor, while uses differential gears that can produce the flexion or extension motions without facing singularities. Finally, the functionality of RoboGlove is evaluated in performing two different tasks. First one is grasping a cylindrical object, while the second consists of grasping an irregular-shaped object. Obtained results reveal the merits of the proposed robotic glove.
Restoration of Poisson-Gaussian noise corrupted images using Euler-Maclaurin approximation

Based on an established statistical model in the literature, we set up a likelihood function of an image field having both Poissonian and Gaussian components. This likelihood function is an infinite series and is approximated by an integral alongwith Bernoulli number correction terms. The approximate expression for the likelihood function is accomplished by Mean value theorem. Subsequently, upon maximization of the likelihood function yields a good estimate of the noiseless image field. The rationality behind our work relies on the study of the variations in the proposed algorithm as a function of the Poissonian and Gaussian component variances. Finally, we justify the performance of our model using MATLAB simulations in the light of the asymptotic efficiency of the M.L. E (Maximum likelihood estimate) for the purpose of restoration of the original image.
Anomaly Detection in Smart Grids using Machine Learning Techniques

Monitoring a smart grid using Information and communication technology tools require mechanisms for detection of anomalies like faults, cyber-attacks, etc. Most of the present power systems are equipped to deal with anomalies caused by faults or other natural disturbances. However, detecting and discriminating anomalies caused by the cyberattack against the power system is yet to be satisfactorily achieved. In this paper, we employ different machine learning techniques to detect power system anomalies. Besides detecting anomalies, machine learning methods can also differentiate between cyberattacks and natural disturbances. We assess several states of the art machine learning techniques in terms of their ability to detect cyber-attacks including those attacks which employ deceptive techniques to hide their foot prints. Evaluation is carried out using a dataset generated by an IEEE 3-bus system, and performances of machine learning techniques are analyzed in terms of accuracy of detection and required processing power.
Dual Band CPW-Fed Double Monopole Antenna for 2.4/5.8 GHz ISM band Medical Applications

The conception and realization of a dual-band coplanar waveguide fed double monopole antenna, working at 2.4 and 5.8 GHz Industrial, Scientific and Medical (ISM) bands, is presented in this paper. To operate effectively at the aforementioned bands, the designed antenna consists of a symmetrical folded long monopole and a short monopole which are responsible of the resonant frequencies at 2.45 and 5.8 GHz, respectively. Furthermore, both monopoles are fed by a coplanar waveguide. The symmetrical configuration allows the proposed antenna to obtain symmetrical radiation patterns. Hence, an omnidirectional radiation pattern is obtained at 2.45 and 5.8 GHz. A detailed parametric study and antenna parameters are reported and the proposed antenna is designed, fabricated and measured in free space. The proposed antenna has a compact size with the overall dimensions of 30 mm × 27 mm × 1.6 mm. It is concluded from the measured results, that the presented antenna could be considered for applications operating at 2.4 and 5.8 GHz ISM bands. Next, a metallic reflector was introduced to the planar structure in order to improve the gain and provide better directivity for onbody applications, for instance wireless capsule endoscopy systems. For this specific application, the antenna will act as receiving antenna and hence will be held by the patient, which requires a primary on/in-body investigation next to the small intestine region (complex organ of the gastrointestinal tract), as discussed in the paper using multi-layer and voxel models. It is concluded that the proposed antenna structure is a good receiving antenna for wireless capsule endoscopy systems.
A CPW-fed Trapezoidal Shape Wideband Antenna with Partial Ground for WLAN and WiMAX Applications

A novel trapezoidal shape wideband patch antenna with co-planer waveguide (CPW) feeding is presented in this paper. This antenna is designed on FR4 epoxy substrate of 1.6 mm thickness and consumes an area of 43×29 mm2 which is much more compact in size as compared to the standard rectangular patch antennas designed for similar bands. The antenna operates at the wide frequency range 5.1 to 5.9 GHz which covers IEEE 802.11a standard of WLAN (5.2 GHz) and IEEE 802.16d standard of WiMAX (5.8 GHz) bands. The trapezoidal patch enhances the impedance bandwidth of the antenna up to 800 MHz (S11< -10 dB) whereas CPW feeding improves the matching characteristics (S11= -31.4 dB). The truncated partial ground plane effectively improves the gain (4.1 dB) of this antenna. The antenna is designed and simulated in Ansys HFSS 15.0 EM simulation software.
A Computational Intelligence-Based Prediction Model for Flight Departure Delays

Flight departure delays are a major problem at OR Tambo International airport (ORTIA) located in Johannesburg in South Africa. These delays are more pronounced at the beginning and end of the month. Flight delays at ORTIA do impact negatively on business, on job opportunities and on tourists. Machine learning algorithms namely Decision Trees (J48), Support Vector Machine (SVM), K-Means Clustering (K-Means) and Multi Layered Perceptron (MLP) were used to construct the flight departure delays prediction models. Cross-validation (CV) was used for evaluating the models. The best prediction model was selected by using a confusion matrix and the ROC curve. The results show that the models constructed using data and the Decision Trees is suited for flight departure delay prediction as it gave the best prediction of 67.144%. The implications of the model is that travellers wishing to travel from ORTIA can foretell the flight departure delays using the tool. The tool will allow the travellers to enter variables such as month, week of month, day of week and time of day.
Double-Slotted Multiband Bowtie Antenna

The article presents a new approach for the design of a multi resonant microstrip bowtie antenna. Four antennas were accordingly designed. Antenna A is a simple bowtie antenna with curved side edges and a coaxial feed. Antenna B is with a single bowtie-shaped slot. Antenna C is with a double half bowtie-shaped slots. Antenna D is similar to Antenna C but fed with a transmission line that is split by a gap to affect feeding the two slots, simultaneously. Antenna D resulted in potentially four resonant frequencies that can be further improved through optimization to find applications in the GSM 900/1800 MHz, LTE 2.1 GHz and GPS 1.25 GHz bands. The antenna is low-profile and easy to fabricate on FR4 dielectric double-copper layer printed circuit board.
A Secure Face Anti-spoofing Approach Using Deep Learning

Face recognition is an attractive field for researchers since the past years and it is going to be the most practical method in identity recognition in the future. But even modern face detection systems have the problem of spoofing and it is safe to say it is the most serious obstacle in the way of becoming practical in more secure fields of identity recognition. In this paper, firstly, we discuss object detection systems in particular face detection and their problems such as using the person's picture in mobile phones or any other screen-based devices instead of a real person's face and also using masks to make faces like someone's face or other spoofing goals. Then, we introduce our method to prevent these attacks to have a high-secure and reliable face recognition system. Finally, some illustrations will be provided to demonstrate the practical and economic benefits of the presented approach.