Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Staff Perception of InfoSec Policy Compliance: Palestine Universities Empirical Study

There is worldwide recognition of the problems associated with insider threats, intentional and unintentional; One of the significant issues in mitigating InfoSec risks is Staff compliance intention of InfoSec policies (ISP‘s). The study purpose seeks to understand and explore Staff compliance intention of ISP's based on how Staff perceive several factors adopted from multi-theories from ISP's research. Such as Sanction from General Deterrence Theory, Rewards as extrinsic motivation, Coping Appraisal from Protection Motivation Theory, and, Information Reinforcement that constitute the theoretical model. In the context of Palestine universities, the research Model first part constitutes the understanding of Staff awareness of ISP's based on four selected Policy-Focused Areas (PFA) from SANS 2014. Moreover, to assess this knowledge to reflect on the multi-theory perception factors effects on Staff compliance intention. Furthermore, to investigated Staff SETA to assess how universities value their Staff knowledge on ISP's. The research Methodology explores the problem empirically using descriptive analysis research design such as summaries and regression analysis. The study has 600 datasets collected from six universities by the developed research quantitative instrument. The findings show that Staff value the importance of the model factors in promoting Staff compliance intention. Staff have some awareness of PFA's and SETA needs extra attention. The Practical implications for creating ISP compliance among university Staff by drawing on their perception of factors adopted from multi-theories. Consequently, as for the organisation, effective SETA programs to sustain the effort of Staff compliance intention of ISP's. Meanwhile, this study seeks to assert that ISP's compliance is the responsibility of all academic and administrative Staff from all department and as a paradigm for other employees. The research covers ISP perception among Palestine Staff, and the expected outcome includes - a novel theoretical contribution model with six significantly contributing factors. Also, PFA in the context of Palestine contributes as a methodological contribution and Staff SETA as practical research contribution.
Power Allocation for Intelligent Interference Exploitation Aided Physical-Layer Security in OFDM-Based Heterogeneous Cellular Networks

In this paper, we consider an orthogonal frequency division multiplexing (OFDM) based heterogeneous cellular network consisting of a macro cell and a small cell, where a macro-cell base station (MBS) and a small-cell base station (SBS) communicate with respective macro-cell user (MU) and small-cell user (SU) with the existence of a common eavesdropper across different OFDM subcarriers. In order to make full use of the mutual interference between MBS and SBS against eavesdropping, an artificially designed signal is emitted at MBS to cancel out the interference received at MU as well as to interfere with the common eavesdropper at each subcarriers. For the purpose of further improving the secrecy performance, a sum secrecy rate (SSR) of OFDM-based heterogeneous cellular networks is maximized by optimizing the power allocation between MBS and SBS across different OFDM subcarriers when the eavesdropper owns the global instantaneous channel state information (ICSI), thus called ICSI based SSR maximization (ICSI-SSRM). As for the case when the ICSI of wiretap channels is unknown, we propose a statistical CSI based SSR maximization (SCSI-SSRM) scheme, where the statistical characteristics of channels from MBS and SBS to eavesdropper are employed to optimally allocate powers of MBS and SBS across different subcarriers under the constraint of MBS's total transmit power. The formulated ICSI-SSRM and SCSI-SSRM problems are all non-convex due to form of the difference between two-convex (D.C.) functions. Thus, we utilize the D.C. approximation approach to respectively convert original optimization problems into convex problems. Moreover, iterative optimal power allocation algorithms for ICSI-SSRM and SCSI-SSRM schemes are also presented to obtain their respective SSR values. Simulation results illustrate that the ICSI-SSRM and SCSI-SSRM algorithms can converge to their optimal values, which confirms the correctness and validation of the proposed algorithms. In addition, numerical results are also given to show that the ICSI-SSRM and SCSI-SSRM schemes outperform conventional power allocation methods in terms of their SSR performance.
Enhanced Exponential Reaching Law SMC For Analyzing PQ Issues in a Distribution System Using Transformer-less Hybrid Series Active Power Filter

In this work, an enhanced Exponential Reaching Law SMC (EERL-SMC) is proposed for a Three phase Transformerless Hybrid series Active power Filter (THSeAF) based on voltage source converters (VSC) to mitigate the power quality issues like voltage distortions and current harmonics. Generally the power quality issues had become quite common in the Electrical Distribution Systems (EDS) due to the usage of power electronic converters. To mitigate these power quality issues, a THSeAF is used in this work. An EERL-SMC is proposed to generate firing pulses to the IGBT switches of the inverter in a THSeAF for voltage and current distortions occurring on the supply side. The voltage and current references are generated using stationary reference frame theory. For obtaining the stability of the system, a mathematical model is derived. Simulations have been performed on PSCAD v4.6 with the EERL-SMC applied on the source side of the system. It is observed through simulations that the THSeAF compensates for sag, swell and voltage harmonics with less total harmonic distortion (THD). A power factor improvement is also observed during the simulation work. The controller performance is found to be robust with less settling time, less steady state error, no chattering during the mitigation of the power quality issues. Desired compensation and THD within the limits are obtained which encourages for effective usage of this topology with EERL-SMC in distribution systems. It can be an alternative to a higher order SMC like super twisting algorithm etc.
A Machine Learning Based Approach for Progeria Syndrome Detection

We proposed a generic framework for diagnosis of Progeria syndrome among the newborns. We proposed novel framework architecture of VGG-16. We have used multiple machine learning algorithms and feature extraction tools and we got best results in Logistic Regression algorithm. Disease identification helps us in early stage diagnosis of a disease. It also helps us to find out effective medicines or treatment for it. Our model gives us the best accuracy of 99.8%.
Effect of Shifting Gate Pulse on CCM/DCM Boundary in Coupled SIDO Boost Converter

The single input dual output (SIDO) converters are efficient than two single input single output (SISO) converters. The SIDO converters have reduced component count, reduced losses related to each component, and increased efficiency. The coupled inductor SIDO (CI-SIDO) boost converter is the topology of focus in this paper. The converters operate in two modes - continuous condition mode (CCM) and discontinuous conduction mode (DCM). The transition between modes occurs at the CCM/DCM boundary. The converters are operated in CCM because the control of the converter is easier in CCM. As the converter enters in DCM the output voltage becomes load dependent and control becomes complex. For the converter to operate in CCM, the average value of inductor currents should be greater than the boundary values. If the boundary currents are reduced, the converter can operate in CCM for a longer range of loads. The CI-SIDO boost converter has two gate pulses, due to the presence of two MOSFETs. The shifting of one gate pulse with respect to the starting point of another gate pulse, is used to analyze the CCM/DCM boundary. The shifting of gate pulse changes the average value of inductor currents at the boundary. The average value of inductor currents at the CCM/DCM boundary is analyzed and compared for shifted and non-shifted pulses. The analytical expressions of the average value of inductor currents at the boundary are calculated for the shifted pulse. The analysis considers all possible values of duty ratios and inductor current slopes. The analysis is verified by simulations in MATLAB/Simulink.
CT and MRI findings of atypical meningiomas

Poster: "ECR 2013 / C-1830 / CT and MRI findings of atypical meningiomas" by: "P. M. Latorre Brajovic1, P. Lemercier2, E. Rodriguez2, F. Aparici-Robles2, F. Mas-Estelles2, C. Poyatos2, C. Leiva Salinas2; 1Santiago/CL, 2Valencia/ES"
Design and Fabrication Of Multiband Sierpinski Fractal Patch Antenna For X And Ku-Band Applications

This paper presents a multiband sierpinski fractal patch antenna for the X and Ku-Band applications. This antenna is designed and fabricated using Rogers RT/Duroid 6202 (lossy) substrate with a dielectric constant of 2.94 and a height of 1.52mm. The zero, first and second iteration of the antenna for multiple frequency band of radiation for a frequency band of 8-18 GHz with simulated and practical results is discussed here.
A Review on Detecting Phishing URLs using Clustering Algorithms

Phishing is a kind of a social engineering attack. The attacker poses as a legitimate entity and communicates with the victim through some mode of communication. The user is prompted to open a link which has been designed to look similar to a legitimate website, or is prompted to relay sensitive credentials over the phone. The attacker steals the users' information to perform identity theft, account hijacking, etc. In this paper, we focus on URL based phishing attacks. Most of the solutions that we investigated focused more on the classification algorithms rather than clustering. Our aim is to experiment and compare the results of both of these types of algorithms. The main premise of our approach is a hybrid machine learning model comprising of two steps- checking with a blacklist and whitelist, and heuristics based detection, to increase the accuracy of the proposed algorithm.
Investigation Reinforcement Learning Method for R-Wave Detection on Electrocardiogram Signal

One of the essential things in recording electrocardiography (ECG) signals is R-wave detection. R-wave is a main component in the QRS wave, where it used for the diagnosis of heart rhythm irregularities and to calculate heart rate variability. On the other hand, Reinforcement Learning (RL) method has been proved that gives an excellent performance for games, network and stock market prediction. Based on this fact, in this paper, we want to investigate the RL for R-wave detection on the ECG signal. For the detection, the lower frequency is removed then we calculate the candidate of the peak, initialize Q-State-Action (QSA) table, peak detection, calculate reward and update the QSA table, respectively. Based on the experiment using the MIT-BIH dataset, the best accuracy of the proposed method is 86.8%, which calculated from alpha and gamma parameters are 0.1 and 0.9, respectively.
Low-Cost Computer Vision Based Real-Time 3D Localization of Object for Robotic Applications

In this paper, we propose low-cost robust 3D vision for robotics. This system plays an important role for robot to automatically detect and locate 3D coordinates of an object in space at real-time. In manufacturing this is very useful to automate repeated object pick and place operations. Initially we improvised 2D object detection. Later, we estimated object depth using Stereo Vision techniques. Overall we combine stereo vision techniques, object detection techniques, geometric calibration techniques, inverse kinematics into one model avoiding redundant computations and greatly simplifying underlying equations to achieve real-time speed and good-accuracy. We reduce redundant computations by replacing standard stereo matching with our own object detection model. We accurately localize detected objects by performing calibrations, improvising real world 2D coordinate equations and improvising depth estimation equation. This single framework is practically implemented and developed using open source platforms. From experimental results, we have observed the proposed model shows superior performance (Above 99% object detection rates, Accuracy upto 8mm, Only 23% CPU utilization, Only ∼155MB of RAM consumption) ∼on an average and is cost-effective (Under $20). This low-cost model can be useful for industrial purpose, small businesses, STEM education or for training and skill development.
The Comparative Study of S-V Model Between 3.5 and 28 GHz in Indoor and Outdoor Scenarios

The 3.5 GHz and 28 GHz bands are both very important for the fifth-generation (5 G) wireless communication system. To model their propagation characteristics and study their channel properties, we conduct measurements at these two bands in indoor and outdoor scenarios. The measured bandwidths at 3.5 and 28 GHz are 100 and 400 MHz, respectively. To make a fair comparison, the measurement results at 28 GHz are divided into four groups with bandwidths from 100 to 400 MHz. This is also helpful to study the effect of bandwidth on the channel properties, especially numbers of clusters and their growth rate. We choose the Saleh-Valenzuela (S-V) model to analyze the wireless channel. Its cluster-based property is very suitable to describe the power delay profiles (PDPs) in our measurement. To maintain the time continuity of multipath components (MPCs) during the clustering, we propose a new heuristic cluster algorithm. Based on the clustering results, we obtain the channel parameters, i.e., the number of clusters, inter-cluster interval, intra-cluster root mean square (RMS) delay spread, cluster decay factor, and ray decay factor. From the comparative study, we can find that the rays suffer a larger attenuation at 28 GHz than at 3.5 GHz. Increasing bandwidth can increase the ray decay factor. But the effects of frequency on the cluster decay rate are different in indoor and outdoor scenarios. The cluster decay rate is smaller at 28 GHz in the indoor scenario.
Mobility-Aware Multi-User Offloading Optimization for Mobile Edge Computing

Mobile Edge Computing (MEC) is a new computing paradigm with great potential to enhance the performance of user equipment (UE) by offloading resource-hungry computation tasks to lightweight and ubiquitously deployed MEC servers. In this paper, we investigate the problem of offloading decision and resource allocation among multiple users served by one base station to achieve the optimal system-wide user utility, which is defined as a trade-off between task latency and energy consumption. Mobility in the process of task offloading is considered in the optimization. We prove that the problem is NP-hard and propose a heuristic mobility-aware offloading algorithm (HMAOA) to obtain the approximate optimal offloading scheme. The original global optimization problem is converted into multiple local optimization problems. Each local optimization problem is then decomposed into two subproblems: a convex computation allocation subproblem and a non-linear integer programming (NLIP) offloading decision subproblem. The convex subproblem is solved with a numerical method to obtain the optimal computation allocation among multiple offloading users, and a partial order based heuristic approach is designed for the NLIP subproblem to determine the approximate optimal offloading decision. The proposed HMAOA is with polynomial complexity. Extensive simulation experiments and comprehensive comparison with six baseline algorithms demonstrate its excellent performance.
Vehicular Task Offloading via Heat-Aware MEC Cooperation Using Game-Theoretic Method

Mobile-edge computing (MEC) has been witnessed as a promising solution for the vehicular task offloading. Due to the limited computing resource of individual MEC servers, it faces challenges when higher requirements are put forward for timely task processing of a large amount of computations in the emerging vehicular applications. In this article, we strive to realize the efficient vehicular task offloading via heat-aware MEC cooperation from the game theory perspective. Here, the heat indicates the vehicle density and is tightly related to the requests of vehicle users when they drive through the hot zones. Specifically, a deep learning-based prediction method is proposed, capturing the dynamic time-varying heat value of the hot zones based on the analysis of the real-world private car trajectory data. To identify the role of MEC in the cooperation, we take the time-delay constraint into consideration for the task offloading. To realize MEC grouping for task offloading in MEC cooperation, we formulate the MEC grouping as a utility maximization problem via designing a noncooperative game-theoretic strategy selection based on regret-matching. Furthermore, we derive the correlated equilibrium and prove that the fast convergence can be achieved. Extensive simulation results validate the effectiveness of the proposed vehicular task offloading approach under various system parameters, such as computation workload, time slots, and MEC servers number. The proposed method outperforms the existing methods, which is able to significantly reduce the task complete delay, and in the meantime enhance the MEC energy efficiency with end users’ quality-of-experience guaranteed.
Small Signal Modeling and Analysis of Single Input Three Output Buck Converter Using Coupled Inductor

Applications like electric vehicles, electronic devices, etc. demand multiple supplies. Single input multiple output converters using coupled inductor are the better choice compared to existing parallel output converters due to the small size and low cost. This paper presents a single input three output buck converter using coupled inductor and is named as CI-SITO. The coupling in inductor currents in CI-SITO buck converter leads to the problem of cross-coupling and cross-regulation, which affects the system performance. Till date, no research has been done that analyze the performance of three output converter. Therefore, this paper studied the performance of CI-SITO buck converter both in steady-state and transient state. For this, the mathematical modeling of three winding coupled inductor and small signal modeling of CI-SITO converter is carried out. The small signal modeling is done using the state-space averaging technique. It is observed that the design of coupled inductor affects the operation of the converter. For proper operation, the coefficient of coupling between any two winding needs to be low. The model is verified using simulation results in MATLAB/SIMULINK.
Quintic Spline Collocation for Real-Time Biped Walking-Pattern Generation with variable Torso Height

This paper presents our newest findings in planning a dynamically and kinematically feasible center of mass motion for bipedal walking robots. We use a simplified robot model to incorporate multi-body dynamics and kinematic limits, while still being able to meet hard real-time requirements. The vertical center of mass motion is obtained through interpolation of a quintic spline whose control points are projected onto the kinematically feasible region. Subsequently, the horizontal motion is computed from multi-body dynamics which we approximate by solving an overdetermined boundary value problem via spline collocation based on quintic polynomials. The proposed algorithm is an improvement of our previous method, which used a parametric torso height optimization for vertical and cubic spline collocation for horizontal components. The novel center of mass motion improves stability, especially for stepping up and down platforms. Moreover, the new method leads to a less complex overall algorithm since it removes the necessity of manually tuned parameters and strongly simplifies the incorporation of boundary values. Lastly, the new approach is more efficient, which leads to a significantly reduced total runtime. The proposed method is validated through successfully conducted simulations and experiments on our humanoid robot platform, LoLA.
Internet of Things in Retail Using Fuzzy Logic for Customer Loyalty

Internet of thing in retail should focus their assets and capacities to improve customer loyalty with the end goal to hold existing clients and pull in new clients. Because loyal customer is a good source of revenue. In any case, there are few studies on customer loyalty using Internet of Thing. The aim of this study is to use sensing device that examine customer loyalty and transmit that data to cloud for further study of customer satisfaction retail industries. To test the research model fuzzy logic approach is included. The result will help to launch loyalty programs, companies to improve the customer equity, to boost the clients' esteem and benefit of organizations
Optimal Position Tracking for an AC Servomotor Using Linear Quadratic and Model Predictive Control

This paper discusses the optimal methods for position control of AC servomotor. Starting with the basic introduction of linear quadratic regulator, model predictive control techniques, this paper presents the mathematical modeling of AC servomotor and the implementation of the above mentioned control techniques. Thus, the results obtained from the techniques have been compared in terms of transient response specifications. Also the controllers' performance has been analyzed when the system has been subjected to external disturbance.
Te Whariki: early childhood curriculum from Samoan teachers' perspective

Te Whāriki positions itself as New Zealand’s first ever Early Childhood Curriculum with an unique bicultural feature honouring the Treaty of Waitangi (signed in 1840), and the partnership between tangata whenua (Māori) and the Crown (Government). The Te Whāriki curriculum found its origins in a need to maintain consistency with the New Zealand Curriculum Framework as a result of major changes in the Education Department in the late 1980s. The establishment of the Te Whāriki involved a long consultative process from 1990 – 1996 with groups and professionals from diverse Early Childhood Education (ECE) backgrounds, with major influence from the two Māori representatives from the Kohanga Reo National Trust (Tamati and Tilly Reedy) and two European writers from Waikato University (Helen May and Margaret Carr) who led the consultation process. One of Te Whāriki’s special features is embedded in its philosophy of inclusivity represented in a metaphor of a whāriki (woven mat), on which all can stand. This inclusivity broke pedagogical boundaries and established new ‘norms’ of equal opportunity for children, their family/whānau and the ECE community. The whāriki is made strong by the interweaving of four principles, strands and goals through its nonprescriptive nature which some find to be useful, while others see it as a hindrance to the implementation of the curriculum, particularly where there is a lack of proper training on how to put the curriculum into practice. This was found as the biggest challenge facing Samoan teachers in ECE, especially the teachers in Mainstream services with a multicultural background. In addition, the findings highlight how the dominant influence of Western theories in the curriculum caused confusion for teachers, and resulted in a programme developed out of teachers’ understanding rather than the children’s development and dispositions.