Miracle-dz/UniFAR-FTUs huggingface dataset:
Half Psi Shaped Dual Band CP Antenna for WLAN/Wi-Fi Applications

In the past few years, the accelerated developments in the contemporary wireless communication systems needs the invention of inexpensive, light weight, low-profile and compact CP antennas capable of operating at two or more different frequencies. In this paper, a half psi shaped dual band CP antenna for Wi-Fi and WLAN appliances is projected and analyzed. This antenna consists of half psi shaped radiating patch on low cost FR-4 with 1.6 mm thickness. It has a εr value of 4.4 and a loss tangent of 0.02. The designed CP patch antenna is resonated at the two different frequencies of 2.4 and 5.2 GHz with the S11 value below -10 dB. The designed CP antenna has the normalized gains of 3.1 dB and 4.2 dB at the corresponding resonant frequencies. The projected CP antenna is designed and analyzed with the help of the HFSS software.
A Leader-Follower Set-theoretic Approach for Cyber-Physical Systems against Denial-of-Service Attacks

In this paper, a novel control architecture capable of managing denial-of-service attacks affecting the communication links between a group of interconnected systems and remote controllers is presented. The basic idea relies on the representation of the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed in order to isolate the attacked unit that otherwise could compromise system operations. Simulations on a multiarea power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial-of-service (DoS) attacks occurring on both sensor-to-controller and controller-to-actuator channels.
Investigations on the Effect on Micro Strip Patch Antennas Using Shaped Slots

Since the Federal Communication Committee has announced a range of frequencies from 3.10GHz to 10.60GHz constituting a bandwidth of 7.5GHz, Ultra wideband technology (UWB) is move ahead quickly as a high data rate technology for wireless communication. The effect of combining different geometrical patches derived from a basic rectangular patch antenna for wireless communications, GPS technology, satellite communication and air-craft applications are presented here. The antenna proposed is designed in FR-4 substrate which has 1.6 mm thick and permittivity of 4.4. The size of the substrate is 37.9mm × 47.63mm × 1.6mm. The antennas are simulated with ANSYS HFSS, the 3D electromagnetic (EM) simulation tool for radio frequency and fast electronic components. The impact on return loss and band width as a result of imperfections on patch can be observed from the obtained results. Introducing slots, defects on ground plane, making irregularities on patch shapes causes a wide variation in antenna parameters. It is clear that an increase in band width and reduction in return loss is obtained by combining the different shaped geometrical patches.
Detecting Behavioral Trajectories in Continued Education Online Courses

Continuing education online has been steadily increasing worldwide and its students' profiles tend to be different from those in other formal modalities. Hence, it is relevant to understand the behavior of these students along their course trajectories. In this work, we investigate a specialization online course involving hearing healthcare professionals (n=96), to discover different navigation strategies and the factors which may influence it. To that end, we applied sequence analysis techniques to interpret different navigation patterns and selected demographic covariables which may influence these behavioral trajectories. Three clusters were found, with subtle differences among them and three variables with greater predictive power: age, professional experience and region.
M-Commerce Model: An Applied Business Transformation Framework for Tourism Industry

Technological innovation in a business organization becomes the trend in the 21st century. With more progress on hand, e-commerce has paved its way to the mainstream giving transformation opportunities such that in socio-economic field. This paper presents the socio- economic situation of a fisherfolk community in the province of Siquijor, Philippines and its development of a marine sanctuary park that created livelihood opportunities to the local fisherfolks in the area which led to the presence of Guiwanon Spring Park Resort. With close competition to other tourism-related establishments, the resort decided to adopt an e-commerce solution to keep abreast of technology innovation. Thus, the researcher creates an interactive mobile-ready application known as the GSPR e-Booking System which includes features that help the resort catch a wider market online. Further, creating conceptual foundations from existing practices, the author develops a new, integrated business transformation framework that helps explain how an e-commerce solution has generated a supplemental aid in the socio-economic development of the said community. This framework is then presented to motivate other developing business communities to embrace more appropriate solution for issues brought by the current technological situation.
High Speed Memory Cell with Data Integrity in QCA

The design issues in CMOS at Nano meter levels has increased the demand for post-CMOS technologies. Quantum-dot Cellular automata is one of the promising post-CMOS technology that can be used in the near future. It is a transistor-less nanotechnology paradigm that has the competence to design high speed and low power Nanoscale circuits with higher packaging densities. Data integrity is a key factor in the design of any memory storage device. In this paper, a novel memory cell architecture is proposed in QCA. The proposed design has more data integrity compared to the existing designs. Simulation results shows that the proposed design has higher speed compared to the existing designs. The proposed memory cell can be extended to implement any large size memory circuit in QCA. QCADesigner 2.0. 3 is used for the validation of the proposed design in QCA.
Integration of the Mobile Robot and Internet of Things to Collect Data from the Agricultural Fields

Robotics and Internet of Things (IoT) are two hot topics in the research area. There are studies in the literature that combine these two topics. In this study, robotics and IoT are used for the agricultural fields. Because, with the technology becoming more available on agriculture; food security, crop yield will be increased and the environmental hazards will be decreased. But this can be achieved by strictly monitoring the agricultural fields and greenhouses. For these purposes, static sensors or sensor networks, and mobile agents are used. IoT forms the backbone of such systems because there are too many units in different places and a lot of data is coming out from these units. Also, processing this data reveals the big data problem. Purpose of this work is integrating the mobile robot platform to gather data from the agricultural fields or greenhouses and then post this gathered data to the web application. So that, data can be stored, processed, and classified on the web application or cloud. This study proposes a design scheme for the mobile internet of things concept where the client or the agent is the mobile robot whether it is autonomous or not. Furthermore, the design structure is not limited to the mobile ground vehicle. Any type of unmanned vehicle or static sensor can be integrated into the system. Internet connection is not limited to only Wi-Fi, there is also a cellular connection in the system. With this study, mobile data acquisition and transferring this acquired data to the web application can be done. Also, the infrastructure of the mobile agent-based internet of things system is shown. On the robot side, autonomy can be added to the system.
An autonomous system of mobile robots for search in disaster affected sites

Search and rescue operations during disasters are normally unsafe and tedious to human firefighters. As an alternative, an autonomous system of mobile robots, which can do the search and rescue operation, will be an efficient mechanism. Most of the systems consisting of mobile robots involve human interaction and control largely, which is again less efficient. So development of an autonomous system of mobile robots which can explore an area and complete the search and rescue operation is important. Such a system should have the options to explore an area in an efficient way by the coordination of robots each other and localization schemes. An autonomous mobile robots system is implemented which explores an unknown area and builds a map of the area. The robots coordinate with each other by building local maps and sharing them with others to build the global map. The robots localize themself using trilateration localization scheme. Marking the area covered by each robot is done by placing RF ID tags in an optimized way. The proposed scheme is implemented in hardware using the FireBird V mobile robots.
Estimation and Nonlinear Predictive Control for an Induction Machine

The work aims to design a reduced order state observer and a parametric estimator for a class of nonlinear systems. A nonlinear predictive model control uses these estimations such that the controlled variable of the system follows some imposed references. The estimation scheme was applied to an induction motor, such that the unknown rotor fluxes, and uncertain rotor resistance are estimated by proper observer/estimator. The controlled output variable is the rotor speed. The efficiency of the estimation and control methods is demonstrated by the performed numerical simulations.
Extended High Gain Observer based Control Design for Buck-Boost Converters

The evolution of the modern technologies and the development of power electronics has led to the extensive use of DC-DC Buck-Boost converters in the application of power amplifier, battery management system, self-regulating power supplies etc, as they have higher output voltage and low operating duty cycle. The problem of degradation in adeptness of the Buck-Boost converters in presence of a load and lumped parameter uncertainties are analyzed. An Extended High Gain Observer is formulated to estimate the output voltage, load current, and its first derivative which is considered to be nonlinear and bounded. The reference current is compared with the estimated load current, forming a sliding surface. Sliding Mode Controller ensures convergence of estimated load current trajectories to reference current trajectories in finite time. Finally, an inner control loop generates a duty ratio resulting in output voltage which tracks the required reference voltage. The simulation results have been implemented in MATLAB/Simulink to validate fast estimation of load current, output voltage and disturbance rejection in a closed-loop process.
A Complex Number Approach to Elliptic Curve Cryptosystems over Finite Fields Implementations and Experiments : Implementations and Experiments

Network security is a general idea to ensure information transmission over PC and portable systems. Elliptic curve cryptosystems are nowadays widely used in public communication channels for network security. Their security relies upon the complexity of clarifying the elliptic curve discrete alogarithm issue. But, there are several general attacks in them. Elliptic bend number juggling is actualized over complex fields to enhance the security of elliptic curve cryptosystems. This paper starts with the qualities of elliptic curve cryptosystems and their security administrations. At that point we talk about limited field number-crunching and its properties, prime field number-crunching, twofold field math and complex number-crunching, and elliptic bend number-crunching over prime field and parallel field. This paper proposes how to execute the unpredictable number of math under prime field and double field utilizing java BigInteger class. also, we actualize elliptic bend math and elliptic bend cryptosystems utilizing complex numbers over prime field and double field and talk about our trials that got from the usage.
A Playful Mobile Digital Environment to Tackle School Burnout using Micro Learning, Persuasion & Gamification

School burnout refers to exhaustion at school combined with a cynical and detached attitude towards school. It often precedes Early School Leave (ESL), which has great impact on the socioeconomic situation of a person. Numerous local programs exist to deal with school burnout and prevent ESL, but they are all very labor-intensive. To come to a less labor-intensive solution, we proposed an ICT solution. The goal was to create an engaging software environment that youngsters would use voluntarily and that could re-engage them in learning. We developed a so-called playful digital environment, called TICKLE. It allows youngsters to collect digital cards by performing associated challenges in their surroundings. The challenges are small activities intended to reactivate the youngster for learning. Persuasive principles and gamification are used to motivate the youngsters to use the tool. In this paper, we discuss the design decisions that have been taken as well as the main components of the tool.
Extraction of influential markers affecting HCC survival chances and its prediction

HCC (Hepatocellular carcinoma) is a primary malignancy of the liver. Patients who have an underlying chronic liver disease and cirrhosis are usually affected by HCC. HCC causes around a third of cancer deaths all around the globe. HCC starts in the Liver and is quite different from the cancer which spreads to the liver that started in different organs. Doctors are still not sure of what exactly causes Hepatocellular carcinoma. In this paper, we have tried to find out the important and causative factors for Hepatocellular carcinoma and have also increased the accuracy to predict the survivability of an HCC patient for the next one year, using the refined factors. This paper will help to reduce the complexity of the prediction model by reducing the number of attriubtes required by the model.
Training-Free Non-Intrusive Load Extracting of Residential Electric Vehicle Charging Loads

Extracting the charging loads of residential electric vehicle (EV) clusters and identifying their charging patterns can help grid operators develop effective regulation strategies. The duration of the power consumption event (PCE) and the interval between adjacent events are used to characterize the difference in the stochastic behavior of the load pattern between the EV cluster and the air conditioner (AC) cluster. An event detection method based on skipping power difference is proposed, which can effectively identify changing edges of the PCE. A training-free non-intrusive load extracting (NILE) algorithm based on bounding-box fitting and load signatures is proposed, which can automatically identify the start time, the end time and the power amplitude of the charging event. The validity of the NILE algorithm is verified by multiple performance metrics on the real data set.
Attention-Based Deep Learning Model for Predicting Collaborations Between Different Research Affiliations

It is challenging but important to predict the collaborations between different entities which in academia, for example, would enable finding evaluating trends of scientific research collaboration and the provision of decision support for policy formulation and incentive measures. In this paper, we propose an attention-based Long Short-Term Memory Convolutional Neural Network (LSTM-CNN) model to predict the collaborations between different research affiliations, which takes both the influence of research articles and time (year) relationships into consideration. The experimental results show that the proposed model outperforms the competitive Support Vector Machine (SVM), CNN and LSTM methods. It significantly improves the prediction precision by a minimum of 3.23 percent points and up to 10.80 percent points when compared with the mentioned competitive methods, while in terms of the F1-score, the performance is improved by 13.48, 4.85 and 4.24 percent points, respectively.
Intra-Cluster Communication Technique Re-using TDMA Idle Slots of Wireless Sensor Networks

To extend throughput, higher data packets sending is a challenge of Wireless Sensor Networks (WSN). A suitable data sending/communication mechanism needs to overcome this challenge. Most of the clustering method used TDMA for intra-cluster communication. In clustering, member nodes send data to Cluster Head (CH) in the TDMA time slot. CHs collect data from member nodes, combine them and send to next CH or Base Station (BS). If there is no data in a time slot (idle slot) of slot owner’s node and if non-owner’s nodes have data, then this slot remains empty in spite of data availability of other nodes. So overall data sending as well as throughput become degrade. We have proposed a protocol to overcome this limitation. We have used idle time slot of owner’s node known as ‘slot reuse’. We send data with different power to CH in TDMA time slot (idle slot) of non-owner’s node called. If TDMA slots of owner’s node is idle, then there is a possibility of non-owner’s node to send data. As we used different level of power of nonowner’s node data according to amount of data, so there is also a scope to send a higher amount of data to CHs and overall throughput will increase. We have used capture effect to detect higher powered data. We have also used time slot and preamble adjustment to avoid collision. We have simulated our protocol and compared with traditional intra-cluster communication method like LEACH-C and another CSMA based intra-cluster communication technique (CICT) and found better performance in terms of throughput.
LLC-Guided Data Migration in Hybrid Memory Systems

Although 3D-stacked DRAM offers substantially higher bandwidth than commodity DDR DIMMs, it cannot yet provide the necessary capacity to replace the bulk of the memory. A promising alternative is to use flat address space, hybrid memory systems of two or more levels, each exhibiting different performance characteristics. One such existing approach employs a near, high bandwidth 3D-stacked memory, placed on top of the processor die, combined with a far, commodity DDR memory, placed off-chip. Migrating data from the far to the near memory has significant performance potential, but also entails overheads, which may diminish migration benefits or even lead to performance degradation. This paper describes a new data migration scheme for hybrid memory systems that takes into account the above overheads and improves migration efficiency and effectiveness. It is based on the observation that migrating memory segments, which are (partly) present in the Last-Level Cache (LLC) introduces lower migration traffic. Our approach relies on the state of the LLC cachelines to predict future reuse and select memory segments for migration. Thereby, the segments are migrated when present (at least partly) in the LLC incurring lower cost. Our experiments confirm that our approach outperforms current state-of-the art migration designs improving system performance by 12.1% and reducing memory system dynamic energy by 13.2%.
Edge Capacity Planning for Real Time Compute-Intensive Applications

Cloud computing is a major breakthrough in enabling multi-user scalable web services, process offloading and infrastructure cost savings. However, public clouds impose high network latency which became a bottleneck for real time applications such as mobile augmented reality applications. A widely accepted solution is to move latency sensitive services from the centralized cloud to the edge of the Internet, close to service users. An important prerequisite for deploying applications at the edge is determining initial required edge capacity. However, little has been done to provide reliable estimates of required computing capacity under Quality-of-Service (QoS) constraints. Differently from previous works that focus only on applications' CPU usage, in this paper, we propose a novel, queuing theory based edge capacity planning solution that takes into account both CPU and GPU usages of real-time compute-intensive applications. Our solution satisfies the QoS requirements in terms of response delays while minimizing the number of required edge computing nodes, assuming that the nodes are with fixed CPU/GPU capacity. We demonstrate the applicability and accuracy of our solution through extensive evaluation, including a case study using real-life applications. The results show that our solution maximizes the resource utilization through intelligent combinations of service requests, and can accurately estimate the minimal amount of CPU and GPU capacity required for satisfying the QoS requirements.
Design and development of Patch Antenna Array with Band-pass Filter for ISM Band Applications

This paper presents the analysis of an array of rectangular micro strip patch antenna radiating at a resonant frequency of ISM band (2.4GHz) and it is integrated with the band pass filter to pass only the desired frequency without any harmonics. The proposed radiator has been constructed using FR4 epoxy substrate having a value of 4.4 as dielectric constant, while the thickness of the substrate (h) being kept at 1.6mm. The gain, field pattern and RL (return loss) are obtained through the simulated results, which have been analyzed and compared with fabricated radiator using network analyzer. It has observed that the array axis along the radiating slot with corporate-feed and with the band pass filter has increased gain in comparison with the single patch antenna and antenna array without band pass filter.
FPGA Based Performance Comparison of Different Basic Adder Topologies with Parallel Processing Adder

Adders are an almost requisite element of every modern integrated circuit. As in the current era of increasing digitalization, where everyone works towards miniaturization, three important aspects of design, i.e. area, power and delay, need to be optimally balanced. Since adders are used in many complex digital circuits as a basic component, enhancing digital adder performance would greatly accelerate binary operations within such complex circuits. In binary adders, the speed of activity is constrained when taken in propagating the carry through the adder. The adder topology used in our work includes the comparison between Carry Select adder, Carry Look ahead adder, Carry Increment adder, Ripple carry adder and Brent-kung adder. The work is being carried out using Hardware Description Language (HDL) in the platform Xilinx ISE 14.7.
An Analysis to Find the Efficient Clustering Algorithm for Identification of User Access Pattern

it is established fact that the out of data available on the internet much of it is unnecessary information which may be bug navigation requests, picture request, and incorrect demands. To avoid such situation the proposed logical data cleaning method is capable of cleaning irrelevant data by deducting from the web log records. We have applied four algorithm such as K-Means, Fuzzy C-Means, Divisive hierarchical clustering and Agglomerative hierarchical clustering on a dataset of “Educational Process Mining”, derived by the UCI Repository System for analyzing the distinct outcomes among them, Based on the co-relation coefficient that is Fuzzy silhouette index, Average silhouette width, Divisive coefficient and Agglomerative coefficient