Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Performance for Prediction of Hungarian Disease Dataset using Deep Learning

Artificial intelligence is to create intelligent machines that can work like human brain. Deep learning is artificial intelligence methods that work like a human brain to store records and process the data. Machine learning algorithms have capacity to learn things that are required for particular application. Hence, they have the ability to learn. There are many algorithms available that work to increase the deep learning performance. The proposed system improves the performance for prediction of Hungarian disease dataset using improved RF HTMC FR deep learning algorithm. It uses Random Forest and HTM algorithm with feature reduction. According to experimental results the proposed algorithm performs better in terms of time, accuracy and also has very less percent of mean absolute error as compared to existing algorithm HTM and RFHTM.
Enhancing Secrecy in Cooperative Networks via Power Optimized Source Based Jamming

In this paper, a power optimized source-based-jamming scheme is proposed for secure communication in a two-hop amplify-and-forward relaying network with multiple trusted relays and a passive eavesdropper. The proposed transmission scheme employs a single jamming signal, which is transmitted from the source node along with the information to degrade the eavesdropper. The power optimization is done by means of Nelder-Mead algorithm. The conventional transmission schemes and optimization methods, jamming scheme without optimization are derived for performance comparison. Simulation results show that the secrecy performance of the proposed power optimized scheme outperforms other schemes.
Redesigning a Website Using Affordance-Based Design

The primary purpose of this research is improving the usability rate by redesigning the website. Based on observations and interviews with NGO (non-profit organization) website managers in this case study, funding and resource constraints are often the main reason NGOs choose a free blog service platform. On the other hand, the NGO has a lot of content to display on the website but not appropriately managed. Website appearance through a blog is considered not enough to support the goals of the organization that in the future wants to add a donation feature. Therefore, Affordance-Based Design is the right method to determine what information/design components need to be maintained, what needs to be eliminated, and what needs to be added based on functional needs and user behavior. This study involved three representative users and three stakeholders who had a role in defining requirements to design solution testing. Through the application of Affordance-Based Design, it was found that there was a need for improvement in eight components. Improvements are designed based on the literature of Research-Based Web Design & Guidelines. As a result, the effectiveness of the use of new designs reached 98.14%
Security-Driven Codesign with Weakly-Hard Constraints for Real-Time Embedded Systems

For many embedded systems, such as automotive electronic systems, security has become a pressing challenge. Limited resources and tight timing constraints often make it difficult to apply even lightweight authentication and intrusion detection schemes, especially when retrofitting existing designs. Moreover, traditional hard deadline assumption is insufficient to describe control tasks that have certain degrees of robustness and can tolerate some deadline misses while satisfying functional properties such as stability. In this work, we explore feasible weakly-hard constraints on control tasks, and then leverage the scheduling flexibility from those allowed misses to enhance system's capability for accommodating security monitoring tasks. We develop a co-design approach that 1) sets feasible weakly-hard constraints on control tasks based on quantitative analysis, ensuring the satisfaction of control stability and performance requirements; and 2) optimizes the allocation, priority, and period assignment of security monitoring tasks, improving system security while meeting timing constraints (including the weakly-hard constraints on control tasks). Experimental results on an industrial case study and a set of synthetic examples demonstrated the significant potential of leveraging weakly-hard constraints to improve security and the effectiveness of our approach in exploring the design space to fully realize such potential.
IoT Based Smart Parking System for Large Parking Lot

Car parking issue is a major contributor and has been yet a noteworthy issue with limited parking spots in urban communities. In this paper we present an IoT based smart parking system for large parking lot that can be used to efficiently manage the parking system by providing information on the nearest parking slot available through the mobile application and thereby reducing the congestion of parking seekers. In order to efficiently manage the parking system, a successful cloud-based smart parking system solution using the Internet of Things technology is been developed to guide the user to the nearest parking spot available.
Convolution Neural Network based Several Orange Leave Disease Detection and Identification Methods: A Review

Agriculture plays an essential role in ecological, social, biological prospects of about 65 per cent to 70 per cent of the human population. The production of the crop decreases due to the bad effects of leaves, fruit leaves and plant diseases. Fruit, leaf infection is the main reason of the maximum damage of the fruit which decrease the amount and superiority of the farming. Citrus canker infection may infect plants or fruits like as orange leaves that disturb the creation of fruit in plants. The early detection of the disease is challenging aspect of improving the productivity of the plant. This analysis emphasized on the identification, classification and detection of the leaf disease. Firstly, describes the concept of the orange, orange leaf disease and symptoms. Then, a detailed survey of various papers has done. In addition, a detection and identification techniques are explained which includes GLCM, multi-SVM, threshold value, neural network and Fuzzy method. Then, a method is explained to diagnose infected orange leaf on the basis of the convolution neural network (CNN). Convolutional neural network (CNN) is one of the main area of research in classification and detection of the leave disease. The features of the fruit (orange) leaves are extracted to detect and classify the disease. In this study, various stages for identification of the leaves disease are described. In addition, different phases to overcome the leaves diseases are also explained namely conjuring up hidden layer method, visualization of feature, semantic library and consideration mapping. Lastly, architecture is demonstrated along with different steps and procedure in orange leaf disease.
Computational linguistic prosody rule-based unified technique for automatic metadata generation for Hindi poetry

Metadata generation for the poems based on the unified rules is very complex from the viewpoint of computational linguistics. This is more tedious when it comes to Hindi poems. Prosody or ‘Chhand’ as it is called in the Hindi language consists of several sets of rules and which are used while construction of a Hindi poem. Currently, no such metadata generator or technique is in existence which can generate the metadata of Hindi poetry based on the prosody or any other Hindi grammatical rule. In this research paper, we are trying to wrap up all the difficulties with respect to the metadata generator based on ‘Chhands’, Types of ‘Chhands’, Parts of ‘Chhands’, Classification of ‘Chhands’. Along with this paper majorly focuses on the unified-rule based technique for the generation of metadata based on the different set of rules of prosody. On 3026 different UTF-8 based inputs of poems, part of poems, stories, etc., We were able to achieve 98.09% accuracy with the implementation of this unified-rule based technique of metadata generation, rest 1.91% failure was mostly due to input data related issue.
The Design and Implementation about Agile Testing for Software Networking Environment based on SDN and Emulating Virtualization Technologies

Agile development is very important to modern IT application. The application testing mode can’t cover the impact of the network when the application version is updated because the complexity. Using SDN theory and emulating virtualization technologies this paper proposed a method to deploy a emulated network environment to clone a production network architecture in a digital space just in 10 minutes. The method can extend the agile testing capability into network area for the first time. The method takes full advantage of SDN to uncouple the controlling and forwarding plane, support the fast change in networking and realize the agile tested network environment.
On the Performance of Hybrid Multi-Core and Few-Mode Fiber Links

We address the performances of signals propagating through both directions of a hybrid few-mode-fiber (FMF) and multi-core-fiber (MCF) link. MCF-crosstalk enhanced by the few-mode receiver yields an additional 0.9dB penalty when the FMF precedes the MCF in the link.
Radar Cross-Section Reduction of Helical Antenna by Replacing Metal With 3-D Printed Zirconia Ceramic

This letter proposes a dielectric helical antenna made of three-dimensional (3-D) printed zirconia ceramic, which possesses a better performance than the conventional metal one. On the one hand, the radiation principle of the proposed antenna is investigated by regarding its structure as a dielectric waveguide. It is found that a dielectric waveguide operating at the cut-off state of higher mode, here is TM01 mode, can radiate electromagnetic (EM) waves. The propagation constant of EM waves in waveguide is extracted to demonstrate that the dielectric waveguide indeed works as a fast-wave status at this moment. On the other hand, both the far-field and scattering performances between the proposed and conventional helical antennas are comparatively studied. It is observed that the structure composed of dielectric helix and metal ground can achieve similar radiation gain, axial ratio (AR), and AR bandwidth as the conventional all-metal helical antenna, but possessing lower radar cross section at high frequency. Benefited from a ceramic stereolithography apparatus, the proposed structure can be fabricated precisely, and measured results have reasonably validated the simulated ones.
A Multi-robot Control System based on ROS for Exploring Disaster Environment

This control system is implemented to coordinate multiple robots in cooperative exploration tasks, in which a task assignment algorithm is used for calculating the expectation cost to achieve the required tasks and then allocate necessary tasks to specific robots. Robot control systems are used to gather crucial information about a disaster environment, such as a victim’s position or changes in an indoor environment before a human is able to enter that environment. There are practical problems in using previous systems because these systems need professionals to operate these multi-robots. The proposed system automatically distributes tasks to each robot based on target positions that are selected by the person who does not possess any prior knowledge about robot operation. Therefore, the operator needs only to determine the target position of interest and not be concerned about controlling the robot. Moreover, the system is implemented using ROS in order to add functions and apply this system to various types of robots. This system has been verified and evaluated by Turtlebot 3 in the Gazebo simulator, as well as in a real setting by conducting the system usability scale (SUS) with 23 firefighters.
The Utilization of Military Lifetime Health Record

With the growth of IT, a comprehensive electronic health record system for the Malaysian armed forces is a must. However, because of the low success rate in the use of electronic health record systems, it is important to identify user acceptance factors for the systems. Thus, a research model that is grounded in TAM and UTAUT is developed to identify user adoption factors for Malaysian Armed Forces Hospital and Clinics to ensure the significant success of Military Lifetime Health Record (MLHR) implementations. A self-administered survey technique is employed and 63 useful responses collected from users (military clinicians and medical personnel). The research model was then tested using the partial least square (PLS) technique. The results of this study confirm that behavioral intention is significant to actual usage of MLHR system by military clinician and medical personnel. Except of effort expectancy, all four (4) factors namely performance expectancy, social influence, facilitating condition and computer self-efficacy positively affect the military clinicians and medical personnel's intention to use the MLHR system. This study confirms that performance expectancy, social influence, facilitating condition and computer self-efficacy drive users' behavioral intention toward MLHR system usage. Having a clear understanding of what and how these determinants influence military clinician and medical personnel' behavioral intention is important as it can help make MLHR systems the main source of module when it comes to the next level HIS project for MAF.
Planar H-Plane Horn Antenna Based on Groove Gap Waveguide Technology

H-plane horn antenna using gap waveguide technology is proposed. The advantage of this technology is its air-filled feature, which improves the impedance matching compared with substrate integrated waveguide (SIW) horn antennas. Corrugated walls as soft surfaces are used on the outer surfaces of the upper and lower horn plates, which act as barriers around the aperture of the antenna and reduce its backlobe levels. The bandwidth of the antenna for $| {{S_{11}}} |$< -10 dB is 19–28 GHz and the gain varies between 8.5 and 12 dBi. The total efficiency is better than 88% in the operation bandwidth. This structure has the capability of easily integrating with other planar microwave components. As a demonstration, a coupled-resonator filter is integrated with the antenna to select the desired frequency band and cancel the out-of-band harmonics. For the proof of concept, a prototype model is fabricated and tested, where measurement data agree well with the simulation results.
Capacitive Diaphragm for Compartment Shielding in the Fifth-Generation Radio Frequency Systems

This work proposes a compartment shielding method for the fifth-generation (5G) radio frequency (RF) systems. In this method, a small capacitive impedance surface is vertically placed in a shielding box as a diaphragm. Benefitting from the large phase shift on the capacitive impedance surface, it would introduce strong transverse resonance and exhibit a good shielding performance with only half height of the package. The simulation results show that this approach realizes above 10 dB shielding effectiveness (SE), covering two of the 5G working bands (24.5–27.5 GHz and 26.5–29.5 GHz). This method is helpful for reducing the size of conventional diaphragms and releasing design space in the miniaturized systems.
Compressed Data Structures for Binary Relations in Practice

Binary relations are commonly used in Computer Science for modeling data. In addition to classical representations using matrices or lists, some compressed data structures have recently been proposed to represent binary relations in compact space, such as the $k^{2}$ -tree and the Binary Relation Wavelet Tree (BRWT). Knowing their storage needs, supported operations and time performance is key for enabling an appropriate choice of data representation given a domain or application, its data distribution and typical operations that are computed over the data. In this work, we present an empirical comparison among several compressed representations for binary relations. We analyze their space usage and the speed of their operations using different (synthetic and real) data distributions. We include both neighborhood and set operations, also proposing algorithms for set operations for the BRWT, which were not presented before in the literature. We conclude that there is not a clear choice that outperforms the rest, but we give some recommendations of usage of each compact representation depending on the data distribution and types of operations performed over the data. We also include a scalability study of the data representations.
Neural Learning Enhanced Variable Admittance Control for Human–Robot Collaboration

In this paper, we propose a novel strategy for human-robot impedance mapping to realize an effective execution of human-robot collaboration. The endpoint stiffness of the human arm impedance is estimated according to the configurations of the human arm and the muscle activation levels of the upper arm. Inspired by the human adaptability in collaboration, a smooth stiffness mapping between the human arm endpoint and the robot arm joint is developed to inherit the human arm characteristics. The estimation of stiffness term is generalized to full impedance by additionally considering the damping and mass terms. Once the human arm impedance estimation is completed, a Linear Quadratic Regulator is employed for the calculation of the corresponding robot arm admittance model to match the estimated impedance parameters of the human arm. Under the variable admittance control, robot arm is governed to be complaint to the human arm impedance and the interaction force exerted by the human arm endpoint, thus the relatively optimal collaboration can be achieved. The radial basis function neural network is employed to compensate for the unknown dynamics to guarantee the performance of the controller. Comparative experiments have been conducted to verify the validity of the proposed technique.
Support the Realistic Mathematics and its Influence in the Mathematical Self-Efficacy in Aspirants to Engineering

The evaluations of the Programme for International Student Assessment (PISA) demonstrate that Peru has serious shortcomings in mathematics, result that is harmful to the formation of future engineers. For it before this problems the Institute of Sciences and Humanities (ICH) promotes the Realistic Mathematical Education (RME) in the pre university education. And before the need to evaluate some achievements of the ICH, the present studies takes as a finality to identify relation between the application of the principles of the RME and the mathematical self-efficacy in a sample of 60 pre university students candidates to the engineering careers (28 men (45.9 %) and 32 women (54.1 %)) (Mage = 17.84, SD = 1.76). The results demonstrate that the application of the principle of guided reinvention and the principle of interconnection is related by them with the mathematical self-efficacy; but only the principle of interconnection predicts to the mathematical self-efficacy.
Design of a 3-DOF prosthetic wrist for low-cost transradial myoelectric upper limb prosthesis

This paper presents the design of a 3-DOF prosthetic wrist for transradial myoelectric upper limb prosthesis that allows the orientation of a prosthetic hand to reduce compensatory movements that cause musculoskeletal problems mainly in the back and shoulder. The device is capable of perform passively abduction-adduction movements and actively flexion-extension and pronation-supination movements. The system has a DC motor that transmits power to the active movements and a solenoid for the choice of the type of movement to be performed. In order to validate the design of the components of the device, calculations and simulations were carried out by finite elements method to determine deformations, mechanical resistance and fatigue to define the critical components and maintenance periods.
A Novel Approach to Glaucoma Screening using Computer Vision

Glaucoma is one of the major and critical eye diseases discovered till date. It is actually a group of diseases that damage the optic nerve and subsequently result in vision loss and blindness. One of the major causes of Glaucoma is the intrinsic distortion of the optic nerve resulting in high fluid pressure on the front portion of the eye. The primary objective of the paper is to classify High Resolution Fundus images of the retina into Glaucomatous and Non-Glaucomatous. In order to achieve that, a DL-ML Hybrid Model has been developed with an initial image processing. The overall methodology followed in this paper has been termed as N-S Model. The HRF (High Resolution Fundus) Image Database consisting of 30 images is used for the purpose. The N-S Model was deployed after development and clocked a 100% Validation Accuracy and Sensitivity of 1.0. Such an Intelligent System can accelerate the process of diagnosis and reduce the review of doctors.
Generic and Robust Localization of Multi-dimensional Root Causes

Operators of online software services periodically collect various measures with many attributes. When a measure becomes abnormal, indicating service problems such as reliability degrade, operators would like to rapidly and accurately localize the root cause attribute combinations within a huge multi-dimensional search space. Unfortunately, previous approaches are not generic or robust in that they all suffer from impractical root cause assumptions, handling only directly collected measures but not derived ones, handling only anomalies with signicant magnitudes but not those insignicant but important ones, requiring manual parameter ne-tuning, or being too slow. This paper proposes a generic and robust multi-dimensional root cause localization approach, Squeeze, that overcomes all above limitations, the first in the literature. Through our novel bottom-up then top-down searching strategy and the techniques based on our proposed generalized ripple effect and generalized potential score, Squeeze is able to reach a good trade off between search speed and accuracy in a generic and robust manner. Case studies in several banks and an Internet company show that Squeeze can localize root causes much more rapidly and accurately than the traditional manual analysis. Furthermore, our extensive experiments on semi-synthetic datasets show that the F1-score of Squeeze outperforms previous approaches by 0.4 on average, while its localization time is only about 10 seconds