Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Technique for Detection of Diabetic Retinopathy using Segmented Retinal Blood Vessels

This paper presents an algorithm that will segment the retinal blood vessels with an accuracy of 96.17%. This algorithm will extract the features from input images present in STARE and CHASE_DB1 databases. The extracted features will be large in number, but all the features are not useful. So, the feature optimization is done by Lion Optimization which has effectively chosen only the features which are useful in representing the extracted features as blood vessels or non-blood vessels. The algorithm was applied first on training images which have results of manually segmented images already. Then the algorithm was implemented on training images and evaluated on training images and it successfully detects the normal as well as abnormal images. The quantitative results were checked using parameters sensitivity, specificity, accuracy, positive predictive rate and false predictive rate and proved to give better results in comparison to existing techniques.
Numerical path planning for autonomous marine vehicle smooth transition between multi-survey segments

Autonomous marine vehicles (AMVs) are commonly used in autonomous marine survey activities. This paper investigates the online swath detection path planning algorithm, in which the smooth transition path planning between multi-survey segments is considered. The active and passive transition mode are realized based on subsea detection application. The Fermat’s Spiral (FS) is specifically used to design the transition path between straight survey segments. The scope of FS segments between straight lines are optimized by considering the maneuverability of the vehicle. In addition, the FS is parameterized to simplify the subsequent path following control problem. Simulation results show that the Autonomous Surface vehicle (ASV) is capable to conduct path following in horizontal plane by employing the proposed online path planning algorithm.
A Reference Oversampling Digital Phase-Locked Loop with -240 dB FOM and -80 dBc Reference Spur

This paper proposes a reference oversampling phase-locked loop that simultaneously suppresses in-band noise and oscillator noise while maintaining a low reference spur. The proposed phase locked loop achieves -240.3 dB Figure of Merit (FOM) and -80 dBc reference spur. The integrated jitter is 508 fs$_{rms}$ and the power consumption is 3.6 mW at 2 GHz output clock frequency.
Analysis of Energy Efficiency of a Parallel AES Algorithm for CPU-GPU Heterogeneous Platforms

Encryption plays an important role in protecting data, especially data transferred on the Internet. However, encryption is computationally expensive and this leads to high energy costs. Parallel encryption solutions using more CPU/GPU cores can achieve high performance. If we consider energy efficiency to be cost effective using parallel encryption solutions at the same time, this problem can be alleviated effectively. Because many CPU/GPU cores and encryption are pervasive currently, saving energy cost by parallel encrypting has become an unavoidable problem. In this paper, we propose an energy-efficient parallel Advance Encryption Standard (AES) algorithm for CPU-GPU heterogeneous platforms. These platforms, such as the Green 500 computers, are popular in both high performance and general computing. Parallelizing AES, using both GPUs and CPUs, balances the workload between CPUs and GPUs based on their computing capacities. This approach also uses the Nvidia Management Library (NVML) to adjust GPU frequencies, overlaps data transfers and computation, and fully utilizes GPU computing resources to reduce energy consumption as much as possible. Experiments conducted on a platform with one K20M GPU and two Xeon E5-2640 v2 CPUs show that this approach can reduce energy consumption by 74% compared to CPU-only parallel AES and 21% compared to GPU-only parallel AES on the same platform. Its energy efficiency is 4.66 MB/Joule on average higher than both CPU-only parallel AES (1.15 MB/Joule) and GPU-only parallel AES (3.65 MB/Joule). As an energy-efficient parallel AES solution, it can be used to encrypt data on heterogeneous platforms to save energy, especially for the computers with thousands of heterogeneous nodes.
Real-Time Implementation of Energy-Efficient Clustering Protocol in WSN

Hierarchical routing protocols are the most prominent energy-efficient routing protocol to attain longer life time in wireless sensor network. In the literature, many cluster-based routing protocols have been proposed by considering energy is the most important parameter. These techniques have been implemented using machine learning algorithms and simulated for approximated network model but not in real time scenarios. In this paper, we have implemented centralized clustering protocol in real time scenario and analyzed energy elapsed during different phases of the nodes. Texas Instruments CC2650 ultra-low power wireless microcontroller is used as target hardware platform and indoor environment monitoring as target application.
High Performance Microstrip Patch Antenna Using High Refractive Index Metamaterial

A metamaterial that is formed by symmetrically etching square metal patches on both sides of a dielectric plate is proposed to realize high refractive index in the frequency range from 4 to 8 GHz. The designed metamaterial is loaded on the microstrip patch antenna as a superstrate to improve the radiation performance of antenna. The measured result show that the impedance bandwidth of S11 < −10 dB is 690 MHz with relative bandwidth of 12.4%. The maximum gain of the proposed antenna is 13dB at 5.6 GHz. At the same time, the profile of the metamaterial loaded antenna is only 0. 19λ (λ is the free space wavelength referring to the antenna central frequency)
Energy - Optimized Route Discovery in AODV

Energy is a scarce resource in the Mobile Adhoc network. The efficient usage of the energy resources in mobile Adhoc environment is a big challenge. Sometimes few paths are utilized more than the other available routes from source to destination. Due to excessive use of that path, the energy of the node is exhausted and the node switched off itself. This paper will discuss about a new approach for efficient route discovery which works on the concept of residual energy available. By integrating the residual energy into consideration the lifetime of the network can be optimized. The performance of the modified protocol is simulated in Ns2 (2.35).
Design of Unequally Excited Two Elements Antenna Array using Gysel Power Divider

In this paper, a Gysel Power Divider has been designed at 1.5 GHz operating frequency. Two rectangular microstrip patch antennas, operating at the same frequency, has been designed and fed to the power divider to form an antenna array. The proposed array offers significant gain, improved reflection co efficient and lower side lobe level compare to that of the conventional antenna array. The relative position of the two output ports have been varied to excite unequal power distribution of the radiating elements to achieve optimum results.
VSIE Method Based on Nonconformal Discretization for EM Scattering From Composite Objects

In this paper, an efficient volume surface integral equation (VSIE) method based on nonconformal discretization is developed for the numerical simulation of electromagnetic scattering by composite objects. This VSIE method introduces the Full-RWG and Half-RWG basis functions for PEC surfaces and Full-SWG and Half-SWG basis functions for dielectric objects. Based on that, the nonconformal discretization is allowed in this VSIE. The nonconformal nature of the VSIE method gives the considerable flexibility in the meshing. Numerical results are presented to demonstrate the accuracy and efficiency of the non-conformal method.
Smart Energy Harvesting for Internet of Things

In this paper, we study the performance of smart networks in terms of energy efficiency (EE) based on the internet of things (IoT) technology. Energy Harvesting (EH) from surroundings is a promising solution for compensating the limitation of batteries lifetime. Fuzzy Q-Learning algorithm has been proposed to determine the sensor movement strategy toward the dedicated power stations (PSs) as energy charger nodes for mobile sensors in order to improve network lifetime via acceleration of the battery charging process of mobile sensors. Simulation results for evaluation of the proposed strategy in term of normalized network lifetime compared to the random sensor motions, confirm the effectiveness of this approach as a practical smart EH for IoT networks.
Humour Agent Detection in Puns

Humour is an integral part of all varieties of linguistic expression. A very popular type of humour is pun. Pun uses word-play and ambiguity to create a humorous effect. Due to the extensive usage that puns find in texts, it becomes imperative that computers understand and learn to process them. While some work has been done to detect the presence of puns in a text, finding the ambiguous word which caused the humour remains a new task. It is important to understand the cause of humour before we can proceed to the next steps, such as humour generation. This paper aims to propose a method to identify the humour agent in pun-based sentences. The method utilizes the structural information of the sentence and then uses a semantic similarity measure to find a relationship between the words. This relationship is used to find the humour agent in the sentence.
Voice Control Interface Prototype for Assistive Robots for People Living with Upper Limb Disabilities

This paper presents a voice control interface prototype for assistive robots aiming to help people living with upper limb disabilities to perform daily activities autonomously. Assistive robotic devices can be used to help people with upper-body disabilities gain more autonomy in their daily life. However, it is very difficult or even impossible for certain users to control the robot with conventional control systems (e.g. joystick, sip-and-puff). This paper presents the design and preliminary evaluation of a voice command system prototype for the control of assistive robotic arms’ movements. This work aims at making the control of assistive robots more intuitive and fluid, and to perform various tasks in less time and with a lesser effort. The prototype of the voice command interface developed is first presented, followed by two experiments with five able-bodied subjects in order to assess the system’s performance and guide future development.
Revisiting Cloud Security Threats: Replay attack

Cloud is an embryonic computing technology that offers immense perspective to develop product efficiency and operational effectiveness. Cloud technology supports resource sharing and multi-tenancy, which in turn contributes to solid capital and operational outgoings.Reduced cost and ease of use are the main benefits of Cloud computing but at the same time, trust and security are the two major concerns imposed on the users using Cloud services. The providers of the cloud technologies are addressing many issues related to vulnerabilities and threats related to virtualization, authentication and authorization. One of the security threats, replay attack is a major threat towards the clod infrastructure. In this paper, attempts have been made to understand the replay attack, followed by its route cause, related work in this area. Major contribution in this paper is to provide comprehensive review and suggest future research areas related to the replay attack. This will researchers to serve as update reviews in the related area, which will in time save their time for doing the same.
Logistic Regression based DFS for Trip Advising Software (ASCEND)

Graphs have played a pivotal role in the field of computer science and has been an efficient method for representing and modeling abstractions in various fields. They can be used to represent several real life models. Several domains in today’s world use the concept of graphs extensively such as GPS Navigation systems, Computer networks, WebCrawler, Social Networking websites, peer to peer networking, medical and biological field, neural networks etc. Taking into account the numerous applications of the concept of graphs in today’s world, graph searching becomes inevitably significant. In this scenario it is important to note that several graph searching algorithms that were proposed to give exhaustive searches doesn’t provide the most satisfying outcome in terms of asymptotic time complexity. Through this paper we intend to highlight the significance of machine learning as a useful tool that can be incorporated in various graph searching algorithms that can reduce its complexity. We classify the existing graph searching techniques as subsets or modifications of two major conventional graph searching algorithms namely BFS(Breadth First Search) and DFS(Depth First Search) and suggest the application of logistic regression to improve their performance. It is confounding that only few research papers explore the application of machine learning to the aforementioned graph searching algorithms. Hence, it is evident that there exists scope for future research on this topic and we aim to suggest directions for the same.
Self-Oscillating Parametric Optical Frequency Comb Generation Using an Electroabsorption Modulated Laser-Based Optoelectronic Oscillator

A scheme for parametric optical frequency comb (OFC) generation using an electroabsorption modulated laser (EML) based optoelectronic oscillator is proposed and experimentally demonstrated. A phase modulator is cascaded with EML in the oscillating loop. In addition, the phase modulated laser is used as pump seeds for the parametric frequency mixer. In the mixer, a 100-m single-mode fiber is employed to compress the pump pulses, and the parametric process is stimulated in a 200-m-high nonlinear fiber (HNLF) with flat normal dispersion. In our experiments, a 10-GHz radio frequency signal with a side-mode suppression radio of 47 dB and a single-sideband phase noise of −109.89 dBc/Hz at 10 kHz offset is obtained. When the pump power injected into HNLF is 28 dBm, a 10-tone parametric OFC with a 5-dB power variation and spacing equal to the oscillation frequency is generated.
Electronic Beam-steering Using 1-Bit Digital Rflective Metasurface at Ka Band

This paper presents a 1-bit digital reflective metasurface operating at 35 GHz. A simple 1-bit digital element structure employing one PIN diode, which has a fractional bandwidth of 5.4%, is proposed. Based on the element, a 20 × 20 metasurface is constructed. By properly leveraging ON and OFF states of PIN diodes mounted on metasurface, two-dimensional electronic beam-steering can be realized to tailor the incoming waves fed by a horn antenna. Finally, high-gain beam-scanning, orbital angular momentum vortex beams, and near-field focal beams are theoretically achieved by using aperture field approach.
Defending DDoS against Software Defined Networks using Entropy

Software defined networking (SDN) has gained the attention of many researchers and networking data centers. SDN provides flexibility and programmability to the network which makes it easy to adapt the changes. As SDN controller has a centralized visibility to the complete network topology, it may be targeted by the attackers. By breaking the integration of forwarding and routing rules in a single device, it offers cost-efficient networking services. However, SDN may suffer from various types of Distributed denial of service (DDoS) attacks. DDoS can disturb the complete network functionality by consuming resources and processing power of controller. Some researchers have designed many efficient defense mechanisms recently. In this research work, entropy which is used to compute the randomness of any event is utilized to detect the DDoS attacks. The attack detection module is implemented in POX controller which monitors the statistics of all the incoming flows. The suggested entropy based detection offers to identify the attack in a short duration and gives a fast response.
Displacement Sensor Based on Separated Inverted-F Antenna

In this paper, the concept of separated Inverted-F antenna (SIFA) is proposed, coupling feeding is used in SIFA, and the thickness of the additional capacitor’s dielectric is studied to find the suitable range of being a displacement sensor. Simulation result shows that the current can get through the capacitor, and feeder’s moving can let the resonant frequency shift linearly. So it’s reliable to transform the SIFA to a displacement sensor, so as to provide evaluation basis for structural health monitoring (SHM).
Optimal Energy Dispatch of Smart Home Equipped with PV, WT, and ESS Using Load Control under RTP

The problem of energy dispatching for smart homes is addressed in this paper. Domestic loads are classified into three groups based on their controllability. The proposed smart home is equipped with distributed generation systems, including photovoltaic system, and a small-size wind turbine. Moreover, a battery is considered as the energy storage system. Electricity pricings are given in 30-minutes intervals. A two-variable objective function which tries to minimize the difference between DGs generation and loads consumption as well as the purchased power, is introduced. The proposed load control strategy determines optimal time allotment for each load. Also, the battery improves performance of smart home through charging or discharging according to the proposed algorithm. Furthermore, the excess demanded or generated power that is exchanged with the power utility is decreased, which means lower losses and transmission expenses. Ultimately, the proposed approach is performing well, and results in better meeting the demand requirement.
A Novel FDTD Algorithm Based on the Vector and Scalar Potentials Equations

As the advance in nanotechnology, the length of electronic devices down to nano-scale structure. It is important to consider multi-scale phenomena ruled by the Maxwell’s equation in the finite-difference time-domain (FDTD) simulation. This paper provides an alternate approach for solving the vector and scalar potentials (A and Φ) formulation of Maxwell’s equations instead of the fields (E and H) which might suffer from low frequency breakdown problem. This new approach is more suitable for multi-scale problem since it is stable in the long wavelength regime which established the proposed method as a better algorithm in the electromagnetic simulation.
Exploring the Impact of Machine-Learned Predictions on Feedback from an Artificial Limb

Learning to get by without an arm or hand can be very challenging, and existing prostheses do not yet fill the needs of individuals with amputations. One promising solution is to improve the feedback from the device to the user. Towards this end, we present a simple machine learning interface to supplement the control of a robotic limb with feedback to the user about what the limb will be experiencing in the near future. A real-time prediction learner was implemented to predict impact-related electrical load experienced by a robot limb; the learning system’s predictions were then communicated to the device’s user to aid in their interactions with a workspace. We tested this system with five able-bodied subjects. Each subject manipulated the robot arm while receiving different forms of vibrotactile feedback regarding the arm’s contact with its workspace. Our trials showed that using machine-learned predictions as a basis for feedback led to a statistically significant improvement in task performance when compared to purely reactive feedback from the device. Our study therefore contributes initial evidence that prediction learning and machine intelligence can benefit not just control, but also feedback from an artificial limb. We expect that a greater level of acceptance and ownership can be achieved if the prosthesis itself takes an active role in transmitting learned knowledge about its state and its situation of use.
Python Based Portable Virtual Text Reader

The idea of this paper is to build an automated virtual reader. In this modern era, there is an urge for an automated reader which is cost-effective, accurate and also portable at the same time. The product is based on a Raspberry Pi module that also has a camera connected to it which is used to take pictures. The whole bodywork is also integrated with Optical Character Recognition (OCR), Text-To-Speech (TTS) and a speaker. A Graphical User Interface (GUI) helps the users to take pictures with the help of a single click. A button is also integrated with the Raspberry Pi which helps initiate the program and carry out all the functions. After the successful capturing of the picture, the system carries out some basic image processing black and white conversion and de-noising. The processed image is then supplied to the Tesseract-OCR which understands the characters and TTS is used to convert the text to audio format. A software named eSpeak is used to read out the audio formatted file which is delivered as an output with the help of a speaker. Conversion of text to speech can also be done in Matlab but that wouldn’t be portable and user-friendly.
Research on Joint Steering Technology of Underwater Vehicle Based on PID

Aiming at depth control problem of underwater vehicle in vertical plane, the paper proposes a joint steering strategy which assigns depth error and pitch error to bow and stern rudders simultaneously. Basing on PID control algorithm, we research the depth control problem of underwater vehicle in vertical plane by MATLAB Simulation. Firstly, we have established a simplified kinematics and dynamics models of the underwater vehicle in vertical plane; Then, we have designed joint steering strategy controller basing on PID control algorithm; Finally, using digital simulation platform, we have made the simulation experiment and comparative analysis for the joint steering strategy proposed in this paper. The results fully indicate the effectiveness and practicability of the joint steering strategy.
Does Macaulay Duration Provide The Most Cost-Effective Immunization Method – A Theoretical Approach

Abstract In the following, we offer a theoretical approach that attempts to explain (Comments 1-3) why and when the Macaulay duration concept happens to be a good approximation of a bond’s price sensitivity. We are concerned with the basic immunization problem with a single liability to be discharged at a future time q. Our idea is to divide the class K of all shifts a(t) of a term structure of interest rates s(t) into many classes and then to find a sufficient and necessary condition a given bond portfolio, dependent on a class of shifts, must satisfy to secure immunization at time q against all shifts a(t) from that class. For this purpose, we introduce the notions of dedicated duration and dedicated convexity. For each class of shifts, we show how to choose from a bond market under consideration a portfolio with maximal dedicated convexity among all immunizing portfolios. We demonstrate that the portfolio yields the maximal unanticipated rate of return and appears to be uniquely determined as a barbell strategy (portfolio) built up with 2 zero-coupon bearing bonds with maximal and respective minimal dedicated durations. Finally, an open problem addressed to researchers performing empirical studies is formulated.