Miracle-dz/UniFAR-FTUs huggingface dataset:
Software Outsourcing Quality Evaluation Management Model (SOQEMM)

Software quality evaluation is the process to investigate any software quality in context of reliable software development where it can enhance the productivity of the system. It gives direction for valuable research in requirement, reliable software development, architecture design and model driven engineering. Variety of challenges is linked with software product in the in the quality evaluation stages. So many efforts have been taken for software quality improvements. The aim of this research project is to develop a model of software outsourcing quality evaluation management model (SOQEMM) from vendors’ perspective. This model will support the vendor organization to evaluate any software at its various stages like pre, mid and post development. This model will gauge the status of vendor organization for the quality evaluation of any software in context of software reliability, maintenance and extension of requirement change. We have plane to identify the various factors that have positive impact on software quality evaluation management and to identify all those challenges that have negative impact on software equality evaluation management. Systematic literature review(SLR) will be used for the identification of critical success factors(CSFs), critical barriers (CBs) and significant practices of software quality evaluation. A questionnaire survey will be performed for the verification of findings of SLR. At last a case study will be performed for evaluation of our findings in real world environment.
Isolation Improvement in Closely Coupled MIMO Antenna

In this communication, a double-layer of metasurface based isolation method is proposed to reduce the mutual coupling MIMO (multiple input multiple output) antenna’s elements at the 3.5GHz. The double-layer metasurface composes of periodic structure pair of even cut patches with exact same lengths. The main advantage of using a double-layer metasurface layer is there is no additional matching technique is employing in antenna structure to compensate for the matching condition of the antennas. The simualated result shows that mutual coupling among two antennas is enhanced to more than 47dB at 3.5GHz frequency while their reflection coefficients remain to be below -10dB after the double-layer metasurface superstrate is introduced. furthermore, the radiation efficiency is improved to 18% at 3.5GHz and the envelop correlation coefficient (ECC) of MIMO antenna is reduced from 0.08 to 0.0014 at 3.5GHz. MIMO antenna shows excellent performance that makes it a promising contender for the 5G communication system.
A Survey on Solar Powered Autonomous Multipurpose Agricultural Robot

Agriculture is considered as one of the most important economic activities in India. This paper deals with trade and development of low cost, low power and less human effort robot in the agronomic applications. Agricultural automata are widely used at the collecting phase, tunneling, cultivating and seeding. This robot is intended to reduce the farmer's effort. The designed Robotics techniques are efficient for achieving the tasks such as automatic cultivating, seed providing, water sprinkling, insecticide spraying and Grassland wounding with the help of solar energy. Seeds are spread in 4 rackets at a single instant. Initially, the robot digs the complete field concurrently providing seeds adjacent by side and finishes the required actions in a robotic mode with embedded programs. For a labor-intensive control, the robot uses the remote controller as android app.
Comparison of different ovulation protocols in patients undergoing controlled ovulation hyperstimulation with intra uterine insemination

Background: For many couples’ advent of a baby is the most beautiful gift of life. Involuntary childlessness by itself does not threaten physical health but can have a strong impact on the psychological and social wellbeing of couples. The aim of the present investigation was comparison of different ovulation protocols in patients undergoing controlled ovulation hyperstimulation with Intra uterine insemination.Methods: A Prospective observational study was conducted in the department of obstetrics and gynaecology. 200 couples who underwent 541 cycles with controlled ovarian hyperstimulation. Variables selected for analysis were female age, menstrual history, duration of infertility, number of cycles, number dominant follicle diameter, endometrial thickness.Results: Maximum patients underwent ovulation induction with clomiphene citrate (202/541) and then with letrozole (202/541). Conclusions: Nowadays when the costs of health care are limited, intrauterine insemination can hold its place as a low-cost method of infertility treatment. Conclusively with careful selection of subjects, appropriate controlled ovarian stimulation and intra uterine insemination, good pregnancy rates with low multiple pregnancy rates can be achieved.
Flexible Fiber Interconnects for Soft Mechatronics

Recent advances in flexible electronics, soft sensors and soft actuators are paving the way towards replacing hard printed circuit boards for soft counterparts in various applications (e.g. soft robotics, wearable devices, etc.). The need to achieve robust electrical connections between both soft and traditional rigid components poses many challenges. In particular, the in-extensiblility of commercially available interconnects (e.g. single/multi-strand conductive wires, conductive metallic tapes, etc.) can affect the structural properties of soft components. Herein we present the design and demonstrate the fabrication method for making flexible fiber interconnects (FFI) by printing flexible guide-paths and simultaneously layering and embedding conductive yarns within. The effectiveness and robustness of the flexible interconnects for use within soft structures is characterized. Simple FFI designs can be used within structures undergoing up to 200% strains without interfering with the substrate stress-strain behavior. Electrical conductivity is also shown to be stable even during cyclic loading.
Aerial Disaster Relief Response System Based on GIS

The frequency of the natural disasters has a significant growth in recent years. For example, economic suffered tremendous losses while heavy casualties occurred during the time that Hurricane Maria hit Puerto Rico. For Problem A, we put more focus on combining the Multi-objective Programming algorithm to establish a 3-D Packing Model in order to obtain the maximum of the utilization of medical packages and drones of the ISO cargo container space. For Problem B, we are mainly aiming to build a Spatial Decision Support System, which is based on DEM and ArcGIS exponential Model at first. Lastly, for Problem C, the optimization method is adopted by us to determining the cargo container configuration and flight route of drones.
CMOS Modified Differential Voltage Multiplier Co-integrated with Indoor Photovoltaic Energy Harvesting in 65nm CMOS Process for WSN Application

This circuit design presents a CMOS Modified Differential Voltage Multiplier co-integrated with indoor photovoltaic energy harvesting circuit for Wireless Sensor Node device in 65nm CMOS process. This work aims to supply power in Microsemi’s ZL70250, a wireless sensor network transceiver. Extraction of high DC voltage from rectifier block is always a serious bottleneck for energy harvesting. Consequently in this work, a simple mechanism to eliminate (Vth) of the MOS transistor by adding an auxiliary Pmos is proposed. Also, an additional capacitor (Cs) has been split into two capacitors that have been connected to the differential output. For analysis and comparison, the traditional and proposed voltage multiplier circuit is simulated and implemented with 3 stages with load capacitance of 100pF. The proposed voltage multiplier obtains a higher voltage conversion ratio (Gv) of 3.96, much higher than the reference voltage multiplier. The Gv and the generated boosted rectifier output voltage was obtained from 0.5V single PV. The modified architecture is integrated in indoor photovoltaic energy harvesting circuit. Accordingly, with this modification and implementation, this work able to supply power for Microsemi’s ZL70250 that requires 1.2V to 1.8V and less than 1.9mA to operate.
Resource Management of Multiple Phased Array Radars for Multi- Target Tracking

In this paper, a resource management method of multiple phased array radars for multi-target tracking is proposed. In order to minimize the track resource usage while still guaranteeing multi-target continued tracking performance, a novel resource allocation model is presented in which the parameters include radar-to-target assignment, revisit time and dwell time can be optimized. And an improved PSO is proposed to solve the optimization problem. The performance of the allocation model and improved PSO is demonstrated by the simulation.
Design and Analysis of LIM Hybrid MTJ/CMOS Logic Gates

Surge in the power dissipation due to increased leakage current has become one of the major concern in conventional CMOS VLSI design because of reduced transistor size, lower threshold voltage and lower supply voltage. To alleviate this, we have designed hybrid magnetic tunnel junction (MTJ)/CMOS circuits based on logic-in-memory (LIM) structure for various logic gates such as NAND/AND, NOR/OR and XNOR/XOR. This paper investigates the performance of hybrid gates and the results are compared with the conventional CMOS based gates in-terms of power, delay and device count. Hybrid gates designed in this paper are not only non-volatile in nature due to the use of MTJs but also they are found superior than the conventional CMOS circuits by dissipating less power and occupying smaller die area.
Unconventional Public Transport Anonymous Data Collection employing Artificial Intelligence

This paper presents results of a research concerning the possibility of collecting anonymous data regarding public transport level of service, employing wireless technologies (Bluetooth and Wi-Fi), big data and statistical filtering. Machine learning algorithms are used to detect, locate, create a map and record presence of travelers in public transport vehicles and stations, along with regular traffic data. The solution could also serve as back-up system for locating vehicles on their path.
IoT Instrumented Food and Grain Warehouse Traceability System for Farmers

In a developing country like India, agriculture is one of the main sectors in terms of income. Good food storage plays a very important role when it comes to food security that is affected by both food loss and food wastage. The losses can be reduced, which will automatically increase the amount of food availability. In this article, we proposed an IoT enabled monitoring system to deploy in remote areas where the accessibility is very minimum for farmers with good storage facilities to reduce food losses and increase food safety. This proposed framework monitors warehouse parameters such as temperature, humidity, CO, motion, vibration, and smoke which is highly affected to grains. The ESP32 WiFi module collects the data from the sensors and this module sends data to Node-red dashboard through MQTT broker. Multiple IoT nodes installed at a different location inside the warehouse and which will give information about the warehouse environment to the farmers through Mobile SMS and E-mail notification.
Smart Routing Management Framework Exploiting Dynamic Data Resources of Cross-Layer Design and Machine Learning Approaches for Mobile Cognitive Radio Networks: A Survey

The concept of Cognitive Radio (CR) has emerged as a practical solution to solve the issue of the fixed spectrum and bandwidth scarcity in wireless communication. However, the nature of dynamic Mobile Cognitive Radio Networks (MCRNs) drives to the emergence of new challenges, especially concerning the routing protocol operations. Applying a cross-layer design is considered a sufficient remedy to overcome routing protocol challenges such (e.g. channel diversity, integration route discovery with spectrum decision, mobility, etc.). Consequently, the cross-layer design has a magic solution to overwhelm routing challenges in MCRNs due to the ability to be free from the strict boundary and share the information and services with other layers in a manner that contributes to enhancing routing performance. Thus, the scope of this survey is to review and taxonomy numerous routing protocols in MCRNs according to methods of design to highlight the strength and weakness points. Also, machine learning has acquired much interest in this literature. A cross-layer framework for smart routing protocol in MCRNs has been proposed by exploiting machine learning mechanisms. Finally, the open research issues of routing protocol in MCRNs are summed up.
A Biologically Inspired Low Energy Clustering Method for Large Scale Wireless Sensor Networks

Recently, the low energy clustering problem has been studied by numerous researchers and engineers. Such a problem is important in improving low energy consumption. In this paper, we propose an improved chaotic parallel monkey algorithm (ICPMA), a randomized swarm optimization algorithm for low energy clustering in large scale wireless sensor network, motivated by chaotic theory and parallel theory. We first establish a mathematical model for the low energy clustering problem. Based on the monkey algorithm, the new optimization method has many advantages due to blend both the chaotic theory as well as parallel theory. Simulations are conducted to compare and evaluate the energy efficiency of ICPMA with shuffled frog leaping algorithm (SFLA), artificial fish swarm algorithm (AFSA) as well as particle swarm optimization (PSO). In our experiments, we obtain that the novel ICPMA approach, when implemented into LSWSNs, is able to offer better performance and an improving energy efficiency compared to SFLA, AFSA and PSO approach.
Application of Learning Analytics Tools in Learning Management Systems

This article describes the use of various Learning Analytics (LA) tools in the Learning Management System (LMS). Using the LA tools consists of four steps: collecting data and choosing the appropriate LA methods, choosing the LA tools, testing the LA tools, and evaluating the results. The main conclusions of this article are that LA tools are still too dependent on the data format and the LMS version, and that teachers find using this type of tool useful, but still difficult toutilize
Analysis on Voltage Stability of AC / DC Hybrid Transmission System based on Continuous Power Flow

With the implementation of China's power development strategy, HVDC power transmission technology has been increasingly applied in China's HVDC power grid due to its unique technical and economic advantages. In this paper, the continuous power flow calculation method of AC / DC hybrid transmission system is studied to obtain the stability margin of the current operating point of the system. The voltage stability margin under different control modes and the voltage of each node are solved by an example.
Economic Load Dispatch Optimation of Thermal Power Plant Based on Merit Order and Bat Algorithm

Fuel cost optimization is generally done using an approach of deterministic and undeterministic methods. This study compares the application of deterministic merit order algorithms with the application of undeterministic bat algorithms. The issue of economic load dispatch has complex equality and inequality constraints, so it is difficult to determine the optimum value using a conventional approach. In determining the optimum value it is necessary to schedule generator units to divide the generated power in meeting system requirements so the optimum fuel costs are obtained. Merit orders are arranged based on the amount of hourly fuel costs per unit operating at its maximum output, while the bat algorithm is based on echolocation characteristics of microbats simulated on a computer program from the position, velocity and frequency of bats. The researched data are the actual data of thermal power plants which amount to 6 (six) plants in the peak loads condition in 2018. By using 2 (two) different method, namely merit order and bat algorithm, the results of different production costs are obtained. The merit order can reduce production costs by 14.67% or $ 291640 of the actual cost, while the bat algorithm produces an efficiency of 15.66% or $ 311405 of the actual cost. From the results of this calculation it can be concluded that the use of bat algorithm can produce a more efficient (smaller) generation costs that is equal to $ 19765 or 0.99% smaller than the merit order method. This can occur because of the bat algorithm manages to create a loading combination of more efficient power plants.
Power System On-line Transient Stability Prediction by Margin Indices and Random Forests

This paper addresses a novel approach for on-line transient stability prediction for power systems. In the proposed framework, the feasible instability classes (ICs) of a power system is first identified by off-line simulation considering the uncertainties of load and all potential contingencies. Accordingly, after contingencies, the stability margins (SMs) for each possible IC can be rapidly calculated using direct methods. These SMs are chosen as features for the prediction models trained by random forests, which further demonstrate a better prediction performance compared to other features used in previous machine learning based method. The proposed approach is validated on two IEEE test systems and compared to existing methods.
Analysis and Comparison of Novel Clock Gating Cell Topologies in 65nm CMOS Process Technology

An analysis and comparison of three novel clock gating topologies in the TSMC 65nm CMOS Process Technology is presented in this study. Additional logic is added to these topologies to accommodate a scan-enable signal for future ASIC implementations. In addition to schematic simulations, a standard cell layout of each topology that conforms to the design constraints of the TSMC 65nm Digital Library are designed and simulated. The circuits are tested at 5MHz, 15MHz, and 25MHz input clock frequencies using TT, SS, and FF process corners within a 1V supply voltage. Data is gathered from the simulations using a fair and uniform environment. A ranking system composed of the power consumption, propagation delay, standard cell width, and rise and fall times is utilized as a basis for performance comparison. The results of the comparison serves as a basis for future low-power digital circuits and custom standard cell design and implementation.
A Novel Data-Driven Scheme for the Ship Wake Identification on the 2-D Dynamic Sea Surface

Because the ship wake spreads into an area much larger than that of the ship hull in the sea surface, it has been widely used in the ship detection. However, due to the complex sea wave motion and the high sea state, the ship wake detection is still a challenging task. In this paper, we propose a novel data-driven method based on dynamic mode decomposition (DMD) to detect, reconstruct, and locate the Kelvin wake on the two-dimensional dynamic sea surface. Through the proposed method, the sea’s dynamic characteristics including the oscillation frequency and decay/growth rate of ship wakes and the time-varying sea surface can be obtained. Meanwhile, the spatial features of ship wakes can be derived by dynamic modes as well. The proposed method can distinguish the dynamic characteristics between the Kelvin wake and sea background. Then the corresponding modes of the Kelvin wake can be successfully identified. The proposed method is demonstrated by analyzing a 2D sea surface where the Kelvin ship wake is superposed. It is found that our new approach provides an effective and accurate ship detection, even in the case of high sea states. Meanwhile, the extracted mode of the wake shows the ship position clearly with very high resolution.
Big Data Analytics Framework for Opinion Mining of Patient Health Care Experience

WAC (Web based life, Analysis and Cloud) s the data system that produces a seamless information spreading quicker that is bigger than a Big data. The huge amount of data derived from this humongous volume of information, so called Big data, demands the advancement of a proficient and viable choice with emotionally ground-breaking supportive network schemes in the region of healthcare. The pool of data could be investigated in a manner to assist the framework that more likely comprehend its partner requirements by gathering, mining conclusions on each subject of premium. Preciously administration might be able to acknowledge the crucial decision making process where the new investigations would be accounted for different research avenues. There is a tire need for review every break down and assess research outcomes of crosswise over writing that encouraged us to distinguish existing patterns, potential headings of the future work within the space. This article is going to deal with detailed review of existing research works proposed in the field of opinion mining for healthcare sector.
Tunneling-based CMOS Floating Gate Synapse for Low Power Spike Timing Dependent Plasticity

We propose a CMOS architecture for spiking neural networks with permanent memory and online learning. It uses a three-transistors synapse with a floating node that stores the synaptic weight, programmed by using only Fowler-Nordheim tunneling current in the pA range for ultra-low power operation. A neuron with a conditioning circuit programs the floating gate synapse following the spike timing dependent plasticity rule. Simulations using a standard 150 nm CMOS process show the online learning capabilities of the architecture.
Performance of Various Algorithms to Reduce the Number of Transmitted Packets by Sensor Nodes in Wireless Sensor Network

Energy consumption is an important issue in the Wireless Sensor Network (WSN). Reducing the number of transmission packet messages by sensor nodes is the most common solutions to save the node battery. Therefore, the main contribution of this paper is to study the performances of different algorithms that can reduce the number of data packets transmitted by sensor nodes within the WSN. The selected algorithms in this study are Move Average (MA) algorithm, Autoregressive all-pole model parameters - Burg's algorithm. (AR-B), Autoregressive all-pole model parameters - Yule-Walker algorithm (AR-YW) and an Efficient Data Collection and Dissemination Algorithm (EDCD1). The performance comparison shows that the on the basis of reduction in the data packet transmissions from the source to the sink, EDCD1 algorithm shows the maximum reduction of 92% while a minimum reduction of 23% is shown in case of MA and the reduction of AR-B and AR-YW are 58% and 56, respectively. Moreover, in terms of the absolute error in the data at the sink, the EDCD1 algorithm shows the best performance with a less average error at 2.2803 for all sensors compared to other algorithms.