Miracle-dz/UniFAR-FTUs huggingface dataset:
A Unified Convolutional Neural Network Framework for Intelligent Decision Making Related to Navigation

Prevalent intellective systems assist the driver in the navigation errands by taking some simple and intricate decisions based upon available input information. Such decisions should be astute and prompt to provide realistic behaviour in real-life navigation scenarios decisions. Proposed unified Convolutional Neural Network framework presents a novel approach for better performance of navigation related autonomous systems.The suggested work is an extension to authors previous work in which best input features for decision making neural network were obtained by shortlisting eleven texture metrics out of thirty-six metrics using state of art algorithmsUnification of Best Feature Selection Method (our previous work) and Principal Component Analysis Technique was done to find out the most pertinent neural network inputs. CNN framework has been used here to provide a simple decision that is either to move or stop at a particular instant based on finalized inputs. It was found that the collective inputs of unified model yield better results in conjunction with CNN framework. The model outperforms our previous model and PCA Furthermore, it was observed that CNN framework can perform equally well with minimal training in comparison to high order training. It implies CNN’s has remarkable ability to learn from imprecise data gives it an edge over others. In nutshell, the proposed model was able to decide promptly and astutely the next move of vehicle.
Framework for National Highway Review System

The long clean road can give the best travel experience. The main problem that is faced by the road users is that if there is any complains that they want to inform the management they cannot stop by the tollbooth and make their complains there because the booth will always be busy with rushing vehicles and the workers there don't have the time or the This paper focuses on the highway review system and how it enhances the interest of the road users and the highway authority. The goal is to attain tranquillity and transparency among users. Crowding of tollbooths is extensively observed, this process can be waste of fuel and time. Ultimately, refining customer satisfaction while receiving valuable feedback because at the end of the day people choose to commute via a national highway for serenity and its comfort. Mainly the tollbooths are setup for the fee collections from the users for the roads that are constructed and maintained by the companies but the main problem that is faced by the users such as people driving cars, buses, trucks, and bikes is that if there any complaints that they wants to inform the management they cannot stop by the tollbooths and make their complaints. Because the booth will always be busy with rushing vehicles and workers won't have any time to stop the work and get the complaint and review from the user and this is the main dissatisfaction problem faced in it by the user. Therefore, instead of stopping near tollbooth and make complaints to the toll workers who don't have patience and time. Therefore, this tollbooth review system a mobile application helps the user to register in it and give review and register complaints about the road and highways which they use, by this both the user and the toll workers save time.
IoT based Agri Soil Maintenance Through Micro-Nutrients and Protection of Crops from Excess Water

Internet of Things is being used in Smart Agriculture, generally for irrigation purpose. Here, for managing the water log in farmland, IoT is used. The soil moisture in the farmland is monitored using the soil moisture sensor. When the moisture level reaches a particular point, the Cloud Service Brokerage commands the relay to switch ON the suction motor. The suction motor takes out the excess water from the farmland. Our objective with this proposal is to manage the excess water log in the farmland and analyse the availability of micronutrients using IoT. This water managing system is semi-automated in which the system can work on its own or be controlled using a mobile application. Using the DHT sensor readings, the weather at that specific location can be analysed and it can be predicted for the next 10 days with the use of a prediction algorithm. IoT is the concept of connecting all the devices to the Internet and allowing them to communicate with each other over the internet. IoT is a huge network of connected devices – all of which gather and share data about how they are used and the environments in which they are operated. IoT is an application of modern Information and Communication Technologies into agriculture. Sensors are used to build a crop monitoring system. This can be monitored using a mobile application. The application is used to monitor and control the motor switch.
Bandwidth, Power and Trajectory Optimization for UAV Base Station Networks With Backhaul and User QoS Constraints

This paper considers an unmanned aerial vehicle (UAV) base station (BS) network with delay-sensitive users and delay-tolerant users on the ground, which have different quality-of-service (QoS) requirements. In the network, the backhaul link connecting the backhaul gateway and the UAV-BS shares the same spectrum with the data links connecting the UAV-BS and the users due to spectrum scarcity. To improve the rate performance of the delay-tolerant users and to guarantee the QoS of the delay-sensitive users, we aim to maximize the minimum rate of the delay-tolerant users by jointly optimizing the bandwidths of the backhaul link and the data links, the transmit power allocated to different users and the trajectory of the UAV-BS, subject to the constraints on UAV mobility, total bandwidth, total transmit power, backhaul data rate, and minimum rate requirements of the delay-sensitive users. Although the formulated problem is non-convex and difficult to solve optimally, we propose an efficient algorithm to find a suboptimal solution to it. Simulation results show that the proposed joint optimization algorithm achieves significantly higher minimum user rate than the benchmark schemes.
Design and Implementation of Secure Transmission on Internet of Drones

Unmanned Aerial Vehicle (UAV) or commonly referred as drone, is a commercial product that is very wellknown to be used in various application, has led scientists to examine the function of drones to maximize their function. Therefore, the architecture of the Internet of Drones (IoD) was created. However, there have been several attacks on the communication protocol so it can be said that these deficiencies can be detrimental to many parties. Authentication and encryption are used to secure transmissions on IoD. In this research, a transmission system that is secure from eavesdropping, hijacking, and DDoS was built. The research was conducted using the SDLC methodology using a prototyping approach. Based on the tests conducted, the system built is resistant to eavesdropping, hijacking, and DDoS attacks with 100% result of security tests.
56Gbps PAM4 SerDes Link Parameter Optimization for Improved Post-FEC BER

For 56G, as well as 112G, PAM4 systems, it is no longer feasible to rely on SerDes equalization alone to achieve the desired BER performance. FEC (forward error correction) becomes mandatory to enhance the SerDes to achieve the post-FEC BER target (e.g., 1E-15). The key takeaway from this paper is that the optimized SerDes equalization settings, particularly the TX settings, i.e., FIR and swing, could be rather different with and without FEC. It is shown that lower pre-FEC BER does not necessarily imply lower post-FEC BER.
Use of Virtual 3D-Model for the Assessment of Premaxilla Position in 3-4-Year-Olds with Complete Bilateral Cleft Lip and Palate – A Pilot Study

This paper considers the results of virtual three-dimensional (3D) model use for the assessment of premaxilla position in 3-4-year-olds with complete bilateral cleft lip and palate (CBCLP) after primary cleft lip and palate repair. The use of 3D models allows measuring premaxilla size, protrusion and deviation. On the basis of measuring 3D full-arch jaw models before and after orthodontic treatment we distinguished 3 degrees of premaxilla deviation which may be useful for treatment planning and the prognosis of treatment outcomes. The children and their parents had good compliance with the use of intraoral scanning. Reviewing the literature we found the use of this method in newborns with clefts in order to manufacture a plate for pre-surgical orthopedics. However, we did not find any data of using this method to evaluate the result of surgical treatment in children with protruding premaxilla to determine the next stage of complex treatment. Compared to traditional cast and plastic model measuring, digital technology has many advantages: it is friendlier for children, more simple, needs less time and no materials for dental casts and plastic models, no storage space. There are no significant differences between manual and digital measuring of jaw models. Intraoral scanning and virtual 3D models may be successfully used for the assessment of premaxilla position in young children with CBCLP, which allows to asses surgical results and to choose the kind of orthodontic treatment.
Design and Evaluation of WriteBetter: A Corpus-Based Writing Assistant

Corpus-based writing assistants are aimed to show how words are used in real context: they provide word use examples from which users can (1) draw inspiration for their writing and (2) understand how words are used together to improve their own writing. Although the idea of integrating a corpus-based writing assistant (concordancer) into word processors is not new, their integration is designed to be not as straightforward as writing in a word processor. In this paper, we present WriteBetter, a corpus-based writing assistant designed to be integrated into Microsoft Word, Google Docs, and Overleaf. This integration makes its use straightforward and easy as users can see corpus-based examples (1) in real-time while writing in the word processor or (2) just selecting a piece of text in their document. This facilitates user-corpus interaction as the required user’s interaction is minimal. After contextualising the state of the art regarding the benefits of corpus-consultation, we discuss the design features of WriteBetter that make it novel in relation to other tools. Next, we present a user evaluation of the first version of WriteBetter, which was carried out on 11 undergraduate students of a Chilean university, who were asked to trial the software while writing in English. Based on this evaluation, we designed a new version of WriteBetter, which was further evaluated online on 36 users. WriteBetter is now available for everyone as SaaS.
Compositional Engineering for Compact Perovskite Absorber Fabrication Toward Efficient Photovoltaics

The compactness of perovskite active layers plays an essential role in the energy conversion. In order to promote the crystal quality, poly(allylamine hydrochloride) (PAH) was employed as an additive to promote the crystal quality for the active layers. The cationic additive significantly enhanced the compactness of the perovskite absorber film, which promoted the charge transport efficiency, resulting in an average efficiency over 19%. The unique properties of PAH make it act as a “glue” to link the grain boundaries and promote the crystal quality, thus favoring the charge transfer and suppressing the recombination under the certain doping amount. Meanwhile, the stability of perovskite solar cells in humidity environments was dramatically promoted without encapsulation. The sample has a long shelf life (over 600 h). This strategy can also be used to guide the crystal development of other optoelectronic devices, such as light-emitting diodes and lasers, which have recently involved the hybrid perovskite materials.
A Printed Monopole Antenna with Radiation Pattern Reconfiguration

This paper presents the design and analysis of a pattern reconfigurable monopole antenna intended for WLAN applications. A parasitic element that is connected to the ground plane by a PIN diode is placed parallel to the radiating monopole. When the diode is switched between the ON and OFF states, the function of the parasitic element changes from a reflector to a director, thus offering the capability to control the direction of the main beam. The two states of the reconfigurable antenna can also be changed at the initial design stage by choosing the distance between the monopole and the parasitic element. The simulations using the CST software proved the feasibility of the proposed antenna.
Chaotic Inertia Weight Particle Swarm Optimization (CIWPSO): An Efficient Technique for Solar Cell Parameter Estimation

Solar cell modeling and optimal estimation of their associated parameters is a key point to improve performance of PV solar system. Recently, different numerical, analytical and hybrid approaches have been developed for parameter extraction of PV model. In this paper the Chaotic Inertia Weight Particle Swarm Optimization (CIWPSO) technique is proposed to estimate PV parameters of single and double diode. Furthermore, the Newton Raphson method (NRM) is employed to guide the fitness indicator towards optimal solution. The propose approach solves the premature convergence problem of the conventional PSO. This new approach is implemented on RTC France Silicon Solar cell, under standard test conditions (STC). CIWPSO has ability to find optimal solution with the requirement of relatively less computational time and number of iterations. The validity of results clearly supports the statement that, the proposed approach is highly accurate, efficient and fast for parameter estimation of PV cells.
A Single-Phase Switched-Boost Inverter for Photovoltaic System

A single-phase switched-boost inverter for photovoltaic (PV) application is introduced in this paper. Shoot-through immunity, buck/boost voltages, continuous input current and single-stage conversion are the benefits of the proposed inverter. PV panel output voltage depends upon the weather conditions. Sometimes the output voltage of the PV panel is less. Therefore, we need boost inverter to get the desired voltage to the load. In addition, the proposed inverter has acceptance for wide range of supply voltage variations. In comparison with quasi Z-source inverter (qZSI), the proposed inverter requires one less inductor. The operating principles, control strategy, comparison with qZSI and simulation results are discussed. The simulation results match the theoretical analysis.
Institutional Collaboration and Competition in Artificial Intelligence

The institutional collaboration and competition in academia have benefited the development of science, with inter-institutional scientific work promoting the exchange of ideas and competing fields developing rapidly. However, understanding of how the institutions collaborate and compete in science is sorely lacking, especially in emerging fields. Artificial intelligence is such a booming field currently, changing the way we live and work daily. To illustrate the problem, we try to reveal the evolution of institutional collaboration and competition in artificial intelligence by applying AI 2000 from the perspective of Science of Science. In this paper, we make multiple multidimensional statistical analyses by scrutinizing the collaboration network, research interests, talent flow, etc. We demonstrate the collaboration evolution in this field and find the advantage of inter-institutional collaboration is growing over time for papers that have been published more than 5 years. We discover the common cooperation modes of top institutions and visualize their closer cooperation. We highlight the critical resources competition among institutions in three dimensions and learn the recent trends in the field. In particular, we are concerned about the competition among institutions for cross-industry cooperation and notice the consistency of competitiveness and cross-industry collaboration. The research of this paper may support further research studies on institutional collaboration and competition as well as policy proposals for promoting scientific innovation, research management, and funding.
Morphological, Texture, and Color Feature Analysis for Erythrocyte Classification in Thalassemia Cases

Abnormal erythrocytes have diverse shapes. The appearance of specific erythrocyte shapes in a person’s blood can indicate certain diseases, including thalassemia. We used thalassemia peripheral blood smear images and applied a segmentation process to produce single erythrocyte sub-images. Each erythrocyte has a unique shape. The selection of appropriate features to represent erythrocytes is critical for classification accuracy. We used morphological features such as moment invariants, geometry parameters of the cell and central pallor, and distance angle signature (DAS) morphological features of the cell and central pallor. We combined morphological features with texture and color features to increase the accuracy of erythrocyte classification. In this study, the multi-layer perceptron is used to classify nine shapes of erythrocytes present in thalassemia cases. The experimental results of 7108 erythrocytes indicated an accuracy of 98.11% based on the combination of features. The experimental results also show that the combination of features we proposed produced higher classification accuracy than previous work, which yielded an accuracy of 93.77%.
NeuronFlow: A Hybrid Neuromorphic – Dataflow Processor Architecture for AI Workloads

We present a novel computing architecture which combines the event-based and compute-in-network principles of neuromorphic computing with a traditional dataflow architecture. The result is a fine-grained dynamic dataflow system which avoids the coding issues intrinsic to spiking systems, and is suitable for both procedural workload and deep neural network (DNN) inference. The architecture is particularly suitable for computation of sparse CNNs and low-latency applications. We present results from GrAIOne, the first chip designed using the NeuronFlow architecture, which has 200 704 neurons implemented in a 28nm HPC + process.
Statistical Approach Based Detection of Distributed Denial of Service Attack in a Software Defined Network

Distributed Denial of Service (DDoS) attack is one of the rapidly growing attack that threat the networks to disrupt the network services available to the intended users. The attack is executed by the perpetrator, who creates a malicious data packets and penetrates it into the normal traffic of the targeted network, thereby disrupting the service which is one of the types of botnet attack. DDoS attacks commonly occur in Software Defined Network (SDN) rather than conventional and ad hoc networks. Since the SDN has a centralized control plane which is completely software-based, the perpetrator overload the controller by sending more attack packets to it thereby resulting in a single point of failure. Due to the periodical changes in the fundamental architecture and the physical separation of forwarding plane from the control plane, the SDN becomes more vulnerable to the DDoS attacks. The usage of entropy is proposed to detect DDoS attacks in the existing methods. The proposed method determines the mean entropy using statistical approach and the rate of packet drops to identify the occurrence of DDoS attack at its early stage to prevent the controller from overloading and thus leading to a failure.
A Detailed Investigation on Reduction of False Positive Rate in Breast Cancer Detection

Breast cancer is known as the most common form of cancer in Indian women and is about 14% of woman cancer. Thus a detailed investigation is done to improve the level of screening mechanisms and accuracy of breast cancer detection in Computer Aided Diagnosis system. The initial level of screening of breast can be performed using thermography and then the suggestions can be provided for necessity of further screening using mammography for cancer detection. If the presence of breast cancer is confirmed using mammograms, to address the high false positive rate with mammograms, the same patient can be examined again with biopsy images for further confirmation of the presence of breast cancer. Thus a detailed investigation on employability of various modalities for the breast cancer uncovering is conducted to minimize the false positive rate in breast cancer detection.
An improved feature extractor for the Lidar Odometry and Mapping (LOAM) algorithm

This work proposes an improved feature extractor for the Lidar Odometry and Mapping (LOAM) algorithm, which is currently the highest ranked algorithm in the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) visual odometry ranking. This article proposes and justifies the substitution of LOAM's current feature extraction method with the Curvature Scale Space (CSS) based feature extraction algorithm for the processing of 3D Point Cloud Data (PCD). The justification is based on in improvement of the repeatability of the detection of robust features for LOAM and an improvement in the associated computational cost. The LOAM's feature extractor and CSS feature extractor were tested and compared with simulated and real data including the KITTI visual odometry dataset using the Optimal Sub-Pattern Assignment (OSPA) and Absolute Trajectory Error (ATE) metrics. The results showed that LOAM based on the CSS feature extractor out performed that based on the original LOAM feature extractor with respect to these metrics.
A Design of Outdoor Display Monitoring System Based on NB-IoT

In recent years, the advertising industry and the media industry have developed rapidly, and the use of outdoor LED screens has also increased dramatically. But there is no open system for unified management of outdoor LED display. As a result, the way through maintenance personnel check the equipment waste a lot of laboring. Therefore, this paper proposes a monitoring system for outdoor LED display based on NB-IoT technology to overcome laboring wasting, the basic information management of outdoor LED display, and the unified remote operation of task management, which provides convenience for outdoor equipment maintenance and other services. In our scheme, the narrow band Internet module is combined with the outdoor LED display as the terminal, and then the detection results are transferred to the open platform through the NB-IoT module, and the monitoring information is viewed at the APP.
Formation, structural and morphological characteristics and some features of electrodes charge transfer of lithium-ion batteries based on ZnO/NiO nanosystems

The paper describes a new method of ZnO/NiO nanosystems formation consisting of Zn vapors condensation under conditions of self-organization of small steady state supersaturations, oxidation of the obtained three-dimensional porous Zn structures in air and subsequent deposition of NiO film on ZnO nanosystems. It is shown, that charge transfer in ZnO/NiO nanosystems is determined by their fractal-percolation characteristics, which are based on the formation of RC – circuits.
A Review on Hybrid Energy Storage Systems in Microgrids

Energy storages have numerous benefits, for instance, improvement of generation and demand balance, power quality and intermittency of renewable resources. Presently, available energy storage systems (ESS) are inadequate to achieve the desired applications on their own. Hybrid energy storage systems (HESSs) are featured by the combination of two or more energy storage technologies to accomplish the desired results. This paper gives an overview of HESSs applications in microgrids (MGs). Initially, benefits and applications of hybridization have been discussed. Then, a brief comparison of capacity sizing for HESSs is presented. The reviewed methodologies have significant implication in defining HESS capacity in MGs, while considering several constraints such as storage life span, cost and efficiency.