Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Machine Learning Based Big Data Analytics

Information investigation includes the procedure of information assortment, information examination, and report age. Information mining work process instruments as a rule coordinate this procedure. The information examination step right now comprises a progression of AI calculations. There exists an assortment of information mining apparatuses and AI calculations. Each device or calculation has its own arrangement of highlights that become variables to influence both practical and nonfunctional characteristics of the arrangement of information examination. Inside the ICT area, as in a few distinct segments of examination and exchange, stages and devices are being served and created to help experts to treat their insight and gain from it naturally. A large portion of these stages come back from enormous firms like Google or Microsoft, or from hatcheries at the Apache Foundation. This audit clarifies Machine learning Algorithms in Big information Analytics, and AI moves us to take choices where there is no known "right way" for the particular issue dependent on past exercises and counts a portion of the first utilized instruments for investigating and demonstrating huge information. This paper endeavors to recognize the prerequisite and the improvement of AI based portable enormous information (MBD) investigation through talking about the bits of knowledge of difficulties in the versatile huge information. Moreover, it audits the best in class uses of information examination in the territory of MBD. Initially, we present the improvement of MBD.
Tracking and Classification of Moving Vehicles from a Traffic Video

According to the development of the monitor system, detection and classification are the major areas of interest within the field of computer vision, in recent year. Vehicle detection, tracking, and classification are applied in several applications such as security and surveillance, traffic monitoring, and car parking. However, the performance of the traditional method is adversely affected under certain conditions like to lighting condition, occlusion, and camera position. Recent remarkable developments of deep learning have led to a renewed interest in tracking and classification. In this paper, we evaluate recent research and traditional method into the tracking and classification of vehicles in a traffic video. In the traditional method, we present technologies such as background subtraction, Pixel Connectivity, and Connected Components Labeling to detect and track moving vehicles. Besides, an algorithm was implemented to improve motion speed. After that, the vehicles are classified by shape-based feature. In the next method, a vehicle type tracking and classification system based on deep learning are proposed. Particularly, this system uses You Only Look Once (YOLO) which is a commonly used method for tracking and classification of vehicles from video. The experimental on GRAM-RTM dataset showed the accuracy of methods in the different type of vehicles.
Ethical Concerns and Solutions in Health Internet of Things

Nowadays, Internet of Things (IoT) devices and applications are largely and successfully used in almost every human activity. Together with smart cities and industrial IoT, one of the top three sectors with a notable estimated growth in the years to come is Health Internet of Things (HIoT). Due to obvious benefits as faster response and better functioning of medical devices, remote diagnosis and treatment, continuous monitoring of patients with implanted devices, better support for clinical decisions, and lower costs, IoT is becoming increasingly relevant in the context of health-care and medical applications. In order to provide these advantages, interconnected patient and hospital IoT devices collect, transmit and process significant amounts of sensitive data. Problems as the lack of transparency in the use of data and contextual metadata, weak security methods implemented in medical devices, probability of human errors and software or hardware malfunctions, autonomous, ambiguous and unpredictable behaviour of the interconnected things expose both the health institutions and their clients to significant risks, from harming the privacy of patients to actual health damage. In this spirit, the paper reviews the ethical and security-related concerns in health-IoT and suggests solutions to present and future challenges.
Optimization of an Automated Examination Generation System Using Hybrid Recurrent Neural Network

Globally, there has been a drastic increase in student-teacher ratio, over the years, which has led to the popularity of the digital examination system over classrooms, which is also eco-friendly. As a result, various new challenges have occurred due to the digitization of online education systems – for those who are not well versed with the technology, and for tracking malpractices. This issue can be acknowledged by automated examination question generation that will generate a unique exam. Using Recurrent Neural Network (RNN) models, the questions can be generated, however, the commonly used models – like, the simple RNN model, the bidirectional RNN model, the RNN model with embeddings and the encoder-decoder RNN model – do not provide high accuracies. This work proposes a hybridized RNN model that incorporates multiple layers of these commonly used RNN models, in a specific order, creating an optimized model that will be able to generate questions with higher accuracy. Additionally, this work also compares the performances of the regular RNN models with that of the hybrid model, to uphold the optimality of the system in terms of several widely accepted accuracy metrices like – precision score, recall score, F1 score, specificity score and sensitivity score. This work shows the output that can be expected from this model using a dummy data with a corpus prepared from a random online source. This system can be used in many domains ranging from offline academic areas to Massive Open Online Courses (MOOCs), and can be modified as required.
Study on Different Transmission Control Protocols Used in Wireless Networks

Conventional TCP protocols treat all packet misfortune as an indication of congestion. Their powerlessness to perceive non-congestion related packet misfortune affects the communication efficiency in the remote networks. As of late proposed protocols, for example, Freeze-TCP, TCP-Probing, TCP Westwood, TCP Veno, TCP-Jersey, and JTCP, all improve over the conventional TCP protocols. This paper reports a quantitative examination of ongoing protocols against the right now frequently utilized to be specific, TCP SACK, TCP New Reno, and TCP Vegas. Reproduction tests were intended for different network formats and with varying outside impedances trying to recreate real situations most precisely. To complete these examinations, the presentation of every convention was estimated dependent on three benchmark measurements: throughput, normal congestion window, and time to finish a file transfer.
Application of Green Communication in Energysaving Transmissions of Ofdma Based Multicarrier Base Stations

Green communication technology provides energy saving implementation of mobile-communication network in the fast growing scenario of digital communication. In the scenario of advanced mobile technology, we utilize more than one component carrier (CC) can now be combinely utilized in a cellular base station (BS). Power consumption at the cellular base station has become an important problem in mobile wireless communication. In this paper, we propose a novel green rate and power control method is proposed for base station to solve the problem of power, power minimization at the cellular-base station transceiver with consideration of quality of service (QoS) and fairness requirements of all cellular users. We used orthogonal space time block code (OSTBC) component carrier for down-link transmission of the base station. Simulation results represent that proposed scheme for providing better energy saving as compared to other energy-saving schemes.
Influence of Electric Loading and Rotor Speed on the Performance of Permanent Magnet Machines

The impact of electric loading such as current, copper loss and current density as well as the effect of rotor speed on the performance of double stator (DS) permanent magnet (PM) machines are analyzed and presented in this work. MAXWELL-2D software package is used in predicting the results. The investigated machine variables include: phase flux-linkage, induced phase voltage, average torque, torque ripple, total harmonic distortion, losses and efficiency. The analysis shows that most of the machines’ output performances are principally dependent on both the operating speed and loading conditions; though, the average torque and phase flux-linkage is fairly insensitive to change in speed.
Implementation on Text Classification Using Bag of Words Model

Bag of words provides one way to deal with text representation and apply it to a standard type of text arrangement. This method depends on the idea of Bag-of-Words (BOW) that measures the content which is accessible from Wikipedia, Kaggle, Gmail and so on. The proposed method is utilized to create a Vector Space Model, which truly sustained into a Support Vector Machine classifier. This is to arrange and gathering of document records that are publically accessible datasets through social media. The text results demonstrate the examination between the raw information and the clean information that is viewed on the word cloud.
Optimization of Spec Sensing with Estimated Information for CRN

In the cognitive radio networks corresponding amount of traffic rapidly expanding, sensing and interference spectrum management on a finite number of possibly unoccupied channels over available whitespace on radio spectrum is the one of the extensive issue. Database estimated information by real time sensing with geolocation to enhance resolution accurately occupancy over a wide frequency bands occupied by primary user. Proposed develop cooperative sensing algorithm sequential optimal at even low signal noise ratio region. Estimated information ensuring disclosure accurate experimental results on simulated, proposed method improves the sensing sensitivity enhanced to previous work with low complexity and limited amount interference.
Inclined Slotted Waveguide Antenna Design

Waveguide antennas are the most powerful tool of Radar system. Slotted Waveguide antennas have been very popular from last two decades. Slotted Waveguide antennas are preferred for Radar System. Maritime Radar &amp; aircraft radar system completely depends on the performance of Slotted Waveguide Antenna Lots of work have been done for the design of Planar arrays but very few are available for Slotted Waveguide. By Changing the position &amp; inclination of the slot optimum gain can be achieved. A prototype microwave slotted designed waveguide antenna will be fabricated and tested to get the design results in accordance with the simulation. The purpose of research paper is to give an objective WaveguideTechnology.
Simulation of 6T and 8T SRAM Cell with Power Dissipation Analysis

Reducing the power consumption in a VLSI circuits is a prime concern now a days. Memory circuits plays an important role in the design of electronic small power devices. Almost every digital systems is having memory as an important part in their design. The high speed circuits dissipate a considerable amount of power in a short time. In this paper conventional SRAM cell is modified little bit to reduce the dynamic power dissipation. The overall capacitance reduced by adding few extra transistors. Because of the fact that charging and the discharging of the bit lines consumes the most power , so 6T cell and 8T cell can be used to reduce the power by adding an extra number of transistors to the pull down path. In this paper 6T SRAM cell as well as 8T SRAM cell simulated and their performance compared in terms of power dissipation.
Arduino Microcontroller Based Underground Cable Fault Distance Locator

The growing concern for safety and infrastructural proliferations in the densely populated urban and suburban areas as well as the quest to preserve the aesthetic values in many modern localities have necessitated the need for underground installations. The underground cabling installations are devoid of faults common to the overhead transmission lines but are associated with certain kinds of faults such as short circuit and open circuit faults. Locating the exact position of any of these kinds of faults is very exhausting, costly and time-consuming because its power distribution system is invisible. Hence, a microcontroller based underground cable fault distance locator powered by Arduino is designed to detect and pinpoint location of faults in underground cable lines. A basic ohm’s law is employed to achieve the variation of current with respect to resistance that determines the position of the fault. This device has a power supply unit, cable unit, control unit, tripping unit and display unit. The power supply unit provides power to the other components. The cable unit consists of a three-phase cabling system with switches between each phase to activate faults. The control unit takes in signals from the cable unit to cause control of tripping unit and display unit. The tripping unit then detects the phase which encounters the fault and the display unit shows the fault characteristics on the LCD. The distance to the fault is displayed, alongside the phase which encounters the fault for easy clearance.
Big and Stream Data Analytics Using Incremental MapReduce Framework for Smart City

Smart city explores the Internet of Things (IoT) to administrate the voluminous, continuous and variety of data produced by the various sensors and digital devices. Smart services build the analytical models over the batch or stream data which can help in periodic or near real-time decision making. Machine Learning and Deep Learning models can be exploited to extract the hidden knowledge. However, voluminous and stream data demands the huge computation. MapReduce, a distributed processing framework, can effectively and efficiently handle the voluminous data with fault-tolerance. However, it is not effectual for real time analytics as MapReduce phases such as Map, Sort/Shuffle and Reduce are dependent on disk I/O which incurs the high latency. In order to address these challenges, voluminous and stream data can be processed incrementally by exploiting the MapReduce framework over the cluster of commodity hardware. This paper presents primary reference architecture for smart city having the capability of batch and stream processing. MapReduce processes the batches of data which is accumulated over a time for periodic analysis, and incremental MapReduce processes the recent batches of stream data for real-time analysis. Proposed Incremental MapReduce architecture exploits the in-memory buffers to reduce the latency incurred due to disk I/O. It also replaces the sort-merge architecture of MapReduce with hash based architecture which reduces the CPU cycles to support stream data processing.
Visualizing Road Damage by Monitoring System in Cloud

Cloud computing gives many beneficial services to share large scale of information, storage resources, computing resources, and provide knowledge for research. In this paper, I have proposed the methodology for visualizing the road damage condition by monitoring and detecting the road damage and specifying the location of the damage by which others can prevent from accident response. In the proposed system is about the visualizing road damages using cloud database. That is we need some prevention by monitoring ‘road damage’ using mobiles. To find the road damage, the roads are monitored and the snapshots are taken. The snapshot images are then processed in the application developed without internet. The information details about the road damage will be sent to the cloud. Then the cloud stores that information in the database. This information is very helpful in visualizin groad damage locations to the users. Different maps are developed for different kinds of users based on the above gathered information. There are three types of users involved. They are Vehicle Users, Corporation Users and Administration Users. The Vehicle user gets the visualized map of the specified road damage on the path between the source and destination. The Corporation user visualizes the road map for damaged locations in a specified area. The Administration user visualizes the map of the Client broker locations in a specified area.
LPWAN Technologies for IoT Deployment

Nowadays, with the increase in the number of factories and production units being automized with IoT. The need for LPWAN networks is required as the deployment of IoT based LPWA networks allow for remote access of different end nodes. This paper shows that Sigfox is useful in applications that require long-range communication, whereas NB-IoT is useful in applications that require massive data to be transferred. It is shown that each technology is equally crucial for LPWAN deployment, as each protocol comes with its advantages and disadvantages.
Fatigue Properties of Ti-6al-4v Gyroid Graded Lattice Structures in Comparison with Uniform Counterparts Fabricated by Selective Laser Melting

Graded lattice structures (GLSs) have drawn much attention in engineering and biological areas due to the enhanced mechanical properties and energy absorption capacity that benefited from the graded porosity design. The aim of this study is to investigate the effect of gradient on fatigue behaviours of lattice structures. A GLS consisted of the Gyroid unit cell, one of the triply periodic minimal surface structures, was designed with continuously varied porosity from 60% to 90%. Uniaxial compressive testing and compression-compression fatigue testing were conducted on the Ti-6Al-4V Gyroid lattice structures with both uniform and graded porosity fabricated by selective laser melting. All three typical fracture modes and mixed fracture modes were all observed on the fracture surfaces of struts after fatigue testing. The fatigue life of Gyroid GLSs is 1.21~1.67 times that of uniform counterparts with an identical overall porosity. The enhancement mechanism on fatigue properties coming from gradient design is elaborated through finite element analysis and experimental characterization. The lower level of tensile stress, bigger macro-area and micro-plastic zone on the strut surface of the main loading-bearing constituent of Gyroid GLS relieve the stress concentration around the crack tip, thus, lower the crack propagation rate and provide stronger fatigue crack resistance. Furthermore, the struts in the main loading-bearing constituent are more prone to stretching, therefore, provide long-term carrying capacity even after the occurrence of penetrating cracks. Experiment results show that the carrying capacity can be still provided by these struts even with penetrating cracks.
Information Security using Data Science: A Critical Assessment

Data science has been displayed as a general way to deal with absolutely access and control security. Data security is along these lines a powerless theory in light of the fact that an absence of approval and examination between such strategies against observational data. This paper fundamentally reviews past work on data security and afterward the utilization of data science for data security. Moreover, numerous presumptions in formal treatments are not exactly all around upheld in operational security and have been received from different fields. Various risks are available with relying upon quantitative techniques with constrained or no approval.
Atomistic Origin of High-Concentration Ce 3+ in {100}-Faceted Cr-Doped CeO 2 Nanocrystals

Improving the potential of promising CeO<sub>2</sub>-based nanocatalysts in practical applications requires an atomic-scale analysis of the effects of active dopants on the distribution of Ce valence states and the formation of oxygen vacancies (Vos). In this study, a Cr dopant is introduced into the cubic {100}-faceted CeO<sub>2</sub> nanocrystals (NCs) with an average size of 7.8 nm via supercritical water. The Cr dopants substitute Ce sites in the amount of approximately 3 mol%. Based on the aberration-corrected STEM-EELS, the effects of Cr dopant on the distribution of cation valence states in the Cr-doped CeO<sub>2</sub> NCs are investigated layer by layer across the ultrafine Cr-doped CeO<sub>2</sub> NC perpendicular to the {100} exposed facet. It is found that an increased amount of Ce<sup>3</sup>+ cations is present in Cr-doped CeO<sub>2</sub> NCs, particularly in the internal atomic layers, compared to the non-doped CeO<sub>2</sub> NCs. The atomic-scale analysis of the local structure combined with theoretical calculations demonstrates that Cr dopant reduces the formation energy of Vos and increases mobility of oxygen atoms for the nano-sized CeO<sub>2</sub>. These effects, in principle, result in an improved oxygen storage capacity and provide a fundamental understanding of role of the dopant in the formation and distribution of VOs in the doped CeO<sub>2</sub> NCs.
Changes in Customer Service Approach, Ecosystem and New Trends in Customer Service

Globally companies are going through turbulence on customer service models, which model is best fit mode to deliver the customer service and where to invest in new technologies on customer service. Customers are moving towards digital platform, companies are finding it difficult to balance the digital and non-digital mode of customer service. There are many factors which affects the customer service e.g. cost of fuel which affects the cost of travel and subsequently results in spike in cost of customer service. On other side cost of mobile / data offers which reduces the cost of accessibility of digital platforms results in lowering the cost of service. This presentation covers traditional ways of customer service, how changes in eco system are helping new ways of customer service, case studies and its impact.
Impact of Solar Water Heaters Systems on the Environment Case Study in Morocco

Solar water heaters are starting to be considerably used by Moroccan citizens for domestic purposes. It has been considered to be a beneficial solution to efficiently decrease energy bills, especially that the majority of Moroccan cities have a high potential in solar radiations. This paper presents an overview of the impact of solar water heaters on the environment. This includes the thermal performance, the life cycle analysis and the potential benefits of these solar systems on the environment. Furthermore, the paper includes a case study in Morocco, in which an environmental impact assessment is presented. A thermal analysis of the performance of a solar water heater system installed for domestic use to satisfy the hot water needs of a family composed of five members is studied. The results show that by using solar energy, considerable amounts of greenhouse polluting gases are avoided. For the case of this domestic water heating system, the energy saving, compared to a conventional system, is about 75%, with electricity back up. Moreover, the energy needed to construct the solar water heater is recuperated in about 13 months. Therefore, it can be concluded that the solar systems are environment friendly alternatives to conventional energy sources and should be massively used whenever possible to protect the environment and ensure sustainability.