bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of fish, poultry, feeds and sediments using NAA for assessment of arsenic and chromium contamination
Authors: Shahnur Alam K M , Hossain S M , Naher K , Islam M A , Khan M R , Das S , Akramuzzaman M M
Published: January 2021

In this study, a systematic analysis of fresh and sea water fishes, poultry and their feeds and sediments was conducted using research reactor based neutron activation analysis (NAA) technique with the aim to determine elemental status with special emphasis on arsenic and chromium contamination. Sixty nine samples in different categories (fresh water fishes from three ponds, and corresponding sediments, sea water fishes from Bay of Bengal, chicken from five farms, their feeds) were analyzed through a series of NAA experiments to determine the translocations of toxic elements from feed to fish, sediments and birds and their excretion through litters. The analytical results revealed that some of the locally produced feeds for poultry and fish are highly contaminated with chromium. The flesh of both the fresh water fish and poultry are free from arsenic contamination. The sea fish contains high arsenic concentration. However, the major form of seafood arsenic as arsenobetaine that is completely harmless and its occurrence in seafood presented no human health concerns. The present study will certainly help to the Food Controlling Authority in Bangladesh to produce fish and poultry in a controlled sustainable manner and will also create public awareness.
A first-principles study of a new ternary silicide superconductor Li2IrSi3†
Authors: Hadi M A , Alam M A , Roknuzzaman M , Nasir M T , Islam A K M A , Naqib S H
Published: January 2021

Ab intio calculations were carried out on the structural, elastic, and electronic properties of a newly synthesized ternary silicide superconductor, Li2IrSi3. The obtained lattice parameters show sound agreement with the experimental values, indicating the reliability of the present study. The rigid structure of Li2IrSi3 is due to the strong covalent Ir-Si and Si-Si bonding. The new compound is mechanically stable, brittle and elastically anisotropic. The relatively low value of the Poisson’s ratio for Li2IrSi3 is indicative of its high degree of directional covalent bonding.
IGAEM: Improved Genetic Algorithm based Entity Matching
Authors: Aassem Y. , Hafidi I. , Aboutabit N.
Published: January 2021

The presence of duplicate records is a major data quality concern in huge datasets. To detect duplicates, entity matching is used as an essential step of the data cleaning process to map records that refer to the same real-world entity. Most of proposed algorithms require labeled data in order to train a classifier. However, we cannot always obtain labeled data. In our paper we propose an unsupervised approach for entity matching problem using an improved version of genetic algorithm. We explain the main improvements added to genetic algorithm and the encoding strategy to encode partitions in the form of a chromosome. Different similarity functions are used to compute similarities between records. The obtained results prove that our proposition stands as a powerful approach in the entity matching field where it outperforms the traditional genetic algorithm based approach.
On the approximation of a Cauchy problem in a non-homogeneous medium
Authors: Aboud F. , Nachaoui A. , Nachaoui M.
Published: January 2021

This paper deals with an inverse Cauchy problem governed by an elliptical equation defined in non-homogeneous domain. We propose two approaches based on alternating algorithm [11] combined with a domain decomposition method [14]. We use the finite elements method to approximate the associate direct problems. Finally, we show the numerical convergence of both proposed algorithms and we discuss there efficiency trough some numerical experiments.
Identification of Complex Network Influencer using the Technology for Order Preference by Similarity to an Ideal Solution
Authors: Ait Rai K. , Agouti T. , Machkour M. , Antari J
Published: January 2021

Marketing through social networks is a recent approach which consists in using these networks to convince potential consumers with the quality of products or services offered by a company. Marketing is developing very quickly, particularly on Facebook, Twitter, LinkedIn, Instagram, YouTube, etc. The major advantage of social networks is the possibility of influencing a panel of people according to their interests but without having the feeling of being guided. Identifying influencers is an interesting topic in social networks, and centrality measures are among the methods used to address this topic. Each measure has some shortcomings. In this paper, we gather centrality measures by using Technology for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, which is a Multi-Criteria Decision Making (MCDM) to identify potential influences in a social network. A case study is presented to explain carefully TOPSIS and to illustrate the effectiveness of the proposed method, three real datasets are used for the experiments. The results show that TOPSIS can rank spreaders more accurately than centrality criteria.
Accuracy assessment of applied supervised machine learning models on usual data probability distributions
Authors: Chefira R. , Rakrak S.
Published: January 2021

In this paper, an application analysis of supervised classification techniques on several probability distributions is carried out. Accuracy as well as usual standard metrics have been highlighted to rate the performance of generated learning models. Using data that fit different distributions, we investigated whether the application of a classification method had an optimizing impact on the accurateness of its correlated learning model.
Anomaly Detection using Machine Learning Techniques in Wireless Sensor Networks
Authors: Ifzarne Samir , Tabbaa Hiba , Hafidi Imad , Lamghari Nidal
Published: January 2021

The number of Wireless sensor network (WSN) deployments have been growing so exponentially over the recent years. Due to their small size and cost-effective, WSN are attracting many industries to use them in various applications. Environmental monitoring, security of buildings and precision agriculture are few example among several other fields. However, WSN faces high security threats considering most of them are deployed in unattended nature and hostile environment. In the aim of providing secure data processing in the WSN, many techniques are proposed to protect the data privacy while being transferred from the sensors to the base station. This work is focusing on attack detection which is an essential task to secure the network and the data. Anomaly detection is a key challenge in order to ensure the security and prevent malicious attacks in wireless sensor networks. Various machine learning techniques have been used by researchers these days to detect anomalies using offline learning algorithms. On the other hand online learning classifiers have not been thoroughly addressed in the literature. Our aim is to provide an intrusion detection model compatible with the characteristics of WSN. This model is built based on information gain ratio and the online Passive aggressive classifier. Firstly, the information gain ratio is used to select the relevant features of the sensor data. Secondly, the online Passive aggressive algorithm is trained to detect and classify different type of Deny of Service attacks. The experiment was conducted on a wireless sensor network-detection system (WSN-DS) dataset. The proposed model ID-GOPA results detection rate of 96% determining whether the network is in its normal mode or exposed to any type of attack. The detection accuracy is 86%, 68%, 63%, and 46% for scheduling, grayhole, flooding and blackhole attacks, respectively, in addition to 99% for normal traffic. These results shows that our model based on offline learning can be providing good anomaly detection to the WSN and replace online learning in some cases.
A new Advanced Greedy perimeter stateless routing for Vehicular Ad Hoc Networks
Authors: Laanaoui D. , Raghay S.
Published: January 2021

In VANET, Vehicles can be seen as probes that locally detect traffic status. Various applications that target transport efficiency could make use of the vast information collected by the vehicles; however, this collection of information needs to be transported over larger distances. For this purpose, various protocols were proposed in the literature and are surveyed in this paper. The information dissemination ‘lifecycle’ is structured in four phases: obtaining information, transport of information, summarization of measurements, and aggregation of information. In this paper, we will focus on the first and second phases to insure the transport of information. And we improve the behavior of GPSR protocol in term of delay and throughput to deal with the limited capacity of the vehicular wireless network.
Recognition of Arabic Handwritten Diacritics using the new database DBAHD
Authors: Lamghari N , Raghay S
Published: January 2021

Recognition of handwritten Arabic characters is gaining momentum and research in this area has increased considerably in recent years. However, research remains modest compared to that performed in other scripts. This is mainly due to the morphology of Arabic writing, in particular its richness in diacritical marks. This signs are generally recognized by adopting structural or morphological measures. However, the difficulty and variability of handwriting can sometimes be misleading, thus influencing the results obtained. This article presents a new database for Arabic handwritten diacritics (DBAHD). It is designed to serve the Arabic handwriting recognition systems based on segmentation and machine learning.
Modeing and Robust Continuous Power Allocation Strategy with Imperfect Channel State Information in Cognitive Radio Networks
Authors: Chen Zhong , Cai Jun , Zhu Feng , Guo Rui , Niu Gengtian , Liu Yanjie
Published: January 2021

A robust continuous power allocation strategy for secondary users (SUs) with imperfect channel state information (CSI) in the cognitive radio networks is proposed. Modeling the error of CSI by normbounded distribution, we address the optimization of the transmit power allocation at SU under the constraints of average transmit power at SU and average interference power at the primary user. Simulation results show that the proposed robust rools can improve the system performance of the SU.
Theory and Application of Logistic-SVM Two-Stage Hybrid Model
Authors: Liu Pingshan , Zeng Ziming
Published: January 2021

Based on the theoretical analysis, this paper combined the Logistic model and the support vector machine (SVM) to construct a Logistic-SVM two-stage hybrid model for credit risk evaluation. Using the two-stage hybrid model to evaluate the credit risk of pharmaceutical supply chain finance, the results showed that the Logistic-SVM two-stage hybrid model had a higher evaluation level than the single Logistic model and the single SVM model, which verified the superiority and effectiveness of the Logistic-SVM two-stage hybrid model applied to the credit risk evaluation.
Influence of Geometrical Dimensions on Negative Differential Resistance in Silicon Based Trench MOS Barrier Schottky Diode
Authors: Chen Huanwen , Wang Yijun , Zhang Hang
Published: January 2021

In this paper, ISE-TCAD, a device simulation software, is used to carry out simulation experiments on silicon-based trench MOS Schottky (TMBS) diodes with different trench dimensions under the condition of forward biases and obtain a series of experiment data associated with the negative resistance. Simulation results show that TMBS diodes under forward biases produce the negative resistance effect. The negative resistance effect intensifies linearly with the increase of mesa width and mitigates wavily with the increase of trench depth. The coupling effect of trench oxidization layer on electric field attenuates the change in device field strength, leading to the fact that TMBS devices present a weaker negative resistance effect than trench barrier Schottky (TBS) diodes which have the same parameters, but are free of oxidization layer. The study result provides a feasible basis for the effective application of TMBS negative resistance features to the design and production of corresponding semiconductor devices and circuits.
Optimal Control for Acrobot with Two-link Manipulators
Authors: Liu Weicai , Zhang Zhifei
Published: January 2021

This paper presents a unified treatment of the optimal control of under-actuated two-link manipulators. Firstly, a nonlinear invertible transfer is introduced to simplify design of controller, then several optimal control laws are established by maximum principle. Controller for swing-up area is based on performance index, while controller for attractive area is based on LQR (linear quadric regulator). It is proved that optimal control is not singular, invariant sets are obtained by theoretical analysis. The strategy for Acrobat is to use optimal control law to pump manipulators into linearizable area, then switch control law to LQR, which drives system to up-straight position. Local and global stability were analyzed in detail under control strategy using LaSalle’s invariance principle and WCLF (non-smooth control Lyapunov function). Simulation and comparison with previous results show that the proposed approach here is valid and of advantages.
Agent-based Simulation of Multi-UAV Search-track for Dynamic Targets in Sweep Coverage
Authors: Liu Zhen , Liu Yukun
Published: January 2021

Agent-based modeling and simulation is an important method to evaluate the efficiency of the multi-UAV search-track problem. In this article, firstly analyse common strategies and then illustrate sweep coverage in parallel searching with changing formation strategy compared with the traditional scanning strategy. Establish an agent-based model by analysing the properties and behaviours of the car agent and UAV agent. Conduct simulation experiments in Anylogic with two strategies, as the results shown, the changing formation strategy can improve the UAVs’ recognition rate more effectively than traditional scanning strategy. Recognition rate has positive correlation with the speed of UAV and the maximum rotation range of the detection area, and is more sensitive to the changes of speed.
A Fuzzy Clustering Based Collaborative Filtering Algorithm for Time-aware POI Recommendation
Authors: Yin Minghao , Liu Yanheng , Zhou Xu , Sun Geng
Published: January 2021

Location based social network develops and gets widely concern along with the population and widespread use of mobile. Point of interest(POI) recommendation become one of the most widely application among location-based service. To get better POI recommendation performance, a fuzzy clustering based collaborative filtering algorithm (FCCF) for time-aware POI recommendation is proposed in this paper. It first constructs the user feature vector from users’ check-in behaviours. Individual’s check-in behaviour can be under the influence of location region and time slots, so user’s feature consists of two parts. One is the vising frequency of each user in different location regions, and the other is the vising frequency of each user in different time slots. Next fuzzy c-means is adopted due to its simplicity to group users according to user feature vector. Then the user similarity computation can be limited in the similar small user groups. In the end, a collaborative filtering algorithm is applied to recommend a number of top-N POIs at a given time for the target user. Some experiments are conducted and the comparative results on Foursquare and Gowalla show that FCCF has higher precision and recall value than the comparative algorithms.
Numerical Analysis and Investigation on the Drawbending Springbackand Fracture
Authors: Ma Wenyu , Yang Jianwei , Li Xiaoqiang , Dou Luyi , Yao Ye , Zhang Yongqiang
Published: January 2021

In this paper, the effect of process parameters on the drawing springbackand fracture mechanism of high strength steel in drawbending process was investigated. The fracture behaviour and fracture morphology were observed and analyzed using Scanning Electron Microscope (SEM). The process parameters studied in this paper includes drawing speed, roll radius, drawing force and roll radius. The springback angle measurement method for drawing springback was also introduced and applied. The conclusions were drawn from the results. The drawbending springback angle increases withthe increase of drawing velocity. The springbackdecreases with the increase of the round roll. The large bending angle leads to the large springback. The large tension force can decrease the springback angle. The springback increases with the increase of the drawing distance. The fracture with theplane angle of 60 indicates a shear fracture and thedominated brittleness mode, which is induced by a large radius against thickness value. The fracture vertical to straight side indicates the ductility tension fracture, which is induced by a small radius against thickness value.
Application of Algorithm with Novel Successive Approximate Registration Method of Medical Image
Authors: Yang Yunfeng , Wang Fei , Guan Chen
Published: January 2021

Medical image registration is widely used in the clinical field. A simple and effective registration method for medical images is proposed, which is not only used images’ hierarchical information, but also the successive approximate method is used. It mainly includes two steps, which are the coarse registration and the fine registration. In the coarse registration procedure, the couple images’ edge features are extracted. Further more, the contour line features are extracted based on the edge features. The contour lines are selected as registration objects to accomplish the coarse registration based on the Principal Axis method. In the second registration procedure, i.e. the fine registration, the hierarchical information of the images are obtained by the convolution operator and pooling method firstly. Then these information are matched from the last scale to the first scale to obtain the last registration result. The proposed method’s validity is proved by different registration experiments, and the proposed method can also be applied to incomplete images’ registration. The error of registration is less than one pixel unit in the different registration experiments of the proposed method.
Numerical Simulation Study on Air - side of Diesel Locomotive Finned Tube Double Channel Radiator
Authors: Guan Ying , Cui Hongjiang , Li Minghai
Published: January 2021

Based on the heat transfer and flow resistance of diesel locomotive radiator, the influence was studied about the cooling air inlet speed on heat transfer coefficient and pressure loss of finned tube double channel radiator with louver by using CFD method. Temperature field, speed field and pressure field distribution of radiator calculation results were analyzed. The radiator was tested at different cooling air inlet speed, compared test results with simulation results, the greatest relative error of the heat transfer coefficient and pressure loss were 7.21% and 7.72%, respectively.
Research on Traffic Dispatching Scheme of Multi-service Data Center for 5G Smart Grid
Authors: Sun Yanzhi , Liu Yuming , Tian Feng , Wen Quan , Jiang Liqiong
Published: January 2021

Aiming at the flow scheduling problem of 5G power network multi-service data center, this paper designs and proposes a multi-service-oriented multi-factor flow scheduling scheme. Based on the shortest path algorithm, this paper improves and perfects the traffic scheduling strategy, and introduces a set of scoring mechanism. The number of hops, the number of large flows and the remaining bandwidth of each path are used as scoring indicators, and the path with the highest comprehensive score is selected. As the forwarding path of traffic. Based on the Mininet simulation platform, use Ryu to control to generate probability model traffic to simulate data center network traffic. The experimental results show that the scheme improves the network throughput and bandwidth utilization, and improves the performance of the data center network.
Optimization Analysis of AR-HUD Technology Application in Automobile Industry
Authors: Zhang Miaoxuan
Published: January 2021

Currently, how to make the driving system safer and more intelligent has been a heated topic. To achieve the goal, quite a few companies argued about introducing HUD technology, which was originally used in aircraft, to the automobile industry. In order to make HUD have better performance in the new area, the public’s attention was paid on the combination of AR and HUD technology. AR-HUD is seen as a good way to improve the convenience and safety factor of driving. This article introduces the usage of AR-HUD in the traffic analysis, man-machine interactive, intelligent navigation and aided driving. Moreover, SWOT method was introduced to this new area, to find out the prospect of AR-HUD application. It is found that although AR-HUD is technology is still relatively immature up to now, it has the power to have broad application space in the future. AR-HUD’s time is around the corner.
Optimization Technology of Passenger Service System based on Railway Intelligent Robot
Authors: Zhao Jiayu , Feng Fan
Published: January 2021

In the post-epidemic era, with the continuous increase of passenger flow in railway stations and people’s increasing attention to public health, traditional service methods such as meal delivery and ticket checking in railway stations cannot keep up with the rhythm of the times, and the transportation sector is facing how to solve the problem of contactless services. This product uses STM32F103 as the core controller to develop a multifunctional intelligent robot system for trains. The system uses A* and artificial potential field algorithms for path planning and obstacle avoidance, combined with integrated software services, cooperates with the cloud to record various data, and finally add intelligence. The power management system ensures that the system can safely, efficiently, accurately and lastingly complete functions such as online ordering, smart ticket checking, temperature measurement and crew call. On the basis of the existing technologies, this paper makes a little technical integration and innovation to complete an intelligent robot system.
Convergence - Divergence of the Finite Volume Method for the Fluid and Heat Flow in Heterogeneous Porous Rocks
Authors: Suárez-Arriaga Mario-César , Verma Mahendra Pal
Published: January 2021

Fluid velocity has an important impact in the Finite Volume numerical method (FVM) used to model fluid and energy flows in heterogeneous porous media. This formulation is based on the energy flow conservation equations under local thermal non-equilibrium conditions (LTNE). The heat transfer from the solid matrix to the moving non-isothermal fluid inside the pores is simulated for several velocities and global different heat transfer coefficients. During the numerical simulation of coupled heat/mass flow in a heterogeneous porous system it is necessary to average highly variable physical parameters at the boundaries between different domains represented geometrically in the computational mesh of the FVM. This can be effectively achieved using appropriate average techniques at the contact interfaces of each domain. The averaging process should correctly represent the behaviour of the fluid velocity crossing different areas of the reservoir. Many numerical divergence problems arise from the fluid velocity value and the interfacial interactions at the boundaries of different continua. The averages have a decisive influence on the numeric results of the simulation. A very stable, convergent averaging scheme for the FVM is presented herein and compared to new analytical diffusion-convection models. Especial attention is paid to the dynamic process of cold water (50°C) injected into a geothermal reservoir at higher temperature (350°C). The fluid temperature profile is calculated when the fluid migrates at constant speed through a permeable corridor from a fluid injection point to an extraction zone. The physical reason for the divergence of a numerical model, and the exploration of the range of validity of the LTNE hypothesis during the injection of cold water into a hot reservoir are both explained.
Research on the Optimization of Urban Cold Chain Logistics System Based on the Example of Guangzhou
Authors: Kuang Mo , Du Yong , Kuang Da , Zhu Xiangyi
Published: January 2021

In view of the realistic environment of the cold chain logistics development in Guangzhou, this paper aims at analyzing the present pre-cooling equipment of the cold chain logistics in Guangzhou, the lack of cold storage facilities, the incomplete cold chain structure, the lagging of the development of the third-party cold chain logistics industry, the lack of trace ability of the products, the information tracking mechanism and the deficiency of the standard specifications of the cold chain, the shortage of cold chain professionals etc., and the countermeasures are put forward from three aspects: strengthening the policy support for the overall planning of the cold chain logistics; strengthening the construction and improvement of the cold chain logistics system and the platform and the main body; and developing the Guangzhou cold chain logistics industry in various modes.
Optimization of Power Supply Section Planning in Medium-Speed Maglev System
Authors: Zhou Haoran , Meng Lingyun , Lai Qingying , Xu Yazhi
Published: January 2021

The power supply planning of medium-speed maglev system (MSM) is related to line capacity greatly. To improving sectional through capacity, this paper takes the problem of dividing power supply zones of MSM as research object, i.e, the optimization of power supply planning. With the known number of zones, optimization object is maximum line capacity without consideration of generalized cost. Considering factors such as stator position in section, train speed profile characteristics, blocking time and blocking time overlap method, an optimization model of MSM stator combination is established. According to the given relative position of stators and target speed profile, a genetic algorithm is designed to obtain power supply plan that meets the target expectation. This method provides guidance for the future MSM power supply planning.
Optimization and Design Based on Data Visualization of Enterprise-class Crawler Systems for Shipping
Authors: Wu Hao
Published: January 2021

The designed crawler scheduling system is a JEE application based on Quartz scheduling framework that sends crawler tasks to the crawler control system automatically or manually at regular intervals. The crawler control system visually manages and controls the shipping crawlers. The HttpCilent-centric crawler system crawls the shipping website. The message queue ActiveMQ is used as a message middleware for the crawler control system and the crawler system to achieve asynchronous communication and reduce coupling. In this system, front-end frameworks such as Bootstrap, AngularJS, and SweetAlert are used to implement a visual scheduling system and data visualization system. Change the crawler deployment environment by deploying containers through Docker. Add Selenium dynamic page processing for shipping website. Adding message queues and MongoDB database data storage. By adopting a series of techniques and designing, testing and quality assurance of the system, we aim to make the crawler more stable and efficient, and to achieve security, stability and ease of maintenance of the system.
Research on Optimal Allocation of Sea Area Utilization Based on Genetic Algorithm: A Case Study of Dengsha Estuary Sea Area
Authors: Wang Xiaowen , Kang Minjie
Published: January 2021

Optimal allocation of sea area utilization is a necessary method to coordinate the conflicts between different departments and realize the dual goals of development and ecological protection. This paper presents an optimal allocation method of sea area utilization based on genetic algorithm. Taking the estuarine sea area of Dengsha Estuary Sea Area as an example, the empirical study was conducted. The results show that the sea area utilization optimization allocation method based on genetic algorithm can produce the optimization result scheme with higher comprehensive benefit and lower ecological loss based on the initial scheme. Under the guidance of constraint conditions, the problem of conflicts between different departments can be solved by optimizing the spatial distribution and the demand of each department can be fully met. Different spatial distribution optimization alternatives can be produced under the same sea area utilization structure.
Research on Optimization Policy Routing Technology of Optical Fiber Communication Network
Authors: Zhang Ning , Yang Yansong , Chen Tingting , Chen Xiaodan , Sun Huijuan , Chen Ming , Xiao Mingming , Chen Bingjun , Luo Yang
Published: January 2021

With the development of global informatization, information has penetrated into every corner of human society. With the popularization of Internet, the transmission bandwidth of information becomes more and more important. Nowadays, people’s demand and dependence on information are becoming stronger and stronger. It is urgent to expand the capacity of wide area backbone communication network, and the optical network composed of wavelength division multiplexing (WDM) can just take this role. In WDM network, it can transmit multiple optical signals of different wavelengths in one fiber at the same time. WDM has the advantages of large transmission capacity, strong technical adaptability, simple implementation and easy expansion. In addition, WDM optical network can also make full use of the huge bandwidth of optical fiber itself to carry out high-speed transmission. Now, the optical network using WDM technology has become the backbone network of long-distance transmission. This paper studies the optical fiber communication system and analyzes the structure of the optical fiber network. For the optical network, how to find the appropriate routing is a very important technology. After analyzing all kinds of basic routing technologies, this paper proposes a new policy based routing technology, and carries out relevant experiments. The experimental results show that the new routing technology has some advantages compared with the old routing technology.
An Improved Dynamic Programming Method in The Optimization of Gas Transmission Pipeline Operation
Authors: He Miao , Xiong Hui , Kou Jiemin , Zhi Shujie
Published: January 2021

The operation and optimization of gas transmission pipe network system is a mixed integer nonlinear programming problem, with nonlinear and nonconvex objective function and constraints. The dynamic programming method has the advantages of not sensitive to the nonlinearity and nonconvexity of the optimization problem, and it can obtain the global optimal solution, which should have convince performance in the operation and optimization applications of gas transmission pipe network system. However, the use of dynamic programming method may lead to dimension disaster and exponentially increasement of the computational cost. In this paper, the traditional dynamic planning method in the operation optimization of gas transmission pipeline is improved, and the idea of two-level optimization and the concept of local search are introduced, which can effectively avoid the dimension disaster and significantly improve calculation efficiency of dynamic planning method. Through the above two improved measures, the dynamic programming method can be applied to the operation optimization of large-scale gas transmission pipe network system to obtain the optimal solution quickly, which provides certain guidance and assists in the formulation of pipeline operation scheme.
Migration towards Bangladesh coastlines projected to increase with sea-level rise through 2100
Authors: Bell A R , Wrathall D J , Mueller V , Chen J , Oppenheimer M , Hauer M , Adams H , Kulp S , Clark P U , Fussell E , Magliocca N , Xiao T , Gilmore E A , Abel K , Call M , Slangen A B A
Published: January 2021

To date, projections of human migration induced by sea-level change (SLC) largely suggest large-scale displacement away from vulnerable coastlines. However, results from our model of Bangladesh suggest counterintuitively that people will continue to migrate toward the vulnerable coastline irrespective of the flooding amplified by future SLC under all emissions scenarios until the end of this century. We developed an empirically calibrated agent-based model of household migration decision-making that captures the multi-faceted push, pull and mooring influences on migration at a household scale. We then exposed ∼4800 000 simulated migrants to 871 scenarios of projected 21st-century coastal flooding under future emissions pathways. Our model does not predict flooding impacts great enough to drive populations away from coastlines in any of the scenarios. One reason is that while flooding does accelerate a transition from agricultural to non-agricultural income opportunities, livelihood alternatives are most abundant in coastal cities. At the same time, some coastal populations are unable to migrate, as flood losses accumulate and reduce the set of livelihood alternatives (so-called ‘trapped’ populations). However, even when we increased access to credit, a commonly-proposed policy lever for incentivizing migration in the face of climate risk, we found that the number of immobile agents actually rose. These findings imply that instead of a straightforward relationship between displacement and migration, projections need to consider the multiple constraints on, and preferences for, mobility. Our model demonstrates that decision-makers seeking to affect migration outcomes around SLC would do well to consider individual-level adaptive behaviors and motivations that evolve through time, as well as the potential for unintended behavioral responses.
AI and Blockchain: potential and challenge for building a smart E-Learning system in Vietnam
Authors: Hung Nguyen Quoc , Phung Thai Kim , Hien Phan , Hoang Thanh Dang Ngoc
Published: January 2021

Smart E-Learning is an education form, in which information technology plays an important role. Smart E-Learning utilizes the achievements of modern technologies such as artificial intelligence (AI). So, it can help to gain the ability of connectivity, sharing, convenience, and flexibility for learners. All activities including teaching, learning, discussing, testing, and grading, are well done over the internet environment. However, some potential risks can cause participants, especially, about data privacy. The issue is a big challenge for developing applications for smart E-Learning. Therefore, the goal to combine E-Learning with Blockchain technology to improve security for smart E-Learning is necessary. In this paper, we discuss potential and challenge for applying AI and Blockchain for developing applications for smart E-Learning in Vietnam. We also propose to combine independent testing models integrated with AI and Blockchain into the same smart E-Learning system.
A Glimpse on Key Applications of Smart City under M2M Communication
Authors: Kaushik Sonam , Aggarwal Gaurav , Tejasvee Sanjay
Published: January 2021

In India, It is very necessary to make normal cities as smart cities near future. So, Develop a smart city is one of the most recent fields in today’s digital era to researches. Machine to Machine (M2M ) communication is the latest innovative-fangled type of communiqué that enables full automation with the help of integrated applications to make a normal city to a smart city. Many devices are connected in a smart city to monitoring many tasks and it is a very challenging task to integrate and manage these connected devices. Interconnection of several devices and machines using the internet to form an M2M Area Network (M2MAN) provides controlling and monitoring smart applications like smart-metering, weather, environment, home, air quality, water supply with quality management, power supply with bill monitoring, traffic, and healthcare, etc. under M2M communication and integrated single level umbrella structured applications. Out of several M2M monitoring and controlling applications towards smart cities, few key applications are presented in this paper with their basic approach, workflow, and concerning issues and used technologies for the implementation with the brief growth analysis.
Study of Deep Learning Techniques on Image Denoising
Authors: Gupta Kanika
Published: January 2021

With the advancement in the area of Artificial Intelligence, the technology of deep learning is widely used in the field of Digital Image Processing and it is showing good results in the domain of Image denoising. To understand the area and progress of the field of deep learning in the domain of denoising, the research work is to be reviewed on various techniques, so that research scholars, academicians and industry professionals can take benefits out of this. The three models are introduced in this paper, such as wavelet neural network, pulse coupled neural network and convolutional neural network which are typically used in the field of noise reduction i.e. image denoising. The method of reduction in noise which is nonlocal in nature is considered as the heart of this technique. The aim of this paper is to better understand the recent developments in the field of machine learning and deep learning with the domain of reduction in noise of digital images.
A Review on Control System Applications in Industrial Processes
Authors: Juneja P K , Sunori S K , Sharma A , Sharma A , Pathak H , Joshi V , Bhasin P
Published: January 2021

Present paper attempts to review the literature related to design of P-I-D control for time delayed complex industrial process for single as well as for multivariable process with interaction considerations, their decoupler design and time delay compensators. General instrumentation of the industrial feedback control systems along with control system analysis has been covered. Also it covers, control features of some paper mill sub-processes like headbox operation, basis weight and retention. The importance of eliminating the effects of interactions, among the process control loops inside a multi input multi output industrial control system, has been discussed with the help of literature study. The importance of the process dynamics knowledge for designing a control system has also been investigated. This paper also investigates the significance and effectiveness of PID controllers through various literature studies. The problems of the classical PID controllers such as constraints, presence of disturbances etc.) can be removed by designing in combination with soft computing techniques. Moreover, possibility of further enhancements in the PID controller with the utilization of various schemes available, has been presented. The present status of control systems in industrial processes in terms of various control parameters such as stability, dead time compensation etc. has been presented and the future improvements have been stated.
Big Data: Big Data Analysis, Issues and Challenges and Technologies
Authors: Rawat R , Yadav R
Published: January 2021

The data generated at an exponential rate has resulted in Big Data. This data has many characteristics and consists of structured, unstructured, and semi-structured data formats. It contains valuable information for the different types of stakeholders based on their need however it is not possible to meet them with the help of traditional tools and techniques. Here the big data technologies play a crucial role to handle, store, and process this tremendous amount of data in real-time. Big data analytics is used to extract meaningful information or patterns from the voluminous data. It can be further divided into three types i.e. text analytics, audio analytics, video analytics, and social media analytics. Big data analytics if followed by big data analysis process plays a significant role in generating meaningful information from big data. Big data analysis process consists of data acquisition, data storage, data management, data analytics, and finally data visualization. However, it is not simple and brings many challenges that need to be resolved. This paper presents the issues and challenges related to big data, prominent characteristics of big data, big data analytics, big data analysis process, and technologies used for processing the massive data.
Implementation of SimpleRNN and LSTMs based prediction model for coronavirus disease (Covid-19)
Authors: Priyanka  , Kumari A , Sood M
Published: January 2021

Deep learning is a powerful technique which is inspired by the structure as well as processing power of the human brain. This technique uses deep neural network to perform complex tasks such as time series prediction, image classification, and cancer detection. In this research work, we used Covid-19 time series datasets and with the help of deep learning we built the model for prediction of Covid-19 cases. For the model building, we used two deep learning neural networks, Recurrent Neural Networks (RNN) and Long Short Term Memory Networks (LSTMs). We built a prediction model using RNN in the first instance and subsequently the second model was built using LSTMs. Out of these two neural networks, we got promising results from the model based on LSTMs with an overall accuracy of 98%. As the cases of Covid-19 are increasing day-by-day at a very high rate, we proposed these models using neural networks to help in predicting the future trends of Covid-19 confirmed, deaths and recovered cases.
A Study on Different Aspects of Web Mining and Research Issues
Authors: Kumar Santosh , Kumar Ravi
Published: January 2021

Web is huge and dynamically increasing day by day with exponential rate. If query is little bit complex then often or sometimes it becomes difficult to get relevant information in response. Several search engines try to optimize the users query and/or search results to provide the relevant information. Also many websites are ecommerce sites which are also competing to attract their customers and some are recommendation based. Now almost all good sites are using web mining techniques to improve their performance. In this paper, an attempt has been made to cover the key aspects used in web mining research. Initially problems faced by users and/or owners have been highlighted. Further it discusses types of data and techniques used by different categories of web mining are discussed. Finally research issues and application areas have been discussed.
Product Recommendation System a Comprehensive Review
Authors: Sharma Jatin , Sharma Kartikay , Garg Kaustubh , Sharma Avinash Kumar
Published: January 2021

In today’s technical era, every startup or a company attempt to establish a better sort of communication between their products and the users, and for that purpose, they require a type of mechanism which can promote their product effectively, and here the recommender system serves this motive. It is basically a filtering system that tries to predict and show the items that a user would like to purchase. By analyzing the preference of the users, companies can decide which product to be launched in the market to procure more benefits. These systems are proved to be very beneficial in variety of domains involving music, books, movies, research articles and products in common. In this paper, we review various mechanisms and techniques that are required for recommender systems for recommending the products or items in the domain of fashion and books.
Performance Evaluation of QoS metrics in Software Defined Networking using Ryu Controller
Authors: Babbar Himanshi , Rani Shalli
Published: January 2021

With assistance from Software Defined Networking (SDN), networks have become more creative to build and maintain over the last few years. The inflexibility of modern network architecture is presenting researchers with a tough achievement. SDN replaces existing inescapable and complicated networks with a creative way of separating the control plane from the data plane and fixing those constraints, namely configurations done manually, monitoring, protection, usability, and functionality. SDN controllers (e.g., POX, RYU, ONOS, OpenDaylight, Floodlight, etc.) have therefore developed as a core for the management of these networks. The performance evaluation of the SDN controller has an outstanding effect on improving the flexibilities and abilities of a network topology of SDN infrastructures. This research summarizes the SDN controller performance tests using criteria (e.g., Bandwidth, Round-Trip Time). This study employs a Mininet emulator to enforce an SDN architecture that comprises an RYU controller with a switching part, one OpenFlow switch, and multiple nodes. The goal is to determine performance QoS (Quality of Service) including Bandwidth, Throughput using the iperf test.
Denoising of images using Thresholding Based on Wavelet Transform Technique
Authors: Kaur Gurjinder , Garg Meenu , Gupta Sheifali , Gupta Rupesh
Published: January 2021

This paper presents an efficient method based on thresholding for images that are corrupted due to Gaussian noise. In order to achieve this task, wavelet transforms and various thresholding techniques have been applied. But the selection of the thresholding technique is restricted due to their widespread use in image denoising application. In this paper, a more efficient thresholding scheme named as neigh shrink sure is studied by incorporating the neighboring wavelet coefficients. Different thresholding techniques like Bayes shrink and Neigh shrink sure algorithms are applied to different images. The results are obtained using 3 different wavelets db-4, sym-4, and coif-4. It has been observed that the use of coif-4 transform produces better results as compared to other wavelet transforms. Further, it has been analyzed that Neigh Shrink sure method performs better in de-noising of corrupted images in comparison to Bayes shrink thresholding technique by possessing higher Peak Signal-to-Noise Ratio (PSNR) and lower Mean Square Error (MSE).
Study of techniques to improve performance of patch antennas for 5G applications at millimeter wave (mmW) frequencies
Authors: Juneja Sagar , Sharma Rajnish
Published: January 2021

Millimeter wave (mmW) frequency signals of 28 GHz and 38 GHz that are being explored for implementing next generation cellular communication network (i.e. 5G) suffer from severe attenuation in the outdoor environment. Therefore, efficient and intelligent antenna design techniques are needed for proper transmission and reception of signals at mmW frequencies. Beamforming, multiple input multiple output (MIMO) and space division multiple access (SDMA) are important requirements of mmW 5G network, and these technologies are heavily dependent upon antenna design and implementation. This paper presents various contemporary techniques for improving performance parameters of patch antennas for 5G implementation at mmW frequencies. These performance parameters include gain, bandwidth, directivity, suppression of surface waves, ease of design, compactness, and mutual coupling between antenna elements for MIMO system. This study also highlights the benefits and drawbacks of each of these techniques discussed in the paper.