Secure Calculation for Position Information of IoT Device with Few Communication and Small Secret Information

Information Technology as a new Technology has been used in businesses from small company until multinational company in almost all industries. IT role as an enabler and differentiation factor separating success company from average company. IT need people to build, operate, maintain and support the systems, hence expect the new hire to immediately contribute from the first day they join the company. The industry define the needs for Information Technology competence and expect Education Institution as one of IT resource work hard to design their program study to fulfill the needs for Information Technology graduates, yet the industry still struggle to succeed in hiring fresh graduate to fill the IT position. Information Technology Training Institution can be an alternative to improve the education result. Also certification on Information Technology competence from third party or independent body might be used as a standard for both Industry and Education. This paper will report literature review several previous paper about all of the above.

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Localization and Non-Localization Node Identification Using Dream in MANET

SMART MOVES JOURNAL IJOSCIENCE ◽

10.24113/ijoscience.v2i2.77 ◽

2016 ◽

Vol 2 (2) ◽

Author(s):

Amit Singh ◽

Nitin Mishra ◽

Angad Singh

Keyword(s):

Ad Hoc Network ◽

Ad Hoc ◽

Mobile Ad Hoc Network ◽

Fundamental Problem ◽

Identification Algorithm ◽

Mobile Nodes ◽

Position Information ◽

Location Services ◽

Wireless Router ◽

Mobile Ad Hoc

A Wireless Mobile Ad-hoc Network consists of variety of mobile nodes that temporally kind a dynamic infrastructure less network. To modify communication between nodes that don’t have direct radio contact, every node should operate as a wireless router and potential forward knowledge traffic of behalf of the opposite node. In MANET Localization is a fundamental problem. Current localization algorithm mainly focuses on checking the localizability of a network and/or how to localize as many nodes as possible. It could provide accurate position information foe kind of expanding application. Localization provide information about coverage, deployment, routing, location, services, target tracking and rescue If high mobility among the mobile nodes occurs path failure breaks. Hence the location information cannot be predicted. Here we have proposed a localization based algorithm which will help to provide information about the localized and non-localized nodes in a network. In the proposed approach DREAM protocol and AODV protocol are used to find the localizability of a node in a network. DREAM protocol is a location protocol which helps to find the location of a node in a network whereas AODV is a routing protocol it discover route as and when necessary it does not maintain route from every node to every other. To locate the mobile nodes in a n/w an node identification algorithm is used. With the help of this algorithm localized and non-localized node can be easily detected in respect of radio range. This method helps to improve the performance of a module and minimize the location error and achieves improved performance in the form of UDP packet loss, received packet and transmitted packets, throughput, routing overhead, packet delivery fraction. All the simulation done through the NS-2 module and tested the mobile ad-hoc network.

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A MATHEMATICAL TRUST MODEL TO ENSURE IN THE INFORMATION ENVIRONMENT

Сборник избранных статей по материалам научных конференций ГНИИ “Нацразвитие” (Санкт-Петербург, Июнь 2020) ◽

10.37539/june291.2020.55.98.007 ◽

2020 ◽

Author(s):

Мадина Усенбай ◽

Акмарал Иманбаева

Keyword(s):

Trust Model ◽

Time Parameter ◽

Information Environment ◽

User Privacy ◽

Cloud Technology ◽

Secret Information ◽

Dynamic Objects

Конфиденциальность является одним из важных параметров для повышения безопасности в сети, цель которого - сохранить секретную информацию. Рассмотрена модель доверия, состоящая из текущих и прошлых оценок на основе репутации объекта в сети. В модели используется параметр времени для защиты конфиденциальности пользователя для статических и динамических объектов, например, в IoT или облачной технологии. Confidentiality is one of the important parameters for increasing security on the network, the coal of which is to keep secret information. A trust model consisting of current and past assessments based on the object reputation in the network is considered. The model uses a time parameter to protect user privacy for static and dynamic objects, for example, in IoT or cloud technology.

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DBP-PSSM: Combination of evolutionary profiles with the XGBoost algorithm to improve the identification of DNA-binding proteins

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323999201124203531 ◽

2020 ◽

Vol 23 ◽

Author(s):

Yanping Zhang ◽

Pengcheng Chen ◽

Ya Gao ◽

Jianwei Ni ◽

Xiaosheng Wang

Keyword(s):

Logistic Regression ◽

Protein Structure ◽

Dna Binding ◽

Molecular Biology ◽

Binding Proteins ◽

Protein Sequences ◽

Low Complexity ◽

Dna Binding Proteins ◽

Position Information ◽

Position Representation

Aim and Objective:: Given the rapidly increasing number of molecular biology data available, computational methods of low complexity are necessary to infer protein structure, function, and evolution. Method:: In the work, we proposed a novel mthod, FermatS, which based on the global position information and local position representation from the curve and normalized moments of inertia, respectively, to extract features information of protein sequences. Furthermore, we use the generated features by FermatS method to analyze the similarity/dissimilarity of nine ND5 proteins and establish the prediction model of DNA-binding proteins based on logistic regression with 5-fold crossvalidation. Results:: In the similarity/dissimilarity analysis of nine ND5 proteins, the results are consistent with evolutionary theory. Moreover, this method can effectively predict the DNA-binding proteins in realistic situations. Conclusion:: The findings demonstrate that the proposed method is effective for comparing, recognizing and predicting protein sequences. The main code and datasets can download from https://github.com/GaoYa1122/FermatS.

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CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

Current Bioinformatics ◽

10.2174/1574893615666210108093950 ◽

2021 ◽

Vol 15 ◽

Author(s):

Lichao Zhang ◽

Zihong Huang ◽

Liang Kong

Keyword(s):

Computational Model ◽

Binding Sites ◽

Noncoding Rna ◽

Computational Models ◽

Information Sources ◽

Rna Binding ◽

Rna Binding Proteins ◽

Gradient Boosting ◽

Position Information ◽

Rna Binding Sites

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.

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Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement

Sensors ◽

10.3390/s21072400 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2400

Author(s):

Ziyong Zhang ◽

Xiaoling Xu ◽

Jinqiang Cui ◽

Wei Meng

Keyword(s):

Quadratic Programming ◽

Wide Band ◽

Area Coverage ◽

Localization Algorithm ◽

Placement Problem ◽

Position Information ◽

Relative Localization ◽

Coverage Control ◽

Localization Algorithms ◽

Multi Uav

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

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Sensorless Pedalling Torque Estimation Based on Motor Load Torque Observation for Electrically Assisted Bicycles

Actuators ◽

10.3390/act10050088 ◽

2021 ◽

Vol 10 (5) ◽

pp. 88

Author(s):

Riccardo Mandriota ◽

Stefano Fabbri ◽

Matthias Nienhaus ◽

Emanuele Grasso

Keyword(s):

External Disturbance ◽

State Observer ◽

Position Estimation ◽

Load Torque ◽

Estimation Errors ◽

Position Information ◽

Longitudinal Dynamics ◽

Rotor Position ◽

Electrically Assisted ◽

Motor Load

The need for reducing the cost of and space in Electrically Assisted Bicycles (EABs) has led the research to the development of solutions able to sense the applied pedalling torque and to provide a suitable electrical assistance avoiding the installation of torque sensors. Among these approaches, this paper proposes a novel method for the estimation of the pedalling torque starting from an estimation of the motor load torque given by a Load Torque Observer (LTO) and evaluating the environmental disturbances that act on the vehicle longitudinal dynamics. Moreover, this work shows the robustness of this approach to rotor position estimation errors introduced when sensorless techniques are used to control the motor. Therefore, this method allows removing also position sensors leading to an additional cost and space reduction. After a mathematical description of the vehicle longitudinal dynamics, this work proposes a state observer capable of estimating the applied pedalling torque. The theory is validated by means of experimental results performed on a bicycle under different conditions and exploiting the Direct Flux Control (DFC) sensorless technique to obtain the rotor position information. Afterwards, the identification of the system parameters together with the tuning of the control system and of the LTO required for the validation of the proposed theory are thoroughly described. Finally, the capabilities of the state observer of estimating an applied pedalling torque and of recognizing the application of external disturbance torques to the motor is verified.

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TDMA Datalink Cooperative Navigation Algorithm Based on INS/JTIDS/BA

Electronics ◽

10.3390/electronics10070782 ◽

2021 ◽

Vol 10 (7) ◽

pp. 782

Author(s):

Shuo Cao ◽

Honglei Qin ◽

Li Cong ◽

Yingtao Huang

Keyword(s):

Distribution System ◽

Large Scale ◽

Satellite System ◽

Time Of Arrival ◽

Military Operations ◽

Position Information ◽

Cooperative Navigation ◽

Navigation Algorithm ◽

Geometric Dilution Of Precision ◽

Global Navigation Satellite

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.

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Improvement of Reliability Determination Performance of Real Time Kinematic Solutions Using Height Trajectory

Sensors ◽

10.3390/s21020657 ◽

2021 ◽

Vol 21 (2) ◽

pp. 657

Author(s):

Aoki Takanose ◽

Yoshiki Atsumi ◽

Kanamu Takikawa ◽

Junichi Meguro

Keyword(s):

Real Time ◽

Urban Areas ◽

Estimation Method ◽

Tall Buildings ◽

Autonomous Driving ◽

Reliability Estimation ◽

Height Variation ◽

Position Information ◽

Real Time Kinematic ◽

Evaluation Test

Autonomous driving support systems and self-driving cars require the determination of reliable vehicle positions with high accuracy. The real time kinematic (RTK) algorithm with global navigation satellite system (GNSS) is generally employed to obtain highly accurate position information. Because RTK can estimate the fix solution, which is a centimeter-level positioning solution, it is also used as an indicator of the position reliability. However, in urban areas, the degradation of the GNSS signal environment poses a challenge. Multipath noise caused by surrounding tall buildings degrades the positioning accuracy. This leads to large errors in the fix solution, which is used as a measure of reliability. We propose a novel position reliability estimation method by considering two factors; one is that GNSS errors are more likely to occur in the height than in the plane direction; the other is that the height variation of the actual vehicle travel path is small compared to the amount of movement in the horizontal directions. Based on these considerations, we proposed a method to detect a reliable fix solution by estimating the height variation during driving. To verify the effectiveness of the proposed method, an evaluation test was conducted in an urban area of Tokyo. According to the evaluation test, a reliability judgment rate of 99% was achieved in an urban environment, and a plane accuracy of less than 0.3 m in RMS was achieved. The results indicate that the accuracy of the proposed method is higher than that of the conventional fix solution, demonstratingits effectiveness.

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Deep Learning-Based Congestion Detection at Urban Intersections

Sensors ◽

10.3390/s21062052 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2052

Author(s):

Xinghai Yang ◽

Fengjiao Wang ◽

Zhiquan Bai ◽

Feifei Xun ◽

Yulin Zhang ◽

...

Keyword(s):

Deep Learning ◽

Optical Flow ◽

Traffic Congestion ◽

Detection Algorithm ◽

Input Image ◽

Vehicle Speed ◽

Position Information ◽

Traffic State ◽

State Discrimination ◽

Discrimination Method

In this paper, a deep learning-based traffic state discrimination method is proposed to detect traffic congestion at urban intersections. The detection algorithm includes two parts, global speed detection and a traffic state discrimination algorithm. Firstly, the region of interest (ROI) is selected as the road intersection from the input image of the You Only Look Once (YOLO) v3 object detection algorithm for vehicle target detection. The Lucas-Kanade (LK) optical flow method is employed to calculate the vehicle speed. Then, the corresponding intersection state can be obtained based on the vehicle speed and the discrimination algorithm. The detection of the vehicle takes the position information obtained by YOLOv3 as the input of the LK optical flow algorithm and forms an optical flow vector to complete the vehicle speed detection. Experimental results show that the detection algorithm can detect the vehicle speed and traffic state discrimination method can judge the traffic state accurately, which has a strong anti-interference ability and meets the practical application requirements.

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