bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on SDP Software Defined Perimeter Initiating Host Protocol Configuration Algorithm
Authors: Xie Xinmeng , Gan Gang , Chen Yong 
Published: January 2020

Abstract
With the popularity of digital and cloud services, the demand for network security products and solutions is increasing day by day. At the same time, the network security problems are becoming more and more serious. The network security architecture and platform are far from meeting the challenges brought by the current situation. As a new generation network security solution concept, the Software Definition Perimeter was first proposed by the Cloud Security Alliance in 2013. The whole central idea is to build a virtual enterprise boundary in the mobile + cloud era through software. The use of identity-based access control is to cope with the problem of coarse control and poor validity caused by boundary fuzziness, so as to achieve the purpose of protecting data security. This paper mainly changes the infrastructure of the Software Defined Perimeter SDP, and adds the message queue, which mainly stores the control information in the message queue to solve the peak congestion and network congestion problem.
Estimation of Soil Temperature Based on Meteorological Parameters by the HYBRID INVASIVE Weed Optimization Algorithm Model
Authors: Guan Yiqing , Shen Yue , Mohammadi Babak , Sadat Mohammad A 
Published: January 2020

Abstract
Soil temperature (ST) is considered as one of the crucial characteristics of soil affecting physical and chemical processes of soil, agricultural products, the optimal time for planting seeds, etc and land surface ecological system. Hence, estimating this parameter can play an important role in agricultural and hydrology engineering. In this study, soil temperature was estimated using multilayer perceptron (MLP) and hybrid models of multilayer perceptron with invasive weed optimization algorithm (MLP-IWO). For training and testing of intelligence models meteorological data such as air temperature, relative moisture, wind speed, sunshine hours with a ten-year statistical period during 2007-2017 related to the meteorological station of Van in Turkey were used. The results showed for nominated scenario that the MLP-IWO performed best with lowest root mean square error (RMSE) at 2.057 °C when compared with original MLP model with RMSE at 2.426 °C, the MLP-IWO model ranked first. With greatly reduced modeling error rate, the MLP-IWO is suggested as superior models in soil temperature modeling and may be extended to other aspect of soil science. Overall, new hybrid MLP-IWO methods showed the potential to estimate soil temperature from freely available meteorological data, which may help reduce costs and labour in the field and this model has provided as a high accurate model for estimation soil temperature.
Android Malicious App Detection Based on CNN Deep Learning Algorithm
Authors: He Peng , Gan Gang 
Published: January 2020

Abstract
In recent years, with the increasing number of Android applications, Android malicious apps have also increased exponentially. This paper proposes a detection scheme based on CNN deep learning algorithms. The scheme uses static analysis and detection methods. CNN deep learning algorithms have become very mature in the field of image classification. Therefore, this article uses a conversion algorithm to convert Android APK binary files to RGB PNG images, and then uses the algorithm to extract permissions in the APK, and converts the permission matrix to a transparency matrix, combines the previous RGB images, and finally generates RGBA images. RGBA images contain more information than RGB images, and the use of CNN deep learning algorithms works better and the final detection rate reaches 93.4%.
The Distribution of Precipitation and Rain Days over the Tianshan Mountains in Northwest of China
Authors: Zhao Chuancheng , Yao Shuxia , Li Qingfeng 
Published: January 2020

Abstract
Analysis of precipitation is important to hydrologists and forecasters over mountain, especially in the arid and semi-arid regions of the world. The distribution of precipitation and rain days are analyzed based on 31 stations during the period from 1960 to 2018 in Tianshan Mountains. The results is show that the precipitation and precipitation days is significantly affected by topography in Tianshan mountains. The pattern of precipitation is increased from southern to northern, from eastern to western. High precipitation and precipitation days are located in the Ili Valley. The precipitation and precipitation days are increase with elevation increase decrease with longitude increase. But, the relationship is different between precipitation and rain days with latitude in south and north slope over Tianshan mountains.
Fatigue Expression Recognition Algorithm Based on Reconstructed LBP-HOG (LBP-RHOG) Feature
Authors: Qi Yaru , Hu Binjie , Qiu Jinguang , Lin Huijiao 
Published: January 2020

Abstract
This paper aims at two problems in fatigue expression recognition. First, texture features extracted by LBP (Local Binary Patterns) descriptor are limited and can not effectively describe the edge and direction information of image. Second, structural features extracted by HOG (Histogram of Oriented Gradient) descriptor are redundant and its computational complexity is high. To fill the gaps of these two problems, we proposed a reconstructed LBPHOG (LBP-RHOG) algorithm which extracted texture spectrum features and edge features from LBP operator and reconstructed HOG operator respectively and obtain fusion information by fusing these two features. To better evaluate the recognition performance, we complete simulation under a self-built fatigue expression database. The results show that our method has low computational complexity and high recognition rate, and can identify fatigue state well.
Dynamic Distributed Algorithm for AP Association under User Random Arrivals and Departures
Authors: Chen Zhenwei , Zhang Wenjie , Yang Jingmin , Chen Shengyu , Yang Liwei , Chai Kiat Yeo 
Published: January 2020

Abstract
In this paper, we study the novel problem of optimizing AP association by maximizing the network throughput, subject to the degree bound of AP. The formulated problem is a combinatorial optimization. We resort to the Markov Chain approximation technique to design a distributed algorithm. We first approximate our optimal objective via Log-Sum-Exp function. Thereafter, we construct a special class of Markov Chain with steady-state distribution specify to our problem to yield a distributed solution. Furthermore, we extend the static problem setting to a dynamic environment where the users can randomly leave or join the system. Our proposed algorithm has provable performance, achieving an approximation gap of

1
η

log

|
F
|

. It is simple and can be implemented in a distributed manner. Our extensive simulation results show that the proposed algorithm can converge very fast, and achieve a close-to-optimal performance with a guaranteed loss bound.
A Ka-band Diode-Based Analog Predistortion Linearizer for Solid-State Power Amplifiers
Authors: Song Kexin , Lv Shengyang , Qin Zhifei , Xia Lei 
Published: January 2020

Abstract
In this paper, A coplanar waveguide transmission type analog predistorter for the Ka-band (29-31GHz) solid-state power amplifier is developed and tested. Two Schottky diodes are adopted symmetrically connected between the main line of the coplanar waveguide transmission line and ground used as non-linear signal generating device. The measured results of the fabricated structure exhibited a gain comprehension greater than 3dB and more than 20 degree phase comprehension capability over 2GHz of bandwidth. As a result, measured 1dB compression point of the power amplifier can be significantly improved by 4.9dB at 30GHz.
Spatial Pattern Analysis of Global Burned Area in 2005 Based on Landsat Satellite Images
Authors: Zhang Zhaoming , He Guojin , Long Tengfei , Tang Chao , Wei Mingyue , Wang Wei , Wang Guizhou 
Published: January 2020

Abstract
In this study, global annual burned area Map of 2005 (GABAM 2005) was generated based on all the available Landsat-5 satellite images between 2004 and 2005, using a machine learning algorithm (random forest) and Google Earth Engine (GEE) platform. Then spatial distribution pattern of global burned areas was analyzed. It is found that the total global burned area in 2005 was approximately 355.71×104km2yr−1, and Africa and South America had the largest burned areas among all the seven continents in the world, with burned areas of 241.76×104km2yr−1 and 34.90×104km2yr−1, accounting for 67.97%, and 9.81% of the global, respectively.
Research on General Model Library Framework of Substation Engineering
Authors: Guan Lan , Wang Wei , Hu Junhui , Zhang Yongzhi , Wang Hui , Yang Xiaoguang 
Published: January 2020

Abstract
The data format of the current substation 3D design results is inconsistent, and the data of different software platforms is not connected. For the problem of these, this paper analyzes the current status and mainstream data format of 3D design of substation comprehensively, and establishes a standard database framework that is suitable for substation engineering, which can ahieve cross-platform data integration and utilization, and provide a technical support for the formation of State Grid Corporation’s substation 3D design standardization model library.
PSO_LSSVM Prediction Model and Its MATLAB Implementation
Authors: Chen Lili , Duan Lei , Shi Yanjun , Du Chenwei 
Published: January 2020

Abstract
The particle swarm optimization (PSO) is added to a least squares support vector machine (LSSVM) prediction model, to achieve an objective optimization of parameters, thus globally optimizing the prediction model and improving the prediction accuracy of the model. According to the experimental results, the estimated values of the model are highly consistent with the actual values, which prove the validity of the prediction via the PSO_LSSVM model.
Effect of Bridge Pier Shape on Depth of Scour
Authors: Jalal Halah Kais , Hassan Waqed H. 
Published: January 2020

Abstract
Scour at bridge piers is a common problem in infrastructure engineering, as local scour around bridge piers is one of the most common causes of bridge failure. Prediction of the maximum depth of local scour thus plays an important role in ensuring safety and economy during design and maintenance. A computational fluid dynamics (CFD)-based simulation methodology for computing the depth of local scour around bridge piers using Flow-3D model is thus proposed in this study. The objective is to investigate the effects of the bridge pier shape on local scour in order to develop an optimal hydraulic design for minimum depth of scour. Local scouring around different shapes of pier (circular, rectangular, square, octagonal, elliptic, and lenticular) in non-cohesive bed sediment under clear water scour conditions was thus simulated for each pier shape at different of flow intensities, fluid depths, and pier sizes. By comparing the numerical results for predicted scour depth around a circular pier with the laboratory experimental results produced by Melville in 1975, the model was found to have about a 10% error rate for prediction of scour depth, demonstrating good agreement with experimental models. The model results revealed that the rectangular pier shape recorded the maximum depth of scour, while the minimum depth of scour was measured for the lenticular shape, this being about 40% lower than for other shapes. All factors investigated were found to have direct effect on scour but the most significant factor was pier width; scour reached its maximum depth value at pier width ratios of 0.2 in rectangular pier shapes; the results also showed that scour depth was comparatively higher upstream and lower downstream. Overall, the proposed numerical simulation Flow-3D method is a reliable tool for predicting and generating discussion of spatial influences on the bridge scour process.
A new physisorption power generation system using advanced adsorbent materials
Authors: Al-Mousawi Fadhel Noraldeen , Al-Dadah Raya , Mahmoud Saad 
Published: January 2020

Abstract
A large number of people worldwide lack access to secure power systems, particularly in developing countries. The abundant solar energy and waste heat energy can be used to generate electric power cleanly using absorption and adsorption systems to build small localized power generation units. The inclusion of a turbine within the physisorption system opens great opportunities to use low-grade and medium-grade heat sources, such as solar energy, geothermal energy and industrial waste heat, for power generation. In this numerical study, the water adsorption system for cooling and electricity (ASCE) is utilized for the first time to generate electric power only using advanced metal organic framework (MOF) materials. The main components of the physisorption power generation cycle (PPGC) are similar to those of ASCE, where the only difference is in the applied operating conditions. In PPGC, the water temperature entering the evaporator is relatively high, so that no cooling effect within the normal range can be obtained. This helps to increase the adsorption uptake in some adsorbent materials like MIL101-Cr, which increases the mass flow rate of the working fluid and improves the power generation process. According to these considerations, the two-bed PPGC system adopted in this study can generate electricity of up to 5.24 kW utilizing about 14.28 kg of MIL101-Cr with heating temperature of 320 ºC. This study highlights the potential of using advanced physical adsorbent materials like MOFs (e.g. MIL101-Cr) in power generation utilizing two-bed PPGC under a range of operating conditions.
Simulation of Triplex Tube Thermal Energy Storage System Using High Temperature Phase Change Material
Authors: Ghaffari Saeed , Ahmadi Rouhollah 
Published: January 2020

Abstract
To increase the capacity factor of a concentrated solar thermal power plant (CSTPP) beyond the hours of sunlight, the use of thermal energy storage systems (TES) can be a promising solution. Phase change materials (PCMs) can store latent thermal energy in the course of the melting process and release it when solar energy is not available. Generally, PCMs have low thermal conductivity. One of the most commercially promising solutions is the application of an extended heat transfer surface inside the PCM container. Moreover, the distance of the heat transfer fluid (HTF) to the core of the PCM in a TES system can affect the storage performance. Accordingly, a triplex tube heat exchanger with eight fins is considered in this paper, to investigate the impact of the different velocity of HTF and different entrance pattern in a vertical PCM container. Notably, the middle enclosure of the triplex tube is filled with PCM. Numerical analysis using an enthalpy porosity technique revealed that increasing HTF velocity reduces the charging time. Also, when the HTF enters from the bottom of the container, the storage time will diminish owing to a natural convection side-effect, but if the HTF flows downward, the amount of sensible thermal energy storage is higher than in the other cases.
Exergy Efficiency for Radiation Heat Transfer
Authors: Mohammed Hayder Noori , Mengüç M. Pinar 
Published: January 2020

Abstract
One of the evaluation criteria for the performance of thermal processes is exergy analysis. Along with energy analysis, exergy calculations provide a clear and highly effective understanding of the performance of a system. Although exergy analysis has been extensively applied to many industrial processes, there are limited works for solar energy conversion systems that include the details of radiation transfer. The use of the Carnot efficiency expressions for calculating the exergy received from the thermal radiation source is questionable because it neglects the directional and spectral aspects of radiation heat transfer. In this study, the exergy efficiency calculations for radiation heat transfer in energy conversion systems are discussed. Comparisons of different expressions for exergy efficiency are presented, and the effects of source and sink temperature variations are explored.
Assessment of Hamming Distance and Self Organization Map in Solving Cell Formation Problem
Authors: Hamza Sanaa A , Khalaf Ammar J 
Published: January 2020

Abstract
The cell formation (CF) problem is considered the most essential issue in cellular manufacturing systems (CMS). CF deals with the arrangement of similar parts into groups known as part families (PFs) and organizes machines also into groups, called machine cells (MCs). In the literature, numerous methods, models and algorithms have been proposed and developed to handle CF problems. However, very few studies have dealt with the assessment and comparison of these methods, to identify the most effective. This has provided strong motivation for the study presented here. The present paper focuses on two methods that are used infrequently to form MCs and PFs, and applies them in three strategies: the first is based on the use of a hamming distance only, while the second uses only a self-organization map (SOM). However, the third method applies a hybrid approach based on SOM and hamming distance. The outputs of the selected methods were compared, to select the best one. A set of five benchmark datasets and three performance measures was used for comparison and evaluation. These performance measures are: percent of the exceptional elements (PE), grouping efficiency (GE), and machine utilization (MU). The results refer to the outperforms of the hamming distance in terms of PE, GE and MU for most of the selected benchmark problems.
Genetic algorithm error criteria as applied to PID controller DC-DC buck converter parameters: an investigation
Authors: Chlaihawi A. A. 
Published: January 2020

Abstract
In this paper, the PID controller parameters of a DC-DC buck converter based on error criteria extracted by means of an applied genetic algorithm (GA)are studied. The GA-PID is designed with optimal parameters by minimising integral errors, and the application of these optimal parameters reduces transient response by minimising overshoot, rise time, peak time, and steady state time during step response. The simulation testing was done in MATLAB, and the performance of the proposed GA-PID method was investigated by the simulation of two different plants. The transfer function of the third order system was initially used as a primary simulation for the proposed method, while DC-DC buck converters were used in the second simulation. The results obtained demonstrate the feasibility of employing genetic algorithms to generate optimal parameters for PID controllers for the further development of DC-DC buck converters.
Cognitive neuroscience techniques in determining the right time of advertising
Authors: Alsakaa Akeel A. , Borawska Anna , Borawski Mariusz , Łatuszyńska Małgorzata , Piwowarski Mateusz , Babiloni‖ Fabio , Nermend Kesra 
Published: January 2020

Abstract
Cognitive neuroscience techniques are used in many different domains. Among them is marketing research. The general assumption driving such research is that human brain activity can provide marketers with information that cannot be obtained otherwise. The aim of this article is to show, how cognitive neuroscience techniques and neurometrics can be helpful in determining the appropriate time for advertising a product. The study was conducted with the use of the advertisement for dietary supplement enhancing the cognitive abilities. The experiment presented in the paper consists of two parts. The first one was conducted two months before the exams and the second one - during exams It was arranged this way to check, if the students would show more interest in the advertisement when they have examinations (in the “right” time) and if the neurometric indexes are able to capture such interest by showing statistically significant difference between these two periods.
Discrimination between Healthy and Unhealthy Mole Lesions using Artificial Swarm Intelligence
Authors: Aljanabi Mohanad , Abed Jameel Kaduim , Abd H.J. , Duhis Ahmed Hussein , Abdallh Ammar O. , Alanı Nadia 
Published: January 2020

Abstract
In recent years, occurrence rates of skin melanoma have shown a rapid increase, resulting in enhancements to death rates. Based on the difficulty and subjectivity of human clarification, computer examination of dermoscopy images has thus developed into a significant research field in this area. One the reasons for applying heuristic methods is that good solutions can be developed with only reasonable computational exertion. This paper thus presents an artificial swarm intelligence method with variations and suggestions. The proposed artificial bee colony (ABC) is a more suitable algorithm in comparison to other algorithms for detecting melanoma in the skin tumour lesions, being flexible, fast, and simple, and requiring fewer adjustments. These is characteristics are recognized assisting dermatologists to detect malignant melanoma (MM) at the lowest time and effort cost. Automatic classification of skin cancers by using segmenting the lesion’s regions and selecting of the ABC technique for the values of the characteristic principles allows. Information to be fed into several well-known algorithms to obtain skin cancer categorization: in terms of whether the lesion is suspicious, malignant, benign (healthy and unhealthy nevi). This segmentation approach can further be utilized to develop handling and preventive approaches, thus decreasing the danger of skin cancer lesions. One of the most significant stages in dermoscopy image examination is the segmentation of the melanoma. Here, various PH2 dataset image were utilized along with their masks to estimate the accuracy, sensitivity, and specificity of various segmentation techniques. The results show that a modified automatic based on ABC images have the highest accuracy and specificity compares with the other algorithms. The results show that a modified automatic based on ABC images displayed the highest accuracy and specificity in such testing.
A high gain microstrip antenna based on substrate integrated waveguide technology for modern wireless communication
Authors: Abd Almuhsan Murooj A. , Salim A J , Ali J K 
Published: January 2020

Abstract
An antenna based on a Substrate Integrated Waveguide (SIW) is proposed in this paper as suitable for modern wireless applications. The presented antenna is formed of two elements; an active and a passive. The active element is directly connected to the feeding line while the passive element, which consists of three segments, is energised by coupling with the active element by a means of a gap. Dimensions of each segment is 3.63 × 19.5 mm2. It was found that the antenna resonates at 16.98 GHz and has an impedance bandwidth of 985 MHz with a reflection coefficient of -35 dB. An overall gain of 9.44 dBi was further achieved with a total area of 30 × 23.5 mm2. A substrate of Rogers Duroid 5880 with relative permittivity of 2.2 and thickness of 0.787 mm is adopted for the design of this antenna. Designing and simulating the antenna accomplished using the Microwave Studio Suite of Computer Simulation Technology (CST) simulator.