Improved Twin Support Vector Machine Algorithm and Applications in Classification Problems

The distribution of data has a significant impact on the results of classification.When the distribution of one class is insignificant compared to the distribution of another class,data imbalance occurs.This will result in rising outlier values and noise.Therefore,the speed and performance of classification could be greatly affected.Given the above problems,this paper starts with the motivation and mathematical representing of classification,puts forward a new classification method based on the relationship between different classification formulations.Combined with the vector characteristics of the actual problem and the choice of matrix characteristics,we firstly analyze the orderly regression to introduce slack variables to solve the constraint problem of the lone point.Then we introduce the fuzzy factors to solve the problem of the gap between the isolated points on the basis of the support vector machine.We introduce the cost control to solve the problem of sample skew.Finally,based on the bi-boundary support vector machine,a twostep weight setting twin classifier is constructed.This can help to identify multitasks with feature-selected patterns without the need for additional optimizers,which solves the problem of large-scale classification that can’t deal effectively with the very low category distribution gap.

Study on the Use of Artificial Intelligence for Cybersecurity in Companies: Case of Companies in Burkina Faso

Poorly secured connected objects can compromise the security of an entire company, or even paralyze others. As useful as they are, they can be open doors for computer attacks against the company. To protect themselves, large companies set up expensive infrastructures to analyze the data that circulates inside and outside the company. They install a SOC, a Security Operation Center whose objective is to identify and analyze, using various tools, the level of protection of a company and, if necessary, to alert on vulnerabilities and leaks of security data. However, the attack detection capabilities of traditional systems are based on a base of known signatures. Problem is that it is increasingly rare to have to face threats whose signature is unknown. Artificial intelligence, on the contrary, does not look for fingerprints in the packets carrying the attack, but rather analyzes how these packets are arranged. The objective of this study is to show that the use of artificial intelligence in companies may be low and to show the positive impacts of its use compared to the traditional system used in companies. We also simulate an attack on a system equipped with artificial intelligence to highlight the advantages of AI in a computer attack. This research is important because it highlights the risks that companies expose themselves to by always remaining secure in their systems based on traditional techniques. The aim of this research is to show the advantages that AI offers on cyber security compared to the traditional security system. The expected result is to show the existing issues regarding the rate of use of AI on cybersecurity in Burkina Faso. .

Novel PAPR Reduction Scheme Based on Continuous Nonlinear Piecewise Companding Transform for OFDM Systems

In this paper,a novel efficient continuous piecewise nonlinear companding scheme is proposed for reducing the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)systems.In the proposed companding transform,signal samples with large amplitudes is clipped for peak power reduction,and the signal samples with medium amplitudes is nonlinear transformed with power compensation.While the signal samples with small amplitudes remain unchanged.The whole companding function is continuous and smooth in the range of positive numbers,which is beneficial for guaranteeing the bit error rate(BER)and power spectral density(PSD)performance.This scheme can achieve a significant reduction in PAPR.And at the same time,it cause little increment in BER and PSD performance.Simulation results indicate the superiority of the proposed scheme over existing companding schemes.

Polarization visualization for low-irradiance regions by perceptually uniform color space

Currently,polarization visualization strategies are accomplished by mapping polarization information into a perceptually uniform color appearance model CAM02-UCS.However,the deviation of the CAM02-UCS space from the lightness prediction results in an inaccurate match between the polarization information and the perceptual information.In this paper,we propose a novel polarization visualization strategy based on the perceptual uniform space Jzazbz.The polarization visualization be completed by placing the polarization information into the lightness Jz,colorfulness Cz and hue angle hz channels of the Jzazbz space.The experimental results show that the proposed method can significantly improve the lightness of the low irradiance and high polarization region,hence more polarization information can be sensed by human visual system.

Gauge Dependence of On-Shell and Pole Mass Renormalization Prescriptions

我们在在壳上和杆团重正常化药方下面讨论物理参数的定义的计量器依赖。由 two-loop-level 计算，我们第一次证明在壳上团重正常化药方做物理结果计量器依赖者。在另一方面，如此的计量器依赖不出现在杆团重正常化药方的结果。我们的计算也显示出在壳上团重正常化药方导致的计量器依赖不能在二环的水平被忽视。

Research and Practice of Traffic Lights and Traffic Signs Recognition System Based on Multicore of FPGA

This thesis will present the research and practice of traffic lights and traffic signs recognition system based on multicore of FPGA. This system consists of four parts as following: the collection of dynamic images, the preprocessing of gray value, the detection of the edges and the patterning and the judgment of the pattern matching. The multiple cores system is consist of three cores. Each core parallels processes the incoming images from camera collection in terms of different colors and graphic elements. The image data read in from the camera works as the sharing data of the three cores.

A New Method for Sensing Cognitive Radio Network under Malicious Attacker

Cognitive radio has been designed for solving the problem of spectrum scarcity by using the spectrum of primary users who don’t use their spectrum on that time. For sensing the spectrum, collaborative spectrum sensing has been utilized because of robustness. In this paper, a new collaborative spectrum method is proposed based on Least Mean Square (LMS) algorithm. In this scheme, the weights of secondary users were updated in time and finally the sensing results were combined in the fusion center based on their trusted weights. Simulation results show that the proposed scheme can significantly reduce the effects of Spectrum Sensing Data Falsification (SSDF) attackers, when they are smart malicious, and even percentage of malicious users are more than trusted users.

Study on the Instability of Information Systems and Security Risks in the Public Administration: Case of Burkina Faso Public Administration

The purpose of this research is to show the instability and the security risks of the information system in Burkina-Faso public administration. In this paper, witnessing unsatisfactory services such as government messaging (mailer.gov.bf) as well as G-cloud services which are the government cloud were studied. The behavior of user agents on the administration’s IT infrastructures which could expose the information system to security risks was also studied. The expected result shows evidence of the weakness of the public administration information system and provides some recommendation.

A Novel Dynamic Bandwidth Assignment Algorithm for Multi-Services EPONs

In this paper we propose a novel Dynamic Bandwidth Assignment （DBA） algorithm for Ethernet-based Passive Optical Networks （EPON） which offers multiple kinds of services. To satisfy crucial Quality of Service （QoS） requirement for Time Division Multiplexing （TDM） service and achieve fair and high bandwidth utilization simultaneously, the algorithm integrates periodic, for TDM service, and polling granting for Ethernet service. Detailed simulation shows that the algorithm guarantees carrier-grade QoS for TDM service, high bandwidth utilization and good fairness of bandwidth assignment among Optical Network Units （ONU）.

Advances in metal halide perovskite lasers: synthetic strategies, morphology control, and lasing emission

.In the past decade,lead halide perovskites have emerged as potential optoelectronic materials in the fields of light-emitting diode,solar cell,photodetector,and laser,due to their low-cost synthesis method,tunable bandgap,high quantum yield,large absorption,gain coefficient,and low trap-state densities.In this review,we present a comprehensive discussion of lead halide perovskite applications,with an emphasis on recent advances in synthetic strategies,morphology control,and lasing performance.In particular,the synthetic strategies of solution and vapor progress and the morphology control of perovskite nanocrystals are reviewed.Furthermore,we systematically discuss the latest development of perovskite laser with various fundamental performances,which are highly dependent on the dimension and size of nanocrystals.Finally,considering current challenges and perspectives on the development of lead halide perovskite nanocrystals,we provide an outlook on achieving high-quality lead perovskite lasers and expanding their practical applications.

A New Enhanced Fast Handover Algorithm in Hierarchical Mobile IPv6 Network

Hierarchical Mobile IPv6 (HMIPv6) can reduce the delay and the amount of signaling during handover compared with the basic mobile IPv6. However, the protocol still cannot meet the requirement for traffic that is delay sensitive, such as voice, especially in macro mobility handover. Duplicate address detection and the transmission time for the handover operation could cause high handover delay. This paper proposes a new mechanism to improve the fast handover algorithm’s efficiency in HMIPv6 network. And we present and analyze the performance testing for our proposal by comparing it with the traditional HMIPv6 fast handover algorithm. The results of simulation show that our scheme can reduce the handover delay much more than the traditional fast handover method for HMIPv6 network.

Procreating Tiles of Double Commutative-Step Digraphs

Double commutative-step digraph generalizes the double-loop digraph. A double commutative-step digraph can be represented by an L-shaped tile, which periodically tessellates the plane. Given an initial tile L（l, h, x, y）, Aguil5 et al. define a discrete iteration L（p） = L（l ＋ 2p, h ＋ 2p, x ＋ p, y ＋ p）, p = 0, 1, 2,..., over L-shapes （equivalently over double commutative-step digraphs）, and obtain an orbit generated by L（l, h, x,y）, which is said to be a procreating k-tight tile if L（p）（p = 0, 1, 2, ~ ~ ~ ） are all k-tight tiles. They classify the set of L-shaped tiles by its behavior under the above-mentioned discrete dynamics and obtain some procreating tiles of double commutative-step digraphs. In this work, with an approach proposed by Li and Xu et al., we define some new discrete iteration over L-shapes and classify the set of tiles by the procreating condition. We also propose some approaches to find infinite families of realizable k-tight tiles starting from any realizable k-tight L-shaped tile L（l, h, x, y）, 0 ≤ y - x ≤ 2k ＋ 2. As an example, we present an infinite family of 3-tight optimal double-loop networks to illustrate our approaches.

陕西省生产性服务业与制造业协同集聚研究

随着全球经济发展的加速和现代产业的演进,生产性服务业与制造业的互动成为区域发展研究中的一个重要方面。目前,在新型工业化时期,在工业化与信息化的紧密融合、生产型制造向服务型制造转变的时代背景下,研究陕西省如何做到生产性服务业与制造业的互动发展,具有非常重要的理论价值和现实意义。