Optimizing Grey Wolf Optimization: A Novel Agents’ Positions Updating Technique for Enhanced Efficiency and Performance

Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of the agents’ positions relative to the leader wolves. In this paper, we provide a brief overview of the Grey Wolf Optimization technique and its significance in solving complex optimization problems. Building upon the foundation of GWO, we introduce a novel technique for updating agents’ positions, which aims to enhance the algorithm’s effectiveness and efficiency. To evaluate the performance of our proposed approach, we conduct comprehensive experiments and compare the results with the original Grey Wolf Optimization technique. Our comparative analysis demonstrates that the proposed technique achieves superior optimization outcomes. These findings underscore the potential of our approach in addressing optimization challenges effectively and efficiently, making it a valuable contribution to the field of optimization algorithms.

Generation and Control of Game Virtual Environment

In this paper, we present a framework for the generation and control of an Internet-based 3-dimensional game virtual environment that allows a character to navigate through the environment. Our framework includes 3-dimensional terrain mesh data processing, a map editor, scene processing, collision processing, and walkthrough control. We also define an environment-specific semantic information editor, which can be applied using specific location obtained from the real world. Users can insert text information related to the characters real position in the real world during navigation in the game virtual environment.

Phonons near Peierls Structural Transition in Quasi-One-Dimensional Organic Crystals of TTF-TCNQ

The Peierls structural transition in quasi-one-dimensional organic crystals of TTF-TCNQ is investigated in the frame of a more complete physical model. The two most important electron-phonon interaction mechanisms are taken into account simultaneously. One is similar of that of deformation potential and the other is of polaron type. For simplicity, the 2D crystal model is considered. The renormalized phonon spectrum and the phonon polarization operator are calculated in the random phase approximation for different temperatures. The effects of interchain interaction on renormalized acoustic phonons and on the Peierls critical temperature are analyzed.

Optimal Tuning of FOPID-Like Fuzzy Controller for High-Performance Fractional-Order Systems

This paper addresses improvements in fractional order(FO)system performance.Although the classical proportional-integral-derivative(PID)-like fuzzy controller can provide adequate results for both transient and steady-state responses in both linear and nonlinear systems,the FOPID fuzzy controller has been proven to provide better results.This high performance was obtained thanks to the combinative benefits of FO and fuzzy-logic techniques.This paper describes how the optimal gains and FO parameters of the FOPID controller were obtained by the use of a modern optimizer,social spider optimization,in order to improve the response of fractional dynamical systems.This group of systems had usually produced multimodal error surfaces/functions that occasionally had many variant local minima.The integral time of absolute error(ITAE)used in this study was the error function.The results showed that the strategy adopted produced superior performance regarding the lowest ITAE value.It reached a value of 88.22 while the best value obtained in previous work was 98.87.A further comparison between the current work and previous studies concerning transient-analysis factors of the model’s response showed that the strategy proposed was the only one that was able to produce fast rise time,low-percentage overshoot,and very small steady-state error.However,the other strategies were good for one factor,but not for the others.

Performance Analysis of an Autoconfiguration Addressing Protocol for Ad Hoc Networks

Autoconfiguration protocols are important in maintaining mobile ad hoc networks (MANETs). In this paper, we present an autoconfiguration protocol called the one-step addressing (OSA) protocol characterized by its simplicity. Mathematical model is developed to evaluate the performance of the proposed protocol. The results of the model, which are validated by the simulation results, show that the OSA protocol outperforms the well-known token-based protocol in terms of both latency and communications overhead.

Effect of Absorption of Patch Antenna Signals on Increasing the Head Temperature

Every new generation of antennas is characterized by increased accuracy and faster transmission speeds.However,patch antennas have been known to damage human health.This type of antenna sends out electromagnetic waves that increase the temperature of the human head and prevent nerve strands from functioning properly.This paper examines the effect of the communication between the patch antenna and the brain on the head’s temperature by developing a hypothetical multi-input model that achieves more accurate results.These inputs are an individual’s blood and tissue,and the emission power of the antenna.These forces depend on the permeability and conductivity characteristics of the metal from which the antenna is fabricated.The proposed model is the first one that links the material the antenna is manufactured from and the head’s temperature.The results show that there are only a small number of materials that should be used as antenna covers.These materials are in the form of thin films.By using these thin films at different temperatures,the risk to the head can be reduced.This paper finds that the best results were obtained when the patch antenna was made of one of the following materials operating at a specific temperature:traditional materials at 305°K;casting cast steel at around 295°K;bismuth telluride(Bi2Te3)at 290°K;or barium sodium niobate at 310°K.

Metal-Insulator Transition of Peierls Type in Quasi-One-Dimensional Crystals of TTT₂I₃

We investigate the metal-insulator transition in quasi-one-dimensional organic crystals of tetrathiotetracene-iodide, TTT2I3, in the 2D model. A crystal physical model is applied which takes into account two the most important hole-phonon interaction mechanisms. One is similar to that of deformation potential and the other is of polaron type. The scattering on defects is also considered and it is crucial for the explanation of the transition. The phonon polarization operator and the renormalized phonon spectrum are calculated in the random phase approximation for different temperatures applying the method of Green functions. We show that the transition is of Peierls type. The effect of lattice distortion on the dispersion of renormalized acoustic phonons is analyzed.

Coupling of Serendipity, Affordance and Taxonomy in Digital Competence: HCI for Illiterates

This research work is the result of multidisciplinary research for the design of a digital learning tool from the basic level. Computer science guarantees the technical concepts of the development of the tool. At the same time, Information and Communication Science discipline describes the concepts of cognitive psychology with digital competence in computerization. The overall goal of this work is to provide an HCI component for basic level learning or HCI for the illiterate. It is about transforming a communication tool from a cognitive system to a digital learning tool adapted to the learner’s level of digital competence. The author relies on the UML class diagram to identify the affordance and serendipity of HCI property entities. The mathematical study of the similarity between these two properties allows us to update the learner’s profile. Stephanie’s approach was used when managing the learner’s profile and the digital competency taxonomy to classify the learner’s level of digital use. The principle of an expert system was taken up in this work to make the decision on the level of digital competence of the learner and to guide the solution so that the learning continues without interruption. This expert system integrates the data science of digital educational materials, defining its specificity. The algorithm of the realization summarizes the implementation of the whole approach. αβGasy@mobile is an application on Android for Malagasy language literacy. To learn the letter “l” with this application, the initially low-level learner had an intermediate assessment score after 2 hours of continuous learning. Self-constructivism has been developed and strengthened by the HCI illiterate component. We have hundreds of learners for the case study and used ten smartphones to 5 inches. On the selected samples, the results of the experiment are close to our objective. More precisely, the inactive time is almost non-existent, the learning time predefined in the system is close to reality, and the speed of return on the interaction is fluid while the evaluation is notified.

Neuro-Based Higher Order Sliding Mode Control for Perturbed Nonlinear Systems

One of the great concerns when tackling nonlinear systems is how to design a robust controller that is able to deal with uncertainty.Many researchers have been working on developing such type of controllers.One of the most effi-cient techniques employed to develop such controllers is sliding mode control(SMC).However,the low order SMC suffers from chattering problem which harm the actuators of the control system and thus unsuitable to be used in many practical applications.In this paper,the drawbacks of low order traditional sliding mode control(FOTSMC)are resolved by presenting a novel adaptive radial basis function neural network–based generalized rth order sliding mode control strategy for nth order uncertain nonlinear systems.The proposed solution adopts neural networks for their excellent capability in function approximation and thus used to approximate the nonlinearities and uncertainties for systems under considera-tion.The approximation errors are completely considered in the developed approach.The proposed approach can be used with any order of sliding mode and thus can be generally used with various types of applications.The global sta-bility of the proposed control approach is proved through Lyapunov stability cri-terion.The proposed approach is validated and assessed through simulations on the nonlinear inverted pendulum system with severe modeling uncertainties.The simulations results show that the proposed approach provide superior perfor-mance compared with other approaches in the literature.

Model of fractured medium and nondestructive control of composite materials

Non-destructive testing of composites is an important issue in the modern aircraft industry.Composites are susceptible to the barely visible impact damage which can affect the residual strength of the material and occurs both during production and operation.The continuum model for describing the damaged zone is presented.The slip theory relations used for a continuous distribution of slip planes are applied.At the initial stage,the isotropic background model is used.This model allows the material slippage along the fractures based on the Coulomb friction law with the small viscous addition.In this regime,the govern system of equations becomes rigid.To overcome this difficulty,the explicit-implicit grid-characteristic scheme is proposed.The standard ultrasound diagnostic procedure of damaged composite materials is successfully simulated.Compared with the trivial free-surface fracture model,different reactions on the compression and stretch waves are registered.This approach provided an effective way for the simulation of complex dynamic behavior of damage zones.

HLR-Net: A Hybrid Lip-Reading Model Based on Deep Convolutional Neural Networks

Lip reading is typically regarded as visually interpreting the speaker’s lip movements during the speaking.This is a task of decoding the text from the speaker’s mouth movement.This paper proposes a lip-reading model that helps deaf people and persons with hearing problems to understand a speaker by capturing a video of the speaker and inputting it into the proposed model to obtain the corresponding subtitles.Using deep learning technologies makes it easier for users to extract a large number of different features,which can then be converted to probabilities of letters to obtain accurate results.Recently proposed methods for lip reading are based on sequence-to-sequence architectures that are designed for natural machine translation and audio speech recognition.However,in this paper,a deep convolutional neural network model called the hybrid lip-reading(HLR-Net)model is developed for lip reading from a video.The proposed model includes three stages,namely,preprocessing,encoder,and decoder stages,which produce the output subtitle.The inception,gradient,and bidirectional GRU layers are used to build the encoder,and the attention,fully-connected,activation function layers are used to build the decoder,which performs the connectionist temporal classification(CTC).In comparison with the three recent models,namely,the LipNet model,the lip-reading model with cascaded attention(LCANet),and attention-CTC(A-ACA)model,on the GRID corpus dataset,the proposed HLR-Net model can achieve significant improvements,achieving the CER of 4.9%,WER of 9.7%,and Bleu score of 92%in the case of unseen speakers,and the CER of 1.4%,WER of 3.3%,and Bleu score of 99%in the case of overlapped speakers.

Black Hole and Sink Hole Attack Detection in Wireless Body Area Networks

In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.

Gauge Model Based on Group G×SU（2）

We present a model of gauge theory based on the symmetry group G×SU（2） where G is the gravitational gauge group and SU（2） is the internal group of symmetry. We employ the spacetime of four-dimensional Minkowski, endowed with spherical coordinates, and describe the gauge fields by gauge potentials. The corresponding strength field tensors are calculated and the field equations are written. A solution of these equations is obtained for the case that the gauge potentials have a particular form potentials induces a metric of Schwarzschild type on with spherical symmetry. The solution for the gravitational the gravitational gauge group space.

An Adaptive Real-Time Third Order Sliding Mode Control for NonlinearSystems

As most real world systems are significantly nonlinear in nature,developing robust controllers have attracted many researchers for decades.Robust controllers are the controllers that are able to cope with the inherent uncertainties of the nonlinear systems.Many control methods have been developed for this purpose.Sliding mode control(SMC)is one of the most commonly used methods in developing robust controllers.This paper presents a higher order SMC(HOSMC)approach to mitigate the chattering problem of the traditional SMC techniques.The developed approach combines a third order SMC with an adaptive PID(proportional,integral,derivative)sliding surface to overcome the drawbacks of using PID controller alone.Moreover,the presented approach is capable of adaptively tuning the controller parameters online to best fit the real time applications.The Lyapunov theory is used to validate the stability of the presented approach and its feasibility is tested through a comparison with other conventional SMC approaches.

基于图像均匀区域的打印技术鉴定方法

0引言文件在财政、法律、社会和个人生活方面都有很重要的作用。文件任何部分的更改都将改变文件的含义。涉嫌欺诈或来源不明的文件被称为问题文件。作为交易的法律证据,证明文件的真实性是必要的。对于打印出来的问题文件,鉴定专员需要从打印机或问题文件的源文件开始进行检验。用来检验一份文件是否被更改的常用仪器有高分辨率显微镜、静电检测仪（ESDA）和视频光谱比较仪（VSC）。高分辨率显微镜如Leica MZ8、Leica MZ12.5,用来检测文件上的图案。ESDA是一种用来显示纸张上锯齿图像的无损检测技术。

Validation of static properties in unified modeling language models for cyber physical systems

Cyber physical systems (CPSs) can be found nowadays in various fields of activity. The increased interest for these systems as evidenced by the large number of applications led to complex research regarding the most suitable methods for design and development. A promising solution for specification, visualization, and documentation of CPSs uses the Object Management Group (OMG) unified modeling language (UML). UML models allow an intuitive approach for embedded systems design, helping end-users to specify the requirements. However, the UML models are represented in an informal language. Therefore, it is difficult to verify the correctness and completeness of a system design. The object constraint language (OCL) was defined to add constraints to UML, but it is deficient in strict notations of mathematics and logic that permits rigorous analysis and reasoning about the specifications. In this paper, we investigated how CPS applications modeled using UML deployment diagrams could be formally expressed and verified. We used Z language constructs and prototype verification system (PVS) as formal verification tools. Considering some relevant case studies presented in the literature, we investigated the opportunity of using this approach for validation of static properties in CPS UML models.