Potential Benefits and Obstacles of the Use of Internet of Things in Saudi Universities: Empirical Study

Internet of Things (IoT) among of all the technology revolutions has been considered the next evolution of the internet. IoT has become a far more popular area in the computing world. IoT combined a huge number of things (devices) that can be connected through the internet. The purpose: this paper aims to explore the concept of the Internet of Things (IoT) generally and outline the main definitions of IoT. The paper also aims to examine and discuss the obstacles and potential benefits of IoT in Saudi universities. Methodology: the researchers reviewed the previous literature and focused on several databases to use the recent studies and research related to the IoT. Then, the researchers also used quantitative methodology to examine the factors affecting the obstacles and potential benefits of IoT. The data were collected by using a questionnaire distributed online among academic staff and a total of 150 participants completed the survey. Finding: the result of this study reveals there are twelve factors that affect the potential benefits of using IoT such as reducing human errors, increasing business income and worker’s productivity. It also shows the eighteen factors which affect obstacles the IoT use, for example sensors’ cost, data privacy, and data security. These factors have the most influence on using IoT in Saudi universities.

Path-Following Control With Obstacle Avoidance of Autonomous Surface Vehicles Subject to Actuator Faults

This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.

A Lightweight UAV Visual Obstacle Avoidance Algorithm Based on Improved YOLOv8

The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.

Stepping up after spinal cord injury:negotiating an obstacle during walking

Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles.After spinal cord injury,stepping over an obstacle becomes challenging.Stepping over an obstacle requires sensorimotor transformations in several structures of the brain,including the parietal cortex,premotor cortex,and motor cortex.Sensory information and planning are transformed into motor commands,which are sent from the motor cortex to spinal neuronal circuits to alter limb trajectory,coordinate the limbs,and maintain balance.After spinal cord injury,bidirectional communication between the brain and spinal cord is disrupted and animals,including humans,fail to voluntarily modify limb trajectory to step over an obstacle.Therefore,in this review,we discuss the neuromechanical control of stepping over an obstacle,why it fails after spinal cord injury,and how it recovers to a certain extent.

Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells

This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Effects of Continuous Cropping on Soil Microbial Flora and Research Progress of Continuous Cropping Obstacle Reduction Techniques

Continuous cropping can bring economic benefits in a short time and meet the growing demand of agricultural products such as grain,but long-term continuous cropping will accelerate soil degradation,lead to the reduction of crop yield and the increase of disease rate,and destroy the balance of soil microbial structure.Therefore,it is not conducive to the sustainable development of soil ecosystem.In this paper,the problems caused by continuous cropping,such as imbalance of soil microbial flora,decrease of biodiversity,accumulation of root exudates and their effects on soil fertility and crop growth,were summarized,and some measures were suggested to alleviate the obstacles of continuous cropping,such as reasonable rotation,adjustment of intercropping planting mode and application of biological fertilizers.Moreover,the paper also looked forward to the development trend of continuous cropping obstacle reduction techniques,including the integration and application of biological techniques,the promotion of green ecological techniques and the application of intelligent management system.This study provides theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promote the healthy and sustainable development of modern agriculture.

Impact of Continuous Cropping on Soil Phenolic Acid Substances and Research Progress on Continuous Cropping Obstacle Reduction Techniques

At present,long-term continuous cropping in agricultural production has formed a relatively common development trend.With the increase of continuous cropping years,soil phenolic acids are also affected to varying degrees.This paper summarized the effects of continuous cropping on soil phenolic acids and the research progress of continuous cropping obstacle reduction techniques,aiming at providing theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promoting the healthy and sustainable development of modern agriculture.

Analysis of the Causes of Continuous Cropping Obstacles for Atractylodes macrocephala Koidz in Pingjiang County and Its Control Methods

First at all, it introduced the concept and the damages of continuous cropping obstacle. Then, it analyzed the causes of continuous cropping obstacles for Atractylodes macrocephala Koidz. In the end, in order to provide guidance for pro- moting sustainable development of Atractylodes macrocephala Koidz industry in Pingjiang County, it put forward some control methods for eliminating continuous cropping obstacles of Atractylodes macrocephala Koidz, including breeding varieties with high resistance; applying rotation cropping and intercropping reasonable; rational fertilization and soil disinfection; introducing antagonistic bacterial and eliminating au- tointoxication.

The Obstacles and Solutions to Improving Non English-major Students' Listening Comprehension

Listening has been playing an essential role in daily communication.However,listening is the most difficult part and has been an obstacle in the process of learning English for most of learners for a variety of reasons.The paper mainly discusses the linguistic and non—linguistic obstacles in the process of listening and aims to help English learners find out their own shortcomings and put forward some corresponding solutions to improve learners' listening ability.

A Research on Middle School Students'English Reading Obstacles and Strategies

English reading,a key procedure of English learning and teaching in middle school,is an essential way of getting information from the globe and communicating with others.Therefore,efficient comprehension on reading materials will directly serve for accepting the information.And it is extremely important for middle school students to acquire certain reading ability.At present,great attention has been paid to the course of reading in the instruction of English by the Chinese Education Department.But middle school students'read ing ability is still much lower than the target they should reach because of a set of existing obstacles that prevent them from being effective English readers.What are these obstacles? How to break them down? This paper will first point out and then analyze the obstacles that af fect middle school students'reading ability from two aspects:linguistic obstacles(obstacles of lexicon,grammar and background knowl edge) and non-linguistic obstacles(obstacles of psychology,interest,skill,and habit).After demonstrating different obstacles,the paper also come up with some corresponding strategies in the hope of helping middle school students to be effective English readers.

The Obstacles in Cross-cultural Communication

In Cross-cultural communication,the ability of the languages and the ability of the cultures are the crucial factors in the communicating activities.People with the same cultural background communicate with each other easily and smoothly,and understand each other better,and there are fewer or no obstacles in their communication at all.The different cultural backgrounds and traditions,the different social customs and everyday living habits,and the different values all will affect the communication quality and will surely result in obstacles in cross-cultural communication. The obstacles which frequently occur in the cross-cultural communication are:ethnocentrism,stereotyping, prejudice,and the different cultural backgrounds.In order to do away with the obstacles and to make the communication smoothly and successfully,the communicating parties both should observe the cooperative principles and politeness principles.And what's more,they must discard their own prejudices,and respect others,together to fulfill the cross-cultural communicating activities.

Application of A* Algorithm for Real-time Path Re-planning of an Unmanned Surface Vehicle Avoiding Underwater Obstacles

This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle(USV) based on multi-beam forward looking sonar(FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom(surge and yaw). In this paper, two-dimensional(2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System(GPS) of the USV.

Effects of Obstacles on Flame Propagation Behavior and Explosion Overpressure Development During Gas Explosions in a Large Closed Tube

AutoReaGas was used for the simulations of premixed gas/air mixtures explosion characteristics in obstacle-filled tubes with a cross-section of 0.2 m×0.2 m and the length of 28 m. Numerical analyses provide a quantitative description of dependence of flame propagation speed and explosion overpressure on obstacles number, blockage ratio and interval distance. Computational results indicate that the obstacles play a significant role in determining the flame transmission speed and explosion overpressure in gas explosions. With the increase of blockage ratio, the explosion overpressure gradually rises. Nevertheless, the flame speed does not always increase along with increasing blockage ratio, but subsequently begins to decrease as the blockage ratio increases to some extend. Also, the interval distance between obstacles strongly influences flame behavior and explosion overpressure. When the obstacle interval distance is equal to inner diameter of the tube, the average flame speed in the obstacle zone and the peak overpressure in tube all reach maximum values.

Method for Six-Legged Robot Stepping on Obstacles by Indirect Force Estimation

Adaptive gaits for legged robots often requires force sensors installed on foot-tips,however impact,temperature or humidity can affect or even damage those sensors.Efforts have been made to realize indirect force estimation on the legged robots using leg structures based on planar mechanisms.Robot Octopus III is a six-legged robot using spatial parallel mechanism（UP-2UPS） legs.This paper proposed a novel method to realize indirect force estimation on walking robot based on a spatial parallel mechanism.The direct kinematics model and the inverse kinematics model are established.The force Jacobian matrix is derived based on the kinematics model.Thus,the indirect force estimation model is established.Then,the relation between the output torques of the three motors installed on one leg to the external force exerted on the foot tip is described.Furthermore,an adaptive tripod static gait is designed.The robot alters its leg trajectory to step on obstacles by using the proposed adaptive gait.Both the indirect force estimation model and the adaptive gait are implemented and optimized in a real time control system.An experiment is carried out to validate the indirect force estimation model.The adaptive gait is tested in another experiment.Experiment results show that the robot can successfully step on a 0.2 m-high obstacle.This paper proposes a novel method to overcome obstacles for the six-legged robot using spatial parallel mechanism legs and to avoid installing the electric force sensors in harsh environment of the robot＇s foot tips.

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However,less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.

Methods for Teachers to Eliminate Lexical Obstacles to Reading Comprehension in High School

Reading comprehension is important for both teacher and students in high school.And there is a phenomenon in stu dents when they do the reading comprehension.If word recognition is difficult,students use too much of their time to read and understand the individual words,which interferes with their ability to comprehend what is read and waste too much of their time in the examination.This makes the comprehension difficult for high school students.The paper focuses on the methods for teach ers to eliminate lexical obstacles to reading comprehension in high school.

Assessment of Potential Aerodrome Obstacles on Flight Safety Operations Using GIS: A Case of Murtala Mohammed International Airport, Lagos-Nigeria

The study focuses on the spatial analysis of the threat of potential Aerodrome obstacles on flight safety operations, in Murtala Mohammed Airport, Ikeja Lagos State. The study arises from the cases of flight safety in Nigerian airports which begins from the time passengers board the flight to the take-off time and location, the taxing of the plane and ends at the landing. The research employs GIS to model the 3D obstacles of the aerodrome, which demonstrated the ability in classifying the various threats on the aerodrome. The data acquired for this study ranging from primary data which included georeferencing of the obstacles that are found along the aerodrome with a Differential Global Positioning System (DGPS) to secondary data which included all base maps and satellite images. The spatial data conversion and manipulations were done using the ArcGIS 10.3.1 software. The 3D simulation of the obstacles was done in the ArcScene environment. To examine the spatial patterns of the obstacles around the aerodrome, the Average Nearest Neighbour Analysis (ANN) was used as statistical function from ArcGIS. The obstacles found within the MM2 aerodrome were grouped into the tolerant and non-tolerant ones. However, the finding shows that MM2 aerodrome conforms to ICAO standards and recommended practices. The study thus recommends strict daily monitoring of flight route to mark objects for foundation on the non-tolerance zones.

Avoiding Non-Manhattan Obstacles Based on Projection of Spatial Corners in Indoor Environment

Monocular vision-based navigation is a considerable ability for a home mobile robot. However, due to diverse disturbances, helping robots avoid obstacles, especially nonManhattan obstacles, remains a big challenge. In indoor environments, there are many spatial right-corners that are projected into two dimensional projections with special geometric configurations. These projections, which consist of three lines,might enable us to estimate their position and orientation in 3 D scenes. In this paper, we present a method for home robots to avoid non-Manhattan obstacles in indoor environments from a monocular camera. The approach first detects non-Manhattan obstacles. Through analyzing geometric features and constraints,it is possible to estimate posture differences between orientation of the robot and non-Manhattan obstacles. Finally according to the convergence of posture differences, the robot can adjust its orientation to keep pace with the pose of detected non-Manhattan obstacles, making it possible avoid these obstacles by itself. Based on geometric inferences, the proposed approach requires no prior training or any knowledge of the camera’s internal parameters,making it practical for robots navigation. Furthermore, the method is robust to errors in calibration and image noise. We compared the errors from corners of estimated non-Manhattan obstacles against the ground truth. Furthermore, we evaluate the validity of convergence of differences between the robot orientation and the posture of non-Manhattan obstacles. The experimental results showed that our method is capable of avoiding non-Manhattan obstacles, meeting the requirements for indoor robot navigation.