Introduction of vibration to manufacturing operations such as casting and welding has proved to improve the physical and mechanical properties of manufactured parts. A vibration exciter is developed for the purpose of generating and inducing vibration, along different degrees of freedom, on objects placed on its surface. The equipment applies an eccentric mass drive system which gives the equipment an overall advantage in varying the vibration parameters. The acceleration of the vibratory motion of the equipment was measured using an accelerometer and oscilloscope set-up. The natural frequencies of the different vibration modes are also obtained from a developed mathematical model executed using the MATLAB Simulink software. The developed equipment successfully generated random sinusoidal vibrations of accelerations ranging from −5 m/s^2 to 8 m/s^2 along the principal axes and angular accelerations ranging from −40 rad/s to 40 rad/s about the pitch and roll axes. Natural frequencies of f_x = 3.78 Hz, f_θ = 7.94 Hz and f_φ = 9.89 Hz are obtained along the vertical, pitch and roll directions respectively. The presented results indicate that the developed machine successfully satisfied the proposed hypothesis of being able to measure vibrational characteristics along different degrees of freedom.

Autonomous vehicle (AV) is a broad field in artificial intelligence which has seen monumental growth in the past decade and this had a significant impact in bridging the gap between the capability the intelligence of human and the efficiency of machines. With millions of people losing their lives, or have being a victim of road traffic accidents. There is a need to find a suitable algorithm for a navigation system in an autonomous vehicle with the purpose of help mitigate the traffic rule violation that most human drivers make that lead leads to traffic accidents. With both researchers and enthusiasts developing several algorithms for AVs, this field has been split into several modules which continually broaden the scope of AV’s technology. In this paper, we focus on the lane navigation which has an important part of the AV movement on the road. Here lane decision making is optimized by using deep learning techniques in creating a Neural Network model that focuses on generating steering commands by taking an image the road mapped out with lane markings. The navigation aid is a front-facing camera mounted and images from the camera are used to compute steering commands. The end to end learning scheme was developed by Nvidia cooperation to train a model to compute steering command from a front-facing camera. The model does not focus on detecting the lane but only generating the appropriate command for steering AVs’ on the road. This focus on one objective of the model helps in maximizing the potential of better accuracy in lane navigation of our AVs. The modeled car navigates through the designed lanes accurately with the level of intelligence the car shows in maneuvering through the lanes shows this method is more suitable in lane navigation.

This paper measured the impact of the implementation of the five core Industry 4.0 technologies (artificial intelligence, big data analytics, cloud computing, cybersecurity, and Internet of Things (IoT)) on organizational behavior and corporate culture of businesses and organizations in Pakistan. Moreover, the influence of organizational behavior and corporate culture on organizational effectiveness was also analyzed in this paper. The retail industry of Pakistan was chosen as the subject of this study, and a quantitative approach, which included a questionnaire based on a five-point Likert scale ranging from “strongly agree” to “strongly disagree,” was employed to gather the responses from participants, including both superiors and subordinates possessing the technological know-how of Industry 4.0. The findings indicated that the implementation of Industry 4.0 in Pakistan’s retail sector helps positively transform organizational behavior and aids in building a great corporate culture. Moreover, it was found that both positive organizational behavior and great corporate culture help in improving the overall organizational effectiveness. This study took an unprecedented step to research Industry 4.0 from an organizational perspective. Furthermore, the carried-out study extended the theoretical body of knowledge by studying and examining the five crucial factors of Industry 4.0 that contribute to the service sector, particularly the retail industry, of the big emerging markets (BEM) economies, including Pakistan.

According to the existing problems in college students' learning, change the teaching method to cultivate students with innovative consciousness and innovative connotation. The article mainly elaborates on the current shortcomings in the teaching process of many ordinary colleges and universities, and proposes that teaching is mainly secondary school; teaching is supplemented, and student-oriented. The main responsibility of teachers is to guide patiently, actively communicate with students, and teach students in accordance with their aptitude. First teachers should understand the student's learning dynamics from the student's perspective, and then prescribe the right medicine to correct its drawbacks, encourage its advantages, and cultivate students' learning enthusiasm. Teachers stimulate students to learn actively, recognize their learning effects, and encourage students to experiment boldly and be creative. The students are more motivated to learn, build self-confidence in learning, and have a sense of innovation. According to the curriculum and being student-oriented, teachers prepare lessons, write lesson plans, design teaching links and do a good job in class counseling, which cultivate students' sense of innovation and enable students to have innovative connotations.