The Effect Of Different Generations Psychosocial Work Climate On The Employees’ Work Performance

The main objective of this paper is to examine the psychosocial work environment factors that influence the employee’s work performance at difference generation

Analyzing Student Experience on Group Work with the Application of Different Group Allocation Approaches

Working as a group can be as challenging as working by oneself. Common issues like ineffective group work, unequal work contribution, and poor communication are believed to be the reasons why many students preferred to work individually. The purpose of this study is to understand if there is a disparity in student experience on group work by implementing different methods of group formation, which are, intentional group formation and random assignment. Topics around team well-being, team communication, and team effectiveness are the main focus of this study. The second emphasis of this study is students’ opinions on whether or not there is a difference in student group work experience when students are working together in person or online during the COVID-19 pandemic. This study allows us to gain insights if the student group work experience is exclusively determined by the methods of group formation or the circumstances of the COVID-19 pandemic, or a mixture of both. In the winter quarter of 2021, participants completed an online survey that took around 10-15 minutes. Data were collected anonymously and analyzed on R. The study focused on the qualitative end by understanding the students’ feedback, as well as performing descriptive analyses through graph visualization

Application of Data Mining Techniques on Tourist Expenses in Malaysia

تلعب السياحة دورًا مهمًا في التنمية الاقتصادية لماليزيا حيث يمكنها تعزيز فرص العمل في الاقتصاد المحيط بها. من خلال تطبيق استخراج البيانات على بيانات السياحة للتنبؤ بمجال الفرص التجارية وهذا يعد اختيارًا جيدًا. استخراج البيانات هو العملية التي تأخذ البيانات كمدخلات وتنتج معرفة المخرجات. بسبب ازدياد عدد السكان الذين يسافرون في بلد آسيا  في هذه السنوات القليلة. يبدأ العديد من رواد الأعمال أعمالهم الخاصة ولكن هناك بعض المشاكل مثل الاستثمار الخاطئ في مجالات الأعمال  الخدمات السيئة التي أثرت على دخل أعمالهم. الهدف من هذه البحث هو استخدام تقنية استخراج البيانات لتلبية احتياجات العمل واحتياجات العملاء للمؤسسات السياحية والعثور على تكنولوجيا استخراج البيانات الأكثر فعالية. بالإضافة إلى ذلك ، تم تجربة تنفيذ هذا البحث لأربع تقنيات تصنيف استخراج البيانات لاستخراج رؤى مهمة من مجموعة البيانات السياحية. كانت الأهداف هي معرفة أفضل الخوارزمية أداءً من بين النتائج المقارنة لتحسين فرص العمل في المجالات المتعلقة بالسياحة. كانت نتائج المصنفات الأربعة الصحيحة هي JRIP (84.09٪) ، Random Tree (83.66٪) ، J48 (85.50٪) ، وشجرة REP (82.47٪). سيتم تحليل جميع النتائج ومناقشتها في البحث.Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective data mining technology. Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. The aims were to find out the best performing algorithm among the compared on the results to improve the business opportunities in the fields related to tourism. The results of the 4 classifiers correctly classifier the attributes were JRIP (84.09%), Random Tree (83.66%), J48 (85.50%), and REP Tree (82.47%). All the results will be analyzed and discussed in this paper

Modeling of Traffic Excitation for System Identification of Bridge Structures

In long-term health monitoring of bridge structures, system identification is often performed based only on the system output (bridge vibration responses) because the system input (traffic excitation) is difficult to measure. To facilitate the identification of the bridge properties, traffic excitation is commonly modeled as spatially uncorrelated white noise. A physical model of a stationary stream of vehicles (moving loads) arriving in accordance with a Poisson process, traversing an elastic beam, shows that the traffic excitation is spatially correlated. Employing the dynamic nodal loading approach, this spatial correlation results in a frequency-dependent excitation spectrum density matrix, and shifts the response spectra obtained from those excited by spatially uncorrelated white noise. It is shown that the application of system identification techniques based on the conventional excitation model may result in misleading structural properties. Hence, this study further proposes an output-only gray-box identification technique for bridge structures, in which knowledge about the nature of the traffic excitation, such as its spatial correlation, is implanted into an autoregressive-moving-average (ARMA) model. The identifiability of the ARMA model so constructed is assured and the feasibility of the proposed identification technique is demonstrated by a numerical example

Modeling of Traffic Excitation for System Identification of Bridge Structures

In long-term health monitoring of bridge structures, system identification is often performed based only on the system output (bridge vibration responses) because the system input (traffic excitation) is difficult to measure. To facilitate the identification of the bridge properties, traffic excitation is commonly modeled as spatially uncorrelated white noise. A physical model of a stationary stream of vehicles (moving loads) arriving in accordance with a Poisson process, traversing an elastic beam, shows that the traffic excitation is spatially correlated. Employing the dynamic nodal loading approach, this spatial correlation results in a frequency-dependent excitation spectrum density matrix, and shifts the response spectra obtained from those excited by spatially uncorrelated white noise. It is shown that the application of system identification techniques based on the conventional excitation model may result in misleading structural properties. Hence, this study further proposes an output-only gray-box identification technique for bridge structures, in which knowledge about the nature of the traffic excitation, such as its spatial correlation, is implanted into an autoregressive-moving-average (ARMA) model. The identifiability of the ARMA model so constructed is assured and the feasibility of the proposed identification technique is demonstrated by a numerical example

Entangling two distant nanocavities via a waveguide

In this paper, we investigate the generation of continuous variable entanglement between two spatially-separate nanocavities mediated by a coupled resonator optical waveguide in photonic crystals. By solving the exact dynamics of the cavity system coupled to the waveguide, the entanglement and purity of the two-mode cavity state are discussed in detail for the initially separated squeezing inputs. It is found that the stable and pure entangled state of the two distant nanocavities can be achieved with the requirement of only a weak cavity-waveguide coupling when the cavities are resonant with the band center of the waveguide. The strong couplings between the cavities and the waveguide lead to the entanglement sudden death and sudden birth. When the frequencies of the cavities lie outside the band of the waveguide, the waveguide-induced cross frequency shift between the cavities can optimize the achievable entanglement. It is also shown that the entanglement can be easily manipulated through the changes of the cavity frequencies within the waveguide band.Comment: 8 pages, 8 figure

A KINEMATIC ANALYSIS OF ROUND KICK IN TAEKWONDO

The purpose of this study is to provide kinematic analysis of the round kick in Taekwondo. The round kick is an important component required in the performance of Taekwondo. In order to accomplish this skill, it is necessary to accelerate the movement of the leg to a high velocity. In order to determine the mechanism involved in this maneuver, kinematic analysis of the motion will be used. This study analyzed the round kick motion through application of the 3D-video analysis system. The data determined that the muscles of the thigh initiate the round kick, transmitting force from the hip, through to the shank and finally to the foot. Before kicking the target, the knee-joint flexes to increase the velocity of leg and then the lower limbs extend. These are the requirements for a rapid and powerful kick