Lean Implementation in Rawdat Al-Khail Health Center

Due to the significant increment of the State of Qatar Population in the Last few years, enormous pressure are puts on the current health care centers across the country. Health care is one of the main pillars of the future vision of Qatar 2030. Therefore, a revision of the current system of the country’s health care system is highly appreciated. In this project, one of Qatar’s busiest health care centers is studied to enhance the workflow of the patients. The walk-in patients are the most unpredictable, and hence, the project is focusing on improving the current walk-in patients’ flow in the health care center. The Lean Thinking approach is utilized to achieve this enhancement to the system. The Value Stream Mapping (VSM) tools are the used tool to accomplish this goal. After mapping the current process of the patients, the non-value-added activities are identified, and improvement ideas are suggested in order to reduce the waiting time of the walk-in patients of Rawdat Al-Khail Health Center. Cost-reduction is also achieved using the recommended approach of organizing the work activities. The improvements in the lead time (LT) and process time (PT) were mainly in the administrative steps of the current workflow since the other actions are not controllable, where a reduction of 8.8% in LT and 9.3% in PT were achieved. Suggestions and recommendations were made to Rawdat Al-Khail Health Center, which are applicable to other health centers in the State of Qatar. Further improvements to the other sectors of the Health Care are going to be addressed in the future in order to achieve a larger enhancement to the entire system

The Influential Factors of TQM and TPM Implementation on Manufacturing Industry Performance (MIP)

The demand for quality is the one crucial factor for businesses in today's highly competitive market, to thrive in this ever expanding global market. As a result of intense global competition, Total quality management (TQM) has been created. Most of the previous papers show that TQM is very related to business success. However, the analysis of the Total productive maintenance (TPM) as mediator between TQM and MIP not widely found and previous researches were commonly regarded as general instruments and techniques without particular emphasis on improvement styles. This paper aims to suggest the relationship between TQM and MIP through mediating impact of TPM. The methodology adopted for this research was to use a review of existing literature, this paper explores the theories of TQM and TPM to provide useful information to ensure effective management of manufacturing industry. The key contribution of this paper is to develop a conceptual model to describe the cause- effect relationship between TQM, TPM activities and MIP. The implication of the proposed conceptual model would help academics and policy makers in the industry to better understand the relationship between activities

Orthosurgical Correction of Severe Vertical Maxillary Excess: Gummy Smile

Gummy smile which is commonly described as excessive gingival display in full smile has become a major esthetic concern for patients and healthcare providers in recent years. Because of the complex etiologic factors and severity of this orofacial deformity including skeletal, dentoalveolar, muscular, and gingival, it is essential that a differential diagnosis be established so that a relevant therapy can be selected from a wide range of treatment options. The complex etiologic factors of this dentofacial deformity necessitates coordination between a team of health care providers, especially between orthodontist and maxillofacial surgeon, to improve diagnosis and treatment planning, accurately predict the outcome, and minimize orthosurgical complications. In this chapter, the author will present several clinical cases and briefly review available treatment modalities for excessive gingival display in full smile. Emphasis will be put on orthosurgical treatment of severe vertical maxillary excess as the optimal solution to restore facial balance and harmony, attractive smile, and patients’ satisfaction

On contextual perception of workers in complex production environments

In this work we focus on the challenges of perceiving and coordinating spatial actions between humans and robots in production systems. We address the fundamental questions of how the affective states of individuals in the production process can be visually captured and interpreted in order to facilitate intuitive interactions without explicit commands. Additionally, we investigate methods to analyze the environment and action context in a semantic scene to anticipate user and action intentions. Lastly, we formulate decision approaches to derive appropriate interaction strategies based on affective user states and intentions in the scene context to improve productive collaboration between humans and robots in production environments. By addressing these challenges, this work aims to improve the efficiency of productive teaming processes in production systems

On Teaching Quality Improvement of a Mathematical Topic Using Artificial Neural Networks Modeling (With a Case Study)

This paper inspired by simulation by Artificial Neural Networks (ANNs) applied recently for evaluation of phonics methodology to teach children "how to read". A novel approach for teaching a mathematical topic using a computer aided learning (CAL) package applied at educational field (a children classroom). Interesting practical results obtained after field application of suggested CAL package with and without associated teacher''s voice. Presented study highly recommends application of a novel teaching trend based on behaviorism and individuals'' learning styles. That is to improve quality of children mathematical learning performance

Towards Robust and Unconstrained Full Range of Rotation Head Pose Estimation

Estimating the head pose of a person is a crucial problem for numerous applications that is yet mainly addressed as a subtask of frontal pose prediction. We present a novel method for unconstrained end-to-end head pose estimation to tackle the challenging task of full range of orientation head pose prediction. We address the issue of ambiguous rotation labels by introducing the rotation matrix formalism for our ground truth data and propose a continuous 6D rotation matrix representation for efficient and robust direct regression. This allows to efficiently learn full rotation appearance and to overcome the limitations of the current state-of-the-art. Together with new accumulated training data that provides full head pose rotation data and a geodesic loss approach for stable learning, we design an advanced model that is able to predict an extended range of head orientations. An extensive evaluation on public datasets demonstrates that our method significantly outperforms other state-of-the-art methods in an efficient and robust manner, while its advanced prediction range allows the expansion of the application area. We open-source our training and testing code along with our trained models: https://github.com/thohemp/6DRepNet360

Study of the Active Compound in the Essential Oil of Myrtus communis L.

This study appears of the major volatile compounds in the essential oil of myrtle leaves because of its significant medical and economic benefits. The essential oil composition of Myrtus communis leaves during its flowering stage was determined. six volatile compounds were identified in leaves essential oils, α-Pinene 308 µg/ml, linalool (23.83 µg/ml), Eucalyptol or 1,8-cineole (41.46 µg/ml), Limonene (45.22 µg/ml), α-terpineol (41.73 µg/ml), Geranyl acetate (18.28 µg/ml) were the main monoterpene compounds. α-Pinene was Represents the bulk of the other compounds in the myrtle leave Keywords: Myrtus communis L., myrtle, flowering stage, essential oil, chemical compounds