Breast cancer is the most common cancer among women globally, and the number of young women diagnosed with this disease is gradually increasing over the years. Mammography is the current gold-standard technique although it is known to be less sensitive in detecting tumors in woman with dense breast tissue. Detecting an early-stage tumor in young women is very crucial for better survival chance and treatment. The thermography technique has the capability to provide an additional functional information on physiological changes to mammography by describing thermal and vascular properties of the tissues. Studies on breast thermography have been carried out to improve the accuracy level of the thermography technique in various perspectives. However, the limitation of gathering women affected by cancer in different age groups had necessitated this comprehensive study which is aimed to investigate the effect of different density levels on the surface temperature distribution profile of the breast models. These models, namely extremely dense (ED), heterogeneously dense (HD), scattered fibroglandular (SF), and predominantly fatty (PF), with embedded tumors were developed using the finite element method. A conventional Pennes' bioheat model was used to perform the numerical simulation on different case studies, and the results obtained were then compared using a hypothesis statistical analysis method to the reference breast model developed previously. The results obtained show that ED, SF, and PF breast models had significant mean differences in surface temperature profile with a p value <0.025, while HD breast model data pair agreed with the null hypothesis formulated due to the comparable tissue composition percentage to the reference model. The findings suggested that various breast density levels should be considered as a contributing factor to the surface thermal distribution profile alteration in both breast cancer detection and analysis when using the thermography technique.

No abstract

Lean Manufacturing System (LMS) implementations in Malaysia's automotive industry has not been extensive in its expected reach, as extensive inquiries revealed it being adopted as a "pick-and-choose" system for certain processes or only upon determined levels within the industry. Current implementation strategy does not permit the industry to gain total benefits from the system itself. Undeniably, a few significant factors are being given less significance in multiple stages of LMS' execution. Employee involvement and employee empowerment have been identified as part of these contributing factors in a successful implementation of LMS in an organization. However, important criterion with its contributing aspects of these factors is not given the necessary attention, translating into a lamer impact upon companies embarking on a LMS deployment. This paper examines the impact of these two factors in the implementation of a lean manufacturing system towards achieving the organizational performances in the automotive industry. A questionnaire-survey was administered to gauge the impact of these two factors in an implementation process of a lean manufacturing system and later analyzing the effect towards their organizational performances. Data from 204 automotive parts manufacturers were gathered and analyzed. The correlation between the influencing factors, 5 lean activities and 6 organizational performances were measured. The results gained suggest that the integration between employee involvement and employee empowerment will be a valuable critical organizational capability impacting organizational performances towards the successful implementation of LMS in the Malaysian automotive industry.

A thermoelectric module was adapted to (1) control the face temperature of an aluminium sample as a function of time, and (2) measure the associated instantaneous rate of heat transfer into the sample. Proportional (P) or Proportional-Integral-Derivative (PID) controls were applied. With respect to time, constant temperature, sinusoidal and triangular temperature variations were tested. These temperatures were well within 0.1 K of the set point (one standard error). Tests on square wave temperature variation indicated the limitations of the module heating and cooling power. For the range of temperatures explored, the thermoelectric properties of the module were found by fitting predicted temperatures to experimental measurements (the module electrical resistance was taken from the manufacturer's data). Associated uncertainty, typically ± 10% of total heat flow at 12 Watt, was far bigger than the ± 2% for heat flow meters assessed against National Institute of Standards and Technology (NIST) calibrations; nonetheless the temporal resolution (3 readings per second) offers some useful insight into thermal processes.

No abstract