Tumour markers assay serum CA125 and Ca153. A preliminary report of USM experience

Cancer is one of the most important medical problems in today's world and in Malaysia it is one of the leading causes of death.Although development of cancer takes a considerable amount of man's life span, it is however possible to detect its early pre-cancerous stage.Death due to cancer may be avoided if detected early and this is usually done by biochemical measurement of tumour markers. Tumour Markers are substances which are related to the presence or progress of a tumour. They include proteins such as enzymes and peptides which are secreted into body fluids by tumours and antigens which are expressed on cell surfaces.In contrast, tumour markers also play a critical role in the monitoring and treatment of patients with cancer. The method employed for this preliminary/pilot study is based on ELISA technique. The CA 125 enzyme immunoassay kit was purchased from TECO USA which uses a monoclonal antibody.It is specific for surface antigen derived from a papillary serous cyst adenocarcinoma. Elevated CA 125 serum levels are also found in patient with serious endometrium and fallopian tube

Implementation study of field programmable gate array (FPGA) and complex programmable logic device (CPLD) in collision avoidance system using vhsic hardware description language (VHDL)

A collision avoidance system, also known as a pre-crash system, forward collision warning system, or collision mitigation system, is a sophisticated driver-assistance system that aims to avoid or mitigate the severity of a collision. For this research, collision avoidance system will be fabricating to show that this system can detect avoidance range before apply the braking action to prevent collision. The ultrasonic sensor will be used in this system to detect the avoidance range. In this collision avoidance system, there will be uses of Field Programmable Gate Array (FPGA) and Complex Programmable Logic Device (CPLD). This research will observe how to implement FPGA and CPLD in the collision avoidance system using VHSIC Hardware Description Language (VHDL). The VHDL will be done in Quartus II 15.0 Software. In this research, Terasic DE-10 Standard board has been used. It contains FPGA microcontroller model Cyclone V SoC 5CSXFC6D6F31C6N. Max II board is used because it contains CPLD microcontroller model EPM240T100C5

A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator

The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. Each agent in SKF is treated as a Kalman filter. The SKF utilizes a Kalman filter process that includes prediction, measurement, and estimation to determine the global optimum. However, the SKF can only operate in the numerical search space. Numerous approaches and modifications have been used in the literature to enable numerical meta-heuristic algorithms to operate in a discrete search space. This paper presents modifications to measurement and estimation in the SKF by utilizing mutation and Hamming distance technique to accommodate the discrete search space. The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). Additionally, the DSKFO algorithm incorporates the swap operator as an extension to improve the solution in solving the travelling salesman problem (TSP). The DSKFO algorithm was compared against four other combinatorial SKF algorithms and outperformed them all

Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. This paper presented an overview of the research progress in SKF from the day it was introduced until the present day, discussing the progress, improvements, modifications, and applications of SKF. The fundamental and standard algorithm were first introduced. Then, the work on the algorithm improvements was surveyed. Finally, the remaining unresolved problems and some directions of SKF research were discussed. We reviewed 57 SKF papers. 16 of them on fundamental improvements, 9 on extension of the algorithm to discrete problems and 25 on their applications. Researchers have worked on ideas to improve exploration capability to prevent premature convergence by trying prediction operators, opposition-based learning, and different iteration strategies. There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. Lastly, a single-agent variant of SKF and a multi-objective SKF were introduced. SKF algorithms and its variants have been implemented in at least nine areas of applications: drill path optimization, airport gate allocation problem (AGAP), assembly sequence planning (ASP), system identification, feature selection, image template matching, controller tuning, wireless sensor network, and engineering design problem. The literature reviewed solely depended on the keyword search that contained the terms simulated Kalman filter from December 2015 to the present date. This is the first review paper on SKF. It is hoped that this survey would be beneficial for the researchers of this area and attracting interest towards the algorithm

A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator

The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. Each agent in SKF is treated as a Kalman filter. To find the global optimum, the SKF employs a Kalman filter mechanism that includes prediction, measurement, and estimate. However, the SKF is limited to operating in the numerical search space only. Numerous techniques and modifications have been made to numerical meta-heuristic algorithms in the literature in order to enable them to operate in a discrete search space. This paper presents modifications to measurement and estimation in SKF to accommodate the discrete search space. The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). Additionally, the DSKFO algorithm incorporates the 2-opt operator to improve the solution in solving the travelling salesman problem (TSP). The DSKFO algorithm was compared against four other combinatorial SKF algorithms and outperformed them all

A novel multi-state gravitational search algorithm for discrete optimization problems

The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism of transition between two states. The performance of the MSGSA is empirically compared to the original BGSA based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The results are statistically analyzed and show that the MSGSA has performed consistently in solving the discrete optimization problems

Sycophant Curve Model and Pearson Correlation Coefficient: An Application to Behavioral Change in Nigeria

This study investigates the behavioural switch and relationship of people (associates) towards a transiting chief executive officer (CEO). During the tenure of a new CEO, the rate of patronage of different categories of people seeking political and economic relevance increases over time, but as the CEO’s tenure wanes, the patronage behavioural pattern decreases. The sycophant curve model (SCM) was proposed to determine the behavioural pattern change of patronage at the onset and transitioning of the CEO tenure to a new CEO. The Pearson correlation coefficient (PCC) was also investigated. The results revealed that during the tenure of any CEO, the associate behaviour is increasingly positive, while during the transitioning period and beyond, the rate of the behavioural switch by associates decreases gradually. The PCC (rp = 0.9966) affirmed a strong positive relationship between the CEO and associates for four years. Meanwhile, rp = –0.9966, indicating a strong negative behavioural switch between the CEO and associates after four years of transition and beyond. This study demonstrated that during the tenure of any CEO, the behavioural switch of the associates towards the CEO is extremely minimal and gradually increases after the transition period and beyon

An improved TOPSIS/EFQM methodology for evaluating the performance of organizations

Studies showed that the scoring system of the EFQM has got some problems that can cause a deviation from the correct assess performance of organization. One of the reasons of this deviation could be due to the scoring approach of EFQM questionnaire. This study is to investigate relationship of each question of the questionnaire with TQM criteria and give a practical way to overcome the existing problem. In this study, with 50 questions of the EFQM and criteria of TQM, a questionnaire has been created. Then, opinions of 175 assessors dealing with EFQM are gathered about the relationship between the questions of EFQM with any of TQM criteria. The data have been processed using SPSS software and the nearest point of a fuzzy number and Topsis model. The results revealed that amount of relationship between each EFQM’s question with TQM criteria isn’t same therefore the weight of each question in EFQM’s questionnaire is not equal to the rest of questions and TQM criteria. Also assigning equal scores to all questions of EFQM’s traditional questionnaire is nonrealistic and consequently, the simplicity additive calculation of assessing performance of organization is also nonrealistic and this is created a deviation to assess properly performance of organization. According to the findings of this study, one should consider the EFQM assessors’ point of view regarding the relationship between criteria of the two models in order to improve organization performance assessments. Finally, considering the level of priority in Topsis method, a relevant scoring system should be created. This can overcome the problem of deviation in assessing the organization’s performance

Fuzzy Logic Controller Design for Intelligent Drilling System

An intelligent drilling system can be commercially very profitable in terms of reduction in crude material and labor involvement. The use of fuzzy logic based controller in the intelligent cutting and drilling operations has become a popular practice in the ever growing manufacturing industry. In this paper, a fuzzy logic controller has been designed to select the cutting parameter more precisely for the drilling operation. Specifically, different input criterion of machining parameters are considered such as the tool and material hardness, the diameter of drilling hole and the flow rate of cutting fluid. Unlikethe existing fuzzy logic based methods, which use only two input parameters, the proposed system utilizes more input parameters to provide spindle speed and feed rate information more precisely for the intelligent drilling operation

Experimental studies on the rheological and hydraulic performance of palm based hydraulic fluid

Development of environmental friendly hydraulic fluid has a major influence in ecologically benign environment. The use of plant oil as hydraulic fluid would help to minimize hazardous pollution caused by accidental spillage, lower disposal costs of the used fluid and meet the environmental regulations. Hydraulic test rig was built to conduct endurance test where it can be operated continuously with several safety features. This research was conducted to evaluate the rheology elements and hydraulic performance of palm based hydraulic fluid. The palm oil shows decreasing trend in volumetric efficiency as the pressure increase while the mechanical efficiency increases as the pressure increase. Properties and characteristics of palm based hydraulic fluid were evaluated via rheology study. The effect of viscosity with temperature and shear rate was studied. The influence of shear rate and temperature on the variation of viscosity was clearly observed but temperature has more significant influence. Interpretations of rheological models indicate that this palm based hydraulic fluid belongs to pseudo-plastic category. Further analysis was done to fit the experimental data with two models and the findings show that Cross rheological model fits well with the experiment data. The plant oil was used in 1000 hours operation in a hydraulic system built in Universiti Malaysia Terengganu. The overall results suggest the potential substitution of palm oil as hydraulic fluid in marine applications. Keywords: Hydraulic fluids; mechanical efficiency; palm oil; rheology; volumetric efficienc