ON VOLTERRA AND ORTHOGONALITY PRESERVING QUADRATIC STOCHAISTIC OPERATORS

A quadratic stochastic operator (in short QSO) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. In the present paper, we first give a simple characterization of Volterra QSO in terms of absolutely continuity of discrete measures. Moreover, we provide its generalization in continuous setting. Further, we introduce a notion of orthogonal preserving QSO, and describe such kind of operators defined on two dimensional simplex. It turns out that orthogonal preserving QSOs are permutations of Volterra QSO. The associativity of genetic algebras generated by orthogonal preserving QSO is studied to

Amalan berfikir dalam Islam dan hubungannya dengan ilmu dan Pendidikan.

Islam adalah agama ilmu dan kemajuan. Umat Islam digalakkan untuk berfikir dan sentiasa mencari jalan penyelesaian terhadap sesuatu masalah yang hadapi. Tradisi berfikir juga mencetus kepada perkembangan ilmu seterusnya membina sistem pendidikan yang begitu tersusun

Death from Malaria infection in a military personnel after a peace keeping mission

Military personnel who are deployed for peace-keeping missions are exposed to many hazards, including infectious diseases. One of the most common and fatal infectious disease is Malaria. Although well controlled in Malaysia, this deadly disease is still widely endemic in many other countries especially Africa. We would like to report the case of a military personnel who was infected with Malaria during a peace-keeping mission in Sudan and subsequently died after returning home. We hope that by reporting this case in depth, strategic actions can be taken to avoid similar unfortunate events in future

Electroactive Artificial Muscles Based on Functionally Antagonistic Core–Shell Polymer Electrolyte Derived from PS-b-PSS Block Copolymer

Electroactive ionic soft actuators, a type of artificial muscles containing a polymer electrolyte membrane sandwiched between two electrodes, have been intensively investigated owing to their potential applications to bioinspired soft robotics, wearable electronics, and active biomedical devices. However, the design and synthesis of an efficient polymer electrolyte suitable for ion migration have been major challenges in developing high-performance ionic soft actuators. Herein, a highly bendable ionic soft actuator based on an unprecedented block copolymer is reported, i.e., polystyrene-b-poly(1-ethyl-3-methylimidazolium-4-styrenesulfonate) (PS-b-PSS-EMIm), with a functionally antagonistic core–shell architecture that is specifically designed as an ionic exchangeable polymer electrolyte. The corresponding actuator shows exceptionally good actuation performance, with a high displacement of 8.22 mm at an ultralow voltage of 0.5 V, a fast rise time of 5 s, and excellent durability over 14 000 cycles. It is envisaged that the development of this high-performance ionic soft actuator could contribute to the progress toward the realization of the aforementioned applications. Furthermore, the procedure described herein can also be applied for developing novel polymer electrolytes related to solid-state lithium batteries and fuel cells

The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme

Case study of the effectiveness of passive grease trap for management on domestic kitchen waste water

Household waste, generally known as trash or garbage is mostly includes food wastes, product packaging, and other miscellaneous inorganic wastes that are coming from domestic household. Grease waste such as oil and fats can contaminate water and also clot on pipes provoking blockages. Thus, waste water from kitchen sink need a proper way of filtration. Grease trap developed in this paper is viable in trapping the grease residue. The experiments have been conducted in controlled environment and the objectives are to investigate the effectiveness of grease trap by proving the existence of retention time and the expected ratio of collected water and oil during experiment process using a prototype model

The application of support vector machine in classifying potential archers using bio-mechanical indicators

This study classifies potential archers from a set of bio-mechanical indicators trained via different Support Vector Machine (SVM) models. 50 youth archers drawn from a number of archery programmes completed a one end archery shooting score test. Bio-mechanical evaluation of postural sway, bow movement, muscles activation of flexor and extensor as well as static balance were recorded. k-means clustering technique was used to cluster the archers based on the indicators tested. Fine, medium and coarse radial basis function kernel-based SVM models were trained based on the measured indicators. The five-fold cross-validation technique was utilised in the present investigation. It was shown from the present study, that the employment of SVM is able to assist coaches in identifying potential athletes in the sport of archery