ALGORITMA CONTENT-BASED FILTERING DAN ALGORITMA MULTILEVEL FEEDBACK QUEUE PADA PROSES PEMESANAN MAKANAN BERBASIS WEB

Teknologi berkembang dengan cepat. Beriringan dengan cepatnya perkembangan tersebut, kebutuhan manusia juga semakin kompleks tidak terkecuali di bidang bisnis makanan. Kafe dan restoran sedang trending bagi kaum milenial karena menu yang disuguhkan sangat variatif dan cepat penyajiannya. Agar bisnis dapat berkembang, dibutuhkan sistem pemesanan berbasis web agar dapat memberikan kemudahan kepada pelanggan serta promosi yang lebih mudah, terlebih kepada pelanggan muda yang daya belinya tinggi. Dalam mengimplementasikan dan memudahkan pengusaha dalam mengembangkan bisnisnya, maka perlu adanya penelitian yang memaparkan proses pembuatan suatu sistem pemesanan menu di Grande Resto berbasis web yang fokus pada desain, implementasi dan analisa dengan observasi lapangan studi literatur sistem yang pernah ada, wawancara serta catatan pembelian pelanggan. Sistem yang telah dibuat mampu menghadirkan rekomendasi menu terfavorit/yang sering dipesan oleh pelanggan dengan ujicoba 482 pelanggan. Menu terfavorit/yang banyak dipesan oleh pelanggan adalah Ice green tea dengan 124 pemesanan Ice Choco dengan 123 pemesanan, Ice Black Coffee dengan 117 pemesanan. Selain itu proses yang di berikan oleh sistem dengan tingkat keakurasian perhitungan rekomendasi dengan uji coba 482 pelanggan dengan hasil 99% akurasi. Selain uji coba pelanggan, sistem juga diuji dengan GTMetrix untuk mengetahui kinerja sistem dan hasilnya 100% dengan performa A. Hasil analisa tersebut kemudian dapat diimplementasikan dalam web canggih memakai sistem barcode untuk memesannya dengan metode pengembangan yang digunakan yaitu algoritma Content-based filtering dan algoritma multilevel feedback queue menggunakan bahasa pemrograman PHP

An Interval Type-2 Fuzzy Logic Based Map Matching Algorithm for Airport Ground Movements

Airports and their related operations have become the major bottlenecks to the entire air traffic management system, raising predictability, safety and environmental concerns. One of the underpinning techniques for digital and sustainable air transport is airport ground movement optimisation. Currently, real ground movement data is made freely available for the majority of aircraft at many airports. However, the recorded data is not accurate enough due to measurement errors and general uncertainties. In this paper, we aim to develop a new interval type-2 fuzzy logic based map matching algorithm, which can match each raw data point to the correct airport segment. To this aim, we first specifically design a set of interval type-2 Sugeno fuzzy rules and their associated rule weights, as well as the model output, based on preliminary experiments and sensitivity tests. Then, the fuzzy membership functions are fine-tuned by a particle swarm optimisation algorithm. Moreover, an extra checking step using the available data is further integrated to improve map matching accuracy. Using the real-world aircraft movement data at Hong Kong Airport, we compared the developed algorithm with other well-known map matching algorithms. Experimental results show that the designed interval type-2 fuzzy rules have the potential to handle map matching uncertainties, and the extra checking step can effectively improve map matching accuracy. The proposed algorithm is demonstrated to be robust and achieve the best map matching accuracy of over 96% without compromising the run time

A fuzzy approach to addressing uncertainty in Airport Ground Movement optimisation

Funded by Engineering and Physical Sciences Research Counci

Synthesis of Thiourea and Guanidine Derivatives and Testing for Biological Activity

Thiourea and guanidine derivatives are versatile compounds that have previously been synthesised for use in a variety of industries from materials manufacturing to medical research. It is this versatility which interests us in new possible pathways for these compounds, with the focus being the potential for advanced oncology research. This thesis discusses a single project in two halves, the first synthesising thiourea and guanidine derivatives, whilst the second half looks at the biological activity of those target molecules on three different ovarian cancer cell lines. Once synthesised, the derivative compounds were fully characterised by ¹H NMR, ¹³C NMR, elemental analysis, mass spectrometry and melting point analysis. Four additional compounds were included for biological testing, which comprise of thiourea and guanidine iridium complexes with alternative uses in OLED technology, whose ligand environment may also provide biological activity in mammalian cell cultures. There were no specific biological targets in which we were attempting to challenge but treated this research as a 'fishing trip', to understand how well these thiourea and guanidine derivatives could perform as potential anticancer drugs. A panel of ovarian cancer cells consisting of adherent cell lines EFO-21 and EFO-27 followed by a suspension cell line (COLO-704) were investigated. Parental and cisplatin resistant sublines of these cells were used to observe effects of the thiourea and guanidine derivatives against cisplatin resistance. These cell lines were then dosed with each derivative from the compound library and their biological activity examined through MTT viability. Cisplatin resistant cell lines were the focus due to the broad extent in which the anticancer drug has been researched, but also due to resistant mechanisms it has produced in human cancer cells. The investigated compounds showed promising results and displayed notable differences in their effects on reducing the viability of ovarian cancer cell lines, with the data collected potentially providing a start to new therapeutic pathways in the battle against cancer resistant cell lines

A Rolling Window with Genetic Algorithm Approach to Sorting Aircraft for Automated Taxi Routing

With increasing demand for air travel and overloaded airport facilities, inefficient airport taxiing operations are a significant contributor to unnecessary fuel burn and a substantial source of pollution. Although taxiing is only a small part of a flight, aircraft engines are not optimised for taxiing speed and so contribute disproportionately to the overall fuel burn. Delays in taxiing also waste scarce airport resources and frustrate passengers. Consequently, reducing the time spent taxiing is an important investment. An exact algorithm for finding shortest paths based on A* allocates routes to aircraft that maintains aircraft at a safe distance apart, has been shown to yield efficient taxi routes. However, this approach depends on the order in which aircraft are chosen for allocating routes. Finding the right order in which to allocate routes to the aircraft is a combinatorial optimization problem in itself. We apply a rolling window approach incorporating a genetic algorithm for permutations to this problem, for real-world scenarios at three busy airports. This is compared to an exhaustive approach over small rolling windows, and the conventional first-come-firstserved ordering. We show that the GA is able to reduce overall taxi time with respect to the other approaches

Gelatin-layered and multi-sized porous β-tricalcium phosphate for tissue engineering scaffold

The multi-sized porous β-tricalcium phosphate scaffolds were fabricated by freeze drying followed by slurry coating using a multi-sized porous sponge as a template. Then, gelatin was dip coated on the multi-sized porous β-tricalcium phosphate scaffolds under vacuum. The mechanical and biological properties of the fabricated scaffolds were evaluated and compared to the uniformly sized porous scaffolds and scaffolds that were not coated by gelatin. The compressive strength was tested by a universal testing machine, and the cell viability and differentiation behavior were measured using a cell counting kit and alkaline phosphatase activity using the MC3T3-E1 cells. In comparison, the gelatin-coated multi-sized porous β-tricalcium phosphate scaffold showed enhanced compressive strength. After 14 days, the multi-sized pores were shown to affect cell differentiation, and gelatin coatings were shown to affect the cell viability and differentiation. The results of this study demonstrated that the multi-sized porous β-tricalcium phosphate scaffold coated by gelatin enhanced the mechanical and biological strengths

Evolutionary Algorithms with Linkage Information for Feature Selection in Brain Computer Interfaces

Abstract Brain Computer Interfaces are an essential technology for the advancement of prosthetic limbs, but current signal acquisition methods are hindered by a number of factors, not least, noise. In this context, Feature Selection is required to choose the important signal features and improve classifier accuracy. Evolutionary algorithms have proven to outperform filtering methods (in terms of accuracy) for Feature Selection. This paper applies a single-point heuristic search method, Iterated Local Search (ILS), and compares it to a genetic algorithm (GA) and a memetic algorithm (MA). It then further attempts to utilise Linkage between features to guide search operators in the algorithms stated. The GA was found to outperform ILS. Counter-intuitively, linkage-guided algorithms resulted in higher classification error rates than their unguided alternatives. Explanations for this are explored

CXCR2 deficient mice display macrophage-dependent exaggerated acute inflammatory responses

CXCR2 is an essential regulator of neutrophil recruitment to inflamed and damaged sites and plays prominent roles in inflammatory pathologies and cancer. It has therefore been highlighted as an important therapeutic target. However the success of the therapeutic targeting of CXCR2 is threatened by our relative lack of knowledge of its precise in vivo mode of action. Here we demonstrate that CXCR2-deficient mice display a counterintuitive transient exaggerated inflammatory response to cutaneous and peritoneal inflammatory stimuli. In both situations, this is associated with reduced expression of cytokines associated with the resolution of the inflammatory response and an increase in macrophage accumulation at inflamed sites. Analysis using neutrophil depletion strategies indicates that this is a consequence of impaired recruitment of a non-neutrophilic CXCR2 positive leukocyte population. We suggest that these cells may be myeloid derived suppressor cells. Our data therefore reveal novel and previously unanticipated roles for CXCR2 in the orchestration of the inflammatory response