An integrated decision support system based on simulation and mathematical programming of Petroleum transportation logistics

Discrete Event simulation (DES), mathematical programming (MP) and analysis of variance (ANOVA) are among the popular tools in operational research (OR) used in dynamic industry like petroleum industry. The integration of these methods even becomes more significant to managerial application in the industry. The objective of this thesis is to present an integrated decision support system by which a decision maker should be able to choose the optimal number of tanks, tank size and truck arrival rate to maximize average total profit and minimize the total transportation cost for an oil refinery terminal operations. The petroleum transportation management system (PTMS) is developed as a DSS using a discrete-event simulation program with ARENA software, mathematical linear programming (LP) with I-Log software and analysis of variance (ANOVA) with SPSS software, and these models are combined in complex program developed using visual basic software (VB). The simulation model represents the logistics operations from oil arriving to the refinery terminal to the supply points. The model process used as a decision support tool to help in evaluating and improving the comprehensive oil terminal operations. And also understanding and assessing of the different steps in a simulation process. An optimization model was formulated with the objective to minimize the total transportation cost. In the model formulation, hard constraints were considered and the linear programming (LP) technique was used. Result obtained suggests the use of certain types of trucks can reduce the operation costs, if compared to that of the current situation. The reduction of costs is due to the reduction of travelling trips as based on the problem constraints. Overall, output of this study has given positive impacts on the transportation operations. The effect of the changes can help the management of the transportation company to make efficient decisions. Multifactor ANOVA is used to determine whether different levels of the three-factors and their interactions significantly impact the oil refinery terminal's profit. ANOVA is also used to determine the flow rate of oil into the tanks station; tank and truck fill rate and a cost and revenue structure. The final step is to expand the model to cover the whole models (DES, LP and ANOVA) and create the integrated user interface. To sum up the combination of these techniques which allows evaluating the actual feasibility of supply planning considering all operations restrictions and variability of the supply logistics and the total transportation cost. In another words, a DSS have been developed to support a decision maker, who is planning to build a new facility or expand an existing oil refinery terminal, should be able to choose the optimal value for all important factors. The PTMS is able to predict with 99% confidence a set of factor levels that yields the highest average total profit

Offline signatures matching using haar wavelet subbands

The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems tosatisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works triedto develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different setsof features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used asa dataset for testing purpose. The results achieved by this technique indicate a high performance in signature recognition

Analysing Shortest Route Problem in Petaling Jaya: A Case Study

In graph theory, the shortest path problem is the problem of finding a path between two vertices or nodes in a graph such that the sum of the weights of its constituent edges is minimized. Shortest path is important to minimize total travelling time or cost. This paper presents a current method to construct the solution on shortest route in Petaling Jaya district area for research staff doing a survey tour. Integer linear programming (ILP), heuristic method and Google Maps were used to analyse the travelling salesman problem (TSP). Result shows that it has agreement with theoretical predictions and significant improvement over previous efforts by researchers. The work presented here has profound implications for future studies of saving time and cost behaviour and may help to solve the problem for the survey tour in the futur

OPTIMIZATION OF REAL TIME IMAGE SEGMENTATION USING EFFICIENT THRESHOLDING TECHNIQUE

The process of image segmentation is how to divide images into regions with similar properties. Threshold-based image segmentation is a multidimensional optimization problem that has been highlighted as one of the most significant image pre-processing approaches. This paper proposes an efficient technique for optimizing real time image segmentation. The approach of image thresholding may be regarded an optimization objective, and it will be discovered by using Otsu's technique in conjunction with Particle Swarm Optimization basics (PSO). For real-time validation, the suggested technique was tested on several images in real time using the PSO algorithm. The simulation results showed that, when compared to Otsu's approach, the PSO algorithm gives the most efficient outcomes in real-time applications with an improved execution time

Green Supply Chain: Simulating Road Traffic Congestion

With the increasing awareness of the consumers about environmental issues, businesses, households and governments increasingly want use green products and services which lead to green supply chain. This paper discusses a simulation study of a selected road traffic system that will contribute to the air pollution if in the congestion state. Road traffic congestion (RTC) can be caused by a temporary obstruction, a permanent capacity bottleneck in the network itself, and stochastic fluctuation in demand within a particular sector of the network, leading to spillback and queue propagation. A discrete-event simulation model is developed to represent the real traffic light control (TLC) system condition during peak hours. Certain performance measures such as average waiting time and queue length were measured using the simulation model. Existing system uses pre-set cycle time to control the light changes which is fixed time cycle. In this research, we test several other combination of pre-set cycle time with the objective to find the best system. In addition, we plan to use a combination of the pre-set cycle time and a proximity sensor which have the authority to manipulate the cycle time of the lights. The sensors work in such situation when the street seems to have less occupied vehicles, obviously it may not need a normal cycle for green light, and automatically change the cycle to street where vehicle is presen

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma

Beyond tertiary lymphoid structures, a significant number of immune-rich areas without germinal center-like structures are observed in non–small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 patients with lung cancer from The Cancer Genome Atlas. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B-cell signatures. Spatial statistical analyses conducted on serial multiplex IHC slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared with peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared with peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance toward increased intratumoral immune hotspots is indicative of a compromised antitumor immune response and poor outcome in lung squamous cell carcinoma

ASSOCIATION BETWEEN THE BASELINE GENE EXPRESSION PROFILE IN PERIAPICAL GRANULOMA AND PERIAPICAL WOUND HEALING AFTER SURGICAL ENDODONTIC TREATMENT

In this study, we have investigated the association between the baseline gene expression profile in periapical granuloma and periapical wound healing after surgical endodontic treatment. Twenty-seven patients aged between 15 and 57 years underwent periapical surgery. The retrieved periapical tissue sample was used for mRNA expression analysis of COL1A1, VTN, ITGA5, IL-4, TNF, ANGPT, VEGFA, and CTGF. All patients were recalled after 6 and 12 months for periapical healing evaluation. Healing was then correlated with baseline gene expression. Healing was observed in 15 patients at the end of 6 months, which increased to 21 patients after 12 months. Six patients showed no healing even after 12 months. Analysis of baseline expression levels of the tested genes with healing status showed the mean relative expression of VTN, VEGFA, ANGPT, TNF, and CTGF to be significantly different (p < 0.05) between the healing group (6 and 12 months) (72.99%) and the non-healing (94.42%) group. Periapical Index scores 3–5 exhibited a positive correlation with ITGA-5 expression. Overexpression of ANGPT and a strong positive correlation between ITGA5 and PAI scores in the non-healing group of patients may suggest these genes to be a potential prognostic biomarker for periapical wound non-healing after surgical endodontic treatment

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma

Beyond tertiary lymphoid structures, a significant number of immune rich areas without germinal center-like structures are observed in non-small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 lung cancer patients from the TCGA. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B cell signatures. Spatial statistical analyses conducted on serial multiplex immunohistochemistry slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared to peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared to peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance towards increased intratumoral immune hotspots is indicative of a compromised anti-tumor immune response and poor outcome in lung squamous cell carcinoma

Biomarkers for site-specific response to neoadjuvant chemotherapy in epithelial ovarian cancer: relating MRI changes to tumour cell load and necrosis.

Funder: We acknowledge funding from Cancer Research UK BIDD grant C1353/A12762 and Cancer Research UK and Engineering and Physical Sciences Research Council support to the Cancer Imaging Centre at the Institute of Cancer Research and Royal Marsden Hospital in association with the Medical Research Council and Department of Health C1060/A10334, C1060/A16464 and National Health Service funding to the National Institute for Health Research Biomedical Research Centres at Royal Marsden Hospital/Institute of Cancer Research and Cambridge, Experimental Cancer Medicine Centres, the Clinical Research Facility in Imaging, and the Cancer Research Network. We are also grateful for financial support from Addenbrooke’s Charitable Trust. The views expressed in this publication are those of the author(s) and not necessarily those of the National Health Service, the National Institute for Health Research or the Department of Health.BACKGROUND: Diffusion-weighted magnetic resonance imaging (DW-MRI) potentially interrogates site-specific response to neoadjuvant chemotherapy (NAC) in epithelial ovarian cancer (EOC). METHODS: Participants with newly diagnosed EOC due for platinum-based chemotherapy and interval debulking surgery were recruited prospectively in a multicentre study (n = 47 participants). Apparent diffusion coefficient (ADC) and solid tumour volume (up to 10 lesions per participant) were obtained from DW-MRI before and after NAC (including double-baseline for repeatability assessment in n = 19). Anatomically matched lesions were analysed after surgical excision (65 lesions obtained from 25 participants). A trained algorithm determined tumour cell fraction, percentage tumour and percentage necrosis on histology. Whole-lesion post-NAC ADC and pre/post-NAC ADC changes were compared with histological metrics (residual tumour/necrosis) for each tumour site (ovarian, omental, peritoneal, lymph node). RESULTS: Tumour volume reduced at all sites after NAC. ADC increased between pre- and post-NAC measurements. Post-NAC ADC correlated negatively with tumour cell fraction. Pre/post-NAC changes in ADC correlated positively with percentage necrosis. Significant correlations were driven by peritoneal lesions. CONCLUSIONS: Following NAC in EOC, the ADC (measured using DW-MRI) increases differentially at disease sites despite similar tumour shrinkage, making its utility site-specific. After NAC, ADC correlates negatively with tumour cell fraction; change in ADC correlates positively with percentage necrosis. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT01505829