Search results for: problem diagnostic

Authors: Sumera, Sanila Amber, Fatima Javed Mirza, Amjad Ali, Saadia Zahid

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Glioblastoma multiforme (GBM) is a widely spread and fatal primary brain tumor with an increased risk of relapse in spite of aggressive treatment. The current procedures for GBM diagnosis include invasive procedures i.e. resection or biopsy, to acquire tumor mass. Implementation of negligibly invasive tests as a potential diagnostic technique and biofluid-based monitoring of GBM stresses on discovering biomarkers in CSF and blood. Therefore, we performed a comprehensive in silico analysis to identify potential circulating biomarkers for GBM. Initially, six gene and protein databases were utilized to mine brain-specific proteins. The resulting proteins were filtered using a channel of five tools to predict the secretory proteins. Subsequently, the expression profile of the secreted proteins was verified in the brain and blood using two databases. Additional verification of the resulting proteins was done using Plasma Proteome Database (PPD) to confirm their presence in blood. The final set of proteins was searched in literature for their relationship with GBM, keeping a special emphasis on secretome proteome. 2145 proteins were firstly mined as brain-specific, out of which 69 proteins were identified as secretory in nature. Verification of expression profile in brain and blood eliminated 58 proteins from the 69 proteins, providing a final list of 11 proteins. Further verification of these 11 proteins further eliminated 2 proteins, giving a final set of nine secretory proteins i.e. OPCML, NPTX1, LGI1, CNTN2, LY6H, SLIT1, CREG2, GDF1 and SERPINI1. Out of these 9 proteins, 7 were found to be linked to GBM, whereas 2 proteins are not investigated in GBM so far. We propose that these secretory proteins can serve as potential circulating biomarker signatures of GBM and will facilitate the development of minimally invasive diagnostic methods and novel therapeutic interventions for GBM.

Keywords: glioblastoma multiforme, secretory proteins, brain secretome, biomarkers

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Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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Authors: Muhammad Mukhtar Aliyu

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This study investigated tutors’ experiences and perceptions of a problem-based learning approach (PBL) in a writing classroom. The study involved two Nigerian lecturers who facilitated an intact class of second-year students in an English composition course for the period of 12 weeks. Semi-structured interviews were employed to collect data of the study. The lecturers were interviewed before and after the implementation of the PBL process. The overall findings of the study show that the lecturers had positive perceptions of the use of PBL in a writing classroom. Specifically, the findings reveal the lecturers’ positive experiences and perception of the group activities. Finally, the paper gives some pedagogical implications which would give insight for better implementation of the PBL approach.

Keywords: experiences and perception, Nigeria, problem-based learning approach, writing classroom

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Anteneh Getachew Gebrie, Rabian Wangkeeree

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The purpose of this paper is to introduce iterative algorithm solving split system of minimization problem given as a task of finding a common minimizer point of finite family of proper, lower semicontinuous convex functions and whose image under a bounded linear operator is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. We obtain strong convergence of the sequence generated by our algorithm under some suitable conditions on the parameters. The iterative schemes are developed with a way of selecting the step sizes such that the information of operator norm is not necessary. Some applications and numerical experiment is given to analyse the efficiency of our algorithm.

Keywords: Hilbert Space, minimization problems, Moreau-Yosida approximate, split feasibility problem

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Authors: Wania Mohammad Akram, Swetha Kannan, Urooj Shahid, Aisha Sajjad

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Ovarian ectopic pregnancy, a rare manifestation of ectopic gestation, involves the implantation of a fertilized egg on the ovarian surface. This condition poses diagnostic challenges and is associated with significant maternal morbidity if not promptly managed. This report presents the case of a 33-year-old nulliparous woman with a history of polycystic ovary syndrome (PCOS) undergoing ovulation induction therapy. Following her first conception in October 2021, she presented with symptoms of per vaginal spotting and low back pain, prompting a diagnosis of left adnexal ectopic pregnancy confirmed by transvaginal ultrasound and serum beta-human chorionic gonadotropin (B-HCG) levels. Medical management with methotrexate was initiated successfully. In August 2022, the patient conceived again, with subsequent ultrasound revealing a large pelvic collection suggestive of a complex ectopic pregnancy involving both ovaries. Despite initial stability, she developed abdominal pain necessitating emergency laparoscopy, which revealed an ovarian ectopic pregnancy with hemoperitoneum. Laparotomy was performed due to the complexity of the presentation, and histopathology confirmed viable chorionic villi within ovarian tissue. This case underscores the clinical management challenges posed by ovarian ectopic pregnancies, particularly in patients with previous ectopic pregnancies. The discussion reviews current literature on diagnostic modalities, treatment strategies, and outcomes associated with ovarian ectopic pregnancies, emphasizing the role of surgical intervention in cases refractory to conservative management. Tailored approaches considering individual patient factors are crucial to optimize outcomes and preserve fertility in such complex scenarios.

Keywords: obgyn, ovarian ectopic pregnancy, laproscopy, pcos

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Eman Tadros

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Solution Focused Therapy sheds a positive light on a client’s problem(s) by instilling hope, focusing on the connection with the client, and describing the problem in a way to display change being possible. Solution focused therapists highlight clients’ positive strengths, reframe what clients say, do, or believe in a positive statement, action, or belief. Narrative Therapy focuses on the stories individuals tell about their past in which shape their current and future lives. Changing the language used aids clients in reevaluating their values and views of themselves, this then constructs a more positive way of thinking about their story. Both therapies are based on treating each client as an individual with a problem rather than that the individual is a problem and being able to give power back to the client. The purpose of these ideologies is to open a client to alternative understandings. This paper displays how clinicians can empower and identify their clients’ positive strengths and resiliency factors. Narrative and Solution-Focused Techniques will be integrated to instill positivity and empowerment in clients. Techniques such as deconstruction, collaboration, complimenting, miracle/exception/scaling questioning will be analyzed and modeled. Furthermore, bridging Solution Focused Therapy and Narrative Therapy gives a voice to unheard client(s).

Keywords: solution focused therapy, narrative therapy, empowerment, resilience

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Authors: Alessandro Poma, Kal Karim, Sergey Piletsky, Giuseppe Battaglia

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The recent increasing emergency threat to public health of infectious influenza diseases has prompted interest in the detection of avian influenza virus (AIV) H5N1 in humans as well as animals. A variety of technologies for diagnosing AIV infection have been developed. However, various disadvantages (costs, lengthy analyses, and need for high-containment facilities) make these methods less than ideal in their practical application. Molecularly Imprinted Polymeric Nanoparticles (MIP NPs) are suitable to overcome these limitations by having high affinity, selectivity, versatility, scalability and cost-effectiveness with the versatility of post-modification (labeling – fluorescent, magnetic, optical) opening the way to the potential introduction of improved diagnostic tests capable of providing rapid differential diagnosis. Here we present our first results in the production and testing of MIP NPs for the detection of AIV H5N1. Recent developments in the solid-phase synthesis of MIP NPs mean that for the first time a reliable supply of ‘soluble’ synthetic antibodies can be made available for testing as potential biological or diagnostic active molecules. The MIP NPs have the potential to detect viruses that are widely circulating in farm animals and indeed humans. Early and accurate identification of the infectious agent will expedite appropriate control measures. Thus, diagnosis at an early stage of infection of a herd or flock or individual maximizes the efficiency with which containment, prevention and possibly treatment strategies can be implemented. More importantly, substantiating the practicability’s of these novel reagents should lead to an initial reduction and eventually to a potential total replacement of animals, both large and small, to raise such specific serological materials.

Keywords: influenza virus, molecular imprinting, nanoparticles, polymers

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Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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Authors: Chibuzo Okoye Daniels, Gillian Glegg, Lynda Rodwell

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The continuously growing quantity of very slow degrading litter deliberately discarded into the coastal waters around Lagos as marine debris is obvious. What is not known is how to tackle this problem to reduce its prevalence and impact on the environment, economy and community. To identify ways of tackling the marine debris problem two case study areas (Ikoyi and Victoria Islands of Lagos State) were used to assess the root causes, the threat posed by marine debris in the coastal waters around Lagos and the efficacy of current instruments, programmes and initiatives that address marine debris in the study areas. The following methods were used: (1) Self-completed questionnaires for households and businesses within the study areas; (2) Semi-structured interviews with key stakeholders; (3) Observational studies of waste management from collection to disposal and waste management facilities for waste originating from land and maritime sources; (4) Beach surveys and marine debris surveys on shorelines and ports; and (5) Fishing for marine debris. Results of this study identified the following root causes: (1) Indiscriminate human activities and behaviors, and lack of awareness on the part of the main stakeholders and the public of the potential consequences of their actions; (2) Poor solid waste management practices; (3) Lack of strict legal frameworks addressing waste and marine debris problem; and (4) Disposal of non-degradable wastes into domestic sewer system and open streets drains. To effectively tackle marine debris problem in the study areas, adequate, appropriate and cost effective solutions to the above mentioned root causes needs to be identified and effectively transferred for implementation in the study areas.

Keywords: marine debris problem, Lagos state, litter, coastal waters

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Authors: Ajay R, Rammohan B, Sridhar K S S, Gurusharan N

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The objective of the work is to develop a numerical method to solve the inverse mode shape problem by determining the cross-sectional area of a structure for the desired mode shape via the vibration response study of the humerus bone, which is in the form of a cantilever beam with anisotropic material properties. The humerus bone is the long bone in the arm that connects the shoulder to the elbow. The mode shape is assumed to be a higher-order polynomial satisfying a prescribed set of boundary conditions to converge the numerical algorithm. The natural frequency and the mode shapes are calculated for different boundary conditions to find the cross-sectional area of humerus bone from Eigenmode shape with the aid of the inverse mode shape algorithm. The cross-sectional area of humerus bone validates the mode shapes of specific boundary conditions. The numerical method to solve the inverse mode shape problem is validated in the biomedical application by finding the cross-sectional area of a humerus bone in the human arm.

Keywords: Cross-sectional area, Humerus bone, Inverse mode shape problem, Mode shape

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: Engy S. El-Kayal, Mohamed M. S. Arafa

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There are various causes of ankle pain including traumatic and non-traumatic causes. Various imaging techniques are available for assessment of AP. MRI is considered to be the imaging modality of choice for ankle joint evaluation with an advantage of its high spatial resolution, multiplanar capability, hence its ability to visualize small complex anatomical structures around the ankle. However, the high costs and the relatively limited availability of MRI systems, as well as the relatively long duration of the examination all are considered disadvantages of MRI examination. Therefore there is a need for a more rapid and less expensive examination modality with good diagnostic accuracy to fulfill this gap. HRU has become increasingly important in the assessment of ankle disorders, with advantages of being fast, reliable, of low cost and readily available. US can visualize detailed anatomical structures and assess tendinous and ligamentous integrity. The aim of this study was to compare the diagnostic accuracy of HRU with MRI in the assessment of patients with AP. We included forty patients complaining of AP. All patients were subjected to real-time HRU and MRI of the affected ankle. Results of both techniques were compared to surgical and arthroscopic findings. All patients were examined according to a defined protocol that includes imaging the tendon tears or tendinitis, muscle tears, masses, or fluid collection, ligament sprain or tears, inflammation or fluid effusion within the joint or bursa, bone and cartilage lesions, erosions and osteophytes. Analysis of the results showed that the mean age of patients was 38 years. The study comprised of 24 women (60%) and 16 men (40%). The accuracy of HRU in detecting causes of AP was 85%, while the accuracy of MRI in the detection of causes of AP was 87.5%. In conclusions: HRU and MRI are two complementary tools of investigation with the former will be used as a primary tool of investigation and the latter will be used to confirm the diagnosis and the extent of the lesion especially when surgical interference is planned.

Keywords: ankle pain (AP), high-resolution ultrasound (HRU), magnetic resonance imaging (MRI) ultrasonography (US)

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Authors: S. Zenhari, M. R. Hematiyan, A. Khosravifard, M. R. Feizi

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The boundary element method (BEM) and the method of fundamental solutions (MFS) are well-known fundamental solution-based methods for solving a variety of problems. Both methods are boundary-type techniques and can provide accurate results. In comparison to the finite element method (FEM), which is a domain-type method, the BEM and the MFS need less manual effort to solve a problem. The aim of this study is to compare the accuracy and reliability of the BEM and the MFS. This comparison is made for 2D potential and elasticity problems with different boundary and loading conditions. In the comparisons, both convex and concave domains are considered. Both linear and quadratic elements are employed for boundary element analysis of the examples. The discretization of the problem domain in the BEM, i.e., converting the boundary of the problem into boundary elements, is relatively simple; however, in the MFS, obtaining appropriate locations of collocation and source points needs more attention to obtain reliable solutions. The results obtained from the presented examples show that both methods lead to accurate solutions for convex domains, whereas the BEM is more suitable than the MFS for concave domains.

Keywords: boundary element method, method of fundamental solutions, elasticity, potential problem, convex domain, concave domain

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Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Describing clinical cases according to a clinical charting standard that enforces interoperability and enables connected care services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. This article presented a multi-tenant extension to the problem-oriented medical record that we have prototyped previously upon using the GraphQL Application Programming Interface to represent the notion of a problem list. Our implemented extension enables physicians and patients to collaboratively describe the patient case via using multi chatbots to collaboratively describe the patient case using the SOAP charting standard. Our extension also connects the described SOAP patient case with the HL7 FHIR (Health Interoperability Resources) medical record for connecting the patient case to the bench data.

Keywords: problem-oriented medical record, graphQL, chatbots, SOAP

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Authors: Jorge Iván Bañol-Betancur, Lina María Martínez-Sánchez, María de los Ángeles Rodríguez-Gázquez, Estefanía Bahamonde-Olaya, Ana María Gutiérrez-Tamayo, Laura Isabel Jaramillo-Jaramillo, Camilo Ruiz-Mejía, Natalia Morales-Quintero

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Acute chest pain is a distressing sensation between the diaphragm and the base of the neck and it represents a diagnostic challenge for any physician in the emergency department. Objective: To establish the main clinical and epidemiological characteristics of patients who present with chest pain to the emergency department in a private clinic from the city of Medellin, during 2014-2015. Methods: Cross-sectional retrospective observational study. Population and sample were patients who consulted for chest pain in the emergency department who met the eligibility criteria. The information was analyzed in SPSS program vr.21; qualitative variables were described through relative frequencies, and the quantitative through mean and standard deviation ‬or medians according to their distribution in the study population. Results: A total of 231 patients were evaluated, the mean age was 49.5 ± 19.9 years, 56.7% were females. The most frequent pathological antecedents were hypertension 35.5%, diabetes 10,8%, dyslipidemia 10.4% and coronary disease 5.2%. Regarding pain features, in 40.3% of the patients the pain began abruptly, in 38.2% it had a precordial location, for 20% of the cases physical activity acted as a trigger, and 60.6% was oppressive. Costochondritis was the most common cause of chest pain among patients with an established etiologic diagnosis, representing the 18.2%. Conclusions: Although the clinical features of pain reported coincide with the clinical presentation of an acute coronary syndrome, the most common cause of chest pain in study population was costochondritis instead, indicating that it is a differential diagnostic in the approach of patients with pain acute chest.

Keywords: acute coronary syndrome, chest pain, epidemiology, osteochondritis

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Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

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We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

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This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

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Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: cartesian graphs, higher education, movement modeling, problem solving

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: P. Moskal, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, A. Gruntowski, D. Kaminska, L. Kaplon, G. Korcyl, P. Kowalski, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, L. Raczynski, Z. Rudy, P. Salabura, N. G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, W. Wislicki, M. Zielinski, N. Zon

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A new concept and results of the performance tests of the TOF-PET detection system developed at the Jagiellonian University will be presented. The novelty of the concept lies in employing long strips of polymer scintillators instead of crystals as detectors of annihilation quanta, and in using predominantly the timing of signals instead of their amplitudes for the reconstruction of Lines-of-Response. The diagnostic chamber consists of plastic scintillator strips readout by pairs of photo multipliers arranged axially around a cylindrical surface. To take advantage of the superior timing properties of plastic scintillators the signals are probed in the voltage domain with the accuracy of 20 ps by a newly developed electronics, and the data are collected by the novel trigger-less and reconfigurable data acquisition system. The hit-position and hit-time are reconstructed by the dedicated reconstruction methods based on the compressing sensing theory and the library of synchronized model signals. The solutions are subject to twelve patent applications. So far a time-of-flight resolution of ~120 ps (sigma) was achieved for a double-strip prototype with 30 cm field-of-view (FOV). It is by more than a factor of two better than TOF resolution achievable in current TOF-PET modalities and at the same time the FOV of 30 cm long prototype is significantly larger with respect to typical commercial PET devices. The Jagiellonian PET (J-PET) detector with plastic scintillators arranged axially possesses also another advantage. Its diagnostic chamber is free of any electronic devices and magnetic materials thus giving unique possibilities of combining J-PET with CT and J-PET with MRI for scanning the same part of a patient at the same time with both methods.

Keywords: PET-CT, PET-MRI, TOF-PET, scintillator

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Authors: Swati Kapoor, Rajeev Upreti, Monica Mahajan, Abhaya Indrayan, Dinesh Srivastava

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Enteric Fever is caused by gram negative bacilli Salmonella typhi and paratyphi. It is associated with high morbidity and mortality worldwide. Timely initiation of treatment is a crucial step for prevention of any complications. Cultures of body fluids are diagnostic, but not always conclusive or practically feasible in most centers. Moreover, the results of cultures delay the treatment initiation. Serological tests lack diagnostic value. The blood counts can offer a promising option in diagnosis. A retrospective study to find out the relevance of leucopenia and eosinopenia was conducted on 203 culture proven enteric fever patients and 159 culture proven non-enteric fever patients in a tertiary care hospital in New Delhi. The patient details were retrieved from the electronic medical records section of the hospital. Absolute eosinopenia was considered as absolute eosinophil count (AEC) of less than 40/mm³ (normal level: 40-400/mm³) using LH-750 Beckman Coulter Automated machine. Leucopoenia was defined as total leucocyte count (TLC) of less than 4 X 10⁹/l. Blood cultures were done using BacT/ALERT FA plus automated blood culture system before first antibiotic dose was given. Case and control groups were compared using Pearson Chi square test. It was observed that absolute eosinophil count (AEC) of 0-19/mm³ was a significant finding (p < 0.001) in enteric fever patients, whereas leucopenia was not a significant finding (p=0.096). Using Receiving Operating Characteristic (ROC) curves, it was observed that patients with both AEC < 14/mm³ and TCL < 8 x 10⁹/l had 95.6% chance of being diagnosed as enteric fever and only 4.4% chance of being diagnosed as non-enteric fever. This result was highly significant with p < 0.001. This is a very useful association of AEC and TLC found in enteric fever patients of this study which can be used for the early initiation of treatment in clinically suspected enteric fever patients.

Keywords: absolute eosinopenia, absolute eosinophil count, enteric fever, leucopenia, total leucocyte count

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Authors: M. Ndeley

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The performance of global manufacturing supply chains depends on the interaction of production and transport processes. Currently, the scheduling of these processes is done separately without considering mutual requirements, which leads to no optimal solutions. An integrated scheduling of both processes enables the improvement of supply chain performance. The integrated production and transport scheduling problem (PTSP) is NP-hard, so that heuristic methods are necessary to efficiently solve large problem instances as in the case of global manufacturing supply chains. This paper presents a heuristic scheduling approach which handles the integration of flexible production processes with intermodal transport, incorporating flexible land transport. The method is based on a graph that allows a reformulation of the PTSP as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario with a manufacturing facility in South Africa and shipments of finished product to customers within the Country. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different scenarios.

Keywords: production and transport scheduling problem, graph based scheduling, integrated scheduling

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

Abstract:

Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

Procedia PDF Downloads 169

Authors: Yu Menshikov

Abstract:

In this paper the influence of errors of function derivatives in initial time which have been obtained by experiment (uncontrollable inaccuracy) to the results of inverse problem solution was investigated. It was shown that these errors distort the inverse problem solution as a rule near the beginning of interval where the solution are analyzed. Several methods for remove the influence of uncontrollable inaccuracy have been suggested.

Keywords: inverse problems, filtration, uncontrollable inaccuracy

Procedia PDF Downloads 511

Authors: E. Koyuncu

Abstract:

The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

Procedia PDF Downloads 342