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مليح وحماره الفريد : المغامرة اللطيفة على كوكب المريخ
تتحدث القصة عن مليح الذي يتوجه نحو قريته من أجل أن يقضي فيها عطلته الصيفية مع جده العزيز تورغوت. وبعدها ينطلق في مغامرة لا يمكن أن يتصورها العقل، مغامرة غريبة وعجيبة مع خشاف العنب اللذيذ الذي يصنعه جده تورغوت، مغامرة يشاركه فيها الحمار الصغير فستق الذي يفهم بالخشاف وبالكلام اللطيف. ولكن ... هل سيتمكن المغامر مليح والحمار الصغير فستق من إنقاذ الكوكب الأحمر \"المريخ\" من براثن الشرير غاسبر ؟ وهل سيتمكن من العثور على علاج لمرض الأمير الصغير ماجي ؟ وما هو سر طائر الروح هذا الذي ظهر أمامنا فجأة ؟ حسنا ... وهل يمكن أن يكون الأسم الحقيقي لكوكب المريخ مليح ؟ مليح وحماره الفريد فستق يدعوانكم لتنطلقوا معهما في مغامرة مثيرة ومضحكة !.
Book
Comparison of approaches for source attribution of ESBL-producing Escherichia coli in Germany
Extended-spectrum beta-lactamase (ESBL)-producing
Escherichia (E
.
) coli
have been widely described as the cause of treatment failures in humans around the world. The origin of human infections with these microorganisms is discussed controversially and in most cases hard to identify. Since they pose a relevant risk to human health, it becomes crucial to understand their sources and the transmission pathways. In this study, we analyzed data from different studies in Germany and grouped ESBL-producing
E
.
coli
from different sources and human cases into subtypes based on their phenotypic and genotypic characteristics (ESBL-genotype,
E
.
coli
phylogenetic group and phenotypic antimicrobial resistance pattern). Then, a source attribution model was developed in order to attribute the human cases to the considered sources. The sources were from different animal species (cattle, pig, chicken, dog and horse) and also from patients with nosocomial infections. The human isolates were gathered from community cases which showed to be colonized with ESBL-producing
E
.
coli
. We used the attribution model first with only the animal sources (Approach A) and then additionally with the nosocomial infections (Approach B). We observed that all sources contributed to the human cases, nevertheless, isolates from nosocomial infections were more related to those from human cases than any of the other sources. We identified subtypes that were only detected in the considered animal species and others that were observed only in the human population. Some subtypes from the human cases could not be allocated to any of the sources from this study and were attributed to an unknown source. Our study emphasizes the importance of human-to-human transmission of ESBL-producing
E
.
coli
and the different role that pets, livestock and healthcare facilities may play in the transmission of these resistant bacteria. The developed source attribution model can be further used to monitor future trends. A One Health approach is necessary to develop source attribution models further to integrate also wildlife, environmental as well as food sources in addition to human and animal data.
Journal Article
Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach
Occupational risk assessment (ORA) is a process that consists of evaluating, ranking, and classifying the hazards and associated risks arising in any workplace from the viewpoint of occupational health and safety. Many ORA methods have been proposed in the literature, from a single independent expert to participatory methodologies made by group decision and simple to complex ones. In this paper, a holistic ORA is presented, which uses two important multi-attribute decision methods named Bayesian Best-Worst Method (Bayesian BWM) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Bayesian BWM is used to determine the importance weights of six different assessment criteria, which are the probability of hazardous event (P), frequency (F), severity (S), detectability (D), cost (C) and sensitivity not to use personal protective equipment (SNP). Since the classical BWM finds solution to the weights of a number of criteria from only one expert's judgment, Bayesian BWM is preferred in this paper (1) to enable participation of a group of experts, (2) to aggregate the preferences of these multiple experts into consensus without loss of information and (3) to follow a probabilistic way for solving the ORA problem. The hazards are then ranked by VIKOR. The approach is implemented in the ORA process of a textile production plant. Results of risk analysis showed that electricity hazard and associated risks constitute the highest risk ratings. These hazards arise from the product, process, human and working environment. The associated risks are evaluated, prioritized, and detailed control measures are proposed. This study made comparisons with the classical BWM-VIKOR approach to demonstrate the proposed approach's difference and practicality. Results can also help practitioners and risk analysts in formulating the improvement measures to increase the overall safety of the working environment further.
Journal Article
Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA
Occupational safety issues encountered in the worksite environment are the issues that companies should consider in improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to mitigate their consequences. In this study, a new model is developed for occupational risk assessment by merging two well-known multi-criteria decision-making methods named best and worst method (BWM) and multi attribute ideal real comparative analysis (MAIRCA) under fuzzy environment. The proposed model differentiates from other similar models by three aspects. First, it considers severity of a hazard and its associated risk from the human and environmental riskiness perspectives. Secondly, it applies fuzzy BWM (F-BWM) to calculate the relative importance of three risk factors named as “probability, frequency and severity” of traditional Fine–Kinney method. Thirdly, it applies fuzzy MAIRCA (F-MAIRCA) to rank hazards according to their risk level using importance values obtained by F-BWM. To show applicability of the approach, a case study of risk assessment in a marble factory is fulfilled. Additionally, a number of validation studies including benchmarking analysis with fuzzy VIKOR and fuzzy TOPSIS methods; a sensitivity analysis by varying importance weights of risk factors are carried out to highlight the solidity of the proposed approach.
Journal Article
Franz Kafka’s “Das Urteil” (1913) as Media History: Writing–Cinema–AI
In this essay, I read Kafka’s 1913 story, “Das Urteil”, as positing an anachronistic media history, with Georg the son representing the older medium of writing, while his father stands in for the newer medium of cinema. The father–son conflict is thus refigured as an intergenerational media war. In addition, I suggest that the end of the story points toward a non-human mediation, which resembles artificial intelligence as imagined by Friedrich Kittler’s media theory.
Journal Article
Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders
The gold standards for gait analysis are instrumented walkways and marker-based motion capture systems, which require costly infrastructure and are only available in hospitals and specialized gait clinics. Even though the completeness and the accuracy of these systems are unquestionable, a mobile and pervasive gait analysis alternative suitable for non-hospital settings is a clinical necessity. Using inertial sensors for gait analysis has been well explored in the literature with promising results. However, the majority of the existing work does not consider realistic conditions where data collection and sensor placement imperfections are imminent. Moreover, some of the underlying assumptions of the existing work are not compatible with pathological gait, decreasing the accuracy. To overcome these challenges, we propose a foot-mounted inertial sensor-based gait analysis system that extends the well-established zero-velocity update and Kalman filtering methodology. Our system copes with various cases of data collection difficulties and relaxes some of the assumptions invalid for pathological gait (e.g., the assumption of observing a heel strike during a gait cycle). The system is able to extract a rich set of standard gait metrics, including stride length, cadence, cycle time, stance time, swing time, stance ratio, speed, maximum/minimum clearance and turning rate. We validated the spatio-temporal accuracy of the proposed system by comparing the stride length and swing time output with an IR depth-camera-based reference system on a dataset comprised of 22 subjects. Furthermore, to highlight the clinical applicability of the system, we present a clinical discussion of the extracted metrics on a disjoint dataset of 17 subjects with various neurological conditions.
Journal Article
A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility
Failure modes and effects analysis (FMEA) is a commonly used step-by-step approach to assess potential failures existing in a product or process design. In this paper, a modified FMEA model based on an interval-valued spherical fuzzy extension of technique for order preference by similarity to ideal solution (IVSF-TOPSIS) is proposed to cope with drawbacks of the traditional risk priority number (RPN) computation. Spherical fuzzy sets are the integration of Pythagorean fuzzy sets and neutrosophic sets. They provide more freedom to experts in decision making by including the degree of membership, non-membership, and hesitation of fuzzy sets. Therefore, initially, TOPSIS is merged with a special branch of spherical sets “interval-valued spherical fuzzy sets” to determine priorities of emerged failures. As a novelty to traditional RPN of FMEA, three parameters called cost, prevention, and effectiveness in addition to the existed parameters of severity, occurrence and detection are attached to the proposed approach. Weights of these parameters are determined via an interval-valued spherical weighted arithmetic mean operator (IVSWAM). As a demonstration, a case study in a marble manufacturing facility is provided to show the applicability of the novel model. Results show that the most crucial failure modes concern with the maintenance and repairing works of the factory and the lack of technical periodic checks of lifting vehicles regarding “block area: crane” failures. Some comparative and validation studies are also performed to test the solidity of the approach.
Journal Article
A general skull stripping of multiparametric brain MRIs using 3D convolutional neural network
Accurate skull stripping facilitates following neuro-image analysis. For computer-aided methods, the presence of brain skull in structural magnetic resonance imaging (MRI) impacts brain tissue identification, which could result in serious misjudgments, specifically for patients with brain tumors. Though there are several existing works on skull stripping in literature, most of them either focus on healthy brain MRIs or only apply for a single image modality. These methods may be not optimal for multiparametric MRI scans. In the paper, we propose an ensemble neural network (EnNet), a 3D convolutional neural network (3DCNN) based method, for brain extraction on multiparametric MRI scans (mpMRIs). We comprehensively investigate the skull stripping performance by using the proposed method on a total of 15 image modality combinations. The comparison shows that utilizing all modalities provides the best performance on skull stripping. We have collected a retrospective dataset of 815 cases with/without glioblastoma multiforme (GBM) at the University of Pittsburgh Medical Center (UPMC) and The Cancer Imaging Archive (TCIA). The ground truths of the skull stripping are verified by at least one qualified radiologist. The quantitative evaluation gives an average dice score coefficient and Hausdorff distance at the 95th percentile, respectively. We also compare the performance to the state-of-the-art methods/tools. The proposed method offers the best performance.
The contributions of the work have five folds: first, the proposed method is a fully automatic end-to-end for skull stripping using a 3D deep learning method. Second, it is applicable for mpMRIs and is also easy to customize for any MRI modality combination. Third, the proposed method not only works for healthy brain mpMRIs but also pre-/post-operative brain mpMRIs with GBM. Fourth, the proposed method handles multicenter data. Finally, to the best of our knowledge, we are the first group to quantitatively compare the skull stripping performance using different modalities. All code and pre-trained model are available at:
https://github.com/plmoer/skull_stripping_code_SR
.
Journal Article
AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis
Risk analysis (RA) contains several methodologies that object to ensure the protection and safety of occupational stakeholders. Multi attribute decision-making (MADM) is one of the most important RA methodologies that is applied to several areas from manufacturing to information technology. With the widespread use of computer networks and the Internet, information security has become very important. Information security is vital as institutions are mostly dependent on information, technology, and systems. This requires a comprehensive and effective implementation of information security RA. Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are commonly used MADM methods and recently used for RA. In this study, a new RA methodology is proposed based on AHP–TOPSIS integration extended with Pythagorean fuzzy sets. AHP strengthened by interval-valued Pythagorean fuzzy numbers is used to weigh risk parameters with expert judgment. Then, TOPSIS with Pythagorean fuzzy numbers is used to prioritize previously identified risks. A comparison of the proposed approach with three approaches (classical RA method, Pythagorean fuzzy VIKOR and Pythagorean fuzzy MOORA) is also provided. To illustrate the feasibility and practicality of the proposed approach, a case study for information security RA in corrugated cardboard sector is executed.
Journal Article