Spiritual Pathology Theory of the Sound Heart Model: Socio-Cultural Factors of Spiritual Distress

Introduction: Spiritual Pathology is the study of disturbing factors in the relationship between man and God, the process of disruption in secure attachment to God, which causes spiritual distress in relation to self, people, and the world of creation.Areas covered: Balbi defines attachment as deep emotional bond with special people in life, whose interaction brings security, joy and happiness, and their presence brings peace in times of stress. Kirkpatrick generalized the style of attachment to parents to attachment to God. Expert opinion: In the Sound Heart Model, worship is natural need. The basis of religion is secure attachment to God. Secure attachment to God is belief in the presence and sufficiency of God, as a responsive safe haven. The basis of attachment to God is positive image of God and “recognizing the truth of religion” by the Prophet. The Prophet, as interpreter of Qur’an and spiritual role-model, has healthy spiritual personality. Acceptance of religion, at the time of intellectual maturity, should be done without imitation and coercion, based on knowing the truth of religion, with a free and informed choice. Spiritual pathology is the study of socio-cultural factors that cause misunderstanding of religion, negative image of God and insecure attachment to God

Long-term Tracking in the Wild: A Benchmark

We introduce the OxUvA dataset and benchmark for evaluating single-object tracking algorithms. Benchmarks have enabled great strides in the field of object tracking by defining standardized evaluations on large sets of diverse videos. However, these works have focused exclusively on sequences that are just tens of seconds in length and in which the target is always visible. Consequently, most researchers have designed methods tailored to this "short-term" scenario, which is poorly representative of practitioners' needs. Aiming to address this disparity, we compile a long-term, large-scale tracking dataset of sequences with average length greater than two minutes and with frequent target object disappearance. The OxUvA dataset is much larger than the object tracking datasets of recent years: it comprises 366 sequences spanning 14 hours of video. We assess the performance of several algorithms, considering both the ability to locate the target and to determine whether it is present or absent. Our goal is to offer the community a large and diverse benchmark to enable the design and evaluation of tracking methods ready to be used "in the wild". The project website is http://oxuva.netComment: To appear at ECCV 201

Experimental study and CFD analysis on vortex tube

Paper presented at the 6th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 30 June - 2 July, 2008.In this experimental study of the vortex tube performance has been carried out to investigate the parameters affecting vortex tube operation. Four cases have been studied, in which the influences of the tube length L, the number of entrance nozzles Nz, cold air orifice diameters dc and inlet pressure under various condition. The effects of these parameters on the hot and cold outlet temperature as function of cold air mass ratio (e ) are discussed and presented. And also the coefficient of performance (COP) of the vortex tube as a refrigerator and as a heat pump has been calculated. Three Dimension numerical modelling of vortex tube has been evolved through CFD analysis by using the k– turbulence model. Axial, radial and tangential components of the velocity together with the temperature and pressure fields within the vortex tube are simulated. Predictions from the present CFD simulations were compared with data obtained from our experiments under the same geometrical and operating conditions.vk201

Pratique anesthésique à Lubumbashi: indications, types de chirurgie et types de patient

Introduction: Cette étude a pour objectif de décrire la pratique anesthésique dans un pays à faible revenu et où le plateau technique anesthésique est moins équipé. Méthodes: Une étude descriptive transversale a été menée durant l'année 2013. L'enquête a concerné les pratiques anesthésiques, les indications chirurgicales et les caractéristiques des malades. L'encodage et l'analyse des données ont été réalisées grâce aux logiciels Epi Info 3.5.3 et Excel 2010. Résultats: Nous avons enregistré 2358 patients dont l'âge médian était de 29 + 15 ans, avec 81,5% âgés de 11 à 50 ans. Parmi eux, 67,3% des malades étaient du sexe féminin. Dans ensemble, 62,5% de ces patients étaient pris en charge pour les interventions programmées. L'évaluation du risque anesthésique a montré que 91,9% des patients étaient de la classe ASA I et II. La chirurgie la plus pratiquée était viscérale (46,7%) suivie de la chirurgie gynéco-obstétricale (29,2%). Les différents types d'anesthésie étaient les suivants: anesthésie générale (87,6%), locorégionale (11,8%) et combinée (0,6%). Conclusion: La pratique anesthésique dans la population d'étude était dominée par l'anesthésie générale. Les malades étaient au trois quart de sexe féminin et de la classe ASA I et II. Les résultats de cette étude indiquent la nécessité d'évaluer l'issue de cette pratique. La pratique anesthésique à Lubumbashi est tributaire du plateau technique, es compétences du personnel et de l'acceptabilité du type d'anesthésie par les patients

Biochemical quality comparison of forced air dried osmo-dehydrated cashew apple products infused with spice mixture and sugar

Cashew apple is a pseudo-fruit available abundantly during harvest seasons (March to July) and majority of them goes as waste because of their perishability and poor shelf life. However, the absence of distinct exocarp and seeds are some of the potential advantages for processing utility. Hence, in the present study, osmo-dehydrated products were prepared from two maturity stages i.e. breaker and ripe stages using sugar, spice mixture and were referred to as cashew fig and chew, respectively. The drying efficiency and product recovery were conquered by cashew chew and fig, respectively. Based on the biochemical and organoleptic qualities, ripe fruits werefound suitable for preparation of chew and fig. The tannin content responsible for acridity got reduced (chew of ripe stage 1.18 to 0.53 mg/g and chew of breaker stage 1.85 to 0.68 mg/g) during the process of osmo- dehydration. Excluding total antioxidant activity, all other biochemical properties were found to be improved compared to their respective controls

Non-Causal Tracking by Deblatting

Tracking by Deblatting stands for solving an inverse problem of deblurring and image matting for tracking motion-blurred objects. We propose non-causal Tracking by Deblatting which estimates continuous, complete and accurate object trajectories. Energy minimization by dynamic programming is used to detect abrupt changes of motion, called bounces. High-order polynomials are fitted to segments, which are parts of the trajectory separated by bounces. The output is a continuous trajectory function which assigns location for every real-valued time stamp from zero to the number of frames. Additionally, we show that from the trajectory function precise physical calculations are possible, such as radius, gravity or sub-frame object velocity. Velocity estimation is compared to the high-speed camera measurements and radars. Results show high performance of the proposed method in terms of Trajectory-IoU, recall and velocity estimation.Comment: Published at GCPR 2019, oral presentation, Best Paper Honorable Mention Awar

Long-Term Visual Object Tracking Benchmark

We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking. The dataset consists of 50 HD videos from real world scenarios, encompassing a duration of over 400 minutes (676K frames), making it more than 20 folds larger in average duration per sequence and more than 8 folds larger in terms of total covered duration, as compared to existing generic datasets for visual tracking. The proposed dataset paves a way to suitably assess long term tracking performance and train better deep learning architectures (avoiding/reducing augmentation, which may not reflect real world behaviour). We benchmark the dataset on 17 state of the art trackers and rank them according to tracking accuracy and run time speeds. We further present thorough qualitative and quantitative evaluation highlighting the importance of long term aspect of tracking. Our most interesting observations are (a) existing short sequence benchmarks fail to bring out the inherent differences in tracking algorithms which widen up while tracking on long sequences and (b) the accuracy of trackers abruptly drops on challenging long sequences, suggesting the potential need of research efforts in the direction of long-term tracking.Comment: ACCV 2018 (Oral

Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers

This paper improves state-of-the-art visual object trackers that use online adaptation. Our core contribution is an offline meta-learning-based method to adjust the initial deep networks used in online adaptation-based tracking. The meta learning is driven by the goal of deep networks that can quickly be adapted to robustly model a particular target in future frames. Ideally the resulting models focus on features that are useful for future frames, and avoid overfitting to background clutter, small parts of the target, or noise. By enforcing a small number of update iterations during meta-learning, the resulting networks train significantly faster. We demonstrate this approach on top of the high performance tracking approaches: tracking-by-detection based MDNet and the correlation based CREST. Experimental results on standard benchmarks, OTB2015 and VOT2016, show that our meta-learned versions of both trackers improve speed, accuracy, and robustness.Comment: Code: https://github.com/silverbottlep/meta_tracker

Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking

Visual object tracking is one of the major challenges in the field of computer vision. Correlation Filter (CF) trackers are one of the most widely used categories in tracking. Though numerous tracking algorithms based on CFs are available today, most of them fail to efficiently detect the object in an unconstrained environment with dynamically changing object appearance. In order to tackle such challenges, the existing strategies often rely on a particular set of algorithms. Here, we propose a robust framework that offers the provision to incorporate illumination and rotation invariance in the standard Discriminative Correlation Filter (DCF) formulation. We also supervise the detection stage of DCF trackers by eliminating false positives in the convolution response map. Further, we demonstrate the impact of displacement consistency on CF trackers. The generality and efficiency of the proposed framework is illustrated by integrating our contributions into two state-of-the-art CF trackers: SRDCF and ECO. As per the comprehensive experiments on the VOT2016 dataset, our top trackers show substantial improvement of 14.7% and 6.41% in robustness, 11.4% and 1.71% in Average Expected Overlap (AEO) over the baseline SRDCF and ECO, respectively.Comment: Published in ACCV 201