Search results for: Amin Akbari

Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Magda Mahmoud Amin Sabbour, El-Sayed H. Shaurub

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The Indian meal moth Plodia interpunctella (Hübner) (Lepidoptera: Pyralidae), of stored grain pests which destroy the seed completely. Their larval stages feed on the nutrient germinating kernels part found in the seeds grain. This leads to a reduction causing a badness to seed germination and seed viability. It controlled by many insecticides which pollute and cusses a harmful diseases to human being. Three tested oils were evaluated on this target pests. Plant extracts, essential oils and medical oils are materials which used to control many stored pests. Plant oils extracts have a lower effects on parasites and predators and not pollute the medium. By using the apparatus gas chromatography flame ionization detector gas chromatography–analysis of three essential oil tested. This research was point to explore and appreciation the activity of three oils and nano gel Beauvericin against P. interpunctella in the laboratory conditions and in the store conditions. The three essential oil tested proved that, percentage of α-Pinene recoded 7.76, 7.72 and 6.66 for C. cyminum, A. squamosal and G. officinale respectively. The composition of the β-Pinene recoded 4.61, 8.92 and 30.63 for the corresponding oils tested. Results showed that after analytically the oils tested, the effective compound of C. cyminum oil are p-cyinene and Terpinene. Results obtained show that the LC50 recorded 125, 112, 55 and 20 ppm after P. interpunctella treated with medical oils of Guaiacum officinale, Annona squamosa, Cuminum cyminum and Beauvericin 3% respectively. The accumulative mortality of P. interpunctella after treated with A.squamosa oil-loaded nanogels which showed that it is the highest oils from infestations recoded when the seed treated with 3% after 48 days, the accumulations obtained 44% at followed by 24 after24 days of storage. Results, cleared that the seed protection by G. officinale recorded 40% at concentrations of 3% after 48 days of storage seeds. C. cyminum was the highest mortality by 98, at concentrations 3%. The highest seed protection proved after C. cyminum oil-loaded nanogels 14% followed by G. officinale 29% and A.squamosa 44%.when the seeds treated with Beauvericin 3%. Results of this work cleared that the essential medical oils have a useful action effect on target insects. Plant essential and medical oils, their active ingredient have potentially high bioactivity against on P. interpunctella. The medical and essential oils incorporation and usage the nano-formulation release stopped the highly degradation vaporization and the increasing in the constancy, and save the lower effectiveness of the dosage/application. The research results proved that the highest seed protection obtained after C. cyminum oil-loaded nanogels followed by G. officinale and A.squamosa. It could be complemented that P. interpunctella were more susceptible to medical oils loaded nanogel (MOLNs ) than medical oils only (MO). MOLNs had best lower amount of the residual activity than MO only. MOLNs might mend the insecticidal action of the medical oil tested by the slow effective release of the medical oils to control P. interpunctella mostly at the lower doses.

Keywords: Cuminum cyminum, annona squamosa, guaiacum officinale, beauvericin 3 %, plodia interpunctella

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Authors: Christiane Paulus

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Post-Islamism assumes that the Quran should not be viewed in terms of what Lyotard identifies as a ‘meta-narrative'. However, its socio-ethical content can be viewed as critical of power discourse (Foucault). Practicing religion seems to be limited to rites and individual spirituality, taqwa. Alternatively, can we build on Muhammad Abduh's classic-modern reform and develop it through a postmodernist frame? This is the main question of this study. Through his general and vague remarks on the context of the Quran, Abduh was the first to refer to the historical and cultural distance of the text as an obstacle for interpretation. His application, however, corresponded to the modern absolute idea of authentic sharia. He was followed by Amin al-Khuli, who hermeneutically linked the content of the Quran to the theory of evolution. Fazlur Rahman and Nasr Hamid abu Zeid remain reluctant to go beyond the general level in terms of context. The hermeneutic circle, therefore, persists in challenging, how to get out to overcome one’s own assumptions. The insight into and the acceptance of the lasting ambivalence of understanding can be grasped as a postmodern approach; it is documented in Derrida's discovery of the shift in text meanings, difference, also in Lyotard's theory of différend. The resulting mixture of meanings (Wolfgang Welsch) can be read together with the classic ambiguity of the premodern interpreters of the Quran (Thomas Bauer). Confronting hermeneutic difficulties in general, Niklas Luhmann proves every description an attribution, tautology, i.e., remaining in the circle. ‘De-tautologization’ is possible, namely by analyzing the distinctions in the sense of objective, temporal and social information that every text contains. This could be expanded with the Kantian aesthetic dimension of reason (critique of pure judgment) corresponding to the iʽgaz of the Coran. Luhmann asks, ‘What distinction does the observer/author make?’ Quran as a speech from God to the first listeners could be seen as a discourse responding to the problems of everyday life of that time, which can be viewed as the general goal of the entire Qoran. Through reconstructing koranic Lifeworlds (Alfred Schütz) in detail, the social structure crystallizes the socio-economic differences, the enormous poverty. The koranic instruction to provide the basic needs for the neglected groups, which often intersect (old, poor, slaves, women, children), can be seen immediately in the text. First, the references to lifeworlds/social problems and discourses in longer koranic passages should be hypothesized. Subsequently, information from the classic commentaries could be extracted, the classical Tafseer, in particular, contains rich narrative material for reconstructing. By selecting and assigning suitable, specific context information, the meaning of the description becomes condensed (Clifford Geertz). In this manner, the text gets necessarily an alienation and is newly accessible. The socio-ethical implications can thus be grasped from the difference of the original problem and the revealed/improved order/procedure; this small step can be materialized as such, not as an absolute solution but as offering plausible patterns for today’s challenges as the Agenda 2030.

Keywords: postmodern hermeneutics, condensed description, sociological approach, small steps of reform

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Authors: Amin Masoumiganjgah, Luke Salmon, Julianne Burnton, Fahimeh Bagheri, Gavin Lenton, S. L. Ezekial Tan

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Introduction: The incidence of proximal biceps tenodesis and acute distal biceps repair is increasing, and rehabilitation protocols following both are variable. Golf is a popular sport within Australia, and the Gold Coast has become a Mecca for golfers, with more courses per capita than anywhere else in the world. Currently, there are no clear guidelines regarding return to golf play following biceps procedures. The aim of this study was to determine biceps brachii activation during the golf swing through electromyographic analysis, and subsequently, aid in rehabilitation guidelines and return to golf following tenodesis and repair. Methods: Subjects were amateur golfers with no previous upper limb surgery. Surface electromyography (EMG) and high-speed video recording were used to analyse activation of the left and right biceps brachii and the anterior deltoid during the golf swing. Each participant’s maximum voluntary contraction (MVC) was recorded, and they were then required to hit a golf ball aiming for specific distances of 2, 50, 100 and 150 metres at a driving range. Noraxon myoResearch and Matlab were used for data analysis. Mean % MVC was calculated for leading and trailing arms during the full swing and its’ 4 phases: back-swing, acceleration, early follow-through and late follow-through. Results: 12 golfers (2 female and 10 male), participated in the study. Median age was 27 (25 – 38), with all being right handed. Over all distances, the mean activation of the short and long head of biceps brachii was < 10% through the full swing. When breaking down the 50, 100 and 150m swing into phases, mean MVC activation was lowest in backswing (5.1%), followed by acceleration (9.7%), early follow-through (9.2%), and late follow-through (21.4%). There was more variation and slightly higher activation in the right biceps (trailing arm) in backswing, acceleration, and early follow-through; with higher activation in the leading arm in late follow-through (25.4% leading, 17.3% trailing). 2m putts resulted in low MVC values (3.1% ) with little variation across swing phases. There was considerable individual variation in results – one tense subject averaged 11.0% biceps MVC through the 2m putting stroke and others recorded peak mean MVC biceps activations of 68.9% at 50m, 101.3% at 100m, and 111.3% at 150m. Discussion: Previous studies have investigated the role of rotator cuff, spine, and hip muscles during the golf swing however, to our knowledge, this is the first study that investigates the activation of biceps brachii. Many rehabilitation programs following a biceps tenodesis or repair allow active range against gravity and restrict strengthening exercises until 6 weeks, and this does not appear to be associated with any adverse outcome. Previous studies demonstrate a range of < 10% MVC is similar to the unloaded biceps brachii during walking(1), active elbow flexion with the hand positioned either in pronation or supination will produce MVC < 20% throughout range(2) and elbow flexion with a 4kg dumbbell can produce mean MVC’s of around 40%(3). Our study demonstrates that increasing activation is associated with the leading arm, increasing shot distance and the late follow-through phase. Although the cohort mean MVC of the biceps brachii is <10% through the full swing, variability is high and biceps activation reach peak mean MVC’s of over 100% in different swing phases for some individuals. Given these EMG values, caution is advised when advising patients post biceps procedures to return to long distance golf shots, particularly when the leading arm is involved. Even though it would appear that putting would be as safe as having an unloaded hand out of a sling following biceps procedures, the variability of activation patterns across different golfers would lead us to caution against accelerated golf rehabilitation in those who may be particularly tense golfers. The 50m short iron shot was too long to consider as a chip shot and more work can be done in this area to determine the safety of chipping.

Keywords: electromyographic analysis, biceps brachii rupture, golf swing, tendon surgery

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