Search results for: structural and statistical pattern recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11889

Search results for: structural and statistical pattern recognition

8349 The Principle of a Thought Formation: The Biological Base for a Thought

Authors: Ludmila Vucolova

Abstract:

The thought is a process that underlies consciousness and cognition and understanding its origin and processes is a longstanding goal of many academic disciplines. By integrating over twenty novel ideas and hypotheses of this theoretical proposal, we can speculate that thought is an emergent property of coded neural events, translating the electro-chemical interactions of the body with its environment—the objects of sensory stimulation, X, and Y. The latter is a self- generated feedback entity, resulting from the arbitrary pattern of the motion of a body’s motor repertory (M). A culmination of these neural events gives rise to a thought: a state of identity between an observed object X and a symbol Y. It manifests as a “state of awareness” or “state of knowing” and forms our perception of the physical world. The values of the variables of a construct—X (object), S1 (sense for the perception of X), Y (object), S2 (sense for perception of Y), and M (motor repertory that produces Y)—will specify the particular conscious percept at any given time. The proposed principle of interaction between the elements of a construct (X, Y, S1, S2, M) is universal and applies for all modes of communication (normal, deaf, blind, deaf and blind people) and for various language systems (Chinese, Italian, English, etc.). The particular arrangement of modalities of each of the three modules S1 (5 of 5), S2 (1 of 3), and M (3 of 3) defines a specific mode of communication. This multifaceted paradigm demonstrates a predetermined pattern of relationships between X, Y, and M that passes from generation to generation. The presented analysis of a cognitive experience encompasses the key elements of embodied cognition theories and unequivocally accords with the scientific interpretation of cognition as the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses, and cognition means thinking and awareness. By assembling the novel ideas presented in twelve sections, we can reveal that in the invisible “chaos”, there is an order, a structure with landmarks and principles of operations and mental processes (thoughts) are physical and have a biological basis. This innovative proposal explains the phenomenon of mental imagery; give the first insight into the relationship between mental states and brain states, and support the notion that mind and body are inseparably connected. The findings of this theoretical proposal are supported by the current scientific data and are substantiated by the records of the evolution of language and human intelligence.

Keywords: agent, awareness, cognitive, element, experience, feedback, first person, imagery, language, mental, motor, object, sensory, symbol, thought

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8348 Adaptive Few-Shot Deep Metric Learning

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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8347 Enhancing Fall Detection Accuracy with a Transfer Learning-Aided Transformer Model Using Computer Vision

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 158
8346 Multimodal Characterization of Emotion within Multimedia Space

Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

Abstract:

Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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8345 Chinese Event Detection Technique Based on Dependency Parsing and Rule Matching

Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing

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8344 Plantar Neuro-Receptor Activation in Total Knee Arthroplasty Patients: Impact on Clinical Function, Pain, and Stiffness - A Randomized Controlled Trial

Authors: Woolfrey K., Woolfrey M., Bolton C. L., Warchuk D.

Abstract:

Objectives: Osteoarthritis is the most common joint disease of adults worldwide. Despite total knee arthroplasty (TKA) demonstrating high levels of success, 20% of patients report dissatisfaction with their result. VOXX Wellness Stasis Socks are embedded with a proprietary pattern of neuro-receptor activation points that have been proven to activate a precise neuro-response, according to the pattern theory of haptic perception, which stimulates improvements in pain and function. The use of this technology in TKA patients may prove beneficial as an adjunct to recovery as many patients suffer from deficits to their proprioceptive system caused by ligamentous damage and alterations to mechanoreceptors during the procedure. We hypothesized that VOXX Wellness Stasis Socks are a safe, cost-effective, and easily scalable strategy to support TKA patients through their recovery. Design: Double-blinded, placebo-controlled randomized trial. Participants: Patients scheduled to receive TKA were considered eligible for inclusion in the trial. Interventions: Intervention group (I): VOXX Wellness Stasis socks containing receptor point-activation technology. Control group (C): VOXX Wellness Stasis socks without receptor point-activation technology. Sock use during the waking hours x 6 weeks. Main Outcome Measures: Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) questionnaire completed at baseline, 2 weeks, and 6 weeks to assess pain, stiffness, and physical function. Results: Data analysis using SPSS software. P-values, effect sizes, and confidence intervals are reported to assess clinical relevance of the finding. Physical status classifications were compared using t-test. Within-subject and between-subject differences in the mean WOMAC were analyzed by ANOVA. Effect size was analyzed using Cramer’s V. Consistent improvement in WOMAC scores for pain and stiffness at 2 weeks post op in the I over the C group. The womac scores assessing physical function showed a consistent improvement at both 2 and 6 weeks post op in the I group compared to C group. Conclusions: VOXX proved to be a low cost, safe intervention in TKA to help patients improve with regard to pain, stiffness, and physical function. Disclosures: None

Keywords: osteoarthritis, RCT, pain management, total knee arthroplasty

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8343 Quest for an Efficient Green Multifunctional Agent for the Synthesis of Metal Nanoparticles with Highly Specified Structural Properties

Authors: Niharul Alam

Abstract:

The development of energy efficient, economic and eco-friendly synthetic protocols for metal nanoparticles (NPs) with tailor-made structural properties and biocompatibility is a highly cherished goal for researchers working in the field of nanoscience and nanotechnology. In this context, green chemistry is highly relevant and the 12 principles of Green Chemistry can be explored to develop such synthetic protocols which are practically implementable. One of the most promising green chemical synthetic methods which can serve the purpose is biogenic synthetic protocol, which utilizes non-toxic multifunctional reactants derived from natural, biological sources ranging from unicellular organisms to higher plants that are often characterized as “medicinal plants”. Over the past few years, a plethora of medicinal plants have been explored as the source of this kind of multifunctional green chemical agents. In this presentation, we focus on the syntheses of stable monometallic Au and Ag NPs and also bimetallic Au/Ag alloy NPs with highly efficient catalytic property using aqueous extract of leaves of Indian Curry leaf plat (Murraya koenigii Spreng.; Fam. Rutaceae) as green multifunctional agents which is extensively used in Indian traditional medicine and cuisine. We have also studied the interaction between the synthesized metal NPs and surface-adsorbed fluorescent moieties, quercetin and quercetin glycoside which are its chemical constituents. This helped us to understand the surface property of the metal NPs synthesized by this plant based biogenic route and to predict a plausible mechanistic pathway which may help in fine-tuning green chemical methods for the controlled synthesis of various metal NPs in future. We observed that simple experimental parameters e.g. pH and temperature of the reaction medium, concentration of multifunctional agent and precursor metal ions play important role in the biogenic synthesis of Au NPs with finely tuned structures.

Keywords: green multifunctional agent, metal nanoparticles, biogenic synthesis

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8342 ACBM: Attention-Based CNN and Bi-LSTM Model for Continuous Identity Authentication

Authors: Rui Mao, Heming Ji, Xiaoyu Wang

Abstract:

Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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8341 Autonomous Quantum Competitive Learning

Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

Abstract:

Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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8340 Understanding the Lithiation/Delithiation Mechanism of Si₁₋ₓGeₓ Alloys

Authors: Laura C. Loaiza, Elodie Salager, Nicolas Louvain, Athmane Boulaoued, Antonella Iadecola, Patrik Johansson, Lorenzo Stievano, Vincent Seznec, Laure Monconduit

Abstract:

Lithium-ion batteries (LIBs) have an important place among energy storage devices due to their high capacity and good cyclability. However, the advancements in portable and transportation applications have extended the research towards new horizons, and today the development is hampered, e.g., by the capacity of the electrodes employed. Silicon and germanium are among the considered modern anode materials as they can undergo alloying reactions with lithium while delivering high capacities. It has been demonstrated that silicon in its highest lithiated state can deliver up to ten times more capacity than graphite (372 mAh/g): 4200 mAh/g for Li₂₂Si₅ and 3579 mAh/g for Li₁₅Si₄, respectively. On the other hand, germanium presents a capacity of 1384 mAh/g for Li₁₅Ge₄, and a better electronic conductivity and Li ion diffusivity as compared to Si. Nonetheless, the commercialization potential of Ge is limited by its cost. The synergetic effect of Si₁₋ₓGeₓ alloys has been proven, the capacity is increased compared to Ge-rich electrodes and the capacity retention is increased compared to Si-rich electrodes, but the exact performance of this type of electrodes will depend on factors like specific capacity, C-rates, cost, etc. There are several reports on various formulations of Si₁₋ₓGeₓ alloys with promising LIB anode performance with most work performed on complex nanostructures resulting from synthesis efforts implying high cost. In the present work, we studied the electrochemical mechanism of the Si₀.₅Ge₀.₅ alloy as a realistic micron-sized electrode formulation using carboxymethyl cellulose (CMC) as the binder. A combination of a large set of in situ and operando techniques were employed to investigate the structural evolution of Si₀.₅Ge₀.₅ during lithiation and delithiation processes: powder X-ray diffraction (XRD), X-ray absorption spectroscopy (XAS), Raman spectroscopy, and 7Li solid state nuclear magnetic resonance spectroscopy (NMR). The results have presented a whole view of the structural modifications induced by the lithiation/delithiation processes. The Si₀.₅Ge₀.₅ amorphization was observed at the beginning of discharge. Further lithiation induces the formation of a-Liₓ(Si/Ge) intermediates and the crystallization of Li₁₅(Si₀.₅Ge₀.₅)₄ at the end of the discharge. At really low voltages a reversible process of overlithiation and formation of Li₁₅₊δ(Si₀.₅Ge₀.₅)₄ was identified and related with a structural evolution of Li₁₅(Si₀.₅Ge₀.₅)₄. Upon charge, the c-Li₁₅(Si₀.₅Ge₀.₅)₄ was transformed into a-Liₓ(Si/Ge) intermediates. At the end of the process an amorphous phase assigned to a-SiₓGey was recovered. Thereby, it was demonstrated that Si and Ge are collectively active along the cycling process, upon discharge with the formation of a ternary Li₁₅(Si₀.₅Ge₀.₅)₄ phase (with a step of overlithiation) and upon charge with the rebuilding of the a-Si-Ge phase. This process is undoubtedly behind the enhanced performance of Si₀.₅Ge₀.₅ compared to a physical mixture of Si and Ge.

Keywords: lithium ion battery, silicon germanium anode, in situ characterization, X-Ray diffraction

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8339 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation

Authors: Carlos Riascos, Peter Thomson

Abstract:

Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

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8338 Intelligent Grading System of Apple Using Neural Network Arbitration

Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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8337 Comparison of the H-Index of Researchers of Google Scholar and Scopus

Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

Abstract:

H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

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8336 An Alternative Institutional Design for Efficient Management of Nepalese Irrigation Systems

Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

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Institutional design is important if water resources are to be managed efficiently. In Nepal, the supply of water in both farmer- and agency-managed irrigation systems is inefficient because of the weak institutional frameworks. This type of inefficiency is linked with collective problems such as non-excludability of irrigation water, inadequate recognition of property rights and externalities. Irrigation scheme surveys from Nepal as well as existing literature revealed that the Nepalese irrigation sector is facing many issues such as low cost recovery, inadequate maintenance of the schemes and inefficient allocation and utilization of irrigation water. The institutional practices currently in place also fail to create/force any incentives for farmers to use water efficiently and to pay for its use. This, thus, compels the need of refined institutional framework that can address the collective problems and improve irrigation efficiency.

Keywords: agency-managed, cost recovery, farmer-managed, institutional design

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8335 Thermal Performance of a Pair of Synthetic Jets Equipped in Microchannel

Authors: J. Mohammadpour, G. E. Lau, S. Cheng, A. Lee

Abstract:

Numerical study was conducted using two synthetic jet actuators attached underneath a micro-channel. By fixing the oscillating frequency and diaphragm amplitude, the effects on the heat transfer within the micro-channel were investigated with two synthetic jets being in-phase and 180° out-of-phase at different orifice spacing. There was a significant benefit identified with two jets being 180° out-of-phase with each other at the orifice spacing of 2 mm. By having this configuration, there was a distinct pattern of vortex forming which disrupts the main channel flow as well as promoting thermal mixing at high velocity within the channel. Therefore, this configuration achieved higher cooling performance compared to the other cases studied in terms of the reduction in the maximum temperature and cooling uniformity in the silicon wafer.

Keywords: synthetic jets, microchannel, electronic cooling, computational fluid dynamics

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8334 Shear Behavior of Reinforced Concrete Beams Casted with Recycled Coarse Aggregate

Authors: Salah A. Aly, Mohammed A. Ibrahim, Mostafa M. khttab

Abstract:

The amount of construction and demolition (C&D) waste has increased considerably over the last few decades. From the viewpoint of environmental preservation and effective utilization of resources, crushing C&D concrete waste to produce coarse aggregate (CA) with different replacement percentage for the production of new concrete is one common means for achieving a more environment-friendly concrete. In the study presented herein, the investigation was conducted in two phases. In the first phase, the selection of the materials was carried out and the physical, mechanical and chemical characteristics of these materials were evaluated. Different concrete mixes were designed. The investigation parameter was Recycled Concrete Aggregate (RCA) ratios. The mechanical properties of all mixes were evaluated based on compressive strength and workability results. Accordingly, two mixes have been chosen to be used in the next phase. In the second phase, the study of the structural behavior of the concrete beams was developed. Sixteen beams were casted to investigate the effect of RCA ratios, the shear span to depth ratios and the effect of different locations and reinforcement of openings on the shear behavior of the tested specimens. All these beams were designed to fail in shear. Test results of the compressive strength of concrete indicated that, replacement of natural aggregate by up to 50% recycled concrete aggregates in mixtures with 350 Kg/m3 cement content led to increase of concrete compressive strength. Moreover, the tensile strength and the modulus of elasticity of the specimens with RCA have very close values to those with natural aggregates. The ultimate shear strength of beams with RCA is very close to those with natural aggregates indicating the possibility of using RCA as partial replacement to produce structural concrete elements. The validity of both the Egyptian Code for the design and implementation of Concrete Structures (ECCS) 203-2007 and American Concrete Institute (ACI) 318-2011Codes for estimating the shear strength of the tested RCA beams was investigated. It was found that the codes procedures gives conservative estimates for shear strength.

Keywords: construction and demolition (C&D) waste, coarse aggregate (CA), recycled coarse aggregates (RCA), opening

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8333 Combining Experiments and Surveys to Understand the Pinterest User Experience

Authors: Jolie M. Martin

Abstract:

Running experiments while logging detailed user actions has become the standard way of testing product features at Pinterest, as at many other Internet companies. While this technique offers plenty of statistical power to assess the effects of product changes on behavioral metrics, it does not often give us much insight into why users respond the way they do. By combining at-scale experiments with smaller surveys of users in each experimental condition, we have developed a unique approach for measuring the impact of our product and communication treatments on user sentiment, attitudes, and comprehension.

Keywords: experiments, methodology, surveys, user experience

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8332 Multimodal Ophthalmologic Evaluation Can Detect Retinal Injuries in Asymptomatic Patients With Primary Antiphospholipid Syndrome

Authors: Taurino S. R. Neto, Epitácio D. S. Neto, Flávio Signorelli, Gustavo G. M. Balbi, Alex H. Higashi, Mário Luiz R. Monteiro, Eloisa Bonfá, Danieli C. O. Andrade, Leandro C. Zacharias

Abstract:

Purpose: To perform a multimodal evaluation, including the use of Optical Coherence Angiotomography (OCTA), in patients with primary antiphospholipid syndrome (PAPS) without ocular complaints and to compare them with healthy individuals. Methods: A complete structural and functional ophthalmological evaluation using OCTA and microperimetry (MP) exam in patients with PAPS, followed at a tertiary rheumatology outpatient clinic, was performed. All ophthalmologic manifestations were recorded and then statistical analysis was performed for comparative purposes; p <0.05 was considered statistically significant. Results: 104 eyes of 52 subjects (26 patients with PAPS without ocular complaints and 26 healthy individuals) were included. Among PAPS patients, 21 were female (80.8%) and 21 (80.8%) were Caucasians. Thrombotic PAPS was the main clinical criteria manifestation (100%); 65.4% had venous and 34.6% had arterial thrombosis. Obstetrical criteria were present in 34.6% of all thrombotic PAPS patients. Lupus anticoagulant was present in all patients. 19.2% of PAPS patients presented ophthalmologic findings against none of the healthy individuals. The most common retinal change was paracentral acute middle maculopathy (PAMM) (3 patients, 5 eyes), followed by drusen-like deposits (1 patient, 2 eyes) and pachychoroid pigment epitheliopathy (1 patient, 1 eye). Systemic hypertension and hyperlipidaemia were present in 100% of the PAPS patients with PAMM, while only six patients (26.1%) with PAPS without PAMM presented these two risk factors together. In the quantitative OCTA evaluation, we found significant differences between PAPS patients and controls in both the superficial vascular complex (SVC) and deep vascular complex (DVC) in the high-speed protocol, as well as in the SVC in the high-resolution protocol. In the analysis of the foveal avascular zone (FAZ) parameters, the PAPS group had a larger area of FAZ in the DVC using the high-speed method compared to the control group (p=0.047). In the quantitative analysis of the MP, the PAPS group had lower central (p=0.041) and global (p<0.001) retinal sensitivity compared to the control group, as well as in the sector analysis, with the exception of the inferior sector. In the quantitative evaluation of fixation stability, there was a trend towards worse stability in the PAPS subgroup with PAMM in both studied methods. Conclusions: PAMM was observed in 11.5% of PAPS patients with no previous ocular complaints. Systemic hypertension concomitant with hyperlipidemia was the most commonly associated risk factor for PAMM in patients with PAPS. PAPS patients present lower vascular density and retinal sensitivity compared to the control group, even in patients without PAMM.

Keywords: antiphospholipid syndrome, optical coherence angio tomography, optical coherence tomography, retina

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8331 Histopathological Features of Basal Cell Carcinoma: A Ten Year Retrospective Statistical Study in Egypt

Authors: Hala M. El-hanbuli, Mohammed F. Darweesh

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The incidence rates of any tumor vary hugely with geographical location. Basal Cell Carcinoma (BCC) is one of the most common skin cancer that has many histopathologic subtypes. Objective: The aim was to study the histopathological features of BCC cases that were received in the Pathology Department, Kasr El-Aini hospital, Cairo University, Egypt during the period from Jan 2004 to Dec 2013 and to evaluate the clinical characters through the patient data available in the request sheets. Methods: Slides and data of BCC cases were collected from the archives of the pathology department, Kasr El-Aini hospital. Revision of all available slides and histological classification of BCC according to WHO (2006) was done. Results: A total number of 310 cases of BCC representing about 65% from the total number of malignant skin tumors examined during the 10-years duration in the department. The age ranged from 8 to 84 years, the mean age was (55.7 ± 15.5). Most of the patients (85%) were above the age of 40 years. There was a slight male predominance (55%). Ulcerated BCC was the most common gross picture (60%), followed by nodular lesion (30%) and finally the ulcerated nodule (10%). Most of the lesions situated in the high-risk sites (77%) where the nose was the most common site (35%) followed by the periocular area (22%), then periauricular (15%) and finally perioral (5%). No lesion was reported outside the head. The tumor size was less than 2 centimeters in 65% of cases, and from 2-5 centimeters in the lesions' greatest dimension in the rest of cases. Histopathological reclassification revealed that the nodular BCC was the most common (68%) followed by the pigmented nodular (18.75%). The histologic high-risk groups represented (7.5%) about half of them (3.75%) being basosquamous carcinoma. The total incidence for multiple BCC and 2nd primary was 12%. Recurrent BCC represented 8%. All of the recurrent lesions of BCC belonged to the histologic high-risk group. Conclusion: Basal Cell Carcinoma is the most common skin cancer in the 10-year survey. Histopathological diagnosis and classification of BCC cases are essential for the determination of the tumor type and its biological behavior.

Keywords: basal cell carcinoma, high risk, histopathological features, statistical analysis

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8330 Assessment of Obesity Parameters in Terms of Metabolic Age above and below Chronological Age in Adults

Authors: Orkide Donma, Mustafa M. Donma

Abstract:

Chronologic age (CA) of individuals is closely related to obesity and generally affects the magnitude of obesity parameters. On the other hand, close association between basal metabolic rate (BMR) and metabolic age (MA) is also a matter of concern. It is suggested that MA higher than CA is the indicator of the need to improve the metabolic rate. In this study, the aim was to assess some commonly used obesity parameters, such as obesity degree, visceral adiposity, BMR, BMR-to-weight ratio, in several groups with varying differences between MA and CA values. The study comprises adults, whose ages vary between 18 and 79 years. Four groups were constituted. Group 1, 2, 3 and 4 were composed of 55, 33, 76 and 47 adults, respectively. The individuals exhibiting -1, 0 and +1 for their MA-CA values were involved in Group 1, which was considered as the control group. Those, whose MA-CA values varying between -5 and -10 participated in Group 2. Those, whose MAs above their real ages were divided into two groups [Group 3 (MA-CA; from +5 to + 10) and Group 4 (MA-CA; from +11 to + 12)]. Body mass index (BMI) values were calculated. TANITA body composition monitor using bioelectrical impedance analysis technology was used to obtain values for obesity degree, visceral adiposity, BMR and BMR-to-weight ratio. The compiled data were evaluated statistically using a statistical package program; SPSS. Mean ± SD values were determined. Correlation analyses were performed. The statistical significance degree was accepted as p < 0.05. The increase in BMR was positively correlated with obesity degree. MAs and CAs of the groups were 39.9 ± 16.8 vs 39.9 ± 16.7 years for Group 1, 45.0 ± 15.3 vs 51.4 ± 15.7 years for Group 2, 47.2 ± 12.7 vs 40.0 ± 12.7 years for Group 3, and 53.6 ± 14.8 vs 42 ± 14.8 years for Group 4. BMI values of the groups were 24.3 ± 3.6 kg/m2, 23.2 ± 1.7 kg/m2, 30.3 ± 3.8 kg/m2, and 40.1 ± 5.1 kg/m2 for Group 1, 2, 3 and 4, respectively. Values obtained for BMR were 1599 ± 328 kcal in Group 1, 1463 ± 198 kcal in Group 2, 1652 ± 350 kcal in Group 3, and 1890 ± 360 kcal in Group 4. A correlation was observed between BMR and MA-CA values in Group 1. No correlation was detected in other groups. On the other hand, statistically significant correlations between MA-CA values and obesity degree, BMI as well as BMR/weight were found in Group 3 and in Group 4. It was concluded that upon consideration of these findings in terms of MA-CA values, BMR-to-weight ratio was found to be much more useful indicator of the severe increase in obesity development than BMR. Also, the lack of associations between MA and BMR as well as BMR-to-weight ratio emphasize the importance of consideration of MA-CA values rather than MA.

Keywords: basal metabolic rate, basal metabolic rate-to-weight-ratio, chronologic age, metabolic age, obesity degree

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8329 Economics of Oil and Its Stability in the Gulf Region

Authors: Al Mutawa A. Amir, Liaqat Ali, Faisal Ali

Abstract:

After the World War II, the world economy was disrupted and changed due to oil and its prices. The research in this paper presents the basic statistical features and economic characteristics of the Gulf economy. The main features of the Gulf economies and its heavy dependence on oil exports, its dualism between modern and traditional sectors and its rapidly increasing affluences are particularly emphasized.  In this context, the research in this paper discussed the problems of growth versus development and has attempted to draw the implications for the future economic development of this area.

Keywords: oil prices, GCC, economic growth, gulf oil

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8328 Consumer’s Behavioral Responses to Corporate Social Responsibility Marketing: Mediating Impact of Customer Trust, Emotions, Brand Image, and Brand Attitude

Authors: Yasir Ali Soomro

Abstract:

Companies that demonstrate corporate social responsibilities (CSR) are more likely to withstand any downturn or crises because of the trust built with stakeholders. Many firms are utilizing CSR marketing to improve the interactions with their various stakeholders, mainly the consumers. Most previous research on CSR has focused on the impact of CSR on customer responses and behaviors toward a company. As online food ordering and grocery shopping remains inevitable. This study will investigate structural relationships among consumer positive emotions (CPE) and negative emotions (CNE), Corporate Reputation (CR), Customer Trust (CT), Brand Image (BI), and Brand attitude (BA) on behavioral outcomes such as Online purchase intention (OPI) and Word of mouth (WOM) in retail grocery and food restaurants setting. Hierarchy of Effects Model will be used as theoretical, conceptual framework. The model describes three stages of consumer behavior: (i) cognitive, (ii) affective, and (iii) conative. The study will apply a quantitative method to test the hypotheses; a self-developed questionnaire with non-probability sampling will be utilized to collect data from 500 consumers belonging to generation X, Y, and Z residing in KSA. The study will contribute by providing empirical evidence to support the link between CSR and customer affective and conative experiences in Saudi Arabia. The theoretical contribution of this study will be empirically tested comprehensive model where CPE, CNE, CR, CT, BI, and BA act as mediating variables between the perceived CSR & Online purchase intention (OPI) and Word of mouth (WOM). Further, the study will add more to how the emotional/ psychological process mediates in the CSR literature, especially in the Middle Eastern context. The proposed study will also explain the effect of perceived CSR marketing initiatives directly and indirectly on customer behavioral responses.

Keywords: corporate social responsibility, corporate reputation, consumer emotions, loyalty, online purchase intention, word-of-mouth, structural equation modeling

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8327 Face Sketch Recognition in Forensic Application Using Scale Invariant Feature Transform and Multiscale Local Binary Patterns Fusion

Authors: Gargi Phadke, Mugdha Joshi, Shamal Salunkhe

Abstract:

Facial sketches are used as a crucial clue by criminal investigators for identification of suspects when the description of eyewitness or victims are only available as evidence. A forensic artist develops a sketch as per the verbal description is given by an eyewitness that shows the facial look of the culprit. In this paper, the fusion of Scale Invariant Feature Transform (SIFT) and multiscale local binary patterns (MLBP) are proposed as a feature to recognize a forensic face sketch images from a gallery of mugshot photos. This work focuses on comparative analysis of proposed scheme with existing algorithms in different challenges like illumination change and rotation condition. Experimental results show that proposed scheme can lead to better performance for the defined problem.

Keywords: SIFT feature, MLBP, PCA, face sketch

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8326 Factors Contributing to Farmers’ Attitude Towards Climate Adaptation Farming Practices: A Farm Level Study in Bangladesh

Authors: Md Rezaul Karim, Farha Taznin

Abstract:

The purpose of this study was to assess and describe the individual and household characteristics of farmers, to measure the attitude of farmers towards climate adaptation farming practices and to explore the individual and household factors contributing in predicting their attitude towards climate adaptation farming practices. Data were collected through personal interviews using a pre-tested interview schedule. The data collection was done at Biral Upazila under Dinajpur district in Bangladesh from 1st November to 15 December 2018. Besides descriptive statistical parameters, Pearson’s Product Moment Correlation Coefficient (r), multiple regression and step-wise multiple regression analysis were used for the statistical analysis. Findings indicated that the highest proportion (77.6 percent) of the farmers had moderately favorable attitudes, followed by only 11.2 percent with highly favorable attitudes and 11.2 percent with slightly favorable attitudes towards climate adaptation farming practices. According to the computed correlation coefficients (r), among the 10 selected factors, five of them, such as education of household head, farm size, annual household income, organizational participation, and information access by extension services, had a significant relationship with the attitude of farmers towards climate-smart practices. The step-wise multiple regression results showed that two characteristics as education of household head and information access by extension services, contributed 26.2% and 5.1%, respectively, in predicting farmers' attitudes towards climate adaptation farming practices. In addition, more than two-thirds of farmers cited their opinion to the problems in response to ‘price of vermi species is high and it is not easily available’ as 1st ranked problem, followed by ‘lack of information for innovative climate-smart technologies’. This study suggests that policy implications are necessary to promote extension education and information services and overcome the obstacles to climate adaptation farming practices. It further recommends that research study should be conducted in diverse contexts of nationally or globally.

Keywords: factors, attitude, climate adaptation, farming practices, Bangladesh

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8325 Spray-Dried, Biodegradable, Drug-Loaded Microspheres for Use in the Treatment of Lung Diseases

Authors: Mazen AlGharsan

Abstract:

Objective: The Carbopol Microsphere of Linezolid, a drug used to treat lung disease (pulmonary disease), was prepared using Buchi B-90 nano spray-drier. Methods: Production yield, drug content, external morphology, particle size, and in vitro release pattern were performed. Results: The work was 79.35%, and the drug content was 66.84%. The surface of the particles was shriveled in shape, with particle size distribution with a mean diameter of 9.6 µm; the drug was released in a biphasic manner with an initial release of 25.2 ± 5.7% at 60 minutes. It later prolonged the release by 95.5 ± 2.5% up to 12 hours. Differential scanning calorimetry (DSC) revealed no change in the melting point of the formulation. Fourier-transform infrared (FT-IR) studies showed no polymer-drug interaction in the prepared nanoparticles.

Keywords: nanotechnology, drug delivery, Linezolid, lung disease

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8324 Machine Learning Techniques in Seismic Risk Assessment of Structures

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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8323 The Late School of Alexandria and Its Influence on Islamic Philosophy

Authors: Hussein El-Zohary

Abstract:

This research aims at studying the late Alexandrian school of philosophy in the 6th century AD, the adaptation of its methodologies by the Islamic world, and its impact on Muslim philosophical thought. The Alexandrian school has been underestimated by many scholars who regard its production at the end of the classical age as mere interpretations of previous writings and delimit its achievement to the preservation of ancient philosophical heritage. The research reviews the leading figures of the Alexandrian school and its production of philosophical commentaries studying ancient Greek philosophy in its entirety. It also traces the transmission of its heritage to the Islamic world through direct translations into Syriac first and then into Arabic. The research highlights the impact of the Alexandrian commentaries on Muslim recognition of Plato and Aristotle as well as its philosophical teaching methodology starting with the study of Aristotle’s Categories as introductory to understand Plato’s philosophy.

Keywords: Alexandrian school of philosophy, categories, commentaries, Syriac

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8322 Numerical Modelling of Shear Zone and Its Implications on Slope Instability at Letšeng Diamond Open Pit Mine, Lesotho

Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

Abstract:

Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

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8321 Displacement Based Design of a Dual Structural System

Authors: Romel Cordova Shedan

Abstract:

The traditional seismic design is the methodology of Forced Based Design (FBD). The Displacement Based Design (DBD) is a seismic design that considers structural damage to achieve a failure mechanism of the structure before the collapse. It is easier to quantify damage of a structure with displacements rather than forces. Therefore, a structure to achieve an inelastic displacement design with good ductility, it is necessary to be damaged. The first part of this investigation is about differences between the methodologies of DBD and FBD with some DBD advantages. In the second part, there is a study case about a dual building 5-story, which is regular in plan and elevation. The building is located in a seismic zone, which acceleration in firm soil is 45% of the acceleration of gravity. Then it is applied both methodologies into the study case to compare its displacements, shear forces and overturning moments. In the third part, the Dynamic Time History Analysis (DTHA) is done, to compare displacements with DBD and FBD methodologies. Three accelerograms were used and the magnitude of the acceleration scaled to be spectrum compatible with design spectrum. Then, using ASCE 41-13 guidelines, the hinge plastics were assigned to structure. Finally, both methodologies results about study case are compared. It is important to take into account that the seismic performance level of the building for DBD is greater than FBD method. This is due to drifts of DBD are in the order of 2.0% and 2.5% comparing with FBD drifts of 0.7%. Therefore, displacements of DBD is greater than the FBD method. Shear forces of DBD result greater than FBD methodology. These strengths of DBD method ensures that structure achieves design inelastic displacements, because those strengths were obtained due to a displacement spectrum reduction factor which depends on damping and ductility of the dual system. Also, the displacements for the study case for DBD results to be greater than FBD and DTHA. In that way, it proves that the seismic performance level of the building for DBD is greater than FBD method. Due to drifts of DBD which are in the order of 2.0% and 2.5% compared with little FBD drifts of 0.7%.

Keywords: displacement-based design, displacement spectrum reduction factor, dynamic time history analysis, forced based design

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8320 Deterioration Prediction of Pavement Load Bearing Capacity from FWD Data

Authors: Kotaro Sasai, Daijiro Mizutani, Kiyoyuki Kaito

Abstract:

Expressways in Japan have been built in an accelerating manner since the 1960s with the aid of rapid economic growth. About 40 percent in length of expressways in Japan is now 30 years and older and has become superannuated. Time-related deterioration has therefore reached to a degree that administrators, from a standpoint of operation and maintenance, are forced to take prompt measures on a large scale aiming at repairing inner damage deep in pavements. These measures have already been performed for bridge management in Japan and are also expected to be embodied for pavement management. Thus, planning methods for the measures are increasingly demanded. Deterioration of layers around road surface such as surface course and binder course is brought about at the early stages of whole pavement deterioration process, around 10 to 30 years after construction. These layers have been repaired primarily because inner damage usually becomes significant after outer damage, and because surveys for measuring inner damage such as Falling Weight Deflectometer (FWD) survey and open-cut survey are costly and time-consuming process, which has made it difficult for administrators to focus on inner damage as much as they have been supposed to. As expressways today have serious time-related deterioration within them deriving from the long time span since they started to be used, it is obvious the idea of repairing layers deep in pavements such as base course and subgrade must be taken into consideration when planning maintenance on a large scale. This sort of maintenance requires precisely predicting degrees of deterioration as well as grasping the present situations of pavements. Methods for predicting deterioration are determined to be either mechanical or statistical. While few mechanical models have been presented, as far as the authors know of, previous studies have presented statistical methods for predicting deterioration in pavements. One describes deterioration process by estimating Markov deterioration hazard model, while another study illustrates it by estimating Proportional deterioration hazard model. Both of the studies analyze deflection data obtained from FWD surveys and present statistical methods for predicting deterioration process of layers around road surface. However, layers of base course and subgrade remain unanalyzed. In this study, data collected from FWD surveys are analyzed to predict deterioration process of layers deep in pavements in addition to surface layers by a means of estimating a deterioration hazard model using continuous indexes. This model can prevent the loss of information of data when setting rating categories in Markov deterioration hazard model when evaluating degrees of deterioration in roadbeds and subgrades. As a result of portraying continuous indexes, the model can predict deterioration in each layer of pavements and evaluate it quantitatively. Additionally, as the model can also depict probability distribution of the indexes at an arbitrary point and establish a risk control level arbitrarily, it is expected that this study will provide knowledge like life cycle cost and informative content during decision making process referring to where to do maintenance on as well as when.

Keywords: deterioration hazard model, falling weight deflectometer, inner damage, load bearing capacity, pavement

Procedia PDF Downloads 393