Search results for: identification theory

Authors: Maha Alaoui Ismaili, Bouchta Saidi, Mohamed Zahar, Abed Hamama

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112 lactic isolates were obtained from 15 samples of camel raw milk produced in Laayoune Boujdour Sakia-El Hamra region (South of Morocco). The main objective was the identification of species of lactic flora belonging to Lactococcus, Lactobacillus and Leuconostoc. Data obtained showed predominance of cocci among lactic isolates (86.6%) while lactic rods represented only 13.4%. With regard to genera identified, Enterococcus was the mostly found out (53.57%), followed by Lactococcus (28.57%), Lactobacillus (13.4%) and Leuconostoc (4.4 %). Identification of the lactic isolates according to their morphological, physiological, and biochemical characteristics led to differentiating 11 species with Lactococcus lactis ssp lactis biovar diacetylactis being the mostly encountered (24.1%) followed by Lactobacillus brevis (3.57%), Lactobacillus plantarum (3.57%), Lactobacillus delbrueckii subsp lactis (3.57%) and Lactococcus lactis subsp cremoris (2.67%).

Keywords: raw camel milk, south of morocco, lactic acid bacteria, identification

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Mogens Frank Mikkelsen

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Special Relativity Theory (SRT) includes only one characteristic of light, the speed is equal to all observers, and by excluding other relevant characteristics of light, the common interpretation of SRT should be regarded as merely an approximative theory. By rethinking the iconic double light cones, a revised version of SRT can be developed. The revised concept of light cones acknowledges an asymmetry of past and future light cones and introduced a concept of the extended past to explain the predictions as something other than the future. Combining this with the concept of photon-paired events, led to the inference that Special Relativity theory can support the existence of Now.

Keywords: relativity, light cone, Minkowski, time

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Authors: Badr Alsulami, Ahmed S. Elamary

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This paper summarizes and presents main results of an in-depth numerical analysis dealing with the shear buckling resistance of aluminum plate girders. The studies conducted have permitted the development of a simple design expression to determine the critical shear buckling stress in aluminum web panels. This expression takes into account the effects of reduction of strength in aluminum alloys due to the welding process. Ultimate shear resistance (USR) of plate girders can be obtained theoretically using Cardiff theory or Hӧglund’s theory. USR of aluminum alloy plate girders predicted theoretically using BS8118 appear inconsistent when compared with test data. Theoretical predictions based on Hӧglund’s theory, are more realistic. Cardiff theory proposed to predict the USR of steel plate girders only. Welded aluminum alloy plate girders studied experimentally by others; the USR resulted from tests are reviewed. Comparison between the test results with the values obtained from Hӧglund’s theory, BS8118 design method, and Cardiff theory performed theoretically. Finally, a new equation based on Cardiff tension-field theory proposed to predict theoretically the USR of aluminum plate girders.

Keywords: shear resistance, aluminum, Cardiff theory, Hӧglund's theory, plate girder

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: A. Ballard

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The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

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Authors: Ayman El Behiry, Rasha Nabil Zahran, Reda Tarabees, Eman Marzouk, Musaad Al-Dubaib

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Mastitis is one of the most economic disease affecting dairy cows worldwide. Its classic diagnosis using bacterial culture and biochemical findings is a difficult and prolonged method. In this research, using of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) permitted identification of different microorganisms with high accuracy and rapidity (only 24 hours for microbial growth and analysis). During the application of MALDI-TOF MS, one hundred twenty strains of Staphylococcus and Streptococcus species isolated from milk of cows affected by clinical and subclinical mastitis were identified, and the results were compared with those obtained by traditional methods as API and VITEK 2 Systems. 37 of totality 39 strains (~95%) of Staphylococcus aureus (S. aureus) were exactly detected by MALDI TOF MS and then confirmed by a nuc-based PCR technique, whereas accurate identification was observed in 100% (50 isolates) of the coagulase negative staphylococci (CNS) and Streptococcus agalactiae (31 isolates). In brief, our results demonstrated that MALDI-TOF MS is a fast and truthful technique which has the capability to replace conventional identification of several bacterial strains usually isolated in clinical laboratories of microbiology.

Keywords: identification, mastitis pathogens, mass spectral, phenotypical

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Feride Eskin Bacaksiz, Aytolan Yildirim

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Practices voluntarily performed by organizations for their employees well-being, create an emotional imperative for employees in accordance with reciprocity norm. Changes in desired course occur in organizational outputs and attitudes towards organization among employees perceiving their organizations as virtuous and supportive. The aim of this study was to examine the effect of organizational virtuousness on performance and organizational identification levels of employees and mediating role of perceived organizational support in this relationship. The data of this descriptive and methodological study were collected from 336 nurses working in a public university hospital in 2015. Participant information form, Organizational Virtuousness, Perceived Organizational Support, Organizational Identification, and Employee Performance scales were used to collect the data. Descriptive, correlative, psychometric analyses and Structural Equation Modeling were performed for the data analysis. Most of the participants were female, under 30 years of age, graduated degrees and staff nurse. Mean scores obtained by the participants from scales were calculated as 3.43(SD=.99) for organizational virtuousness, 2.99 (SD=1.16) for perceived organizational support, 3.18 (SD=1.03) for organizational identification and 3.84 (SD=0.66) for employee performance. It was found that correlation between organizational virtuousness and employee performance regressed from r=0.64 to r=-0.01 and correlation between organizational virtuousness and organizational identification regressed from r=0.55 to r=-0.16 and became statistically non-significant (p < 0.05) via mediating role of perceived organizational support. According to the results, perceived organizational support assumes full mediation on the impact of organizational virtues of employee performance and organizational identification levels. Therefore, organizations, which intend to positively affect employees attitudes towards organization and their performance, should both extend organizational virtuous activities and affect perceptions of employees; whereas, employees should perceive that they are supported by their organization.

Keywords: employee performance, organizational identification, organizational virtuousness, perceived organizational support

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Samuel Quashie

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The importance of theory for PhD construction management research cannot be underestimated, as it requires a sound theoretical basis. Theory efficiency reduces errors in the research problem, solving it by building upon current theory. Provides a structure for examination, enables the efficient development of the construction management field and to it practical real world problems. The aim is to develop the theoretical framework for the application of descriptive theory within the PhD research design To apply the proposed theoretical framework using the case of the topic of ‘integrated management system,’ classifying the phenomena into categories, explore the association between the category–defining attributes and the outcome observed. Forming categorization based upon attributes of phenomena (framework and typologies), and statement of association (models). Predicting (deductive process) and confirming (inductive process). The descriptive theory is important and provides a structure for examination, enables the efficient development of construction management field and to it practical real world problems. In conclusion, the work done in management presents fertile ground for research and theory development.

Keywords: descriptive theory, PhD research design, theoretical framework, construction management

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Authors: Y. S. Oh, P. Abhishesh, B. S. Ryuh

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This paper presents the method of trajectory planning by the robot end-effector which accounts for more accurate and smooth differential geometry of the ruled surface generated by tool line fixed with end-effector based on the methods of curvature theory of ruled surface and the dual curvature theory, and focuses on the underlying relation to unite them for enhancing the efficiency for trajectory planning. Robot motion can be represented as motion properties of the ruled surface generated by trajectory of the Tool Center Point (TCP). The linear and angular properties of the six degree-of-freedom motion of end-effector are computed using the explicit formulas and functions from curvature theory and dual curvature theory. This paper explains the complete dualization of ruled surface and shows that the linear and angular motion applied using the method of dual curvature theory is more accurate and less complex.

Keywords: dual curvature theory, robot end effector, ruled surface, TCP (Tool Center Point)

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Authors: Danielle L. Iamarino

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This paper explores the embattled territory of academic creative writing—and most focally, the use of critical theory in the teaching and structuring of creative practice. It places creative writing in contemporary social, cultural, and otherwise anthropological contexts, and evaluates conventional creative writing pedagogies based on how well they serve the updated needs of increasingly diverse student congregations. With continued emphasis on student-centered learning, this paper compares theoretical to practical applications of discipline-specific knowledge, examining and critiquing theory in terms of its relevance, accessibility, and whether or not it is both actionable and beneficial in the creative writing classroom.

Keywords: creative writing, literary theory, content, pedagogy, workshop, teaching

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Authors: Farideh Alizadeh, Mohd Nasir Hashi

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Present research investigates eclecticism in Iranian theatre on the basis of eclectic theory. Eclectic theatre is a new theory in postmodernism. The theory appeared during 60th – 70th century in some theatres such as “Conference of the Birds”. Special theatrical forms have been developed in many geographical- cultural areas of the world and are indigenous to that area. These forms, as compared with original forms, are considered to be traditional while being comprehensive, the form is considered to be national. Kaboudan and Sfandiar theatre has been influenced by elements of traditional form of Iran.

Keywords: eclectic theatre, theatrical forms, tradition, play

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Authors: E. Krasnova, E. Bulgakova, V. Shchemelinin

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The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field.

Keywords: speaker identification, acoustic-spectrographic method, non-native speech, performance evaluation

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Mehmet Hakan Karaata

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In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: Akbar

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Pros and cons of the capital punishment in Indonesia have been out of the date. The discourse of capital punishment has no relevance to the theory of punishment and theories of cultural relativism. In fact, the provisions of exceptions to the right to life by administering the death penalty against the perpetrators of serious crimes in Indonesia is a narrow perspective that does not pay attention to the development of the punishment of the crime. This thing is aggravated by an error to understand the natural right and legal right where the prohibition of those rights is result from a failure to distinguish the characteristic of the rights and to remember the raison d’être of law. To parse the irrational above, this paper will try to analyze normatively the error referring to the complementary theory between the sources of international law and the sources of municipal law of Indonesia. Both sources of the law above should be understood in the mutually reinforcing relationship enforceability because of false perceptions against those will create the disintegration between international law and municipal law of Indonesia. This disintegration is explicit not only contrary to the integrative theory of international law but also integrative theory of municipal law of Indonesia.

Keywords: capital punishment, municipal law, right to life, international law, the raison d’être of law, complementary theory, integrative theory

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Authors: Gholamreza Koochaki

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This paper presents the buckling analysis of functionally graded beams with various boundary conditions. The first order shear deformation beam theory (Timoshenko beam theory) and the classical theory (Euler-Bernoulli beam theory) of Reddy have been applied to the functionally graded beams buckling analysis The material property gradient is assumed to be in thickness direction. The equilibrium and stability equations are derived using the total potential energy equations, classical theory and first order shear deformation theory assumption. The temperature difference and applied voltage are assumed to be constant. The critical buckling temperature of FG beams are upper than the isotropic ones. Also, the critical temperature is different for various boundary conditions.

Keywords: buckling, functionally graded beams, Hamilton's principle, Euler-Bernoulli beam

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Authors: Rebecca Angeles

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This qualitative case study seeks to understand and explain the deployment of radio frequency identification (RFID) systems in two countries (i.e. in Taiwan for the adoption of electric scooters and in Finland for supporting glass bottle recycling) using the 'Technology-Organization-Environment' theoretical framework. This study also seeks to highlight the relevance and importance of pursuing environmental sustainability in firms and in society in general due to the social urgency of the issues involved.

Keywords: environmental sustainability, radio frequency identification, technology-organization-environment framework, RFID system implementation, case study, content analysis

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Authors: Hind Hassan Arruwaite

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Conceptual metaphor is a cognitive semantic tool that provides access to people's conceptual systems. The correlation in the human conceptual system surpasses limited time and specific cultures. The universal associations provide universal schemas that organize people's conceptualization of the world. The study aims to explore how the cultural associations used in conceptual metaphors create commonalities and harmony between people of the world. In the research methodology, the researcher implemented Critical Metaphor Analysis, Metaphor Candidate Identification and Metaphor Identification Procedure models to deliver qualitative and descriptive findings. The semantic tension was the key criterion in identifying metaphorically used words in the headlines. The research materials are the oil trade conceptual metaphors used in the headlines of Arab News and Saudi Gazette Newspapers. The data will be uploaded to the self-constructed corpus to examine electronic lists for identifying conceptual metaphors. The study investigates the types of conceptual metaphors used in the headlines of the newspapers, the cultural associations identified in the conceptual metaphors, and whether the identified cultural associations in conceptual metaphors create universal conceptual schemas. The study aligned with previous seminal works on conceptual metaphor theory in emphasizing the distinctive power of conceptual metaphors in exposing the cultural associations that unify people's perceptions. The correlation of people conceptualization provides universal schemas that involve elements of human sensorimotor experiences. The study contributes to exposing the shared cultural associations that ensure the commonality of all humankind's thinking mechanism.

Keywords: critical discourse analysis, critical metaphor analysis, conceptual metaphor theory, primary and specific metaphors, corpus-driven approach, universal associations, image schema, sensorimotor experience, oil trade

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Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

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The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Rania A. Aboalela, Javed I. Khan

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This research presents a learning assessment theory of Cognitive Skill in Concept Space (CS2) to measure the assessed knowledge in terms of cognitive skill levels of the concepts. The cognitive skill levels refer to levels such as if a student has acquired the state at the level of understanding, or applying, or analyzing, etc. The theory is comprised of three constructions: Graph paradigm of a semantic/ ontological scheme, the concept states of the theory and the assessment analytics which is the process to estimate the sets of concept state at a certain skill level. Concept state means if a student has already learned, or is ready to learn, or is not ready to learn a certain skill level. The experiment is conducted to prove the validation of the theory CS2.

Keywords: cognitive skill levels, concept states, concept space, knowledge assessment theory

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Ahmed S. Elamary

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Ultimate shear resistance (USR) of slender plate girders can be predicted theoretically using Cardiff theory or Hӧglund theory. This paper will be concerned with predicting the USR using Hӧglund theory and EC3. Two main factors can affect the USR, the panel width “b” and the web depth “d”, consequently, the panel aspect ratio (b/d) has to be identified by limits. In most of the previous study, there is no limit for panel aspect ratio indicated. In this paper theoretical analysis has been conducted to study the effect of (b/d) on the USR. The analysis based on ninety-six test results of steel plate girders subjected to shear executed and collected by others. New formula proposed to predict the percentage of the distance between the plastic hinges form in the flanges “c” to panel width “b”. Conservative limits of (c/b) have been suggested to get a consistent value of USR.

Keywords: ultimate shear resistance, plate girder, Hӧglund’s theory, EC3

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Authors: Michael Luc Andre, Célia Maintenant

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Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

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Authors: Leah Wright, Trevor Townsend

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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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