Search results for: identification theory

Authors: Kate Whitman, Zahra Murad, Joe Cox

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Corporate social responsibility projects are suggested to motivate consumers to reciprocate good corporate deeds with their custom. When the projects benefit the ingroup vs the outgroup, such as locals rather than foreigners, the effect on reciprocity is suggested to be more powerful. This may be explained by group heuristics, a theory which indicates that favours to the ingroup (but not outgroup) are expected to be reciprocated, resulting in ingroup favouritism. The heuristic is theorised to explain prosocial behaviours towards the ingroup. The aim of this study is to test whether group heuristics similarly explain a reduction in antisocial behaviours towards the ingroup, measured by illegal consumption which harms a group that consumers identify with. In order to test corporate social responsibility messages, a population of interested consumers is required, so sport fans are recruited. A pre-registered experiment (N = 600) tests the influence of a focused “team” benefiting message vs a broader “sport” benefiting message on change in illegal intentions. The influence of group (team) identity and trait reciprocity on message efficacy are tested as measures of group heuristics. Results suggest that the “team” treatment significantly reduces illegal consumption intentions. The “sport” treatment interacted with the team identification measure, increasing illegal consumption intentions for low team identification individuals. The results suggest that corporate social responsibility may be effective in reducing illegal consumption, if the messages are delivered directly from brands to consumers with brand identification. Messages delivered on the behalf of an industry may have an undesirable effect.

Keywords: live sports, piracy, counterfeiting, corporate social responsibility, group heuristics, ingroup bias, team identification

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Authors: Jae Won Shin, Chang Ho Hyun

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A disintegration of deuterons by photons (dγ → np) reaction model for GEANT4 is developed in this work. An effective field theory with dibaryon fields Introducing a dibaryon field, we can take into account the effective range contribution to the propagator up to infinite order, and it consequently makes the convergence of the theory better than the pionless effective field theory without dibaryon fields. We develop a hadronic model for GEANT4 which is specialized for the disintegration of the deuteron by photons, dγ → np. For the description of two-nucleon interactions, we employ an effective field theory so called pionless theory with dibaryon fields (dEFT). In spite of its simplicity, the theory has proven very effective and useful in the applications to various two-nucleon systems and processes at low energies. We apply the new model of GEANT4 (G4dEFT) to the calculation of total and differential cross sections in dγ → np, and obtain good agreements to experimental data for a wide range of incoming photon energies.

Keywords: dγ → np, dibaryon fields, effective field theory, GEANT4

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Authors: Paulus Maulana

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Forensic identification is to help investigators determine a person's identity. Personal identification is often a problem in civil and criminal cases. Orthodontists like all other dental professionals can play a major role by maintaining lateral cephalogram and thus providing important or vital information or can clues to the legal authorities in order to help them in their search. Radiographic lateral cephalometry is a measurement method which focused on the anatomical points of human lateral skull. Sex determination is one of the most important aspects of the personal identification in forensic. Lateral cephalogram is a valuable tool in identification of sex as reveal morphological details of the skull on single radiograph. This present study evaluates the role of lateral cephalogram in identification of sex that parameters of lateral cephalogram are linear measurement and angle measurement. The linear measurements are N-S ( Anterior cranial length), Sna-Snp (Palatal plane length), Me-Go (menton-gonion), N-Sna ( Midfacial anterior height ), Sna-Me (Lower anterior face height), Co-Gn (total mandibular length). The angle measurements are SNA, SNB, ANB, Gonial, Interincical, and facial.

Keywords: lateral cephalometry, cephalogram, sex, forensic, parameter

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: Shi Jiaxin

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The Government Work Report is an essential form of document in the government of the People’s Republic of China. It covers all aspects of Chinese society and reflects China’s development strategy and trend. There are countless special terms in Government Work Report. Only by understanding Chinese-specific terms can we understand the content of the Government Work Report. Only by accurately translating the Chinese-specific terms can people come from all across the world know the Chinese government work report and understand China. Relevance theory is a popular theory of cognitive pragmatics. Relevance Translation Theory, which is closely related to Relevance Theory, has crucial and major guiding significance for the translation of Chinese-specific. Through studying Relevance Theory and researching the translation techniques, strategies and applications in the process of translating Chinese-specific terms from the perspective of Relevance Theory, we can understand the meaning and connotation of Chinese-specific terms, then solve various problems in the process of C-E translation, and strengthen our translation ability.

Keywords: government work report, Chinese-specific terms, relevance theory, translation

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Authors: Daan F. Oostveen

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‘Religion’ as a term is not native to the Global East. The concept ‘religion’ is both understood in its meaning of ‘religious traditions’, commonly referring to the ‘World Religions’ and in its adjective meaning ‘the religious’ or ‘religiosity’ as a separate domain of human culture, commonly contrasted to the secular. Though neither of these understandings are native to the historical worldviews of East Asia, their development in modern Western scholarship has had an enormous impact on the self-understanding of cultural diversity in the Global East as well. One example is the identification and therefore elevation to the status of World Religion of ‘Buddhism’ which connected formerly dispersed religious practices throughout the Global East and subsumed them under this powerful label. On the other hand, we see how popular religiosity, shamanism and hybrid cultural expressions have become excluded from genuine religion; this had an immense impact on the sense of legitimacy of these practices, which became sometimes labeled as superstition are rejected as magic. Our theoretical frameworks on religion in the Global East do not always consider the complex power dynamics between religious actors, both elites and lay expressions of religion in everyday life, governments and religious studies scholars. In order to get a clear image of how religiosity functions in the context of the Global East, we have to take into account these power dynamics. What is important in particular is the issue of religious identity or absence of religious identity. The self-understanding of religious actors in the Global East is often very different from what scholars of religion observe. Religious practice, from an etic perspective, is often unrelated to religious identification from an emic perspective. But we also witness the rise of Christian churches in the Global East, in which religious identity and belonging does play a pivotal role. Finally, religion in the Global East has since the beginning of the 20th Century been conceptualized as the ‘other’ or republicanism or Marxist-Maoist ideology. It is important not to deny the key role of colonial thinking in the process of religion formation in the Global East. In this paper, it is argued that religious realities constituted emerging as a result from our theory of religion, and that these religious realities in turn inform our theory. Therefore, the relationship between phenomenology of religion and theory of religion can never be disentangled. In fact, we have to acknowledge that our conceptualizations of religious diversity are always already influenced by our valuation of those cultural expressions that we have come to call ‘religious’.

Keywords: global east, religion, religious belonging, secularity

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

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Authors: Vilem Paril, Dominika Tothova

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This paper discusses the value theory in cultural heritage and the value theory in environmental economics. Two economic views of the value theory are compared within the field of cultural heritage maintenance and within the field of the environment. The main aims are to find common features in these two differently structured theories under the layer of differently defined terms as well as really differing features of these two approaches, to clear the confusion which stems from different terminology as in fact these terms capture the same aspects of reality and to show possible inspiration these two perspectives can offer one another. Another aim is to present these two value systems in one value framework. First, important moments of the value theory from the economic perspective are presented, leading to the marginal revolution of (not only) the Austrian School. Then the theory of value within cultural heritage and environmental economics are explored. Finally, individual approaches are compared and their potential mutual inspiration searched for.

Keywords: cultural heritage, environmental economics, existence value, value theory

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Sello Mokwena, Monyepao Thabang

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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: learning style, VARK, sensory preferences, identification model, didactic practices

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Authors: Davoud Maleki, Neda Zamani

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The present study aims at exploring the effective accountability model of Islamic Azad University using a qualitative approach of grounded theory. The data of this study were obtained from semi-structured interviews with 25 professors and scholars in Islamic Azad University of Tehran who were selected by theoretical sampling method. In the data analysis, the stepwise method and Strauss and Corbin analytical methods (1992) were used. After identification of the main component (balanced response to stakeholders’ needs) and using it to bring the categories together, expressions and ideas representing the relationships between the main and subcomponents, and finally, the revealed components were categorized into six dimensions of the paradigm model, with the relationships among them, including causal conditions (7 components), main component (balanced response to stakeholders’ needs), strategies (5 components), environmental conditions (5 components), intervention features (4 components), and consequences (3 components). Research findings show an exploratory model for describing the relationships between causal conditions, main components, accountability strategies, environmental conditions, university environmental features, and that consequences.

Keywords: accountability, effectiveness, Islamic Azad University, grounded theory

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Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

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Authors: Bin Liu

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Prokaryotic promoter, consisted of two short DNA sequences located at in -35 and -10 positions, is responsible for controlling the initiation and expression of gene expression. Different types of promoters have different functions, and their consensus sequences are similar. In addition, their consensus sequences may be different for the same type of promoter, which poses difficulties for promoter identification. Unfortunately, all existing computational methods treat promoter identification as a binary classification task and can only identify whether a query sequence belongs to a specific promoter type. It is desired to develop computational methods for effectively identifying promoters and their types. Here, a two-layer predictor is proposed to try to deal with the problem. The first layer is designed to predict whether a given sequence is a promoter and the second layer predicts the type of promoter that is judged as a promoter. Meanwhile, we also analyze the importance of feature and sequence conversation in two aspects: promoter identification and promoter type identification. To the best knowledge of ours, it is the first computational predictor to detect promoters and their types.

Keywords: promoter, promoter type, random forest, sequence information

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Authors: Ali Nouri

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Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research

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Authors: S. B. Rathna Kumar, Sandya K. Varudhini, Aparna Ravichandran

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Telugu is a south central Dravidian language spoken in Andhra Pradesh, a southern state of India. The available speech identification tests in Telugu have been developed to determine the communication problems of individuals having a flat frequency hearing loss. These conventional speech audiometric tests would provide redundant information when used on individuals with high-frequency sloping hearing loss because of better hearing sensitivity in the low- and mid-frequency regions. Hence, conventional speech identification tests do not indicate the true nature of the communication problem of individuals with high-frequency sloping hearing loss. It is highly possible that a person with a high-frequency sloping hearing loss may get maximum scores if conventional speech identification tests are used. Hence, there is a need to develop speech identification test materials that are specifically designed to assess the speech identification performance of individuals with high-frequency sloping hearing loss. The present study aimed to develop speech identification test for individuals with high-frequency sloping hearing loss in Telugu. Individuals with high-frequency sloping hearing loss have difficulty in perception of voiceless consonants whose spectral energy is above 1000 Hz. Hence, the word lists constructed with phonemes having mid- and high-frequency spectral energy will estimate speech identification performance better for such individuals. The phonemes /k/, /g/, /c/, /ṭ/ /t/, /p/, /s/, /ś/, /ṣ/ and /h/are preferred for the construction of words as these phonemes have spectral energy distributed in the frequencies above 1000 KHz predominantly. The present study developed two word lists in Telugu (each word list contained 25 words) for evaluating speech identification performance of individuals with high-frequency sloping hearing loss. The performance of individuals with high-frequency sloping hearing loss was evaluated using both conventional and high-frequency word lists under recorded voice condition. The results revealed that the developed word lists were found to be more sensitive in identifying the true nature of the communication problem of individuals with high-frequency sloping hearing loss.

Keywords: speech identification test, high-frequency sloping hearing loss, recorded voice condition, Telugu

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Authors: Divine Kwaku Ahadzie

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Project management (PM) as a concept has evolved from the early 20th Century into a recognized academic and professional discipline, and indications are that it has come to stay in the 21st Century as a world-wide paradigm shift for managing successful construction projects. However, notwithstanding the strong inroads that PM has made in legitimizing its academic and professional status in construction management practice, the underlining philosophies are still based on cases and conventional practices. An important theoretical issue yet to be addressed is the lack of a universal theory that offers philosophical legitimacy for the PM concept as a uniquely specialized management concept. Here, it is hypothesized that the law of entropy, the theory of uncertainties and the theory of risk management offer plausible explanations for addressing the lacuna of what constitute PM theory. The theoretical bases of these plausible underlying theories are argued and attempts made to establish the functional relationships that exist between these theories and the PM concept. The paper then draws on data related to the success and/or failure of a number of construction projects to validate the theory.

Keywords: concepts, construction, project management, universal theory

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Authors: J. Ritonja

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Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: R. Manjula, Kaustav Bagchi, Sushant Ramesh, Anush Baskaran

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In the past century, the emergence of information technology has had a significant positive impact on human life. While companies tend to be more involved in the completion of projects, the turn of the century has seen importance being given to investment in information security policies. These policies are essential to protect important data from adversaries, and thus following these policies has become one of the most important attributes revolving around information security models. In this research, we have focussed on the factors affecting information security policy compliance in two models : The theory of planned behaviour and the integration of the social bond theory and the involvement theory into a single model. Finally, we have given a proposal of where these theories would be successful.

Keywords: information technology, information security, involvement theory, policies, social bond theory

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Authors: Alina M. Udall, Judith de Groot, Simon de Jong, Avi Shankar

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There are many ways in which environmentally significant behavior can be explained. Dominant psychological theories, namely, the theory of planned behavior, the norm-activation theory, its extension, the value-belief-norm theory, and the theory of habit do not explain large parts of environmentally significant behaviors. A new and rapidly growing approach is to focus on how consumer’s identities predict environmentally significant behavior. Identity may be relevant because consumers have many identities that are assumed to guide their behavior. Therefore, we assume that many identities will guide environmentally significant behavior. Many identities can be relevant for environmentally significant behavior. In reviewing the literature, over 200 identities have been studied making it difficult to establish the key identities for explaining environmentally significant behavior. Therefore, this paper first aims to establish the key identities previously used for explaining environmentally significant behavior. Second, the aim is to test which key identities explain environmentally significant behavior. To address the aims, an online survey study (n = 578) is conducted. First, the exploratory factor analysis reveals 15 identity factors. The identity factors are namely, environmentally concerned identity, anti-environmental self-identity, environmental place identity, connectedness with nature identity, green space visitor identity, active ethical identity, carbon off-setter identity, thoughtful self-identity, close community identity, anti-carbon off-setter identity, environmental group member identity, national identity, identification with developed countries, cyclist identity, and thoughtful organisation identity. Furthermore, to help researchers understand and operationalize the identities, the article provides theoretical definitions for each of the identities, in line with identity theory, social identity theory, and place identity theory. Second, the hierarchical regression shows only 10 factors significantly uniquely explain the variance in environmentally significant behavior. In order of predictive power the identities are namely, environmentally concerned identity, anti-environmental self-identity, thoughtful self-identity, environmental group member identity, anti-carbon off-setter identity, carbon off-setter identity, connectedness with nature identity, national identity, and green space visitor identity. The identities explain over 60% of the variance in environmentally significant behavior, a large effect size. Based on this finding, the article reveals a new, theoretical framework showing the key identities explaining environmentally significant behavior, to help improve and align the field.

Keywords: environmentally significant behavior, factor analysis, place identity, social identity

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Authors: Hyun-Woo Cho

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The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

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Authors: Shabnam

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The purpose of this study was to see importance of successful intelligence in education which can enhance achievement. There are a number of researches which have tried to apply psychological theories of education and many researches emphasized the role of thinking and intelligence. While going through the various researches, it was found that many students could learn more effectively than they do, if they were taught in a way that better matched their patterns of abilities. Attempts to apply psychological theories to education can falter on the translation of the theory into educational practice. Often, this translation is not clear. Therefore, when a program does not succeed, it is not clear whether the lack of success was due to the inadequacy of the theory or the inadequacy of the implementation of the theory. A set of basic principles for translating a theory into practice can help clarify just what an educational implementation should (and should not) look like. Sternberg’s theory of successful intelligence; analytical, creative and practical intelligence provides a way to create such a match. The results suggest that theory of successful intelligence provides successful interventions in classrooms and provides a proven model for gifted education. This article presents principles for translating a triarchic theory of successful intelligence into educational practice.

Keywords: successful intelligence, analytical, creative and practical intelligence, achievement, success, resilience

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Authors: Morteza Rahiminejad

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There are over 1200 cities and municipalities all around Iran, including 30 mega cities, which municipal organizations, Interior ministries, and city councils supervise. Even so, there has been neither any research about the process of success nor performance assessment in municipalities. In this research an attempt is made to build a comprehensive theory (or model) to show the reasons or success process among the local governments. The present research is based on the contingency approach in which the relevant circumstances are important, and both environment and situations call for their own management methods. The methodology of research is grounded theory, which uses Atlas.ti software as a tool.

Keywords: success, municipality, Iran, theory building

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Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Mehran Nasiri, Ardeshir Poornemat

Abstract:

The aim of this study was to investigate the current and ideal situations of the process of talent identification in Iranian football from the point of view of Iranian instructors of the Asian Football Confederation (AFC). This research was a descriptive-analytical study; in data collection phase a questionnaire was used, whose face validity was confirmed by experts of Physical Education and Sports Science. The reliability of questionnaire was estimated through the use of Cronbach's alpha method (0.91). This study involved 122 participants of Iranian instructors of the AFC who were selected based on stratified random sampling method. Descriptive statistics were used to describe the variables and inferential statistics (Chi-square) were used to test the hypotheses of the study at significant level (p ≤ 0.05). The results of Chi-square test related to the point of view of Iranian instructors of the AFC showed that the grass-roots scientific method was the best way to identify football players (0.001), less than 10 years old were the best ages for talent identification (0.001), the Football Federation was revealed to be the most important organization in talent identification (0.002), clubs were shown to be the most important institution in developing talents (0.001), trained scouts of Football Federation were demonstrated to be the best and most appropriate group for talent identification (0.001), and being referred by the football academy coaches was shown to be the best way to attract talented football players in Iran (0.001). It was also found that there was a huge difference between the current and ideal situation of the process of talent identification in Iranian football from the point of view of Iranian instructors of the AFC. Hence, it is recommended that the policy makers of talent identification for Iranian football provide a comprehensive, clear and systematic model of talent identification and development processes for the clubs and football teams, so that the talent identification process helps to nurture football talents more efficiently.

Keywords: current situation, talent finding, ideal situation, instructors (AFC)

Procedia PDF Downloads 191

Authors: Abdulkader Helwan

Abstract:

Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

Procedia PDF Downloads 515