Search results for: decentralized distributed training

Authors: Namdeo Jadhav, Nitin Salunkhe

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Currently, sericin is being treated as waste of sericulture industry, especially at reeling process. Looking at prospective physicochemical properties, an attempt has been made to explore pharmaceutical applications of sericin waste in fabrication of medicated solid dispersions. Solid dispersions (SDs) of poorly soluble drugs (Lornoxicam, Meloxicam & Felodipine) were prepared by spray drying, solvent evaporation, ball milling and physical kneading in mass ratio of drug: sericin (1:0.5, 1:1, 1:1.5, 1:2, 1:2.5 and 1:3 w/w) and were investigated by solubility, ATR-FTIR, XRD and DSC, micromeritics and tablettability, surface morphology and in-vitro dissolution. It has been observed that sericin improves solubility of drugs by 8 to 10 times compared to pure drugs. The presence of hydrogen bonding between drugs and sericin was confirmed from the ATR-FTIR spectra. Amongst these methods, spray dried (1:2 w/w) SDs showed fully amorphous state representing molecularly distributed drug as confirmed from XRD and DSC study. Spray dried meloxicam SDs showed better compressibility and compactibility. The microphotograph of spray dried batches of lornoxicam (SDLX) and meloxicam SDs (SDMX) showed bowl shaped, and bowl plus spherical particles respectively, while spray dried felodipine SDs (SDFL) showed spherical shape. The SDLX, SDMX and SDFL (1:2 w/w) displayed better dissolution performance than other methods. Conclusively, hydrophilic matrix of sericin can be used to deliver poor water soluble drugs and its aerodynamic shape may show a great potential for various drug deliveries. If established as pharmaceutical excipient, sericin holds a potential to revolutionise economics of pharmaceutical industry, and sericulture farming, especially of Asian countries.

Keywords: biosericin, poorly soluble drugs, solid dispersion, solubility and dissolution improvement

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Authors: Oluwatosin Oyewale

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This research work seeks to take technology used for business systems as a product that requires marketing activities. Technology is invented and innovated upon in developed countries and are introduced into Africa through marketing activities. Businesses in Africa now adopt this technology for global competitiveness and hitherto unemployed but educationally advantaged people are trained in handling and utilising the technology. The aim of this study is to examine how marketing activities make this technology help in solving the unemployment problem in Africa. The areas of study are both the premier local government and the local government of the industrial haven in Ogun State, Nigeria. Area or cluster sampling technique was employed and Questionnaires were administered to two hundred respondents in the areas of study. Findings revealed that marketing has contributed to the promotion of technology; thereby making businesses globally competitive. In addition, technology has helped in reducing unemployment in developing countries. Recommendations are that training programmes that will address existing knowledge gap in technology utilisation needs to be conducted for the labour force in Africa. Moreover, adequate power supply that will aid effective utilisation of these technologies needs to be put in place by the government in these various African countries.

Keywords: marketing, unemployment, problem, panacea

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Authors: Qi Wang

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Chinese has become a powerful worldwide language and millions of learners are studying it all over the words. Chinese is a tone language with unique meaningful characters, which makes foreign learners master it with more difficulties. On the other hand, as each foreign language, the learners of Chinese first will learn the basic Chinese Sound Structure (the initials and finals, tones, Neutral Tone and Tone Sandhi). It’s quite common that in the following studies, teachers made a lot of efforts on drilling and error correcting, in order to help students to pronounce correctly, but ignored the training of suprasegmental features (e.g. stress, intonation). This paper analysed the oral data based on our graduation students (two-year program) from 2006-2013, presents the intonation pattern of our graduates to speak Chinese as second language -high and plain with heavy accents, without lexical stress, appropriate stop endings and intonation, which led to the misunderstanding in different real contexts of communications and the international official Chinese test, e.g. HSK (Chinese Proficiency Test), HSKK (HSK Speaking Test). This paper also demonstrated how the Chinese to use the suprasegmental features strategically in different functions and moods (declarative, interrogative, imperative, exclamatory and rhetorical intonations) in order to train the learners to achieve better Communicative Performance.

Keywords: second language learning, suprasegmental, communication, HSK (Chinese Proficiency Test)

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Authors: Agastya Pratap Singh

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Generative Adversarial Networks (GANs) have emerged as powerful tools in the fields of image recognition and anomaly detection due to their ability to model complex data distributions and generate realistic images. This systematic review explores recent advancements and applications of GANs in both image recognition and anomaly detection tasks. We discuss various GAN architectures, such as DCGAN, CycleGAN, and StyleGAN, which have been tailored to improve accuracy, robustness, and efficiency in visual data analysis. In image recognition, GANs have been used to enhance data augmentation, improve classification models, and generate high-quality synthetic images. In anomaly detection, GANs have proven effective in identifying rare and subtle abnormalities across various domains, including medical imaging, cybersecurity, and industrial inspection. The review also highlights the challenges and limitations associated with GAN-based methods, such as instability during training and mode collapse, and suggests future research directions to overcome these issues. Through this review, we aim to provide researchers with a comprehensive understanding of the capabilities and potential of GANs in transforming image recognition and anomaly detection practices.

Keywords: generative adversarial networks, image recognition, anomaly detection, DCGAN, CycleGAN, StyleGAN, data augmentation

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Authors: Abdullah Almulhim

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The International Accounting Standards Board (IASB) was established in 2001 to develop International Financial Reporting Standards (IFRS) that bring transparency, accountability, and efficiency to financial markets around the world. In addition, the IFRS provide a unified accounting language, which is especially important in the era of globalization. However, the establishment of a single set of high-quality international accounting standards is a matter of growing importance, as participants in the increasingly integrated world capital market demand comparability and transparency of financial reporting worldwide. Saudi Arabia became the 149th member of the World Trade Organization (WTO) on 11 December 2005, which has increased the need to convert to IFRS. Currently, the Saudi Arabian Monetary Authority (SAMA) requires banks and insurance companies in Saudi Arabia to report under IFRS Standards. However, until the end of 2016, SOCPA standards were applied to all other companies, listed and unlisted. From 2017, listed Saudi companies would be required to report under IFRS Standards as adopted by SOCPA effective 2017. This paper is to investigate the expected benefits gained and highlight the challenges faced by adopting IFRS by the listed companies in the Saudi Stock Exchange. Questionnaires were used as the main method of data collection. They were distributed to listed companies in the Saudi Capital Market. Data obtained through the questionnaires have been imported into SPSS statistical software for analysis. The expected results of this study will show the benefits of adopting IFRS by Saudi Listed Companies. However, this study will investigate the challenges faced by adopting IFRS by the listed companies in the Saudi Arabian Stock Market. Findings will be discussed later upon completion of initial analysis.

Keywords: challenges, IAS, IFRS, opportunities, Saudi, SOCPA

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Authors: Monette S. De Castro, Veneranda A. Magpantay, Christine B. Adiova, Mark D. Arboleda

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One-hundred-layer chicken farmers were randomly selected and interviewed using structured questionnaires to assess the production system and management practices in layer chicken farms. The respondents belonged to the commercial scale operation. Results showed that the predominant rearing and housing systems were intensive/complete confinement and open-sided, while slatted was the common type of flooring used during the brood-grow period. Dekalb and Lohmann were the common chicken layer strains reared by farmers. The majority of commercial chicken layer farms preferred ready-to-lay (RTL) pullets as their replacement stocks. Selling was the easiest way for farmers to dispose of and utilize poultry manure, while veterinary waste and mortality were disposed of in pits. Biosecurity practices employed by the farmers conformed with the ASEAN Biosecurity Management Manual for Commercial Poultry Farming. Flies and odor were the major problems in most layer farms that are associated with their farm wastes. Therefore, the application of new technologies and husbandry practices through training and actual demonstrations could be implemented to further improve the layer chicken raising in the province.

Keywords: layer chicken farms, marketing, production system, waste management

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Authors: Jun Hee Lee, Young Kyu Kim, Seong Jae Hong, Chamroeun Chhorn, Seung Woo Lee

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Roller-compacted concrete pavement (RCCP), an environmental friendly pavement of which load carry capacity benefitted from both hydration and aggregate interlock from roller compacting, demonstrated a superb structural performance for a relatively small amount of water and cement content. Even though an excellent structural performance can be secured, it is required to investigate roller-compacted concrete (RCC) under environmental loading and its long-term durability under critical conditions. In order to secure long-term durability, an appropriate internal air-void structure is required for this concrete. In this study, a method for improving the long-term durability of RCCP is suggested by analyzing the internal air-void structure and corresponding durability of RCC. The method of improving the long-term durability involves measurements of air content, air voids, and air-spacing factors in RCC that experiences changes in terms of type of air-entraining agent and its usage amount. This test is conducted according to the testing criteria in ASTM C 457, 672, and KS F 2456. It was found that the freezing-thawing and scaling resistances of RCC without any chemical admixture was quite low. Interestingly, an improvement of freezing-thawing and scaling resistances was observed for RCC with appropriate the air entraining (AE) agent content; Relative dynamic elastic modulus was found to be more than 80% for those mixtures. In RCC with AE agent mixtures, large amount of air was distributed within a range of 2% to 3%, and an air void spacing factor ranging between 200 and 300 μm (close to 250 μm, recommended by PCA) was secured. The long-term durability of RCC has a direct relationship with air-void spacing factor, and thus it can only be secured by ensuring the air void spacing factor through the inclusion of the AE in the mixture.

Keywords: durability, RCCP, air spacing factor, surface scaling resistance test, freezing and thawing resistance test

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: Katarzyna Rzeszut, Ilona Szewczak

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The review of selected methods of strengthening of steel structures with carbon fiber reinforced polymer (CFRP) tapes and the analysis of influence of composite materials on the steel thin-walled elements are performed in this paper. The study is also focused to the problem of applying fast and effective strengthening methods of the steel structures made of thin-walled profiles. It is worth noting that the issue of strengthening the thin-walled structures is a very complex, due to inability to perform welded joints in this type of elements and the limited ability to applying mechanical fasteners. Moreover, structures made of thin-walled cross-section demonstrate a high sensitivity to imperfections and tendency to interactive buckling, which may substantially contribute to the reduction of critical load capacity. Due to the lack of commonly used and recognized modern methods of strengthening of thin-walled steel structures, authors performed the experimental studies of thin-walled sigma profiles strengthened with CFRP tapes. The paper presents the experimental stand and the preliminary results of laboratory test concerning the analysis of the effectiveness of the strengthening steel beams made of thin-walled sigma profiles with CFRP tapes. The study includes six beams made of the cold-rolled sigma profiles with height of 140 mm, wall thickness of 2.5 mm, and a length of 3 m, subjected to the uniformly distributed load. Four beams have been strengthened with carbon fiber tape Sika CarboDur S, while the other two were tested without strengthening to obtain reference results. Based on the obtained results, the evaluation of the accuracy of applied composite materials for strengthening of thin-walled structures was performed.

Keywords: CFRP tapes, sigma profiles, steel thin-walled structures, strengthening

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Authors: Rylyne Mande Nchu, Robertson Tengeh, Chux Iwu

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Blended learning is a global phenomenon and is essential to many institutes of learning as an additional method of teaching that complements more traditional methods of learning. In this paper, the lack of practice of a blended learning approach to entrepreneurship education and how it impacts learners' perception of being entrepreneurial. E-learning is in its infancy within the secondary and high school sectors in South Africa. The conceptual framework of the study is based on theoretical aspects of systemic-constructivist learning implemented in an interactive online learning environment in an entrepreneurship education subject. The formative evaluation research was conducted implementing mixed methods of research (quantitative and qualitative) and it comprised a survey of high school learners and informant interviewing with entrepreneurs. Theoretical analysis of literature provides features necessary for creating interactive blended learning environments to be used in entrepreneurship education subject. Findings of the study show that learners do not always objectively evaluate their capacities. Special attention has to be paid to the development of learners’ computer literacy as well as to the activities that would bring online learning to practical training. Needs analysis shows that incorporating blended learning in entrepreneurship education may have a positive perception of entrepreneurship.

Keywords: blended learning, entrepreneurship education, entrepreneurship intention, entrepreneurial skills

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Authors: Ailin Agaahi, Nafise Daneshvar Hoseini, Shahnaz Tamizi, Mehrdad Sabet

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This study investigates the impact of the Tehran Conservatory's music program on children with autism spectrum disorder (ASD) and their families. Recognizing music education as a beneficial therapeutic intervention, the research highlights how engagement in musical activities can foster cognitive, emotional, and social growth. Through qualitative interviews with parents of children enrolled in the program, the study explores their motivations for participation, observations of their children's progress, and assessments of the program's effectiveness. Preliminary findings indicate that the program significantly enhances social interaction, emotional regulation, and communication skills in children with ASD. Parents appreciate the program's adaptability to individual needs and the supportive training of instructors. Despite these positive outcomes, the study identifies challenges, including a lack of awareness and limited access to similar programs. The findings contribute valuable perspectives to the existing literature and suggest pathways for developing more inclusive music education initiatives, both in Iran and globally, to better support children with ASD and their families.

Keywords: autism spectrum disorder, music education, therapeutic intervention, parental perspectives, social interaction

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Authors: Saroj Panthi, Sher Singh Thagunna

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Reliable and sufficient information regarding status, distribution and habitat preference of red panda (Ailurus fulgens fulgens) is lacking in Nepal. The research activities on red panda in the mid-western Nepal are very limited, so the status of red panda in the region is quite unknown. The study conducted during May, 2013 in three Village Development Committees (VDCs) namely Godhemahadev, Malikathata and Tamti of Jumla district was an important step for providing vital information including distribution and habitat preference of this species. The study included the reconnaissance, key informants survey, interviews, and consultation for the most potential area identification, opportunistic survey comprising the direct observation and indirect sign count method for the presence and distribution, habitat assessment consisting vegetation sampling and ocular estimation. The study revealed the presence of red panda in three forests namely Bahirepatan, Imilchadamar and Tyakot of Godhemahadev, Tamti and Malikathata VDCs respectively. The species was found distributed between 2880 and 3244 m with an average dropping encounter rate of 1.04 per hour of searching effort and 12 pellets per dropping. Red panda mostly preferred the habitat in the elevation range of 2900 - 3000 m with southwest facing steep slopes (36˚ - 45˚), associated with water sources at the distance of ≤100 m. Trees such as Acer spp., Betula utilis and Quercus semecarpifolia, shrub species of Elaeagnus parvifolia, Drepanostachyum spp. and Jasminum humile, and the herbs like Polygonatum cirrhifolium, Fragaria nubicola and Galium asperifolium were found to be the most preferred species by red panda. The red panda preferred the habitat with dense crown coverage ( >20% - 100%) and 31% - 50% ground cover. Fallen logs (39%) were the most preferred substrate used for defecation.

Keywords: distribution, habitat preference, jumla, red panda

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Authors: Mahmoud Nassar

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This paper was designed for interviews with companies that had implemented Management Accounting Innovations (MAIs) within Jordanian Industrial Sector in full. Each company in this paper was examined as an entity to obtain an understanding of the process of MAIs adoption and implementation as well as the respondents’ opinions and perspectives of each individual company as to what are considered to be the important factors in the company. By firstly using within-case analysis has the potential to aid in-depth views of the issues and their impact on each particular company. Then, cross-case analysis was used to analyse the similarities and differences of the six companies. The study concludes that, the six companies interviewed gradually moved to using MAIs over the last ten years. The length of time required to implement the MAIs varied across the companies. Interviewees revealed several factors from both the demand and supply side that influence implementation of MAIs within the Jordanian industrial companies. Respondents mentioned and emphasised the important effect of the following factors: top management support, education about ABC concept and benefits, training programmes, shortcoming of existing cost system, competition, size of company, professional accounting bodies, management accounting journals, management accounting research and PhD degrees, and cooperation between universities and companies.

Keywords: industrial sector, innovations, Jordan, management accounting

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Authors: Ge Zheng, Jun Peng

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Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

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Authors: Christiane H. Kellner, Sarah Reker

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The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centred design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like centre in Schönbrunn - a large residential complex and service provider for persons with disabilities in the outskirts of Munich - will be remodelled to open up the community to all people as well as transform social space. This strategy should lead to more equal opportunities and open the way for a much more diverse community. The research project “Index for participation development and quality of life for persons with disabilities” (TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at the Franziskuswerk Schönbrunn supports this transformation process called “Vision 2030”. In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees using person-centred planning). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one sub-project more in-depth, namely “The Person-Centred Think Tank” [Arbeitskreis Personenzentriertes Denken; PZD]. In the context of person-centred thinking (PCT), persons with disabilities are encouraged to (re)gain or retain control of their lives through the development of new choice options and the validation of individual lifestyles. PCT should thus foster and support both participation and quality of life. The project aims to establish PCT as a fundamental approach for both employees and persons with disabilities in the institution through in-house training for the staff and, subsequently, training for users. Hence, for the academic support and supervision team, the questions arising from this venture can be summed up as follows: (1) has PCT already gained a foothold at the Franziskuswerk Schönbrunn? And (2) how does it affect the interaction with persons with disabilities and how does it influence the latter’s everyday life? According to the holistic approach described above, the target groups for this study are both the staff and the users of the institution. Initially, we planned to implement the group discussion method for both target-groups. However, in the course of a pretest with persons with intellectual disabilities, it became clear that this type of interview, with hardly any external structuring, provided only limited feedback. In contrast, when the discussions were moderated, there was more interaction and dialogue between the interlocutors. Therefore, for this target-group, we introduced structured group interviews. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. We analysed and evaluated the group interviews and discussions with the help of qualitative content analysis according to Mayring in order to obtain information about users’ quality of life. We sorted out the statements relating to quality of life obtained during the group interviews into three dimensions: subjective wellbeing, self-determination and participation. Nevertheless, the majority of statements were related to subjective wellbeing and self-determination. Thus, especially the limited feedback on participation clearly demonstrates that the lives of most users do not take place beyond the confines of the institution. A number of statements highlighted the fact that PCT is anchored in the everyday interactions within the groups. However, the implementation and fostering of PCT on a broader level could not be detected and thus remain further aims of the project. The additional interviews we have planned should validate the results obtained until now and open up new perspectives.

Keywords: person-centered thinking, research with persons with disabilities, residential complex and service provider, participation, self-determination.

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Authors: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

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Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Sarah K. Taylor, Miratun M. Saharuddin, Zabri A. Talib

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Cybercrime is on the rise, and yet many Law Enforcement Agencies (LEAs) in Malaysia have no Digital Forensics Laboratory (DFL) to assist them in the attrition and analysis of digital evidence. From the estimated number of 30 LEAs in Malaysia, sadly, only eight of them owned a DFL. All of the DFLs are concentrated in the capital of Malaysia and none at the state level. LEAs are still depending on the national DFL (CyberSecurity Malaysia) even for simple and straightforward cases. A survey was conducted among LEAs in Malaysia owning a DFL to understand their history of establishing the DFL, the challenges that they faced and the significance of the DFL to their case investigation. The results showed that the while some LEAs faced no challenge in establishing a DFL, some of them took seven to 10 years to do so. The reason was due to the difficulty in convincing their management because of the high costs involved. The results also revealed that with the establishment of a DFL, LEAs were better able to get faster forensic result and to meet agency’s timeline expectation. It is also found that LEAs were also able to get more meaningful forensic results on cases that require niche expertise, compared to sending off cases to the national DFL. Other than that, cases are getting more complex, and hence, a continuous stream of budget for equipment and training is inevitable. The result derived from the study is hoped to be used by other LEAs in justifying to their management the benefits of establishing an in-house DFL.

Keywords: digital evidence, digital forensics, digital forensics laboratory, law enforcement agency

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Marjan Golmaryami, Marzieh Behzadi

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Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Hurgesa Hundera, Samuel Shibeshibikeko, Tarike Daba, Tesfaye Ganamo

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The study aimed at examining the ongoing adaptation strategies used by smallholder farmers in response to climate variability in Boset district. It also assessed the socioeconomic factors that influence the choice of adaptation strategies of smallholder farmers to climate variability risk. For attaining the objectives of the study, both primary and secondary sources of data were employed. The primary data were obtained through a household questionnaire, key informant interviews, focus group discussions, and observations, while secondary data were acquired through desk review. Questionnaires were distributed and filled by 328 respondents, and they were identified through systematic random sampling technique. Descriptive statistics and binary logistic regression model were applied in this study as the main analytical methods. The findings of the study reveal that the sample households have utilized multiple adaptation strategies in response to climate variability, such as cropping early mature crops, planting drought resistant crops, growing mixed crops on the same farm lands, and others. The results of the binary logistic model revealed that education, sex, age, family size, off farm income, farm experience, access to climate information, access to farm input, and farm size were significant and key factors determining farmers’ choice of adaptation strategies to climate variability in the study area. To enable effective adaptation measures, Ministry of Agriculture and Natural Resource, with its regional bureaus and offices and concerned non–governmental organizations, should consider climate variability in their planning and budgeting in all levels of decision making.

Keywords: adaptation strategies, boset district, climate variability, smallholder farmers

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

Procedia PDF Downloads 447

Authors: Siddique Ullah Baig, Alisha Manzoor

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The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

Procedia PDF Downloads 66

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 196

Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

Procedia PDF Downloads 101

Authors: Chia-Chun Wu, Ying-Yao Cheng

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The purpose of this study was developing the 'short-form BASIC scale' psychotic tendencies subscale so as to provide a more efficient, economical and effective way to assess the mental health of recruits. 1749 students from Naval Recruit Training Center participated in this study. The multidimensional constructs of psychotic tendencies subscale include four dimensions: schizophrenic tendencies, manic tendencies, depression tendencies, and suicidal ideation. We cut down the 36-item psychotic tendencies subscale to 25 items by using multidimension Rasch techniques. They were applied to assess model-data fit and to provide the validity evidence of the short form BASIC scale of psychotic tendencies subscale. The person separation reliabilities of the measures from four dimensions were .70, .67, .74 and .57, respectively. In addition, there is a notable correlation between the length version and short version of schizophrenic tendencies (scaled .89), manic tendencies (.96), depression tendencies (.97) and suicidal ideation (.97). The results have indicated that the development of the study of short-form scale sufficient to replace the original scale. Therefore, it is suggested that short-form basic scale is used to assess the mental health with participants being more willing to answer questions to ensure the validation of assessments.

Keywords: BASIC scale, military, Rasch analysis, short-form scale

Procedia PDF Downloads 361

Authors: N. Rashed, Z. Aysha, M. Fakher

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Patient satisfaction is one of the core objectives of health care facilities. It is difficult to evaluate patients response in the emergency setting. The current study aimed to evaluate patients and family aspects of satisfaction in both adult and pediatric emergency departments and their recommendations for improvement. Cross-section survey(Brief Emergency department Patient Satisfaction Scale (BEPSS), was translated and validated, then performed to evaluate patients satisfaction in two governmental hospitals Emergency departments. Three hundred patients and their families were enrolled in the study. The waiting time in the adult Emergency department ranged from (5 minutes to 120 minutes), and most admissions were at the morning shift while at the pediatric hospital the waiting time ranged from 5 minutes to 100 minutes) and most admissions were at the afternoon shift. The results showed that the main domain of satisfaction in BEPSS in the adult emergency department was respecting the patients family while in the pediatric emergency department, the main domain was the nursing care about treatment. The main recommendation of improvement in pediatric Emergency Department was modifying the procedures while in adult Emergency Department was improving the training of physicians.

Keywords: emergency, department-patient, satisfaction-adult-pediatric

Procedia PDF Downloads 144

Authors: S. J. Higgs, E. Van Eck, K. Heynis, S. H. Broadberry

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Engagement with non-human animals is a rapidly-growing field of study within the animal science and social science sectors, with human-interactions occurring in many forms; interactions, encounters and animal-assisted therapy. To our knowledge, there has been a wide array of research published on domestic and livestock human-animal interactions, however, there appear to be fewer publications relating to zoo animals and the effect these interactions have on the animal, human and establishment. The aim of this study was to identify if there were any perceivable benefits from the human-animal interaction for the cheetah, the human and the establishment. Behaviour data were collected before, during and after the interaction on the behaviour of the cheetah and the human participants to highlight any trends with nine interactions conducted. All 35 participants were asked to fill in a questionnaire prior to the interaction and immediately after to ascertain if their perceptions changed following an interaction with the cheetah. An online questionnaire was also distributed for three months to gain an understanding of the perceptions of human-animal interactions from members of the public, gaining 229 responses. Both questionnaires contained qualitative and quantitative questions to allow for specific definitive answers to be analysed, but also expansion on the participants perceived perception of human-animal interactions. In conclusion, it was found that participants’ perceptions of human-animal interactions saw a positive change, with 64% of participants altering their opinion and viewing the interaction as beneficial for the cheetah (reduction in stress assumed behaviours) following participation in a 15-minute interaction. However, it was noted that many participants felt the interaction lacked educational values and therefore this is an area in which zoological establishments can work to further improve upon. The results highlighted many positive benefits for the human, animal and establishment, however, the study does indicate further areas for research in order to promote positive perceptions of human-animal interactions and to further increase the welfare of the animal during these interactions, with recommendations to create and regulate legislation.

Keywords: Acinonyx jubatus, encounters, human-animal interactions, perceptions, zoological establishments

Procedia PDF Downloads 189