Search results for: conditional random fields

Authors: Thirsa Sherry, Utkarsh Shrivastav, Kannan B. T., Iynthezhuton K.

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The field of aerodynamics and aeroacoustics remains one of the most poignant and well-researched fields of today. The current paper aims to investigate the predominant problem concerning the effects of noise of varying frequencies and waveforms on airflow surrounding an airfoil. Using a single speaker beneath the airfoil at different positions, we wish to simulate the effects of sound directly impinging on an airfoil and study its direct effects on airflow. We wish to study the same using smoke visualization methods with incense as our smoke-generating material in a variable-speed subsonic wind tunnel. Using frequencies and wavelengths similar to those of common engine noise, we wish to simulate real-world conditions of engine noise interfering with airflow and document the arising trends. These results will allow us to look into the real-world effects of noise on airflow and how to minimize them and expand on the possible relation between waveforms and noise. The parameters used in the study include frequency, Reynolds number, waveforms, angle of attack, and the effects on airflow when varying these parameters.

Keywords: engine noise, aeroacoustics, acoustic excitation, low speed

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Authors: S. M. Azad, H. Ghodsi Pour, F. Roshannafasa

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In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: Technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’ which came from Technological IS literature and using them into sectoral system as measurable indicators.

Keywords: innovation system, technology, techno-sectoral system, functional indicators, system dynamics

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Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

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Authors: Aneri Mehta, Krunal Mehta

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Administration is largely based on two sciences: ‘management science’ and ‘political science’. The approach of new public management is more inclined towards the management science. Era of ‘New Public Management’ has affected the developing countries very immensely. Public management reforms are needed to enhance the development of the countries. This reform mainly includes capacity building, control of corruption, political decentralization, debureaucratization and public empowerment. This gives the opportunity to create self-sustaining change in the governance. This paper includes the link of approach of new public management and their effect on building effective democratization in the country. This approach mainly focuses on rationality and effectiveness of governance system. These need to have deep efforts on technological, organizational, social and cultural fields. Bringing citizen participation in governance is main objective of NPM. The shift from traditional public management to new public management have low success rate of reforms. This research includes case study of RTI which is a big step of government towards citizen centric approach of governance. The aspect of ‘publicness’ in the democratic policy implementation is important for good governance in India.

Keywords: public management, development, public empowerment, governance

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Authors: N. Masoudnia, M. Fatahi

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An experimental study of saturated pool boiling on a single artificial nucleation site without and with the application of an electric field on the boiling surface has been conducted. N-pentane is boiling on a copper surface and is recorded with a high speed camera providing high quality pictures and movies. The accuracy of the visualization allowed establishing an experimental bubble growth law from a large number of experiments. This law shows that the evaporation rate is decreasing during the bubble growth, and underlines the importance of liquid motion induced by the preceding bubble. Bubble rise is therefore studied: once detached, bubbles accelerate vertically until reaching a maximum velocity in good agreement with a correlation from literature. The bubbles then turn to another direction. The effect of applying an electric field on the boiling surface in finally studied. In addition to changes of the bubble shape, changes are also shown in the liquid plume and the convective structures above the surface. Lower maximum rising velocities were measured in the presence of electric fields, especially with a negative polarity.

Keywords: single bubbles, electric field, boiling, effect

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Authors: Hu Yinyao

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Learning and using a second language have become more and more common in daily life. Understanding the complexity of second language proficiency can help students develop their interpersonal relationships with their friends and professors, even enhancing intimacy. This paper examines Wenzhou-Kean University students' second language proficiency and interpersonal relationships. The purpose of the research was to explore the relationship between second language proficiency, extent of intimacy, and interpersonal relationships of the 100 Wenzhou-Kean University students. A mixed methodology was utilized in the research study. Student respondents from Wenzhou-Kean University were chosen randomly by using random sampling. The data analysis used descriptive data in terms of figures and thematical data in the table. The researcher found that Wenzhou-Kean University’s students have shown lower intermediate level of second language proficiency and that their intimacy is middle when using a second language. Especially when talking about some sensitive topics, students tend not to use a second language due to low proficiency. This research project has a strong implication on interpersonal relationships and second language proficiency. The outcome of the study would be greatly helpful to enhance the interpersonal relationship and intimacy between students and students, students and professors who use.

Keywords: Interpersonal relationship, second language proficiency, intimacy, education, univeristy students

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Authors: Waheed Gul, Muhammad Zeeshan, Ahmad Raza Khan, Muhammad Khurram

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Wireless Sensor Nodes (WSNs) have developed significantly over the years and have significant potential in diverse applications in the fields of science and technology. The inadequate energy accompanying WSNs is a key constraint of WSN skills. To overcome this main restraint, the development and expansion of effective and reliable energy harvesting systems for WSN atmospheres are being discovered. In this research, low-power acoustic energy harvesters are designed and developed by applying different techniques of energy transduction from the sound available in the surroundings. Three acoustic energy harvesters were developed based on the piezoelectric phenomenon, electromagnetic transduction, and hybrid, respectively. The CAD modelling, lumped modelling and Finite Element Analysis of the harvesters were carried out. The voltages were obtained using FEA for each Acoustic Harvester. Characterization of all three harvesters was carried out and the power generated by the piezoelectric harvester, electromagnetic harvester and Hybrid Acoustic Energy harvester are 2.25x10-9W, 0.0533W and 0.0232W, respectively.

Keywords: energy harvesting, WSNs, piezoelectric, electromagnetic, power

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Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda

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Brownfields are one of the most important problems that must be solved by today's cities. The topic of this article is description of developing a comprehensive transformation of post-industrial area of the former iron factory national cultural heritage Lower Vítkovice. City of Ostrava used to be industrial superpower of the Czechoslovak Republic, especially in the area of coal mining and iron production, after declining industrial production and mining in the 80s left many unused areas of former factories generally brownfields and backfields. Since the late 90s we are observing how the city officials or private entities seeking to remedy this situation. Regeneration of brownfields is a very expensive and long-term process. The area is now rebuilt for tourists and residents of the city in the entertainment, cultural, and social center. It was necessary do the reconstruction of the industrial monuments. Equally important was the construction of new buildings, which helped reusing of the entire complex. This is a unique example of transformation of technical monuments and completion of necessary new objects, so that the area could start working again and reintegrate back into the urban system.

Keywords: brown fields, conversion, historical and industrial buildings, reconstruction

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Authors: Halima Adel Halim Shnishah, David Mulvaney

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Applying traditional symmetric cryptography algorithms while computing encryption and decryption provides immunity to secret keys against different attacks. One of the popular techniques generating automated secret keys is evolutionary computing by using Eureqa API tool, which got attention in 2013. In this paper, we are generating automated secret keys for image encryption and decryption using Eureqa API (tool which is used in evolutionary computing technique). Eureqa API models pseudo-random input data obtained from a suitable source to generate secret keys. The validation of generated secret keys is investigated by performing various statistical tests (histogram, chi-square, correlation of two adjacent pixels, correlation between original and encrypted images, entropy and key sensitivity). Experimental results obtained from methods including histogram analysis, correlation coefficient, entropy and key sensitivity, show that the proposed image encryption algorithms are secure and reliable, with the potential to be adapted for secure image communication applications.

Keywords: image encryption algorithms, Eureqa, statistical measurements, automated key generation

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Authors: Mustafa Ekici, Sacide Güzin Mazman

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Programming is the one of ability in computer science fields which is generally perceived difficult by students and various individual differences have been implicated in that ability success. Although several factors that affect programming ability have been identified over the years, there is not still a full understanding of why some students learn to program easily and quickly while others find it complex and difficult. Programming self-efficacy and mathematic success are two of those essential individual differences which are handled as having important effect on the programming success. This study aimed to identify the relationship between programming performance, programming self efficacy and mathematics success. The study group is consisted of 96 undergraduates from Department of Econometrics of Uşak University. 38 (39,58%) of the participants are female while 58 (60,41%) of them are male. Study was conducted in the programming-I course during 2014-2015 fall term. Data collection tools are comprised of programming course final grades, programming self efficacy scale and a mathematics achievement test. Data was analyzed through correlation analysis. The result of study will be reported in the full text of the study.

Keywords: programming performance, self efficacy, mathematic success, computer science

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Authors: Rundong Li, Peng Wu, Junfeng Zhang, Zhipeng Ren, Chen Yang, Jiahui Gan, Lu Feng, Haibo Tong, Xuemei Xiao, Yuying Chen

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The research of Beidou-3 satellite navigation is on the rise, but in actual work, it is inevitable that satellite data is insecure, research and development is inefficient, and there is no ability to deal with failures in advance. Digital twin technology has obvious advantages in the simulation of life cycle models of aerospace satellite navigation products. In order to meet the increasing demand, this paper builds a Beidou-3 satellite navigation digital twin platform (BDSDTP). The basic establishment of BDSDTP was completed by establishing a digital twin double, Beidou-3 comprehensive digital twin design, predictive maintenance (PdM) mathematical model, and visual interaction design. Finally, this paper provides a time application case of the platform, which provides a reference for the application of BDSDTP in various fields of navigation and provides obvious help for extending the full cycle life of Beidou-3 satellite navigation.

Keywords: BDS-3, digital twin, visualization, PdM

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Riffat Sultana Pathan, Waheed Ali Panhwar, Muhammad Saeed Wagan

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Tettigonioidea are phytophagous insects damaging agricultural crops, forest, fruit orchards, berry shrubs, and grasses. The material was collected from different agricultural fields of rice, sugarcane, wheat, maize surrounding by different grasses. Beside this, forest, hilly areas, semi-desert and desert regions were also inspected time to time. All material was captured, killed and stored by using the standard entomological method. As a result of extensive survey fair numbers were captured from the different climatic zone of country. Seven sub-families of Tettigonioidea viz: Pseudophyllinae, Phaneropterinae, Conocephalinae, Tettigoniinae, Hexacentrinae, Mecopodinae and Decticinae came in collection. This fauna contributes 29 new records to Pakistan and 5 new species to science. Beside this, a brief description of each supra-generic category of Tettigonioidea along with photographs and synonymy is also documented. In addition to this, detailed list of host plants from Pakistan was also composed. This study provides important data for Integrated Pest Management (IPM) of Tettigonioidea biodiversity conservation and grassland restoration in Pakistan.

Keywords: agriculture, conocephalinae, pest, phaneropterinae, tettigoniidae

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Authors: David Chapola Nggada

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This is a survey designed to find out the impact of the ongoing insurgency in north eastern Nigeria on educational attainment. It is a mixture of both qualitative and quantitative research work on a sample size of 71 secondary school students currently displaced from Baga Biu and Monguno areas of Borno State, now residing as internally displaced persons(IDPs) in Gombe and Yola IDP camps. This was done through both semi structured interview and questionnaire administration. Statistical methods used include percentage and cross tables to gain specific insight into different dimensions of what this implies. Two major aspects of the impact covered were impact on individual student and impact on societal development. These two dimensions were measured against national development variables and analyzed against reviewed literature and findings across the globe. A combination of theories from different fields led to a deeper and better insight. The results confirm a significant relationship between educational attainment and the development of the north east region and Nigeria as a whole. Recommendations were made on ways of reintegrating this group back to the educational system.

Keywords: education, insurgency, national development, threat

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Authors: Şebnem Aslan, Demet Akarçay

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The objective of this study is to investigate the feelings of health employees occurred by bullying and the relationships between these feelings at work place. In this context, the relationships between bullying and the feelings of self-esteem, employee silence, anger, self- blame and shame. This study was conducted among 512 health employees in three hospitals in Konya by using survey method and simple random sampling. The scales of bullying, self-esteem, employee silence, anger, self-blame, and shame were performed within the study. The obtained data were analyzed with descriptive analysis, correlation, confirmative factor analysis, structural equation modeling and path analysis. The results of the study showed that while bullying had a positive effect on self-esteem (.61), employee silence (.41), anger (.18), a negative effect on self-blame and shame (-.26) was observed. Employee silence affected self-blame and shame (.83) as positively. Besides, self-esteem impacted on self- blame and shame (.18), employee silence (.62) positively and self-blame and shame was observed as negatively affecting on anger (-.20). Similarly, self-esteem was found as negatively affected on anger (-.13).

Keywords: bullying, self-esteem, employee silence, anger, shame and guilt, healthcare employee

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Authors: Niloufar Yadgari

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GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang

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Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.

Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Malki Fatima Zahra Nadia, Kellal Cheiimaa, Brahimi Houria

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Total Quality Management (TQM) is one of the most important modern management systems in marketing, that help organizations to survive and remain competitive in the dynamic market with frequent changes. It assists them in gaining a competitive advantage, growth, and excellence compared to their competitors. To understand the impact of TQM on competitive advantage in economic companies, a study was conducted in Ooredoo Telecommunications Company. A questionnaire was designed and distributed to OOredoo' 75 employees in each of the departments of leadership, quality assurance, quality control, research and development, production, customer service, Similarly, resulting in the retrieval of 72 questionnaires. To analyze the descriptive results of the study, the SPSS software version 25 was used. Additionally, Structural Equation Modeling (SEM) with the help of Smart Pls4 software was utilized to test the study's hypotheses. The study concluded that there is an impact between total quality management and competitive advantage in Ooredoo company to different degrees. On this basis, the study recommended the need to implement the total quality management system at the level of all organizations and in various fields.

Keywords: total quality management, ISO system, competitive advantage, competitive strategies

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Authors: Mohamedou El Boukhary, Farba Bouyagui Tamboura, A. Hamady Barry, T. Moussa Seck, Mohamed L. Gaye

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Nowadays, low-schiff acyl-hydrazone ligands are highly sought after due to their wide applications in various fields of biology, coordination chemistry, and catalysis. They are studied for their antioxidant, antibacterial and antiviral properties. The complexes of transition metals and the lanthanide they derive are well known for their magnetic, optical, and catalytic properties. In this work, we present the synthesis of an acyl-hydrazone (H2L) schiff base and their 3d transition complexes. The ligand (H2L) is characterized by IR, NMR (1H; 13C) spectroscopy. The complexes are characterized by different physic-chemical techniques such as IR, UV-visible, conductivity, measurement of magnetic susceptibility. The study of XRD allowed us to elucidate the crystalline structure of the manganese (Mn) complex. The asymmetric unit of the complex is composed of two molecules of the ligand, one manganese (II) ion, and two coordinate chloride ions; the environment around Mn is described as a pentagonal base bipyramid. In the crystal lattice, the asymmetric unit is bound by hydrogen bonds.

Keywords: synthene, acyl-hydrazone, 3D transition metal complex, application

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

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Authors: Ouafek Nora, Keghouche Nassira, Dehdouh Heider, Untidt Carlos

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A lot of knowledge has been accumulated on the metal clusters supported on oxide surfaces because of their multiple applications in microelectronics, heterogeneous catalysis, and magnetic devices. In this work, the surface state of Ni / MgO has been studied by XPS (X-ray Photoemission Spectroscopy). The samples were prepared by impregnation with ion exchange Ni²⁺ / MgO, followed by either a thermal treatment in air (T = 100 -350 ° C) or a gamma irradiation (dose 100 kGy, 25 kGy dose rate h -1). The obtained samples are named after impregnation NMI, NMR after irradiation, and finally NMC(T) after calcination at the temperature T (T = 100-600 °C). A structural study by XRD and HRTEM reveals the presence of nanoscaled Ni-Mg intermetallic phases (Mg₂Ni, MgNi₂, and Mg₆Ni) and magnesium hydroxide. Mg(OH)₂ in nanometric range (2- 4 nm). Mg-Ni compounds are of great interest in energy fields (hydrogen storage…). XPS spectra show two Ni2p peaks at energies of about 856.1 and 861.9 eV, indicating that the nickel is primarily in an oxidized state on the surface. The shift of the main peak relative to the pure NiO (856.1 instead of 854.0 eV) suggests that in addition to oxygen, nickel is engaged in another link with magnesium. This is in agreement with the O1s spectra which present an overlap of peaks corresponds to NiO and MgO, at a calcination temperature T ≤ 300 °C.

Keywords: XPS, XRD, nanoparticules, Ni-MgO

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Authors: Simon Ayorinde Okanlawon

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This study examines residents’ assessment of with infrastructural facilities in the urban fringe of Ibadan, Nigeria. Random sampling technique was used in selecting four Local Government Areas out of the six suburban LGAs of the city. Google earth and ground trotting were used in capturing and selecting seven hundred and forty-two new houses. The questionnaires administered on house owners were harvested on the spot. The information collected includes socio-economic and demographic characteristics of residents as well as characteristics of infrastructural facilities. The study utilised both descriptive and inferential statistical analyses; Facility Availability Index (FAI) Facility Functionality Index (FFI) and Residents’ Satisfactions Index (RSI) were used to compare respectively residents’ perceived levels of availability of, the functionality of, and satisfaction with facilities across Local Government Areas. The study shows that levels of both availability of, and satisfaction with infrastructural facilities are low with respective overall FAI (0.8) and RSI (0.05), while the functionality of the facilities is generally very poor IFFI = - 0.58). Strategies were proposed to enhance the good, livable, and healthy environment.

Keywords: infrastructural facilities, infrastructural perception index, residents’ satisfaction, urban fringe of Ibadan

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Authors: Mehravar Javid, James Sexton, Farzaneh Amani, Kainaz Patravala

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Self-expansion is a procedure through which people expand the dimensions of their self-concept by incorporating novel content into their sense and experience of identity. Greater self-expansion predicts positive consequences for individuals and romantic relationships. The self-expansion questionnaire (SEQ) originally developed by Lewandowski & Aron (2002) assumes that self-expansion is constituted of key components from the self-expansion model. This study aimed to confirm the factor structure of SEQ and adapt the questions of the scale to the Iranian culture. The sample included 190 participants who responded to 14 items and were selected by simple random sampling. Using Amos-21 and SPSS-21, descriptive statistics, Pearson correlation and Confirmatory Factor Analysis (CFA) were calculated. Cronbach’s alpha coefficient for total SEQ items was 0.92. Results of CFA supported the factor structure SEQ [RMSEA=0.08, GFI=0.88 and CFI=0.92] that showed the model has a good fit and also all the items of SEQ, have a high correlation and have a direct and significant relationship. So, the SEQ demonstrated acceptable psychometric properties in Tehran University students. Looking forward, it would be interesting and exciting to see the implications of the scale as applied to romantic relationships.

Keywords: validity, reliability, confirmatory factor analysis, self-expansion questionnaire

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Nabiha Bouafia, Asma Ben Cheikh, Asma Ammar, Olfa Ezzi, Mohamed Mahjoub, Khaoula Meddeb, Imed Chouchene, Hamadi Boussarsar, Mansour Njah

Abstract:

Background: Hospital acquired infections (HAI) cause significant morbidity, mortality, length of stay and hospital costs, especially in the intensive care unit (ICU), because of the debilitated immune systems of their patients and exposure to invasive devices. The aims of this study were to determine the rate and the risk factors of HAI in an ICU of a university hospital in Tunisia. Materials/Methods: A prospective study was conducted in the 8-bed adult medical ICU of a University Hospital (Sousse Tunisia) during 14 months from September 15th, 2015 to November 15th, 2016. Patients admitted for more than 48h were included. Their surveillance was stopped after the discharge from ICU or death. HAIs were defined according to standard Centers for Disease Control and Prevention criteria. Risk factors were analyzed by conditional stepwise logistic regression. The p-value of < 0.05 was considered significant. Results: During the study, 192 patients had admitted for more than 48 hours. Their mean age was 59.3± 18.20 years and 57.1% were male. Acute respiratory failure was the main reason of admission (72%). The mean SAPS II score calculated at admission was 32.5 ± 14 (range: 6 - 78). The exposure to the mechanical ventilation (MV) and the central venous catheter were observed in 169 (88 %) and 144 (75 %) patients, respectively. Seventy-three patients (38.02%) developed 94 HAIs. The incidence density of HAIs was 41.53 per 1000 patient day. Mortality rate in patients with HAIs was 65.8 %( n= 48). Regarding the type of infection, Ventilator Associated Pneumoniae (VAP) and central venous catheter Associated Infections (CVC AI) were the most frequent with Incidence density: 14.88/1000 days of MV for VAP and 20.02/1000 CVC days for CVC AI. There were 5 Peripheral Venous Catheter Associated Infections, 2 urinary tract infections, and 21 other HAIs. Gram-negative bacteria were the most common germs identified in HAIs: Multidrug resistant Acinetobacter Baumanii (45%) and Klebsiella pneumoniae (10.96%) were the most frequently isolated. Univariate analysis showed that transfer from another hospital department (p= 0.001), intubation (p < 10-4), tracheostomy (p < 10-4), age (p=0.028), grade of acute respiratory failure (p=0.01), duration of sedation (p < 10-4), number of CVC (p < 10-4), length of mechanical ventilation (p < 10-4) and length of stay (p < 10-4), were associated to high risk of HAIS in ICU. Multivariate analysis reveals that independent risk factors for HAIs are: transfer from another hospital department: OR=13.44, IC 95% [3.9, 44.2], p < 10-4, duration of sedation: OR= 1.18, IC 95% [1.049, 1.325], p=0.006, high number of CVC: OR=2.78, IC 95% [1.73, 4.487], p < 10-4, and length of stay in ICU: OR= 1.14, IC 95% [1.066,1.22], p < 10-4. Conclusion: Prevention of nosocomial infections in ICUs is a priority of health care systems all around the world. Yet, their control requires an understanding of epidemiological data collected in these units.

Keywords: healthcare associated infections, incidence, intensive care unit, risk factors

Procedia PDF Downloads 369

Authors: Yu Zhang, Pedro Desouza

Abstract:

Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

Procedia PDF Downloads 353