Search results for: random features

Authors: A. Pallavi, N. Vijay Mohan

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A nation can be economically progressive only when the citizens have sufficient capacity to work efficiently to increase the productivity. So, good health must be regarded as a primary need of the community. This helps the growth and development of the body and the mind, which in turn leads to progress and prosperity of the nation. An optimum growth is a necessity for an efficient existence in a biologically adverse and economically competitive world. It is also necessary for the execution of daily routine work. Yoga is a method or a system for the complete development of the personality in a human being. It can be further elaborated as an all-around and complete development of the body, mind, morality, intellect and soul of a being. Sri Aurobindo defines yoga as 'a methodical effort towards self-perfection by the development of the potentialities in the individual.' Aerobic exercise as any activity that uses large muscle groups, can be maintained continuously, and is rhythmic I nature. It is a type of exercise that overloads the heart and lungs and causes them to work harder than at rest. The important idea behind aerobic exercise today, is to get up and get moving. There are more activities that ever to choose from, whether it is a new activity or an old one. Find something you enjoy doing that keeps our heart rate elevated for a continuous time period and get moving to a healthier life. Middle aged selected and served as the subjects for the purpose of this study. The selected subjects were in the age group of 30 to 40 years. By going through the literature and after consulting the experts in yoga and aerobic training, the investigator had chosen the variables which are specifically related to the middle-aged men. The selected physiological variables are pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity. The selected psychological variables are job anxiety, occupational stress. The study was formulated as a random group design consisting of aerobic exercise and yogic exercises groups. The subjects (N=60) were at random divided into three equal groups of twenty middle-aged men each. The groups were assigned the names as follows: 1. Experimental group I- aerobic exercises group, 2. Experimental group II- yogic exercises, 3. Control group. All the groups were subjected to pre-test prior to the experimental treatment. The experimental groups participated in their respective duration of twenty-four weeks, six days in a week throughout the study. The various tests administered were: prior to training (pre-test), after twelfth week (second test) and twenty-fourth weeks (post-test) of the training schedule.

Keywords: pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity, psychological variables, job anxiety, occupational stress, aerobic exercise, yogic exercise

Procedia PDF Downloads 440

Authors: Nazi Pharsadanishvili, Anastasia Kitiashvili

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The importance of studying the social-psychological features of people living in poverty is often emphasized in international research. Building a multidimensional economic framework for reducing poverty grounded in people’s experiences and values is the main goal of famous Poverty Research Centers (such as Oxford Poverty and Human Development Initiative, Abdul Latif Jameel Poverty Action Lab). The aims of the proposed research are to investigate the following characteristics of socially vulnerable people living in Georgia: 1) The features of the perceived stigma of poverty; 2) economic system justification and social justice beliefs; 3) Perceived social mobility and actual attempts at upward social mobility. Qualitative research was conducted to address the indicated research goals and descriptive research questions. Conducting in-depth interviews was considered to be the most appropriate method to capture the vivid feelings and experiences of people living in poverty. 17 respondents (registered in the unified database of socially vulnerable families) participated in in-depth interviews. According to the research results, socially vulnerable people living in Georgia perceive stigma targeted toward them. Two sub-dimensions were identified in perceived stigma: experienced stigma and internalized stigma. Experienced stigma reflects the instances of being discriminated and perceptions of negative treatment from other members of society. Internalized stigma covers negative personal emotions, the feelings of shame, the fear of future stigmatization, and self-isolation. The attitudes and justifications of the existing economic system affect people’s attempts to cope with poverty. Complex analysis of those results is important during the planning and implementing of social welfare reforms. Particularly, it is important to implement poverty stigma reduction mechanisms and help socially vulnerable people to see real perspectives on upward social mobility.

Keywords: coping with poverty, economic system justification, perceived stigma of poverty, upward social mobility

Procedia PDF Downloads 179

Authors: B. Tiseo, V. Quaranta, G. Bruno, R. Gardi, T. Watts, S. Dussy

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This paper describes the qualification test campaign performed on the Demise Observation Capsule DOC-EQM as part of the Future Launch Preparatory Program FLPP3. The mechanical environment experienced during launch ascent and separation phase was first identified and then replicated in terms of sine, random and shock vibration. The loads identification is derived by selecting the worst possible case. Vibration and shock qualification test performed at CIRA Space Qualification laboratory is herein described. Mechanical fixtures’ design and validation, carried out by means of FEM, is also addressed due to its fundamental role in the vibrational test campaign. The Demise Observation Capsule (DOC) successfully passed the qualification test campaign. Functional test and resonance search have not been point any fault and damages of the capsule.

Keywords: capsule, demise, demise observation capsule, DOC, launch environment, re-ntry, qualification

Procedia PDF Downloads 138

Authors: Elif Esiyok

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Brand placement practices have become a popular advertising strategy, which is widely used in movies. Whether these brands are remembered by the audience after the film, or if they affect the purchasing preferences of the consumers has become one of the most important topics in the field of advertising. From this point, in this study, the "Devil Wears Prada" movie which includes high amount of brand placements is chosen. The movie watched to the undergraduate students in Turkey to measure the impact of brand placements on the attitudes of the consumers relating with a specific brand. In total 100 students were the subjects of this study. The participants were selected through using a simple random sampling method. The findings revealed that there is a significant difference between male and females in terms of brand recall. Female students were remembered the fashion brands more than the males, whereas males generally recalled the automotive brands and restaurant names.

Keywords: brand placement, brand recall, advertising, media

Procedia PDF Downloads 154

Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Revytia Tanera

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This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.

Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self

Procedia PDF Downloads 290

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: Rabia Göçmen, Gülşah Kanbur, Sinan Sefa Parlat

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In this study, in the breeding Japanese quails (coturnix coturnix japonica), it was aimed to study the effects of cellular insulin receptor stimulation on the performance, some blood parameters, and hatchability features. In the study, a total of 84 breeding quails were used, which are in 6 weeks age, and whose 24 are male and 60 female. In the trial, rations which contain 2900 kcal/kg metabolic energy; crude protein of 20%, and water whose pH is calibrated to 7.45 were administered as ad-libitum, to the animals, as metformin source, metformin-HCl was used and as chrome resource, Chromium Picolinate. Trial groups were formed as control group (basal ration), metformin group (basal ration, added metformin at the level of fodder of 20 mg/kg), and chromium picolinate group (basal ration, added fodder of 1500 ppb Cr. When regarded to the results of performance at the end of trial, it is seen that live weight gain, fodder consumption, egg weight, fodder evaluation coefficient, and egg production were affected at the significant level (p < 0.05). When the results are evaluated in terms of incubation features at the end of trial, it was identified that incubation yield and hatchability are not affected by the treatments but in the groups, in which metformin and chromium picolinate are added to ration, that fertility rose at the significant level compared to control group (p < 0,05). According to the results of blood parameters and hormone at the end of the trial, while the level of plasma glucose level was not affected by treatments (p > 0.05), with the addition of metformin and chromium picolinate to ration, plasma, total control, cholesterol, HDL, LDL, and triglyceride levels were significantly affected from insulin receptor stimulators added to ration (p<0,05). Hormone level of Plasma T3 and T4 were also affected at the significant level from insulin receptor stimulators added to ration (p < 0,05).

Keywords: cholesterol, chromium picolinate, hormone, metformin, performance, quail

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Authors: P. Jayashree, S. Rajkumar

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With the trend of virtual and augmented reality environments booming to provide a life like experience, gaming is a major tool in supporting such learning environments. In this work, a variant of Voronoi heuristics, employing supervised learning for the TRON game is proposed. The paper discusses the features that would be really useful when a machine learning bot is to be used as an opponent against a human player. Various game scenarios, nature of the bot and the experimental results are provided for the proposed variant to prove that the approach is better than those that are currently followed.

Keywords: artificial Intelligence, automation, machine learning, TRON game, Voronoi heuristics

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Authors: Paul W. Murray

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This research explores the relationship between leadership style and continuous improvement (CI) teams. CI teams have several features that are not always found in other types of teams, including multi-functional members, short time period for performance, positive and actionable results, and exposure to senior leadership. There is not only one best style of leadership for these teams. Instead, it is important to select the best leadership style for the situation. The leader must have the flexibility to change styles and the skill to use the chosen style effectively in order to ensure the team’s success.

Keywords: leadership style, lean manufacturing, teams, cross-functional

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Fikri, Rozmi Ismail, Fatimah Wati Halim, Sarah Waheeda

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The aim of this research is to investigate the influence of personality and driver behavior on road accident among bus driver who have the high risk behavior on road accident in Riau Province. The hypotheses proposed this research is there are has a significant influences of Treat of Personality and Driver Behavior among bus driver in Riau Province Indonesia. Subject participated in this research are 100 bus driver in Riau Province. This study using the purposive random sampling technique and quantitative design. The data is collected using the Big Five Personality questionnaires, Driver Behavior questionnaires and Road Accident Inventory. Research found that there are significant influence of personality and driver behavior on road accident among bus driver in Riau Province Indonesia.

Keywords: personality, driver behavior, driver stress, road accident

Procedia PDF Downloads 476

Authors: Mohammad A. Alolayan, John S. Evans, James K. Hammitt

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The value of statistical life has been estimated for a middle eastern country with high economical subsidization system. In this study, in-person interviews were conducted on a stratified random sample to estimate the value of mortality risk. Double-bounded dichotomous choice questions followed by open-ended question were used in the interview to investigate the willingness to pay of the respondent for mortality risk reduction. High willingness to pay was found to be associated with high income and education. Also, females were found to have lower willingness to pay than males. The estimated value of statistical life is larger than the ones estimated for western countries where taxation system exists. This estimate provides a baseline for monetizing the health benefits for proposed policy or program to the decision makers in an eastern country. Also, the value of statistical life for a country in the region can be extrapolated from this this estimate by using the benefit transfer method.

Keywords: mortality, risk, VSL, willingness-to-pay

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Taksina Bunbut, Kevin Wongleedee

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The purposes of this research were to study factors influencing the decision of international tourists to revisit Bangkok, Thailand. A random 200 samples was collected. Half the sample group was male and the other half was female. A questionnaire was used to collect data and small in-depth interviews were also used to get their opinions about importance of tourist decision making factors. The findings revealed that the majority of respondents rated these factors at medium level of importance. The ranking showed that the first three important factors were a safe place to stay, friendly people, and clean food. The three least important factors were a convenience transportation, clean country, and child friendly. In addition there was no significance difference between male and female in their ratings of the factors of influencing the decision of international tourists to revisit Bangkok, Thailand.

Keywords: factors, international tourists, revisit, Thailand

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Authors: Luminiţa Duţică, Gheorghe Duţică

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One of the most powerful language innovation in the twentieth century music was the heterophony–hypostasis of the vertical syntax entered into the sphere of interest of many composers, such as George Enescu, Pierre Boulez, Mauricio Kagel, György Ligeti and others. The heterophonic syntax has a history of its growth, which means a succession of different concepts and writing techniques. The trajectory of settling this phenomenon does not necessarily take into account the chronology: there are highly complex primary stages and advanced stages of returning to the simple forms of writing. In folklore, the plurimelodic simultaneities are free or random and originate from the (unintentional) differences/‘deviations’ from the state of unison, through a variety of ornaments, melismas, imitations, elongations and abbreviations, all in a flexible rhythmic and non-periodic/immeasurable framework, proper to the parlando-rubato rhythmics. Within the general framework of the multivocal organization, the heterophonic syntax in elaborate (academic) version has imposed itself relatively late compared with polyphony and homophony. Of course, the explanation is simple, if we consider the causal relationship between the sound vocabulary elements – in this case, the modalism – and the typologies of vertical organization appropriate for it. Therefore, adding up the ‘classic’ pathway of the writing typologies (monody – polyphony – homophony), heterophony - applied equally to the structures of modal, serial or synthesis vocabulary – reclaims necessarily an own macrotemporal form, in the sense of the analogies enshrined by the evolution of the musical styles and languages: polyphony→fugue, homophony→sonata. Concerned about the prospect of edifying a new musical ontology, the composer Ştefan Niculescu experienced – along with the mathematical organization of heterophony according to his own original methods – the possibility of extrapolation of this phenomenon in macrostructural plan, reaching this way to the unique form of ‘synchrony’. Founded on coincidentia oppositorum principle (involving the ‘one-multiple’ binom), the sound architecture imagined by Ştefan Niculescu consists in one (temporal) model / algorithm of articulation of two sound states: 1. monovocality state (principle of identity) and 2. multivocality state (principle of difference). In this context, the heterophony becomes an (auto)generative mechanism, with macrotemporal amplitude, strategy that will be grown by the composer, practically throughout his creation (see the works: Ison I, Ison II, Unisonos I, Unisonos II, Duplum, Triplum, Psalmus, Héterophonies pour Montreux (Homages to Enescu and Bartók etc.). For the present demonstration, we selected one of the most edifying works of Ştefan Niculescu – Simphony II, Opus dacicum – where the form of (heterophony-)synchrony acquires monumental-symphonic features, representing an emblematic case for the complexity level achieved by this type of vertical syntax in the twentieth century music.

Keywords: heterophony, modalism, serialism, synchrony, syntax

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Authors: A. B. M. Najmus Sakib

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Being one of the most densely populated cities in the world, Dhaka is facing diversified types of crimes every day. Limitations of resources insert serious strains among the inhabitants of this city. This paper aims to analyze the correlation between crime and class, more especially the violent crime in connection with social class. Following the stratified random sampling technique, one of the police divisions among eight of the Dhaka Metropolitan Police (DMP) will be selected. The data will be collected by evaluating the case files found in the police report. First, this paper discusses the nature and pattern of violent crimes in Dhaka city. Then, it assesses the socio-economic status of the accused persons considering their professions. Furthermore, by testing hypothesis, it will identify how the social classes are connected with violent crimes. Finally, the paper will ascertain the particular class that has an impact on violent crime in Dhaka City and will be ended by suggesting possible measures should take by the law enforcement agencies of Bangladesh.

Keywords: social class, violent crime, crime prevention, nature of crime

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Authors: Charu Sharma

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San Francisco Public Utilities Commission’s Headquarters was listed in the 2013-American Institute of Architects Committee of the Environment (AIA COTE) Top Ten Green Projects. This 13-story, 277,000-square-foot building, housing more than 900 of the agency’s employees was completed in June 2012. It was designed to achieve LEED Platinum Certification and boasts a plethora of green features to significantly reduce the use of energy and water consumption, and provide a healthy office work environment with high interior air quality and natural daylight. Key sustainability features include on-site clean energy generation through renewable photovoltaic and wind sources providing $118 million in energy cost savings over 75 years; 45 percent daylight harvesting; and the consumption of 55 percent less energy and a 32 percent less electricity demand from the main power grid. It uses 60 percent less water usage than an average 13-story office building as most of that water will be recycled for non-potable uses at the site, running through a system of underground tanks and artificial wetlands that cleans and clarifies whatever is flushed down toilets or washed down drains. This is one of the first buildings in the nation with treatment of gray and black water. The building utilizes an innovative structural system with post tensioned cores that will provide the highest asset preservation for the building. In addition, the building uses a “green” concrete mixture that releases less carbon gases. As a public utility commission this building has set a good example for resource conservation-the building is expected to be cheaper to operate and maintain as time goes on and will have saved rate-payers $500 million in energy and water savings. Within the anticipated 100-year lifespan of the building, our ratepayers will save approximately $3.7 billion through the combination of rental savings, energy efficiencies, and asset ownership.

Keywords: energy efficiency, sustainability, resource conservation, asset ownership, rental savings

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Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

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Authors: Jana Gutierez Chvalkovska, Michal Mejstrik, Matej Urban

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There are pending discussions over the mapping of country export potential in order to refocus export strategy of firms and its evidence-based promotion by the Export Credit Agencies (ECAs) and other permitted vehicles of governments. In this paper we develop our version of an applied model that offers “stepwise” elimination of unattractive markets. We modify and calibrate the model for the particular features of the Czech Republic and specific pilot cases where we apply an individual approach to each sector.

Keywords: export strategy, modeling export, calibration, export promotion

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Authors: Masoumeh Khosravi

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Introduction: The complementary therapies and Qigong exercises is important in order to maintain physical and mental health. Objective: This study was done to compare and investigate well-being and mental health's state between practitioners of a Qigong practice (Falun Dafa) and non-practitioners. Method: It was a comparative study with 60 samples (30 practitioners of Falun Dafa, and 30 non-practitioners), who were selected by random sampling from Tehran city of Iran. Data were collected by mental health inventory (SCL90) and well-being questionnaire. Multivariate variance analyzing and t-test were used for analyzing data. Results: Results showed significant differences in most components of mental health including anxiety, aggressiveness, obsessive-compulsion, interpersonal sensitivity, somatization disorder, depression, phobia between practitioners and non-practitioners. Well-being was significantly higher in practitioners than non-practitioners. Conclusion: Accordingly, we concluded Falun Gong exercises have high impact on mental health and well-being in people.

Keywords: mental health, well-being, Qigong, Falun Dafa

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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Authors: Avik Banerjee, Kavita Saggar

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Infections of the nervous system and adjacent structures are often life-threatening conditions. Despite the recent advances in neuroimaging evaluation, the diagnosis of unclear infectious CNS disease remains a challenge. Our aim is to evaluate the typical and atypical neuro-imaging features of the various routinely encountered CNS infected patients so as to form guidelines for their imaging recognition and differentiation from tumoral, vascular and other entities that warrant a different line of therapy.

Keywords: central nervous system (CNS), Cerebro Spinal Fluid (Csf), Creutzfeldt Jakob Disease (CJD), progressive multifocal leukoencephalopathy (PML)

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Dimitris Varsamis, Christos Talagkozis, Alkiviadis Tsimpiris, Paris Mastorocostas

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The aim of this work is the parallel implementation of k-means in MATLAB, in order to reduce the execution time. Specifically, a new function in MATLAB for serial k-means algorithm is developed, which meets all the requirements for the conversion to a function in MATLAB with parallel computations. Additionally, two different variants for the definition of initial values are presented. In the sequel, the parallel approach is presented. Finally, the performance tests for the computation times respect to the numbers of features and classes are illustrated.

Keywords: K-means algorithm, clustering, parallel computations, Matlab

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Authors: Surinder Sood, Debajyoti Mukherjee

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Formal verification techniques have become widely popular in pre-silicon verification as an alternate to constrain random simulation based techniques. This paper proposed a novel formal verification-based coverage augmentation technique in verifying complex RTL functional verification faster. The proposed approach relies on augmenting coverage analysis coming from simulation and formal verification. Besides this, the functional qualification framework not only helps in improving the coverage at a faster pace but also aids in maturing and qualifying the formal verification infrastructure. The proposed technique has helped to achieve faster verification sign-off, resulting in faster time-to-market. The design picked had a complex control and data path and had many configurable options to meet multiple specification needs. The flow is generic, and tool independent, thereby leveraging across the projects and design will be much easier

Keywords: COI (cone of influence), coverage, formal verification, fault injection

Procedia PDF Downloads 110

Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

Abstract:

Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

Procedia PDF Downloads 170

Authors: Sinan Bilgen, Bekir Ozer Ay, Nilay Sezer Uzol

Abstract:

After decades of conventional shapes, irregular forms with complex geometries are getting more popular for form generation of tall buildings all over the world. This trend has recently brought out diverse building forms such as twisting tall buildings. This study investigates both the aerodynamic and design features of twisting tall buildings through comparative analyses. Since twisting a tall building give rise to additional complexities related with the form and structural system, lateral load effects become of greater importance on these buildings. The aim of this study is to analyze the inherent characteristics of these iconic forms by comparing the wind loads on twisting tall buildings with those on their prismatic twins. Through a case study research, aerodynamic analyses of an existing twisting tall building and its prismatic counterpart were performed and the results have been compared. The prismatic twin of the original building were generated by removing the progressive rotation of its floors with the same plan area and story height. Performance-based measures under investigation have been evaluated in conjunction with the architectural design. Aerodynamic effects have been analyzed by both wind tunnel tests and computational methods. High frequency base balance tests and pressure measurements on 3D models were performed to evaluate wind load effects on a global and local scale. Comparisons of flat and real surface models were conducted to further evaluate the effects of the twisting form without façade texture contribution. Comparisons highlighted that, the twisting form under investigation shows better aerodynamic behavior both for along wind but particularly for across wind direction. Compared to the prismatic counterpart; twisting model is superior on reducing vortex-shedding dynamic response by disorganizing the wind vortices. Consequently, despite the difficulties arisen from inherent complexity of twisted forms, they could still be feasible and viable with their attractive images in the realm of tall buildings.

Keywords: aerodynamic tests, motivation for twisting, tall buildings, twisted forms, wind excitation

Procedia PDF Downloads 229

Authors: Mohamed Barbary, Mohamed H. Abd El-azeem

Abstract:

Maneuvering non-ellipsoidal extended object tracking (M-NEOT) using high-resolution inverse synthetic aperture radar (ISAR) observations is gaining momentum recently. This work presents a new robust implementation of the Jump Markov (JM) multi-Bernoulli (MB) filter for M-NEOT, where the M-NEOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on an MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, JM-MB-TBD filter

Procedia PDF Downloads 48

Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

Abstract:

The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

Procedia PDF Downloads 82