Search results for: feature generation

Authors: Rashmi Malik, Videep Mishra

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The practice of generative design has become a transformative approach for an efficient way of generating multiple iterations for any design project. The conventional way of modeling the game elements is very time-consuming and requires skilled artists to design. A 3D modeling tool like 3D S Max, Blender, etc., is used traditionally to create the game library, which will take its stipulated time to model. The study is focused on using the generative design tool to increase the efficiency in game development at the stage of prop and environment generation. This will involve procedural level and customized regulated or randomized assets generation. The paper will present the system design approach using generative tools like Grasshopper (visual scripting) and other scripting tools to automate the process of game library modeling. The script will enable the generation of multiple products from the single script, thus creating a system that lets designers /artists customize props and environments. The main goal is to measure the efficacy of the automated system generated to create a wide variety of game elements, further reducing the need for manual content creation and integrating it into the workflow of AAA and Indie Games.

Keywords: iterative game design, generative design, gaming asset automation, generative game design

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

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The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA

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Authors: Marwan Jarrah

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This research paper provides two pieces of phonological and syntactic evidence from Arabic for biolinguistics perspective of language processing. The first piece of evidence concerns the instances where a singular noun is converted to a plural noun in Arabic. Based on the findings of several research papers, this study shows that a singular word does not lose any of its moras when it is pluralized either regularly or irregularly. This mora conservation principle complies with the general physical law of the conservation of mass which states that mass is neither created nor destroyed but changed from one form into another. The second piece of evidence concerns the observation that when the object in some Arabic dialects including Jordanian Arabic and Najdi Arabic is a topic and positioned in situ (i.e. after the verb), the verb agrees with it, something that generates an agreeing inflection marker of the verb that agrees in Number, Person, and Gender with the in-situ topicalized object. This interaction between the verb and the object in such cases is invoked because of the extra feature the object bears, i.e. TOPIC feature. We suggest that such an interaction complies with the general natural law that elements become active when they, e.g., get an additional electron, when the mass number is not equal to the atomic number.

Keywords: biolinguistics, Arabic, physics, interaction

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Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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Authors: Berker Bayazit, Gulgun Kayakutlu

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The World Energy Outlook shows that energy markets will substantially change within a few forthcoming decades. First, determined action plans according to COP21 and aim of CO₂ emission reduction have already impact on policies of countries. Secondly, swiftly changed technological developments in the field of renewable energy will be influential upon medium and long-term energy generation and consumption behaviors of countries. Furthermore, share of electricity on global energy consumption is to be expected as high as 40 percent in 2040. Electrical vehicles, heat pumps, new electronical devices and digital improvements will be outstanding technologies and innovations will be the testimony of the market modifications. In order to meet highly increasing electricity demand caused by technologies, countries have to make new investments in the field of electricity production, transmission and distribution. Specifically, electricity generation mix becomes vital for both prevention of CO₂ emission and reduction of power prices. Majority of the research and development investments are made in the field of electricity generation. Hence, the prime source diversity and source planning of electricity generation are crucial for improving the wealth of citizen life. Approaches considering the CO₂ emission and total cost of generation, are necessary but not sufficient to evaluate and construct the product mix. On the other hand, employment and positive contribution to macroeconomic values are important factors that have to be taken into consideration. This study aims to constitute new investments in renewable energies (solar, wind, geothermal, biogas and hydropower) between 2018-2023 under 4 different goals. Therefore, a multi-objective programming model is proposed to optimize the goals of minimizing the CO₂ emission, investment amount and electricity sales price while maximizing the total employment and positive contribution to current deficit. In order to avoid the user preference among the goals, Dinkelbach’s algorithm and Guzel’s approach have been combined. The achievements are discussed with comparison to the current policies. Our study shows that new policies like huge capacity allotment might be discussible although obligation for local production is positive. The improvements in grid infrastructure and re-design support for the biogas and geothermal can be recommended.

Keywords: energy generation policies, multi-objective linear programming, portfolio planning, renewable energy

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Authors: Tarandeep Kaur

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Generation Y and Z nursing students have a much higher need for technology-based stimulation than previous generations, as they may find traditional methods of education boring and disinterested. These generations prefer experiential learning and the use of advanced technology for enhanced learning. Therefore, nursing educators must acquire knowledge to make better use of technology and technological tools for instruction. Millennials and generation are digital natives, optimistic, assertive, want engagement, instant feedback, and collaborative approach. The integration of technology and the efficacy of its use can be challenging for nursing educators. The SAMR (substitution, augmentation, modification, and redefinition) model designed and developed by Dr. Ruben Puentedura can help nursing educators to engage their students in different levels of technology integration for effective learning. Nursing educators should understand that technology use in the classroom must be purposeful. The influx of technology in nursing education is ever-changing; therefore, nursing educators have to constantly enhance and develop technical skills to keep up with the emerging technology in the schools as well as hospitals. In the Saskatchewan Collaborative Bachelor of Nursing (SCBSCN) program at Saskatchewan polytechnic, we use technology at various levels using the SAMR model in our program, including low and high-fidelity simulation labs. We are also exploring futuristic options of using virtual reality and gaming in our classrooms as an innovative way to motivate, increase critical thinking, create active learning, provide immediate feedback, improve student retention and create collaboration.

Keywords: generations, nursing, SAMR, technology

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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Authors: Anthony R. Hassan, Jacob A. Gbadeyan

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In this paper, the analysis of a reactive hydromagnetic Poiseuille fluid flow under each of sensitized, Arrhenius and bimolecular chemical kinetics through a channel in the presence of heat source is carried out. An exothermic reaction is assumed while the concentration of the material is neglected. Adomian Decomposition Method (ADM) together with Pade Approximation is used to obtain the solutions of the governing nonlinear non – dimensional differential equations. Effects of various physical parameters on the velocity and temperature fields of the fluid flow are investigated. The entropy generation analysis and the conditions for thermal criticality are also presented.

Keywords: chemical kinetics, entropy generation, thermal criticality, adomian decomposition method (ADM) and pade approximation

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Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat

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Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Raj Kumar Rajak, Bharat Mishra

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Bio-batteries represent an entirely new long-term, reasonable, reachable, and eco-friendly approach to generation of sustainable energy. In the present experimental work, we have studied the effect of the generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow’s urine as an electrolyte. C-Mg electrode pair shows maximum Voltage and Short Circuit Current (SCC), while C-Zn electrode pair shows less Open Circuit Voltage (OCV) and SCC. By the studies of cow urine and different electrodes, it is found that C-Zn electrode battery is more economical. The cow urine battery with C-Zn electrode provides maximum power (707.4 mW) and durability (up to 145 h). This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: bio-batteries, cow's urine, electrodes, non-conventional

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Authors: Ruchi Agarwal

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The Indian diaspora in Thailand is as ethnically diverse as any other country. Although a relatively small community, the Indian diaspora has long established its roots, some with their fifth generation now living in Thailand. The community has a solid social and economic standing recognized by the host country but lacks connections with its ethnic roots in the home country. The biggest dilemma faced by the younger generation of the Indian diasporic community is the identity crisis. Regardless of being born and brought up in Thailand and possessing Thai citizenship, they do not get recognition as Thais by their Thai counterparts. However, with the Act Asia Policy of the Indian government, there has been an increase in social and political activities organized by old and new Indian associations, bringing new hopes of recognizing the Thai-Indian diasporic community.

Keywords: Indian, Thailand, diaspora, Act East Policy, Thai

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Authors: Xiong Xie, Yuhang Chen

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Vulnerability discovery technology is a significant field of the current. In this paper, a fuzzy framework based on concolic execution has been proposed. Fuzzy test and symbolic execution are widely used in the field of vulnerability discovery technology. But each of them has its own advantages and disadvantages. During the path generation stage, path traversal algorithm based on generation is used to get more accurate path. During the constraint solving stage, dynamic concolic execution is used to avoid the path explosion. If there is external call, the concolic based on function summary is used. Experiments show that the framework can effectively improve the ability of triggering vulnerabilities and code coverage.

Keywords: concolic execution, constraint solving, fuzzy test, vulnerability discovery

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Authors: Md. Danish Eqbal, Venkat Gundabala

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Microparticles and microcapsules are basically used as a carrier for cells, tissues, drugs, and chemicals. Due to its biocompatibility, non-toxicity and biodegradability, alginate based microparticles have numerous applications in drug delivery, tissue engineering, organ repair and transplantation, etc. The production of uniform monodispersed microparticles was a challenge for the past few decades. However, emergence of microfluidics has provided controlled methods for the generation of the uniform monodispersed microparticles. In this work, we present a successful method for the generation of both microparticles and microcapsules (single and double core) using merging approach of two droplets, completely inside the microfluidic device. We have fabricated hybrid glass- PDMS (polydimethylsiloxane) based microfluidic device which has coflow geometry as well as the T junction channel. Coflow is used to generate the single as well as double oil-alginate emulsion in oil and T junction helps to form the calcium chloride droplets in oil. The basic idea is to match the frequency of the alginate droplets and calcium chloride droplets perfectly for controlled generation. Using the merging of droplets technique, we have successfully generated the microparticles and the microcapsules having single core as well as double and multiple cores. The cores in the microcapsules are very stable, well separated from each other and very intact as seen through cross-sectional confocal images. The size and the number of the cores along with the thickness of the shell can be easily controlled by controlling the flowrate of the liquids.

Keywords: double-core, droplets, microcapsules, microparticles

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

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Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

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Authors: Saeid Jalilzadeh, Majid Pakdel

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The customer demand for better power quality and higher reliability has forced the power industry to use distributed generations (DGs) such as wind power and photo voltaic arrays. Islanding is a phenomenon occurs when a power grid becomes electrically isolated from the power system and the distribution system is energized by distributed generators. It is necessary to disconnect all distributed generators immediately after islanding occurrence. Therefore a DG system should have the capability to detect islanding phenomena. In this paper, a novel micro controller based relay for anti-islanding protection of a typical DG system is proposed. The simulation results using Proteus software verify the proper operation and effectiveness of the proposed protective relay.

Keywords: islanding, distributed generation (DG), protective relay, micro controller, proteus software

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Vaishali Joshi, Pallav Joshi

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The main objective of this study is to examine the fashion consumption behavior of females with respect to their age group. Differences were studied in the pre-purchase, purchase and post-purchase behavior of females belonging to three age cohorts such as Generation X, Generation Y, and Generation Z. Quantitative approach was used to conduct this research. Data was collected through structured questionnaire. The questionnaire consisted of three sections. Section one included a question of the source of information of purchasing fashion apparels which measure the pre-purchase behavior. Section two measures purchase behavior which included two questions: i. motivations for purchasing fashion apparel and ii. important attributes considered for purchasing fashion apparel. The last section included a question regarding disposal of fashion apparel which measures the post-purchase behavior. Hundred females were selected as the respondents for this study through convenience sampling in the fashion streets. They were categorized into three age groups and then the results were analyzed. Four hypotheses were developed after reviewing the existing literature. Regression analysis was conducted for testing the hypothesis. Hypothesis one was accepted which stated that ‘social influence’ as a source of information for purchasing fashion apparels decreases with age. Hypothesis two was accepted which suggested that motivation of ‘Attention seeking’ for purchasing fashion apparel decreases with age. Hypothesis three and four also accepted which suggested that the importance of ‘Quality’ and ‘Price’ increases with age but hypothesis five was rejected which suggested that the importance of ‘Fit’ increases with age and last but not the least hypothesis six was accepted which suggested that the ‘duration’ of using fashion apparel increases with age. Limitation of the study deals with the sample of only female respondents. Implication can be made from this research in the field of Fashion apparel industry with respect to consumer segmentation and better marketing approaches can be implemented by the marketers form this study. Further research can be concluded by including male respondents also.

Keywords: fashion, consumption behavior, age cohorts, motivation

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Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Jiechen Yin, Xiang Hong, Ran Liu

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Atrazine (ATR), a widely used triazine herbicide, is an environmental endocrine disruptor that can cause health problems. However, whether there are multi/trans-generational reproductive impacts of ATR have not been studied to our best knowledge. Therefore, in this study, Caenorhabditis elegans was used as a preferable model organism to identify the multi/trans-generational reproductive toxicity of ATR. L1 larvae were exposed to different concentrations (0.0004–40 mg/L) of ATR for 48 h. Successive generations (F1 to F5) were fed without ATR and consecutive exposure. The results showed that ATR exposure during P0 decreased fecundity, including a reduction in fertilized eggs, oocytes, and ovulation rate, delayed gonadal development, and decreased the relative area of the gonad arm and germ cell number. Furthermore, continuous ATR exposure (P0–F5) causes a significant increase in reproductive toxicity in subsequent generations, although no significant toxicity occurred in the P0 generation after exposure to environmental-related concentrations, suggesting that ATR exposure might have cumulative effects. Likewise, parental exposure to ATR caused transgenerational toxicity impairments. Interestingly, reproductive toxicity not development toxicity was transmitted to several generations (F1–F4), and the F2 generation showed the most notable changes. QRT-PCR results showed that genes related to DNA methylation 6mA (damt-1, nmad-1) and histone H3 methylation (mes-4, met-2, set-25, set-2, and utx-1) can also be passed on to offspring. The function of H3K4 and H3K9 methylation were explored by using loss-of-function mutants for set-2, set-25, and met-2. Transmissible reproductive toxicity was absent in met-2(n4256), set-2(ok952), and set-25(n5021) mutants, which suggests that the histone methyltransferases H3K4 and H3K9 activity are indispensable for the transgenerational effect of ATR. Finally, the downstream genes of DNA methylation and histone H3 methylation were determined. ATR upregulated the expression of ZC317.7, hsp-6, and hsp-60. Mitochondrial stress in parental generation dependent transcription 6mA modifiers may establish these epigenetic marks in progeny.

Keywords: ATR, Caenorhabditis elegans, multi-/trans-generation, reproductive toxicity

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Authors: Ojiegbe Ikenna Nathan

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Obesity is a medical condition in which excess body fat has accumulated to the extent that it leads to reduced life expectancy and or increased health problems. Obesity as a worldwide problem is seen clustered in the families and it moves from generation to generation. It causes some disabilities, mortality and morbidity if left unattended to. The predisposing factors to obesity are either genetic or environment in origin. Nevertheless, the main predisposing factor to obesity is the excessive consumption of food rich in low-density lipoprotein (LDL) such as organ meats, saturated fats etc. This low-density lipoprotein causes an increase in adipose tissue and complicates to obesity. There are varieties of obesity which one needs to take appropriate measures to avoid; such as android, gynoid and morbid obesity. Nonetheless, studies have shown that there is hope for the obese individuals, despite the cause, type and degree of their obesity. This is through the use of the different available treatment measures which increase in physical activities, caloric restrictions, drug therapy and surgical intervention.

Keywords: low-density, lipoprotein, culprit, obesity

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Authors: A. I. Dovgjallo, A. B. Tsapkova, A. A. Shimanov

Abstract:

The paper is devoted to one of engine types with external heating – a thermoacoustic engine. In thermoacoustic engine heat energy is converted to an acoustic energy. Further, acoustic energy of oscillating gas flow must be converted to mechanical energy and this energy in turn must be converted to electric energy. The most widely used way of transforming acoustic energy to electric one is application of linear generator or usual generator with crank mechanism. In both cases, the piston is used. Main disadvantages of piston use are friction losses, lubrication problems and working fluid pollution which cause decrease of engine power and ecological efficiency. Using of a bidirectional impulse turbine as an energy converter is suggested. The distinctive feature of this kind of turbine is that the shock wave of oscillating gas flow passing through the turbine is reflected and passes through the turbine again in the opposite direction. The direction of turbine rotation does not change in the process. Different types of bidirectional impulse turbines for thermoacoustic engines are analyzed. The Wells turbine is the simplest and least efficient of them. A radial impulse turbine has more complicated design and is more efficient than the Wells turbine. The most appropriate type of impulse turbine was chosen. This type is an axial impulse turbine, which has a simpler design than that of a radial turbine and similar efficiency. The peculiarities of the method of an impulse turbine calculating are discussed. They include changes in gas pressure and velocity as functions of time during the generation of gas oscillating flow shock waves in a thermoacoustic system. In thermoacoustic system pressure constantly changes by a certain law due to acoustic waves generation. Peak values of pressure are amplitude which determines acoustic power. Gas, flowing in thermoacoustic system, periodically changes its direction and its mean velocity is equal to zero but its peak values can be used for bi-directional turbine rotation. In contrast with feed turbine, described turbine operates on un-steady oscillating flows with direction changes which significantly influence the algorithm of its calculation. Calculated power output is 150 W with frequency 12000 r/min and pressure amplitude 1,7 kPa. Then, 3-d modeling and numerical research of impulse turbine was carried out. As a result of numerical modeling, main parameters of the working fluid in turbine were received. On the base of theoretical and numerical data model of impulse turbine was made on 3D printer. Experimental unit was designed for numerical modeling results verification. Acoustic speaker was used as acoustic wave generator. Analysis if the acquired data shows that use of the bi-directional impulse turbine is advisable. By its characteristics as a converter, it is comparable with linear electric generators. But its lifetime cycle will be higher and engine itself will be smaller due to turbine rotation motion.

Keywords: acoustic power, bi-directional pulse turbine, linear alternator, thermoacoustic generator

Procedia PDF Downloads 378

Authors: Ira Joseph

Abstract:

The LNG paradox addresses the issue of how the most expensive form of gas supply, which is LNG, will grow in an end user market where demand is most competitive, which is power generation. In this case, LNG demand growth is under siege from two entirely different directions. At one end is price; it will be extremely difficult for gas to replace coal in Asia due to the low price of coal and the age of the generation plants. Asia's coal fleet, on average, is less than two decades old and will need significant financial incentives to retire before its state lifespan. While gas would cut emissions in half relative to coal, it would also more than double the price of the fuel source for power generation, which puts it in a precarious position. In most countries in Asia other than China, this cost increase, particularly from imports, is simply not realistic when it is also necessary to focus on economic growth and social welfare. On the other end, renewables are growing at an exponential rate for three reasons. One is that prices are dropping. Two is that policy incentives are driving deployment, and three is that China is forcing renewables infrastructure into the market to take a political seat at the global energy table with Saudi Arabia, the US, and Russia. Plus, more renewables will lower import growth of oil and gas in China, if not end it altogether. Renewables are the predator at the gate of gas demand in power generation and in every year that passes, renewables cut into demand growth projections for gas; in particular, the type of gas that is most expensive, which is LNG. Gas does have a role in the future, particularly within a domestic market. Once it crosses borders in the form of LNG or even pipeline gas, it quickly becomes a premium fuel and must be marketed and used this way. Our research shows that gas will be able to compete with batteries as an intermittency and storage tool and does offer a method to harmonize with renewables as part of the energy transition. As a baseload fuel, however, the role of gas, particularly, will be limited by cost once it needs to cross a border. Gas converted into blue or green hydrogen or ammonia is also an option for storage depending on the location. While this role is much reduced from the primary baseload role that gas once aspired to land, it still offers a credible option for decades to come.

Keywords: natural gas, LNG, demand, price, intermittency, storage, renewables

Procedia PDF Downloads 61

Authors: N. K. Mohd Affendi, T. A. R. Tuan Abdullah, S. A. Syed Mustaffa

Abstract:

In power industry transformer is an important component and most of us familiar by the functioning principle of a transformer electrically. There are many losses occur during the operation of a transformer that causes heat generation. This heat, if not dissipated properly will reduce the lifetime and effectiveness of the transformer. Transformer cooling helps in maintaining the temperature rise of various paths. This paper proposed to minimize the ambient temperature of the transformer room in order to lower down the temperature of the transformer. A simulation has been made using finite element methods programs called FEMM (Finite Elements Method Magnetics) to create a virtual model based on actual measurement of a transformer. The generalization of the two-dimensional (2D) FEMM results proves that by minimizing the ambient temperature, the heat of the transformer is decreased. The modeling process and of the transformer heat flow has been presented.

Keywords: heat generation, temperature rise, ambient temperature, FEMM

Procedia PDF Downloads 400

Authors: A. Mathieu, B. Aubry, E. Chhim, M. Jobe, M. Arnaud

Abstract:

Present project consists in a study and a development of piezoelectric devices for supplying power to new generation pacemakers. They are miniaturized leadless implants without battery placed directly in right ventricle. Amongst different acceptable energy sources in cardiac environment, we choose the solution of a device based on conversion of the energy produced by pressure variation inside the heart into electrical energy. The proposed energy harvesters can meet the power requirements of pacemakers, and can be a good solution to solve the problem of regular surgical operation. With further development, proposed device should provide enough energy to allow pacemakers autonomy, and could be good candidate for next pacemaker generation.

Keywords: energy harvester, heart, leadless pacemaker, piezoelectric cells, pressure variation

Procedia PDF Downloads 445

Authors: Rajat Raj, Rohini S. Hallikar

Abstract:

The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in this paper, i.e., GRID connected, the transition between Grid-connected and Islanded State, and changing the irradiance of PVs and doing the transitioning. The simulation results show total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes, respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability and ensuring a seamless transition between grid-connected and islanded modes.

Keywords: islanded modes, microgrids, photo voltaic, total harmonic distortion

Procedia PDF Downloads 170