Search results for: Attention Multiple Instance Learning

Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: Sound Detection, Impulsive Signal, Background Noise, Neural Network.

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Authors: Manat Srivanit, Hokao Kazunori

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Facing the concern of the population to its environment and to climatic change, city planners are now considering the urban climate in their choices of planning. The urban climate, representing different urban morphologies across central Bangkok metropolitan area (BMA), are used to investigates the effects of both the composition and configuration of variables of urban morphology indicators on the summer diurnal range of urban climate, using correlation analyses and multiple linear regressions. Results show first indicate that approximately 92.6% of the variation in the average maximum daytime near-surface air temperature (Ta) was explained jointly by the two composition variables of urban morphology indicators including open space ratio (OSR) and floor area ratio (FAR). It has been possible to determine the membership of sample areas to the local climate zones (LCZs) using these urban morphology descriptors automatically computed with GIS and remote sensed data. Finally result found the temperature differences among zones of large separation, such as the city center could be respectively from 35.48±1.04ºC (Mean±S.D.) warmer than the outskirt of Bangkok on average for maximum daytime near surface temperature to 28.27±0.21ºC for extreme event and, can exceed as 8ºC. A spatially disaggregation of urban thermal responsiveness map would be helpful for several reasons. First, it would localize urban areas concerned by different climate behavior over summer daytime and be a good indicator of urban climate variability. Second, when overlaid with a land cover map, this map may contribute to identify possible urban management strategies to reduce heat wave effects in BMA.

Keywords: Urban climate, Urban morphology, Local climate zone, Urban planning, GIS and remote sensing

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Authors: Toby Gibbs, Glen Craigie, Suwaree Yordchim

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The Speexx results revealed four main factors affecting the success of 190 Thai sophomores as follows: 1) Future English training should be pursued in applied Speexx development. 2) Thai students didn’t see the benefit of having an Online Language Training Program. 3) There is a great need to educate the next generation of learners on the benefits of Speexx within the community. 4) A great majority of Thai Sophomores didn't know what Speexx was. A guideline for self-reliance planning consisted of four aspects: 1) Development planning: by arranging groups to further improve English abilities with the Speexx Language Training program and encourage using Speexx into every day practice. Local communities need to develop awareness of the usefulness of Speexx and share the value of using the program among family and friends. 2) Humanities and Social Science staff should develop skills using this Online Language Training Program to expand on the benefits of Speexx within their departments. 3) Further research should be pursued on the Thai Students progression with Speexx and how it helps them improve their language skills with Business English. 4) University’s and Language centers should focus on using Speexx to encourage learning for any language, not just English.

Keywords: Ability, Comprehension, Sophomore, Speexx.

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Authors: M. Ardelean, F. Manea, A. Pop, J. Schoonman

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The presence of pharmaceuticals in the environment and especially in water has gained increasing attention. They are included in emerging class of pollutants, and for most of them, legal limits have not been set-up due to their impact on human health and ecosystem was not determined and/or there is not the advanced analytical method for their quantification. In this context, the development of various advanced analytical methods for the quantification of pharmaceuticals in water is required. The electrochemical methods are known to exhibit the great potential for high-performance analytical methods but their performance is in direct relation to the electrode material and the operating techniques. In this study, two types of carbon-based electrodes materials, i.e., boron-doped diamond (BDD) and carbon nanofiber (CNF)-epoxy composite electrodes have been investigated through voltammetric techniques for the detection of naproxen in water. The comparative electrochemical behavior of naproxen (NPX) on both BDD and CNF electrodes was studied by cyclic voltammetry, and the well-defined peak corresponding to NPX oxidation was found for each electrode. NPX oxidation occurred on BDD electrode at the potential value of about +1.4 V/SCE (saturated calomel electrode) and at about +1.2 V/SCE for CNF electrode. The sensitivities for NPX detection were similar for both carbon-based electrode and thus, CNF electrode exhibited superiority in relation to the detection potential. Differential-pulsed voltammetry (DPV) and square-wave voltammetry (SWV) techniques were exploited to improve the electroanalytical performance for the NPX detection, and the best results related to the sensitivity of 9.959 µA·µM^-1 were achieved using DPV. In addition, the simultaneous detection of NPX and fluoxetine -a very common antidepressive drug, also present in water, was studied using CNF electrode and very good results were obtained. The detection potential values that allowed a good separation of the detection signals together with the good sensitivities were appropriate for the simultaneous detection of both tested pharmaceuticals. These results reclaim CNF electrode as a valuable tool for the individual/simultaneous detection of pharmaceuticals in water.

Keywords: Boron-doped diamond electrode, carbon nanofiber-epoxy composite electrode, emerging pollutants, pharmaceuticals.

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, Speech Emotion Recognition, longitudinal biomarker, machine learning.

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: Assembly, assistive technologies, augmented reality, manufacturing, visualization.

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Authors: Mohammad Ebrahim Kianifar, Ehsan Ahmadi

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Reinforced concrete structures experience local defects such as cracks over their lifetime under various environmental loadings. Consequently, they are repaired by mortars to avoid detrimental effects such as corrosion of reinforcement, which in long-term may lead to strength loss of a member or collapse of structures. However, repaired structures may need multiple repairs due to changes in load distribution, and thus, lack of compatibility between mortar and substrate concrete. On the other hand, waste tire rubber alkali-activated (WTRAA)-based materials have very high potential to be used as repair mortars because of their ductility and flexibility, which may delay failure of repair mortar, and thus, provide sufficient compatibility. Hence, this work presents a study on suitability of WTRAA-based materials as mortars for repair of concrete structures through an experimental program. To this end, WTRAA mortars with 15% aggregate replacement, alkali-activated (AA) mortars, and ordinary mortars are made to repair a number of concrete beams. The WTRAA mortars are composed of slag as base material, sodium hydroxide as alkaline activator, and different gradation of waste tire rubber (fine and coarse gradations). Flexural tests are conducted on the concrete beams repaired by the ordinary, AA, and WTRAA mortars. It is found that, despite having lower compressive strength and modulus of elasticity, the WTRAA and AA mortars increase flexural strength of the repaired beams, give compatible failures, and provide sufficient mortar-concrete interface bondings. The ordinary mortars, however, show incompatible failure modes. This study demonstrates promising application of WTRAA mortars in practical repairs of concrete structures.

Keywords: Alkali-activated mortars, concrete repair, mortar compatibility flexural strength, waste tire rubber.

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Authors: Y. Z. Wu, Z. Dong, S. K. You

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Global approximation using metamodel for complex mathematical function or computer model over a large variable domain is often needed in sensibility analysis, computer simulation, optimal control, and global design optimization of complex, multiphysics systems. To overcome the limitations of the existing response surface (RS), surrogate or metamodel modeling methods for complex models over large variable domain, a new adaptive and regressive RS modeling method using quadratic functions and local area model improvement schemes is introduced. The method applies an iterative and Latin hypercube sampling based RS update process, divides the entire domain of design variables into multiple cells, identifies rougher cells with large modeling error, and further divides these cells along the roughest dimension direction. A small number of additional sampling points from the original, expensive model are added over the small and isolated rough cells to improve the RS model locally until the model accuracy criteria are satisfied. The method then combines local RS cells to regenerate the global RS model with satisfactory accuracy. An effective RS cells sorting algorithm is also introduced to improve the efficiency of model evaluation. Benchmark tests are presented and use of the new metamodeling method to replace complex hybrid electrical vehicle powertrain performance model in vehicle design optimization and optimal control are discussed.

Keywords: Global approximation, polynomial response surface, domain decomposition, domain combination, multiphysics modeling, hybrid powertrain optimization

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Authors: Farzaneh Tahmoorian, Bijan Samali, John Yeaman

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Road networks are increasingly expanding all over the world. The construction and maintenance of the road pavements require large amounts of aggregates. Considerable usage of various natural aggregates for constructing roads as well as the increasing rate at which solid waste is generated have attracted the attention of many researchers in the pavement industry to investigate the feasibility of the application of some of the waste materials as alternative materials in pavement construction. Among various waste materials, construction and demolition wastes, including Recycled Construction Aggregate (RCA) constitute a major part of the municipal solid wastes in Australia. Creating opportunities for the application of RCA in civil and geotechnical engineering applications is an efficient way to increase the market value of RCA. However, in spite of such promising potentials, insufficient and inconclusive data and information on the engineering properties of RCA had limited the reliability and design specifications of RCA to date. In light of this, this paper, as a first step of a comprehensive research, aims to investigate the feasibility of the application of RCA obtained from construction and demolition wastes for the replacement of part of coarse aggregates in asphalt mixture. As the suitability of aggregates for using in asphalt mixtures is determined based on the aggregate characteristics, including physical and mechanical properties of the aggregates, an experimental program is set up to evaluate the physical and mechanical properties of RCA. This laboratory investigation included the measurement of compressive strength and workability of RCA, particle shape, water absorption, flakiness index, crushing value, deleterious materials and weak particles, wet/dry strength variation, and particle density. In addition, the comparison of RCA properties with virgin aggregates has been included as part of this investigation and this paper presents the results of these investigations on RCA, basalt, and the mix of RCA/basalt.

Keywords: Asphalt, basalt, pavement, recycled aggregate.

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Authors: A. Nour Eddine, D. Chalet, L. Aixala, P. Chessé, X. Faure, N. Hatat

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Thermal power technology such as the TEG (Thermo-Electric Generator) arouses significant attention worldwide for waste heat recovery. Despite the potential benefits of marine application due to the permanent heat sink from sea water, no significant studies on this application were to be found. In this study, a test rig has been designed and built to test the performance of the TEG on engine operating points. The TEG device is built from commercially available materials for the sake of possible economical application. Two types of commercial TEM (thermo electric module) have been studied separately on the test rig. The engine data were extracted from a commercial Diesel engine since it shares the same principle in terms of engine efficiency and exhaust with the marine Diesel engine. An open circuit water cooling system is used to replicate the sea water cold source. The characterization tests showed that the silicium-germanium alloys TEM proved a remarkable reliability on all engine operating points, with no significant deterioration of performance even under sever variation in the hot source conditions. The performance of the bismuth-telluride alloys was 100% better than the first type of TEM but it showed a deterioration in power generation when the air temperature exceeds 300 °C. The temperature distribution on the heat exchange surfaces revealed no useful combination of these two types of TEM with this tube length, since the surface temperature difference between both ends is no more than 10 °C. This study exposed the perspective of use of TEG technology for marine engine exhaust heat recovery. Although the results suggested non-sufficient power generation from the low cost commercial TEM used, it provides valuable information about TEG device optimization, including the design of heat exchanger and the types of thermo-electric materials.

Keywords: Internal combustion engine application, Seebeck, thermo-electricity, waste heat recovery.

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Authors: R. Sharma, M. Gopal

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Markov games can be effectively used to design controllers for nonlinear systems. The paper presents two novel controller design algorithms by incorporating ideas from gametheory literature that address safety and consistency issues of the 'learned' control strategy. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. We generate an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed approaches aim to achieve 'safe-consistent' and 'safe-universally consistent' controller behavior by hybridizing 'min-max', 'fictitious play' and 'cautious fictitious play' approaches drawn from game theory. We empirically evaluate the approaches on a simulated Inverted Pendulum swing-up task and compare its performance against standard Q learning.

Keywords: Fictitious Play, Cautious Fictitious Play, InvertedPendulum, Controller, Markov Games, Mobile Robot.

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Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam

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The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.

Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.

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Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: Chromosome, genetic algorithm, subtree, test.

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Authors: Muhammad Arslan Usman, Muhammad Rehan Usman, Soo Young Shin

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Live video streaming is one of the most widely used service among end users, yet it is a big challenge for the network operators in terms of quality. The only way to provide excellent Quality of Experience (QoE) to the end users is continuous monitoring of live video streaming. For this purpose, there are several objective algorithms available that monitor the quality of the video in a live stream. Subjective tests play a very important role in fine tuning the results of objective algorithms. As human perception is considered to be the most reliable source for assessing the quality of a video stream subjective tests are conducted in order to develop more reliable objective algorithms. Temporal impairments in a live video stream can have a negative impact on the end users. In this paper we have conducted subjective evaluation tests on a set of video sequences containing temporal impairment known as frame freezing. Frame Freezing is considered as a transmission error as well as a hardware error which can result in loss of video frames on the reception side of a transmission system. In our subjective tests, we have performed tests on videos that contain a single freezing event and also for videos that contain multiple freezing events. We have recorded our subjective test results for all the videos in order to give a comparison on the available No Reference (NR) objective algorithms. Finally, we have shown the performance of no reference algorithms used for objective evaluation of videos and suggested the algorithm that works better. The outcome of this study shows the importance of QoE and its effect on human perception. The results for the subjective evaluation can serve the purpose for validating objective algorithms.

Keywords: Objective evaluation, subjective evaluation, quality of experience (QoE), video quality assessment (VQA).

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Authors: Wajeeh Daher, Nimer Baya'a

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High Order Thinking Skills (HOTS) are suggested today as essential for the cognitive development of students and as preparing them for real life skills. Teachers are encouraged to use HOTS activities in the classroom to help their students develop higher order skills and deep thinking. So it is essential to prepare preservice teachers to write and use HOTS activities for their students. This paper describes a model for integrating HOTS activities with GeoGebra in pre-service teachers’ preparation. This model describes four aspects of HOTS activities and working with them: activity components, preparation procedure, strategies and processes used in writing a HOTS activity and types of the HOTS activities. In addition, the paper describes the pre-service teachers' difficulties in preparing and working with HOTS activities, as well as their perceptions regarding the use of these activities and GeoGebra in the mathematics classroom. The paper also describes the contribution of a HOTS activity to pupils' learning of mathematics, where this HOTS activity was prepared and taught by one pre-service teacher.

Keywords: Higher order thinking, HOTS activities, pre-service teachers, teachers' preparation.

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Authors: Poom Thiparpakul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that does not translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: User Experience Design, User Experience, Electric Vehicle, Dashboard Design, Thailand driver.

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: Image processing, Illumination equalization, Shadow filtering, Object detection, Colour models, Image segmentation.

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Authors: Jayant Sakhardande, Pratik Pattanayak, Mita Bhowmick

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An efficient reintegration of the disabled people in the family and society should be fulfilled; hence it is strongly needful to assist their diminished functions or to replace the totally lost functions. Assistive technology helps in neutralizing the impairment. Recent advancements in embedded systems have opened up a vast area of research and development for affordable and portable assistive devices for the visually impaired. Granted there are many assistive devices on the market that are able to detect obstacles, and numerous research and development currently in process to alleviate the cause, unfortunately the cost of devices, size of devices, intrusiveness and higher learning curve prevents the visually impaired from taking advantage of available devices. This project aims at the design and implementation of a detachable unit which is robust, low cost and user friendly, thus, trying to aggrandize the functionality of the existing white cane, to concede above-knee obstacle detection. The designed obstruction detector uses ultrasound sensors for detecting the obstructions before direct contact. It bestows haptic feedback to the user in accordance with the position of the obstacle.

Keywords: Visually impaired, Ultrasonic sensors, Obstruction detector, Mobility aid

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Authors: Pamita Awasthi, Kirna, Shilpa Dogra, Manu Vatsal, Ritu Barthwal

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Doxorubicin, also known as Adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemia, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, antiinflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilinoethyl) benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 μM whereas for doxorubicin is 7.2 μM.

Keywords: Anticancer, Auto Dock, Doxorubicin, Sulfonamide.

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Authors: Abinash Tripathy, Girish Muralidharan, Amitava Pramanik, Prosenjit Sen

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Superhydrophobic surfaces are abundant in nature. Several surfaces such as wings of butterfly, legs of water strider, feet of gecko and the lotus leaf show extreme water repellence behaviour. Self-cleaning, stain-free fabrics, spill-resistant protective wears, drag reduction in micro-fluidic devices etc. are few applications of superhydrophobic surfaces. In order to design robust superhydrophobic surface, it is important to understand the interaction of water with superhydrophobic surface textures. In this work, we report a simple coating method for creating large-scale flexible superhydrophobic paper surface. The surface consists of multiple layers of silanized zirconia microparticles decorated with zirconia nanoparticles. Water contact angle as high as 159±1⁰ and contact angle hysteresis less than 8⁰ was observed. Drop impact studies on superhydrophobic paper surface were carried out by impinging water droplet and capturing its dynamics through high speed imaging. During the drop impact, the Weber number was varied from 20 to 80 by altering the impact velocity of the drop and the parameters such as contact time, normalized spread diameter were obtained. In contrast to earlier literature reports, we observed contact time to be dependent on impact velocity on superhydrophobic surface. Total contact time was split into two components as spread time and recoil time. The recoil time was found to be dependent on the impact velocity while the spread time on the surface did not show much variation with the impact velocity. Further, normalized spreading parameter was found to increase with increase in impact velocity.

Keywords: Contact angle, contact angle hysteresis, contact time, superhydrophobic.

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Authors: Elzo Alves Aranha, Marcio M. Araki

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Business model (BM) is a term that has been receiving the attention of scholars and practitioners and has been consolidating itself as a field of study and research. Although there is no agreement in the academic literature on the definition of BM, at least there is an explicit agreement: BM defines a logical structure of how an organization creates value, capture value and delivers value for the customers and stakeholders. The lack of understanding about connections and elements among BM and higher education, university, and entrepreneurship education opens a gap in the academic literature. Thus, it is interesting to analyze how BM has been approached by the literature and applied in higher education, university, and entrepreneurship education aimed to know the main streams of research. This is because higher education institutions are characterized by innovation, leading to a greater acceptance of new and modern concepts such as BM. Our research has the main motivation to fill the gap in the academic literature, making it possible to increase the power of understanding about connections and aspects among BM and higher education, university, and entrepreneurship education. The objective of the research is to analyze the main aspects among BM and higher education, university, and entrepreneurship education in academic literature. The research followed the systematic literature review (SLR). The SLR is based on three main factors: clarity, validity, and auditability. 82 academic papers were found in the past 10 years, from 2009-2019. The search was carried out in Science Direct and Periodicos Capes databases. The main findings indicate that there are links between BM and higher education, BM and university, BM, and entrepreneurship education. The main findings are inserted within seven aspects. The findings are innovative and contribute to increase the power of understanding about the connection among BM and higher education, university, and entrepreneurship education in academic literature. The research findings addressed to the gap exposed in academic literature. The research findings have several practical implications, and we highlight only two main ones. First, researchers will be able to use the research findings to mitigate a BM research agenda involving connections between BM and higher education, BM and university, and BM and entrepreneurship education. Second, directors, deans, and university leaders will be able to carry out BM awareness programs, BM professors training programs, and makers planning for the inclusion of BM, as one of the components of the curricula of the undergraduate and graduate courses.

Keywords: Business model, entrepreneurship education, higher education, university.

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Authors: M. Sedighizadeh, A. Rezazadeh

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Movable power sources of proton exchange membrane fuel cells (PEMFC) are the important research done in the current fuel cells (FC) field. The PEMFC system control influences the cell performance greatly and it is a control system for industrial complex problems, due to the imprecision, uncertainty and partial truth and intrinsic nonlinear characteristics of PEMFCs. In this paper an adaptive PI control strategy using neural network adaptive Morlet wavelet for control is proposed. It is based on a single layer feed forward neural networks with hidden nodes of adaptive morlet wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. The proposed method is applied to a typical 1 KW PEMFC system and the results show the proposed method has more accuracy against to MLP (Multi Layer Perceptron) method.

Keywords: Adaptive Control, Morlet Wavelets, PEMFC.

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: Color moments, visual thing recognition system, SIFT, color SIFT.

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Authors: Xiaoshu Lu, Esa-Pekka Takala, Risto Toivonen

Abstract:

This paper systematically investigates the timedependent health outcomes for office staff during computer work using the developed mathematical model. The model describes timedependent health outcomes in multiple body regions associated with computer usage. The association is explicitly presented with a doseresponse relationship which is parametrized by body region parameters. Using the developed model we perform extensive investigations of the health outcomes statically and dynamically. We compare the risk body regions and provide various severity rankings of the discomfort rate changes with respect to computer-related workload dynamically for the study population. Application of the developed model reveals a wide range of findings. Such broad spectrum of investigations in a single report literature is lacking. Based upon the model analysis, it is discovered that the highest average severity level of the discomfort exists in neck, shoulder, eyes, shoulder joint/upper arm, upper back, low back and head etc. The biggest weekly changes of discomfort rates are in eyes, neck, head, shoulder, shoulder joint/upper arm and upper back etc. The fastest discomfort rate is found in neck, followed by shoulder, eyes, head, shoulder joint/upper arm and upper back etc. Most of our findings are consistent with the literature, which demonstrates that the developed model and results are applicable and valuable and can be utilized to assess correlation between the amount of computer-related workload and health risk.

Keywords: Computer-related workload, health outcomes, dynamic association, dose-response relationship, systematic analysis.

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Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam

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This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.

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Authors: L. Basha, E. Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable on one country's competitiveness, trade and current account, inflation, wages, domestic economic activity and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021 and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables in the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: Exchange rate, Random Forest, time series, Machine Learning, forecasting.

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Authors: Kelly Grani Yuen

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Accounting scandals and auditing frauds are perceived to be driven by aggressive companies and misrepresentation of audit reports. However, local legal systems and law enforcements may affect the services auditors provide to their ‘important’ clients. Under the civil law and common law jurisdictions, the standard setters, the government, and the regulatory bodies treat cases differently. As such, whether or not different forms of legal systems and extent of law enforcement plays an important role in auditor’s Audit Quality is a question this paper attempts to explore. The paper focuses on the investigation in Asia, where Hong Kong represents the common-law jurisdiction, while Taiwan and China represent the civil law jurisdiction. Only the ten reputable accounting firms are used in this study due to the differences in rankings and establishments of some of the small local audit firms. This will also contribute to the data collected between the years 2007-2013. By focusing on the use of multiple regression based on the dependent (Audit Quality) and independent variables (Client Importance, Law Enforcement, and Press Freedom), six different models are established. Results demonstrate that since different jurisdictions have different legal systems and market regulations, auditor’s treatment on ‘important’ clients will vary. However, with the moderators in place (law enforcement and press freedom), the relationship between client importance and audit quality may be smoothed out. With that in mind, this study contributes to local governments and standard setters’ consideration on legal reform and proper law enforcement in the market. Perhaps, with such modifications on the economic systems, collusion between companies and auditors can finally be put to a halt.

Keywords: Audit quality, client importance, jurisdiction, modified audit opinions.

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: Academic identity, embodied learning, digitized lecture, performance coaching.

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Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: A second language, Chinese language teaching, immersion teaching, instructional strategies.

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard A. Jorswieck

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The capacity of fifth-generation (5G)vehicle-to-everything (V2X) networks poses significant challenges.To address this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a vehicular heterogeneous network (HetNet). We propose a framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles, while guarantying the WiFi users throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: Vehicle-to-everything, resource allocation, BS assignment, new radio, new radio unlicensed, coexistence NR-U and WiFi, deep deterministic policy gradient, Deep Q-network, Duty cycle mechanism.

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