Search results for: community based total sanitation (CBTS)

Authors: Hae-Yeoun Lee

Abstract:

Reversible watermarking that not only protects the copyright but also preserve the original quality of the digital content have been intensively studied. In particular, the demand for reversible watermarking has increased. In this paper, we propose a reversible watermarking scheme based on interpolation-error shifting and error precompensation. The intensity of a pixel is interpolated from the intensities of neighbouring pixels, and the difference histogram between the interpolated and the original intensities is obtained and modified to embed the watermark message. By restoring the difference histogram, the embedded watermark is extracted and the original image is recovered by compensating for the interpolation error. The overflow and underflow are prevented by error precompensation. To show the performance of the method, the proposed algorithm is compared with other methods using various test images.

Keywords: reversible watermarking, high capacity, high quality, interpolated error shifting, error precompensation

Procedia PDF Downloads 310

Authors: Hadi Kafil, Ali Ecder

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Heat transfer by natural convection in two-dimensional and three-dimensional axisymmetric enclosure fitted with partially heated vertical walls is investigated numerically. The range of Rayleigh number is varied from 10³ until convective flow becomes unstable. This research focuses on multiplicity and transition phenomena in natural convection and is based on a parametric analysis to study the onset of bifurcations. It is found that, even at low Rayleigh numbers, the flow undergoes a series of turning-point bifurcations which increase the rate of natural convention. On the other hand, by partially heating or cooling the walls, more effective results can be achieved for both heating and cooling applications, such as cooling of electronic devices and heating processes in solidification and crystal growth.

Keywords: natural convection, partial heated, onset of bifurcation, Rayleigh number

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Chris Miskelly, Eoin Cunningham, Beatrice Smyth, John. D. Holbrey, Gosia Swadzba-Kwasny, Emily L. Byrne, Yoan Delavoux, Mantian Li.

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Recently, the use of ionic liquids (ILs) for the preparation of lignocellulose derived cellulosic materials as alternatives to petrochemical feedstocks has been the focus of considerable research interest. While the technical viability of IL-based lignocellulose treatment methodologies has been well established, the high cost of reagents inhibits commercial feasibility. This work aimed to assess the technoeconomic viability of the preparation of cellulose rich materials (CRMs) using protic ionic liquids (PILs) synthesized from low cost alkylamines and sulphuric acid. For this purpose, the tertiary alkylamines, triethylamine, and dimethylbutylamine were selected. Bulk scale production cost of the synthesized PILs, triethylammonium hydrogen sulphate and dimetheylbutylammonium hydrogen sulphate, was reported as $0.78 kg-1 to $1.24 kg-1. CRMs were prepared through the treatment of common wheat (Triticum aestivum) straw with these PILs. By controlling treatment parameters, CRMs with a cellulose content of ≥ 80 wt% were prepared. This was achieved using a T. aestivum straw to PIL loading ratio of 1:15 w/w, a treatment duration of 180 minutes, and ethanol as a cellulose antisolvent. Infrared spectra data and decreased onset degradation temperature of CRMs (ΔTONSET ~ 70 °C) suggested the formation of cellulose sulphate esters during treatment. Chemical derivatisation can aid the dispersion of prepared CRMs in non-polar polymer/ composite matrices, but act as a barrier to thermal processing at temperatures above 150 °C. It was also shown that treatment increased the crystallinity of CRMs (ΔCrI ~ 40 %) without altering the native crystalline structure or crystallite size (~ 2.6 nm) of cellulose; peaks associated with the cellulose I crystalline planes (110), (200), and (004) were observed at Bragg angles 16.0 °, 22.5 ° and 35.0 ° respectively. This highlighted the inability of assessed PILs to dissolve crystalline cellulose and was attributed to the high acidity (pKa ~ - 1.92 to - 6.42) of sulphuric acid derived anions. Electron micrographs revealed that the stratified multilayer tissue structure of untreated T. aestivum straw was significantly modified during treatment. T. aestivum straw particles were disassembled during treatment, with prepared CRMs adopting a golden-brown film-like appearance. This work demonstrated the degradation of non-cellulosic fractions of lignocellulose without dissolution of cellulose. It is the first to report on the derivatisation of cellulose during treatment with protic hydrogen sulphate ionic liquids, and the potential implications of this with reference to biopolymer feedstock preparation.

Keywords: cellulose, extraction, protic ionic liquids, esterification, thermal stability, waste valorisation, biopolymer feedstock

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Authors: C. Angel, S. Asha

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Despite the advances made in various new technologies, application of these technologies for agriculture still remains a formidable task, as it involves integration of diverse domains for monitoring the different process involved in agricultural management. Advances in ambient intelligence technology represents one of the most powerful technology for increasing the yield of agricultural crops and to mitigate the impact of water scarcity, climatic change and methods for managing pests, weeds, and diseases. This paper proposes a GPS-assisted, machine to machine solutions that combine information collected by multiple sensors for the automated management of paddy crops. To maintain the economic viability of paddy cultivation, the various techniques used in agriculture are discussed and a novel system which uses ambient intelligence technique is proposed in this paper. The ambient intelligence based agricultural system gives a great scope.

Keywords: ambient intelligence, agricultural technology, smart agriculture, precise farming

Procedia PDF Downloads 589

Authors: Hyeondal Jeong, Yoonjung Baek

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This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: positive psychological capital , satisfaction, commitment, OCB, creativity, meta-analysis

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Authors: I. Martinez-Conesa, E. Garcia-Meca, M. Barradas-Quiroz

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The objective of this study is to assess the impact on earnings management of latest two Hofstede cultural dimensions: long-term orientation and indulgence. Long-term orientation represents the alignment of a society towards the future and indulgence expresses the extent to which a society exhibits willingness, or restrain, to realise their impulses. Additionally, this paper tests if there are relevant differences by testing the moderating role of the legal tradition, Continental versus Anglo-Saxon. Our sample comprises 15 countries: Belgium, Canada, Germany, Spain, France, Great Britain, Hong Kong, India, Japan, Korea, Netherlands, Philippines, Portugal, Sweden, and Thailand, with a total of 12,936 observations from 2003 to 2013. Our results show that managers in countries with high levels of long-term orientation reduce their levels of discretionary accruals. The findings do not confirm the effect of indulgence on earnings management. In addition, our results confirm previous literature regarding the effect of individualism, noting that firms in countries with high levels of collectivism might be more inclined to use earnings discretion to protect the welfare of the collective group of firm stakeholders. Uncertainty avoidance results in downwards earnings management as well as high disclosure, suggesting that less manipulation takes place when transparency is higher. Indulgence is the cultural dimension that confronts wellbeing versus survival; dimension is formulated including happiness, the perception of live control and the importance of leisure. Indulgence shows a weak negative correlation with power distance indicating a slight tendency for more hierarchical societies to be less indulgent. Anglo-Saxon countries are a positive effect of individualism and a negative effect of masculinity, uncertainty avoidance, and disclosure. With respect to continental countries, we can see a significant and positive effect of individualism and a significant and negative effect of masculinity, long-term orientation, and indulgence. Therefore, we observe the negative effect on earnings management provoked by higher disclosure and uncertainty avoidance only happens in Anglo-Saxon countries. Meanwhile, the improvement in reporting quality motivated by higher long-term orientation and higher indulgence is dominant in Continental countries. Our results confirm that there is a moderating effect of the legal system in the association between culture and earnings management. This effect is especially relevant in the dimensions related to uncertainty avoidance, long term orientation, indulgence, and disclosure. The negative effect of long-term orientation on earnings management only happens in those countries set in continental legal systems because of the Anglo-Saxon legal systems is supported by the decisions of the courts and the traditions, so it already has long-term orientation. That does not occur in continental systems, depending mainly of contend of the law. Sensitivity analysis used with Jones modified CP model, Jones Standard model and Jones Standard CP model confirm the robustness of these results. This paper collaborates towards a better understanding on how earnings management, culture and legal systems relate to each other, and contribute to previous literature by examining the influence of the two latest Hofstede’s dimensions not previously studied in papers.

Keywords: Hofstede, long-term-orientation, earnings management, indulgence

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Authors: Dariush Jafari, Seyed Ali Jafari

Abstract:

The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

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Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

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Authors: Changgil Lee, Junkyeong Kim, Jihwan Park, Seunghee Park

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In this study, bridge weigh-in-motion (BWIM) system was simulated under various environmental conditions such as temperature, humidity, wind and so on to improve the performance of the BWIM system. The environmental conditions can make difficult to analyze measured data and hence those factors should be compensated. Various conditions were considered as input parameters for ANN (Artificial Neural Network). The number of hidden layers for ANN was decided so that nonlinearity could be sufficiently reflected in the BWIM results. The weight of vehicles and axle weight were more accurately estimated by applying ANN approach. Additionally, the type of bridge which was a target structure was considered as an input parameter for the ANN.

Keywords: bridge weigh-in-motion (BWIM) system, environmental conditions, artificial neural network, type of bridges

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Authors: Mengjie Shen, Jianhua Wu, Chun Gan, Lifeng Zhang, Qingguo Sun

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Switching flux permanent magnet (SFPM) motor has doubly salient structure which lead to high torque ripple, and also has cogging torque as a permanent magnet motor. Torque ripple and cogging torque have impact on the motor performance. A novel stator structure SFPM motor is presented in this paper. A triangular shape silicon steel sheet is put in the stator slot to reduce the torque ripple, which will not deteriorate the cogging torque. The simulation of proposed motor is analyzed using 2-D finite element method (FEM) based on Ansoft and Simplorer software, and the result show a good performance of the proposed SFPM motor.

Keywords: switching flux permanent magnet (SFPM) motor, torque ripple, Ansoft, FEM

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Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

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In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Okike Benjamin, Garba E J. D.

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Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt.

Keywords: image encryption, matrices, pixel, matrix transpose

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Authors: Ana Hol

Abstract:

Technological inventions such as websites, blogs, smartphone applications are on a daily basis influencing our decision making, are improving our productivity and are shaping futures of many consumer and service/product providers. This research identifies that these days both customers and providers heavily rely on smart phone applications. With this in mind, iTunes mobile applications store has been studies. It was identified that food related applications used by consumers can broadly be categorized into purchase apps, diaries, tracking health apps, trip farm location apps and cooking apps. On the other hand, apps used by farmers can be classified as: weather apps, pests / fertilizer app and general Facebook apps. With the aim to blur this farmer-consumer divide our research utilizes Context Specific eTransformation Framework and based on it identifies characteristic of the app that would allow this to happen.

Keywords: smart phone applications, SME - farmers, consumer, technology, business innovation

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Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

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The Markov Decision Process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, dynamic programming, Monte Carlo simulation, periodic replacement, Weibull distribution

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Authors: Abubakar Sa’adatu Mohammed

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This paper reports on a study of problem solving differences between expert and novice Problem solvers for effective physics teaching. Significant differences were found both at the conceptual level and at the level of critical thinking, creative thinking and reasoning. It is suggested for a successful solution of a problem, conceptual knowledge alone may not be sufficient. There is the need of the knowledge of how the conceptual knowledge should be applied (problem solving skills). It is hoped that this research might contribute to efforts of exploring ways for students to acquire a powerful conceptual toolkit based on experts like problem solvers approach for effective teaching delivery.

Keywords: conceptual knowledge, procedural knowledge, critical thinking, creative thinking, reasoning ability

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Authors: Yassir M. Abbas, Mohammad Iqbal Khan, Galal Fare

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In the present work, the structural responses of 12 ultrahigh-performance concrete (UHPC) beams to four-point loading conditions were experimentally and analytically studied. The inclusion of a fibrous system in the UHPC material increased its compressive and flexural strengths by 31.5% and 237.8%, respectively. Based on the analysis of the load-deflection curves of UHPC beams, it was found that UHPC beams with a low reinforcement ratio are prone to sudden brittle failure. This failure behavior was changed, however, to a ductile one in beams with medium to high ratios. The implication is that improving UHPC beam tensile reinforcement could result in a higher level of safety. More reinforcement bars also enabled the load-deflection behavior to be improved, particularly after yielding.

Keywords: ultrahigh-performance concrete, moment capacity, RC beams, hybrid fiber, ductility

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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Authors: Arwa Alnowaiser, Hala Shoukri

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The ‘FreeAITherapist’ is an artificial intelligence application that uses the power of AI to offer advice and mental health counseling to its users through its chatbot services. The AI therapist is designed to understand users' issues, concerns, and problems and respond appropriately; it provides empathy and guidance and uses evidence-based therapeutic techniques. With its user-friendly platform, it ensures accessibility for individuals in need, regardless of their geographical location. This website was created in direct response to the growing demand for mental health support, aiming to provide a cost-effective and confidential solution. Through promising confidentiality, it considers user privacy and data security. The ‘FreeAITherapist’ strives to bridge the gap in mental health services, offering a reliable resource for individuals seeking guidance and counseling to improve their overall well-being.

Keywords: artificial intelligence, mental health, AI therapist, website, counseling

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Authors: Nidal H. Abu-Zahra, Subhashini Gunashekar

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Polyurethane foam is functionalized with Sulfonic acid groups to remove lead ions (Pb2+) from drinking water through a action exchange process. The synthesis is based on addition polymerization of the -NCO groups of an isocyanine with the –OH groups of a polio to form the urethane. Toluene-diisocyanateis reacted with Polypropylene glycol to form a linear pre-polymer, which is further polymerized using a chain extender, N, N-bis(2-hydorxyethyl)-2-aminoethane-sulfonic acid (BES). BES acts as a functional group site to exchange Pb2+ ions. A set of experiments was designed to study the effect of various processing parameters on the performance of the synthesized foam. The maximum Pb2+ ion exchange capacity of the foam was found to be 47ppb/g from a 100ppb Pb2+ solution over a period of 60 minutes. A multistage batch filtration process increased the lead removal to 50-54ppb/3g of foam over a period of 90 minutes.

Keywords: adsorption, functionalized, ion exchange, polyurethane, sulfonic

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Authors: Mouna Abarkan, Abdelillah Byou, Nacer M'Sirdi, El Hossain Abarkan

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This paper presents the estimation of the state of charge of the battery using two types of observers. The battery model used is the combination of a voltage source, which is the open circuit battery voltage of a strength corresponding to the connection of resistors and electrolyte and a series of parallel RC circuits representing charge transfer phenomena and diffusion. An adaptive observer applied to this model is proposed, this observer to estimate the battery state of charge of the battery is based on EFK and sliding mode that is known for their robustness and simplicity implementation. The results are validated by simulation under MATLAB/Simulink and implemented in Arduino-LabView.

Keywords: model of the battery, adaptive sliding mode observer, the EFK observer, estimation of state of charge, SOC, implementation in Arduino/LabView

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Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

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Authors: Leila Rashidian, Mina Rajabali

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Industrialization has made progress and comfort for human beings in many aspects. It is not only achievement for the global environment but also factor for destruction and disruption of the Earth's climate. In this study, we used LARS.WG model and down scaling of general circulation climate model HADCM-3 daily precipitation amounts, minimum and maximum temperature and daily sunshine hours. These data are provided by the meteorological organization for Caspian Sea coastal station such as Anzali, Manjil, Rasht, Lahijan and Astara since their establishment is from 1982 until 2010. According to the IPCC scenarios, including series A1b, A2, B1, we tried to simulate data from 2010 to 2040. The rainfall pattern has changed. So we have a rainfall distribution inappropriate in different months.

Keywords: climate change, Lars.WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Mohammad Jafariahangari, Marjan Habibi, Miresmaeil Mirnabibaboli, Mirza Hassan Hosseini

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Self-service technologies (SSTs) make an important contribution to the daily life of people nowadays. However, the introduction of SST does not lead to its usage. Thereby, this paper was an attempt on discovery of the most preferred SST in the customers’ point of view. To fulfill this aim, the Analytical Hierarchy Process (AHP) was applied based on Saaty’s questionnaire which was administered to the customers of e-banking services located in Golestan providence, north of Iran. This study used qualitative factors in association with the intention of consumers’ usage of SSTs to rank three SSTs: ATM, mobile banking, and internet banking. The results showed that mobile banking get the highest weight in consumers’ point of view. This research can be useful both for managers and service providers and also for customers who intend to use e-banking.

Keywords: analytical hierarchy process, decision-making, e-banking, self-service technologies, Iran

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Authors: Yasmin Tantawi, Mary Beth Rosson

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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

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Authors: Rashi Jain

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The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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Authors: Dingyang Hu, Dan Liu

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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: Edward Hage, Pieter Lietaert, Gabriel Abedrabbo

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Musculoskeletal disorders are an important category of work-related diseases. They are often caused by working in non-ergonomic postures and are preventable with proper workplace design, possibly including human-machine collaboration. This paper presents a methodology and a supporting software prototype to design a simple assembly cell with minimal ergonomic risk. The methodology helps to determine the optimal position and orientation of workpieces and workplace resources for specific operator assembly actions. The methodology is tested on an industrial use case: a collaborative robot (cobot) assisted assembly of a clamping device. It is shown that the automated methodology results in a workplace design with significantly reduced ergonomic risk to the operator compared to a manual design of the cell.

Keywords: ergonomics optimization, design for ergonomics, workplace design, pose generation

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Authors: Ijaz Ul Haq, Fiorenzo Franceschini

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The distributed manufacturing methodology brings a new concept of decentralized manufacturing operations close to the proximity of end users. A preliminary scale, to measure distributed capacity and evaluate positioning of firms, is developed in this research. In the first part of the paper, a literature review has been performed which highlights the explorative nature of the studies conducted to present definitions and classifications due to novelty of this topic. From literature, five dimensions of distributed manufacturing development stages have been identified: localization, manufacturing technologies, customization and personalization, digitalization and democratization of design. Based on these determinants a conceptual scale is proposed to measure the status of distributed manufacturing of a generic firm. A multiple case study is then conducted in two steps to test the conceptual scale and to identify the corresponding level of distributed potential in each case study firm.

Keywords: distributed manufacturing, distributed capacity, localized production, ordinal scale

Procedia PDF Downloads 152