Search results for: bi-directional long and short-term memory networks

Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

Procedia PDF Downloads 292

Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 379

Authors: Santanu Pakhira, Chandan Mazumdar, R. Ranganathan, Maxim Avdeev

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Magnetically frustrated systems are of great interest and one of the most adorable topics for the researcher of condensed matter physics, due to their various interesting properties, viz. ground state degeneracy, finite entropy at zero temperature, lowering of ordering temperature, etc. Ternary intermetallics with the composition RE₂TX₃ (RE = rare-earth element, T= d electron transition metal and X= p electron element) crystallize in hexagonal AlB₂ type crystal structure (space group P6/mmm). In a hexagonal crystal structure with the antiferromagnetic interaction between the moments, the center moment is geometrically frustrated. Magnetic frustration along with disorder arrangements of non-magnetic ions are the building blocks for metastable spin-glass ground state formation for most of the compounds of this stoichiometry. The newly synthesized compound Er₂NiSi₃ compound forms in single phase in AlB₂ type structure with space group P6/mmm. The compound orders antiferromagnetically below 5.4 K and spin freezing of the frustrated magnetic moments occurs below 3 K for the compound. The compound shows magnetic relaxation behavior and magnetic memory effect below its freezing temperature. Neutron diffraction patterns for temperatures below the spin freezing temperature have been analyzed using FULLPROF software package. Diffuse magnetic scattering at low temperatures yields spin glass state formation for the compound.

Keywords: antiferromagnetism, magnetic frustration, spin-glass, neutron diffraction

Procedia PDF Downloads 263

Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

Procedia PDF Downloads 86

Authors: Qin Yang, Fan Zhang, Juan Du, Chongkui Sun, Krishna Kota, Yun-Ling Zheng

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Telomeres are specialized structures at chromosome ends consisting of tandem repetitive DNA sequences [(TTAGGG)n in humans] and associated proteins, which are necessary for telomere function. Telomere lengths are tightly regulated within a narrow range in normal human somatic cells, the basis of cellular senescence and aging. Previous studies have extensively focused on how short telomeres are extended and have demonstrated that telomerase plays a central role in telomere maintenance through elongating the short telomeres. However, the molecular mechanisms of regulating excessively long telomeres are unknown. Here, we found that telomerase enzymatic component hTERT plays a dual role in the regulation of telomeres length. We analyzed single telomere alterations at each chromosomal end led to the discoveries that hTERT shortens excessively long telomeres and elongates short telomeres simultaneously, thus maintaining the optimal telomere length at each chromosomal end for an efficient protection. The hTERT-mediated telomere shortening removes large segments of telomere DNA rapidly without inducing telomere dysfunction foci or affecting cell proliferation, thus it is mechanistically distinct from rapid telomere deletion. We found that expression of hTERT generates telomeric circular DNA, suggesting that telomere homologous recombination may be involved in this telomere shortening process. Moreover, the hTERT-mediated telomere shortening is required its enzymatic activity, but telomerase RNA component hTR is not involved in it. Furthermore, shelterin protein TPP1 interacts with hTERT and recruits it on telomeres to mediate telomere shortening. In addition, telomere-associated proteins, DKC1 and TCAB1 also play roles in this process. This novel hTERT-mediated telomere shortening mechanism not only exists in cancer cells, but also in primary human cells. Thus, the hTERT-mediated telomere shortening is expected to shift the paradigm on current molecular models of telomere length maintenance, with wide-reaching consequences in cancer and aging fields.

Keywords: aging, hTERT, telomerase, telomeres, human cells

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Authors: Lukas Kober, Vladimir Littva, Vladimir Siska

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The pandemic has had a significant impact on our lives. One of the most affected professions is the nursing profession. Nurses are closest to the patient, spend the most time with him, support him, often replace the closest family members, and of course, are part of the whole treatment process. Current nurses have more competencies and roles than in the past. The healthcare system has reached a turning point, also in connection with the spreading Delta variant and the risk of the arrival of the third wave. The lack of nurses is a long-term problem, but it did not arise by itself. The reasons for the departure of nurses from the health care system are not only due to the increasing average age of nurses and midwives in Slovakia and their retirement. Thousands of nurses are leaving due to poor working conditions, low wages, and poor management of individual workplaces. We need to keep older nurses in the health care system, otherwise, we risk their early departure. The pandemic only exacerbates this situation, and the associated risks, such as occupational infections or enormous overload and exhaustion, only accelerate the exit from the profession. According to current data from the register of nurses and midwives, we canceled 772 registrations from January to September 2021, and 584 nurses requested the suspension of registration due to non-performance of the profession. During the same period, we registered only 240 new nurses graduate. We have had this significant disparity here for a long time. For the whole of 2020, we canceled 911 registrations and suspended 973 registrations. We registered a total of 389 graduates. Our system loses hundreds of graduates a year and loses experienced nurses with decades of experience who leave due to poor working conditions, wages and suffer from burnout. Such compensation should also be awarded to the families of health professionals who have lost their lives due to work and to COVID-19. These options can also be motivating for promising people interested in studying nursing, who can gradually replace the missing workforce. This purchase is supported by the KEGA project no. 015KU-4/2019.

Keywords: pandemic, COVID-19, nursing, nursing workforce, lack of nurses

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: Jonathan Bolduc

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Studies have demonstrated the effectiveness of music training approaches to help children with language disabilities. Because music is closely associated with a number of cognitive functions, including language, it has been hypothesized that musical skills transfer to other domains. Research suggests that music training strengthens basic auditory processing skills in dyslexic children and may ameliorate phonological deficits. Furthermore, music instruction has the particular advantage of being non-literacy-based, thus removing the frustrations that can be associated with reading and writing activities among children with specific learning disabilities. In this study, we assessed the effect of implementing an intensive music program on the development of language skills (phonological and reading) in 4- to 9-year-old children. Seventeen children (N=17) participated in the study. The experiment took place over 6 weeks in a controlled environment. Eighteen lessons of 40 minutes were offered during this period by two music specialists. The Dalcroze, Orff, and Kodaly approaches were used. A series of qualitative measures were implemented to document the contribution of music training to this population. Currently, the data is being analyzed. The first results show that learning music seems to significantly improve verbal memory. We already know that language disabilities are considered one of the main causes of school dropout as well as later professional and social failure. We aim to corroborate that an integrated music education program can provide children with language disabilities with the same opportunities to develop and succeed in school as their classmates. Scientifically, the results will contribute to advance the knowledge by identifying the more effective music education strategies to improve the overall development of children worldwide.

Keywords: music education, music, art education, language diasabilities

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Authors: Matthew Pleshaw, Caroline Lynch, Caleb Eaton, Ali Kiapour

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The problem addressed in this proposal is that of the lacking comfort and safety of inpatient rooms, specifically at Boston Children’s Hospital, with the implementation of a system that will allow inpatient children to feel more comfortable in the unfamiliar environment of a hospital. The focus is that of advancing and enhancing the healing process for children in a long-term inpatient stay at the hospital, though a combination of announcing a clinician or hospital staff’s arrival utilizing RFID (Fig. 1), and improving communication between clinicians, parents/guardians, patients, etc. by integrating a mobile application.

Keywords: Pediatrics, Hospital, RFID, Technology

Procedia PDF Downloads 158

Authors: M. R. Vijayakumar, Sanjay Kumar Singh, Lakshmi, Hithesh Dewangan, Sanjay Singh

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Trans resveratrol (RES) is a natural molecule proved for cancer preventive and therapeutic activities devoid of any potential side effects. However, the therapeutic application of RES in disease management is limited because of its rapid elimination from blood circulation thereby low biological half life in mammals. Therefore, the main objective of this study is to enhance the circulation as well as therapeutic efficacy using PEGylated liposomes. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS) is applied as steric surface decorating agent to prepare RES liposomes by thin film hydration method. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Encapsulation efficiency and invitro drug release were determined by dialysis bag method. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies were performed in sprague dawley rats. The prepared liposomes were found to be spherical in shape. Particle size and zeta potential of prepared formulations varied from 64.5±3.16 to 262.3±7.45 nm and -2.1 to 1.76 mV, respectively. DSC study revealed absence of potential interaction. XRD study revealed presence of amorphous form in liposomes. Entrapment efficiency was found to be 87.45±2.14 % and the drug release was found to be controlled up to 24 hours. Minimized MEC in MTT assay and tremendous enhancement in circulation time of RES PEGylated liposomes than its pristine form revealed that the stearic stabilized PEGylated liposomes can be an alternative tool to commercialize this molecule for chemopreventive and therapeutic applications in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating liposomes, bioavailability enhancement, liposomes for cancer therapy, PEGylated liposomes

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Authors: Ajmal Khan Kassi, Humayun Javed, Muhammad Asif Aziz

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Response of different aubergine cultivars against Brinjal shoot and fruit borer (Leucinodes orbonalis Guenee.) was evaluated at research farm of PMAS, Arid Agriculture University, Rawalpindi, during 2013. Field trials were conducted in randomized completed block design with four replications for the screening of five cultivars of Brinjal (Solanum melongena L) (Short Purpal, Singhnath 666, Brinjal long 6275, Round Brinjal 86602, Round Egg Plant White). Cultivar Round White Brinjal showed maximum fruit infestation (54.44%) followed by Singhnath 666 (53.19%), while minimum fruit infestation was observed in Round Brinjal 86602 (42.39%). Cultivar Short Purpal showed maximum larval population (0.43) followed by Round White Brinjal (0.39), while the minimum larval population was observed in Round Brinjal 86602 with (0.27). It was observed that Round Brinjal 86602 cultivar showed comparatively minimum (L. orbonalis) larval population per leaf. The correlation of Brinjal fruit infestation and larval population of (L. orbonalis) with the different environmental factors showed that, the average relative humidity was positively and significantly correlated with fruit infestation on cultivars average precipitation showed positive but non- significant correlation on all the cultivars except Singhnath 666 with the value of (0.79) which was positive and significant. The average temperature showed non-significant and negative correlation with Brinjal long 6275, Round Brinjal 86602 and Singhnath 666, but significant negative correlation with Short Purpal and Round White Brinjal. Maximum temperature also showed the significant and negative correlation on all the five Brinjal cultivars which were significant and highly significant. Minimum temperature showed negative correlation and not significant correlation with all the cultivars. Consequently, based on the (L. orbonalis) larval density and Brinjal fruit infestation, the Round Brinjal 86602 proved least susceptible and Short Purpal highly susceptible cultivar.

Keywords: evaluation, Brinjal (Solanum melongena L), Cultivars, L. orbonalis

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 223

Authors: F. Ece Cetin, H. Nezih Ozdemir, Emre Kumral

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Ischemic stroke of the precuneal cortex (PC) alone is extremely rare. This study aims to evaluate the clinical, neurocognitive, and behavioural characteristics of isolated PC infarcts. We assessed neuropsychological and behavioral findings in 12 patients with isolated PC infarct among 3800 patients with ischemic stroke. To determine the most frequently affected brain locus in patients, we first overlapped the ischemic area of patients with specific cognitive disorders and patients without specific cognitive disorders. Secondly, we compared both overlap maps using the 'subtraction plot' function of MRIcroGL. Patients showed various types of cognitive disorders. All patients experienced more than one category of cognitive disorder, except for two patients with only one cognitive disorder. Lesion topographical analysis showed that damage within the anterior precuneal region might lead to consciousness disorders (25%), self-processing impairment (42%), visuospatial disorders (58%), and lesions in the posterior precuneal region caused episodic and semantic memory impairment (33%). The whole precuneus is involved in at least one body awareness disorder. The cause of the stroke was cardioembolism in 5 patients (42%), large artery disease in 3 (25%), and unknown in 4 (33%). This study showed a wide variety of neuropsychological and behavioural disorders in patients with precuneal infarct. Future studies are needed to achieve a proper definition of the function of the precuneus in relation to the extended cortical areas. Precuneal cortex region infarcts have been found to predict a source of embolism from the large arteries or heart.

Keywords: cognition, pericallosal artery, precuneal cortex, ischemic stroke

Procedia PDF Downloads 130

Authors: Marta Gràcia, Ana Luisa Adam-Alcocer, Jesús M. Alvarado, Verónica Quezada, Tere Zarza, Priscila Garza

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In secondary education, integrating linguistic content and reflection on it is a crucial challenge that should be included in course plans to enhance students' oral communication competence. In secondary education classrooms, a continuum can be identified in relation to teaching methodologies: 1) the traditional teacher-dominated transmission approach, which is described as that in which teachers transmit content to students unidirectionally; 2) dialogical, bidirectional teaching approach that encourages students to adopt a critical vision of the information provided by the teacher or that is generated through students’ discussion. In this context, the EVALOE-DSS (Assessment Scale of Oral Language Teaching in the School Context-Decision Support System) digital instrument has emerged to help teachers in transforming their classes into spaces for communication, dialogue, reflection, evaluation of the learning process, teaching linguistic contents, and to develop curricular competencies. The tool includes various resources, such as a tutorial with the objectives and an initial screen for teachers to describe the class to be evaluated. One of the main resources of the digital instrument consists of 30 items-actions with three qualitative response options (green, orange, and red face emoji) grouped in five dimensions. In the context of the participation of secondary education teachers in a professional development program using EVALOE-DSS, a digital tool resource aimed to generate more participatory, interactive, dialogic classes, the objectives of the study were: 1) understanding the changes in classrooms’ dynamics and in the teachers’ strategies during their participation in the professional developmental program; 2) analyzing the impact of these changes in students’ oral language development according to their teachers; 3) Deeping on the impact of these changes in the students’ assessment of the classes and the self-assessment of oral competence; 4) knowing teachers’ assessment and reflections about their participation in the professional developmental program. Participants were ten teachers of different subjects and 250 students of secondary education (16-18 years) schools in Spain. The principal instrument used was the digital tool EVALOE-DSS. For 6 months, teachers used the digital tool to reflect on their classes, assess them (their actions and their students’ actions), make decisions, and introduce changes in their classes to be more participatory, interactive, and reflective about linguistic contents. Other collecting data instruments and techniques used during the study were: 1) a questionnaire to assess students’ oral language competence before and at the end of the study, 2) a questionnaire for students’ assessment of the characteristics of classes, 3) teachers’ meetings during the professional developmental program to reflect collaboratively on their experience, 4) questionnaire to assess teacher’s experience during their participation in the professional developmental program, 5) focus group meetings between the teachers and two researchers at the end of the study. The results showed relevant changes in teaching strategies, in the dynamics of the classes, which were more interactive, participative, dialogic and self-managed by the students. Both teachers and students agree about the progressive classes’ transformation into spaces for communication, discussion, and reflection on the language, its development, and its use as an essential instrument to develop curricular competencies.

Keywords: digital tool, individual and collaborative reflection, oral language competence, professional development program, secondary education

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: F. Rahmani, F. Razaghian, A. R. Kashaninia

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This article proposes a new method for application in communication circuit systems that increase efficiency, PAE, output power and gain in the circuit. The proposed method is based on a combination of switching class-E and class-J and has been termed class-EJ. This method was investigated using both theory and simulation to confirm ~72% PAE and output power of > 39 dBm. The combination and design of the proposed power amplifier accrues gain of over 15dB in the 2.9 to 3.5 GHz frequency bandwidth. This circuit was designed using MOSFET and high power transistors. The load- and source-pull method achieved the best input and output networks using lumped elements. The proposed technique was investigated for fundamental and second harmonics having desirable amplitudes for the output signal.

Keywords: power amplifier (PA), high power, class-J and class-E, high efficiency

Procedia PDF Downloads 492

Authors: Yaxuan Wang

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It has long been a mystery that why the Mongolian possessive suffix, which is constrained by Condition A of binding theory, has the ability to probe a potential antecedent outside of its binding domain. This squib argues that binding theory alone is not sufficient to explain the linguistic facts and proposes an analysis adopting the Agree operation. The current analysis correctly predicts all the possible and impossible structures, with an additional hypothesis that Mongolian possessive suffixes serve as an antecedent for PROs in adjunct. The findings thus provide insights into how Agree operates in Mongolian language.

Keywords: syntax, Mongolian, agreement, possessive particles

Procedia PDF Downloads 101

Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Latif Adnane, Benaatou Wafa, Pla Vicent

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Handover is of great significance to achieve seamless connectivity in wireless networks. This paper gives an impression of the main factors which are being affected by the soft and the hard handovers techniques. To know and understand the handover process in The Universal Mobile Telecommunications System (UMTS) network, different statistics are calculated. This paper focuses on the quality of service (QoS) of soft and hard handover in UMTS network, which includes the analysis of received power, signal to noise radio, throughput, delay traffic, traffic received, delay, total transmit load, end to end delay and upload response time using OPNET simulator.

Keywords: handover, UMTS, mobility, simulation, OPNET modeler

Procedia PDF Downloads 321

Authors: Dora Triki, Irena Vida, Claude Obadia

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Social networks such as e-Forums or dating sites often face the reluctance of key members to participate. Relying on the conation theory, this study investigates this phenomenon and proposes solutions to mitigate the issue. We show that highly experienced e-Forum members refuse to share business information in a peer to peer information exchange forums. However, forums managers can mitigate this behavior by developing a sentiment of belongingness to the network. Furthermore, by selecting only elite forum participants with ample experience, they can reduce the reluctance of key information providers to engage in information exchange. Our hypotheses are tested with PLS structural equations modeling using survey data from members of a French e-Forum dedicated to the exchange of business information about exporting.

Keywords: conation, e-Forum, information exchange, members participation

Procedia PDF Downloads 158

Authors: Akwesi Assensoh-Kodua

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Online Social Networks (OSN) has come and gone, yet the explosion of business activities on such platforms continuous to surge high, giving advantage to the bold entrepreneurs. It is therefore a practical requirement that practitioners and researchers understand the key determinants of costumers’ online social network business activities and continuance intention. An exploratory literature research to examine OSN continuous intention of business participants on OSN revealed that the practice of doing business on social network has come to stay and the following factors are the likely drivers for this new business model: perceived trust, perceived ease of use, confirmation, habit, social norm, perceived behavioural control, expected benefit, and satisfaction are the most probable factors that can lead to online social network (OSN) continuance intention.

Keywords: online social network, continuance intention, business continuance

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Javeria Khurshid

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The aim of this study is to bring forth the interpretation that Agha Shahid Ali in his verses exhibits. The study will focus on the conflict and chaos in his verses, reflecting the sense of identity attached to Kashmir. His verse advertently depicts the political turmoil and social dissent in the 'un-silent' valley, and ultimately, it expresses the chaos, anguish, and suffering, a sense of longing and belonging to this conflicted state of 'being' as well as 'mind.' Agha Shahid Ali, Kashmiri- American poet who writes of Kashmiri tragedies that continue to remain unarticulated and unheard to the major parts of world, articulates the narrative that showcases the conflicted self of Kashmiris in general and Ali’s in particular. The focus of the paper will be his poetry that debunks the claims of civility and how Kashmiri identity is kept either maligned or obscured in the major narratives that arise from the mainstream writers. However, Ali’s verses are substantially broad and clear, and very brilliantly, he rewrites Kashmir in his avid and novel voice, his verses embracing the Kashmiri self, effectively anew in English language. The paper will clearly indicate how Ali remains true to his name, 'shaheed' and 'shahid,' both a martyr and witness. Ali’s fate has been intricately entangled with Kashmir, even after his untimely death. He has fully and beautifully immersed himself in the surreal world of the conflict prevalent in the Valley, and this paper will examine the grotesque and gory history that has been spanning over the years in Kashmir with never ending cycle of conflict. The originality and innovation of his poetry surfaces from the anarchy of Kashmir, spanning between its culture, historical context, the art of memory and imagery.

Keywords: identity, self, turmoil, Kashmir

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Stephanie Wall, Guido Wimmers

Abstract:

The construction and operation of buildings greatly contribute to environmental degradation through resource and energy consumption and greenhouse gas emissions. The design of the envelope system affects the environmental impact of a building in two major ways; 1) high thermal performance and air tightness can significantly reduce the operational energy of the building and 2) the material selection for the envelope largely impacts the embodied energy of the building. Life cycle assessment (LCA) is a scientific methodology that is used to systematically analyze the environmental load of processes or products, such as buildings, over their life. The paper will discuss the results of a comparative LCA of different envelope designs and the long-term monitoring of the Wood Innovation Research Lab (WIRL); a Passive House (PH), industrial building under construction in Prince George, Canada. The WIRL has a footprint of 30m x 30m on a concrete raft slab foundation and consists of shop space as well as a portion of the building that includes a two-story office/classroom space. The lab building goes beyond what was previously thought possible in regards to energy efficiency of industrial buildings in cold climates due to their large volume to surface ratio, small floor area, and high air change rate, and will be the first PH certified industrial building in Canada. These challenges were mitigated through the envelope design which utilizes solar gains while minimizing overheating, reduces thermal bridges with thick (570mm) prefabricated truss walls filled with blown in mineral wool insulation and a concrete slab and roof insulated with EPS rigid insulation. The envelope design results in lower operational and embodied energy when compared to buildings built to local codes or with steel. The LCA conducted using Athena Impact Estimator for Buildings identifies project specific hot spots as well illustrates that for high-efficiency buildings where the operational energy is relatively low; the embodied energy of the material selection becomes a significant design decision as it greatly impacts the overall environmental footprint of the building. The results of the LCA will be reinforced by long-term monitoring of the buildings envelope performance through the installation of temperature and humidity sensors throughout the floor slab, wall and roof panels and through detailed metering of the energy consumption. The data collected from the sensors will also be used to reinforce the results of hygrothermal analysis using WUFI®, a program used to verify the durability of the wall and roof panels. The WIRL provides an opportunity to showcase the use of wood in a high performance envelope of an industrial building and to emphasize the importance of considering the embodied energy of a material in the early stages of design. The results of the LCA will be of interest to leading researchers and scientists committed to finding sustainable solutions for new construction and high-performance buildings.

Keywords: high performance envelope, life cycle assessment, long term monitoring, passive house, prefabricated panels

Procedia PDF Downloads 162

Authors: Jung-Il Suh, Hong-Gun Park, Jae-Eun Oh

Abstract:

Recently, the use of long-span precast concrete (PC) construction has increased in modular construction such as storage buildings and parking facilities. When applying long span PC member, reducing weight of long span PC member should be conducted considering lifting capacity of crane and self-weight of PC member and use of structural lightweight concrete made by lightweight aggregate (LWA) can be considered. In the process of lightweight concrete production, segregation and bleeding could occur due to difference of specific gravity between cement (3.3) and lightweight aggregate (1.2~1.8) and reducing weight of binder is needed to prevent the segregation between binder and aggregate. Also, lightweight precast concrete made by cementitious materials such as fly ash and ground granulated blast furnace (GGBFS) which is lower than specific gravity of cement as a substitute for cement has been studied. When only using fly ash for cementless binder alkali-activation of fly ash is most important chemical process in which the original fly ash is dissolved by a strong alkaline medium in steam curing with high-temperature condition. Because curing condition is similar with environment of precast member production, additional process is not needed. Na-based chloride generally used as a strong alkali activator has a practical problem such as high pH toxicity and high manufacturing cost. Instead of Na-based alkali activator calcium hydroxide [Ca(OH)2] and sodium hydroxide [Na2CO3] might be used because it has a lower pH and less expensive than Na-based alkali activator. This study explored the influences on Ca(OH)2-Na2CO3-activated fly ash system in its microstructural aspects and strength and permeability using powder X-ray analysis (XRD), thermogravimetry (TGA), mercury intrusion porosimetry (MIP). On the basis of microstructural analysis, the conclusions are made as follows. Increase of Ca(OH)2/FA wt.% did not affect improvement of compressive strength. Also, Ca(OH)2/FA wt.% and Na2CO3/FA wt.% had little effect on specific gravity of saturated surface dry (SSD) and absolute dry (AD) condition to calculate water absorption. Especially, the binder is appropriate for structural lightweight concrete because specific gravity of the hardened paste has no difference with that of lightweight aggregate. The XRD and TGA/DTG results did not present considerable difference for the types and quantities of hydration products depending on w/b ratio, Ca(OH)2 wt.%, and Na2CO3 wt.%. In the case of higher molar quantity of Ca(OH)2 to Na2CO3, XRD peak indicated unreacted Ca(OH)2 while DTG peak was not presented because of small quantity. Thus, presence of unreacted Ca(OH)2 is too small quantity to effect on mechanical performance. As a result of MIP, the porosity volume related to capillary pore depends on the w/b ratio. In the same condition of w/b ratio, quantities of Ca(OH)2 and Na2CO3 have more influence on pore size distribution rather than total porosity. While average pore size decreased as Na2CO3/FA w.t% increased, the average pore size increased over 20 nm as Ca(OH)2/FA wt.% increased which has inverse proportional relationship between pore size and mechanical properties such as compressive strength and water permeability.

Keywords: Ca(OH)2, compressive strength, microstructure, fly ash, Na2CO3, water absorption

Procedia PDF Downloads 226

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

Abstract:

Unconventional oil reservoirs have the characteristics of strong heterogeneity and poor injectability, and traditional chemical flooding technology is not effective in such reservoirs; polymer flooding in the production of heavy oil reservoirs is difficult to handle produced fluid and easy to block oil wells, etc. Therefore, a viscoelastic fluid flooding system with good adaptability, low interfacial tension, plugging, and diverting capabilities was studied. The viscosity, viscoelasticity, surface/interfacial activity, wettability, emulsification, and oil displacement performance of the anionic Gemini surfactant flooding system were studied, and the adaptability of the system to the reservoir environment was evaluated. The oil displacement effect of the system in low-permeability and high-permeability (heavy oil) reservoirs was investigated, and the mechanism of the system to enhance water flooding recovery was discussed. The results show that the system has temperature resistance and viscosity increasing performance (65℃, 4.12mPa•s), shear resistance and viscoelasticity; at a lower concentration (0.5%), the oil-water interfacial tension can be reduced to ultra-low (10-3mN/m); has good emulsifying ability for heavy oil, and is easy to break demulsification (4.5min); has good adaptability to reservoirs with high salinity (30000mg/L). Oil flooding experiments show that this system can increase the water flooding recovery rate of low-permeability homogeneous and heterogeneous cores by 13% and 15%, respectively, and can increase the water-flooding recovery rate of high-permeability heavy oil reservoirs by 40%. The anionic Gemini surfactant flooding system studied in this paper is a viscoelastic fluid, has good emulsifying and oil washing ability, can effectively improve sweep efficiency, reduce injection pressure, and has broad application in unconventional reservoirs to enhance oil recovery prospect.

Keywords: oil displacement system, recovery factor, rheology, interfacial activity, environmental adaptability

Procedia PDF Downloads 124

Authors: Andrew Kurochkin, Kostiantyn Bokhan

Abstract:

In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 138

Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

Abstract:

Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

Procedia PDF Downloads 65