Search results for: long short-term memory networks

Authors: Yogitha Shetty

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Tulunadu, a Tulu-speaking ethno-linguistic minority region in the west coast of India is abundant with oral narratives and associated rituals very unique to this region. One such major worship tradition prevalent here is the mass possession cult of women called Siri Jatre. Deriving its referential script from the Siri epic or pāḍdana, Siri rituals are performed annually in many places of Tulunadu. During these rituals thousands of afflicted women gather at the temple premises and get possessed by the pantheon of seven Siri spirits. While mapping the existing corpus of literature on Siri Jatre – analyzing it as a mode of spirit possession, its psycho-therapeutic significance, its emancipatory potential, etc – this paper offers a paradigm shift by perceiving the entire Siri ritual as a death rite offered to Siri’s grandfather Berma Alva. It draws its arguments from the fieldworks conducted recently in some Siri shrines, interviews conducted among adept Siri women and by analyzing the death rites performed among Bunt caste of the region, and locating it within the historically matrilineal fabric. Thereby, it problematizes the existing analytical frames and raises the question of – if annual Siri ceremonies are a means to bemoan the end of a matrilineal family of Siri? It would delve on the gender configuration as manifested in the Siri cult, having its base in the Tuluva society’s matrilineage, and thereby add to the prevalent ethnographic investigative approaches.

Keywords: death rite, matrilineage, possession, women

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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 290

Authors: Eashwari Dahoe, Jody Scheuer, Harm-Jan Vink

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Alzheimer's disease is a progressive brain condition and is the most common form of dementia. Dementia is a global concern. It is an increasing crisis due to the worldwide aging population. The disease alters the body in different stages leading to several issues. The most common issues result in memory loss, responsive decline, and social decline. During the various stages, the dementia patient must be supported more in performing daily tasks. Eventually, the patient will have to be cared for entirely. There are many efforts in various domains to support this brain condition. This study focuses on the connection between three generations of solutions in the domain of technology and the struggles they tackle. To gather information regarding the struggles seniors with dementia face data has been acknowledged through reading scientific articles. The struggles are extracted from these articles and classified into various category struggles. To gather information regarding the three generations of technology data has been acknowledged through reading scientific articles regarding the generations. After understanding the difference between the three generations, international technological solutions from the past 20 years are connected to the generation they fit. This info is mainly collected through research on companies that aim to improve the lives of senior citizens with early stages of dementia. Eventually, the technological solutions (divided by generations) are linked to the struggles they tackle. By connecting the struggles and the solutions , it is hoped that this paper contributes to an informative overview of the currently available technological solutions and the struggles they tackle.

Keywords: Alzheimer’s disease, technological solutions to support dementia, struggles of seniors with dementia, struggles of dementia

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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

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Authors: Sabahat Nadeem, Farman Ali Khan

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Emotions are considered as a vital factor affecting the process of information handling, level of attention, memory capacity and decision making. Latest e-Learning systems are therefore taking into consideration the effective state of learners to make the learning process more effective and enjoyable. One such use of user’s affective information is in the systems that tend to regulate users’ emotions to a state optimally desirable for learning. So for, this objective has been tried to be achieved with the help of teaching strategies, background music, guided imagery, video clips and odors. Nevertheless, we know that colors can affect human emotions. Relationship between color and emotions has a strong influence on how we perceive our environment. Similarly, the colors of the interface can also affect the user positively as well as negatively. This affective behavior of color and its use as emotion regulation agent is not yet exploited. Therefore, this research proposes a Color-based Emotion Regulation Model (CERM), a new framework that can automatically adapt its colors according to user’s emotional state and her personality type and can help in producing a desirable emotional effect, aiming at providing an unobtrusive emotional support to the users of e-learning environment. The evaluation of CERM is carried out by comparing it with classical non-adaptive, static colored learning management system. Results indicate that colors of the interface, when carefully selected has significant positive impact on learner’s emotions.

Keywords: effective learning, e-learning, emotion regulation, emotional design

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Authors: Anna Solovyeva, Ivan Levakin, Nickolai Galaktionov, Olga Podgornaya

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Animals that reproduce asexually were thought to have the same genotypes within generations for a long time. However, some refuting examples were found, and mobile genetic elements (MGEs) or transposons are considered to be the most probable source of genetic instability. Dispersed nature and the ability to change their genomic localization enables MGEs to be efficient mutators. Hence the study of MGEs genomic impact requires an appropriate object which comprehends both representative amounts of various MGEs and options to evaluate the genomic influence of MGEs. Animals that reproduce asexually seem to be a decent model to study MGEs impact in genomic variability. We found a small marine trematode Himasthla elongata (Himasthlidae) to be a good model for such investigation as it has a small genome size, diverse MGEs and parthenogenetic stages in the lifecycle. In the current work, clonal diversity of cercaria was traced with an AFLP (Amplified fragment length polymorphism) method, diverse zones from electrophoretic patterns were cloned, and the nature of the fragments explored. Polymorphic patterns of individual cercariae AFLP-based fingerprints are enriched with retrotransposons of different families. The bulk of those sequences are represented by open reading frames of non-Long Terminal Repeats containing elements(non-LTR) yet Long-Terminal Repeats containing elements (LTR), to a lesser extent in variable figments of AFLP array. The CR1 elements expose both in polymorphic and conservative patterns are remarkably more frequent than the other non-LTR retrotransposons. This data was confirmed with shotgun sequencing-based on Illumina HiSeq 2500 platform. Individual cercaria of the same clone (i.e., originated from a single miracidium and inhabiting one host) has a various distribution of MGE families detected in sequenced AFLP patterns. The most numerous are CR1 and RTE-Bov retrotransposons, typical for trematode genomes. Also, we identified LTR-retrotransposons of Pao and Gypsy families among DNA transposons of CMC-EnSpm, Tc1/Mariner, MuLE-MuDR and Merlin families. We detected many of them in H. elongata transcriptome. Such uneven MGEs distribution in AFLP sequences’ sets reflects the different patterns of transposons spreading in cercarial genomes as transposons affect the genome in many ways (ectopic recombination, gene structure interruption, epigenetic silencing). It is considered that they play a key role in the origins of trematode clonal polymorphism. The authors greatly appreciate the help received at the Kartesh White Sea Biological Station of the Russian Academy of Sciences Zoological Institute. This work is funded with RSF 19-74-20102 and RFBR 17-04-02161 grants and the research program of the Zoological Institute of the Russian Academy of Sciences (project number AAAA-A19-119020690109-2).

Keywords: AFLP, clonal polymorphism, Himasthla elongata, mobile genetic elements, NGS

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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: Saeid Asghari

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The growing interest in sustainability and healthy lifestyles has stimulated the development of solutions that promote mindful consumption and healthier choices. One such solution is the use of transparent graded lanes in product packaging, which enables consumers to visually track their product consumption and encourages portion control. However, the extent to which this packaging affects consumer behavior, trust, and loyalty towards a product or brand, as well as the effectiveness of messaging on the graded lanes, remains unclear. The research aims to examine the impact of transparent graded lanes on consumer behavior, trust, and loyalty towards products or brands in the context of the Janbo chain supermarket in Tehran, Iran, focusing on Ketchup and edible oils containers. A representative sample of 720 respondents is selected using quota sampling based on sex, age, and financial status. The study assesses the effect of messaging on the graded lanes in enhancing consumer recall and recognition of the product at the time of purchase, increasing repeat purchases, and fostering long-term relationships with customers. Furthermore, the potential outcomes of using transparent graded lanes, including the promotion of healthy consumption habits and the reduction of food waste, are also considered. The findings and results can inform the development of effective messaging strategies for graded lanes and suggest ways to enhance consumer engagement with product packaging. Moreover, the study's outcomes can contribute to the broader discourse on sustainable consumption and healthy lifestyles, highlighting the potential role of packaging innovations in promoting these values. We used four theories (social cognitive theory, self-perception theory, nudge theory, and marketing and consumer behavior) to examine the effect of these transparent graded lanes on consumer behavior. The conceptual model integrates the use of transparent graded lanes, consumer behavior, trust and loyalty, messaging, and promotion of healthy consumption habits. The study aims to provide insights into how transparent graded lanes can promote mindful consumption, increase consumer recognition and recall of the product, and foster long-term relationships with customers. Findings suggest that the use of transparent graded lanes on Ketchup and edible oils containers can have a positive impact on consumer behavior, trust, and loyalty towards a product or brand, as well as promote mindful consumption and healthier choices. The messaging on the graded lanes is also found to be effective in promoting recall and recognition of the product at the time of purchase and encouraging repeat purchases. However, the impact of transparent graded lanes may be limited by factors such as cultural norms, personal values, and financial status. Broadly speaking, the investigation provides valuable insights into the potential benefits and challenges of using transparent graded lanes in product packaging, as well as effective strategies for promoting healthy consumption habits and building long-term relationships with customers.

Keywords: packaging customer behavior, purchase, brand loyalty, healthy consumption

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Authors: R. Pääkkönen, L. Korpinen

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This study aimed to evaluate parameters influencing well-being and how to maintain well-being as long as possible after retirement. There is contradictory information on the health changes after retirement in Finland. This work is based on interviews, statistics, and literature evaluation of Finland. Most often, balance, multitasking reaction time, and adaptation of vision in dim and darks areas are worsened. Slowing is one characteristic that is difficult to measure properly. The most important is try to determine ways to manage daily activities and symptoms of disease after retirement. Medicine is advancing, problems are often also on the economic side. Information of technical aids is important. It is worth planning a retirement age.

Keywords: retirement, working, aging, wellness

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Authors: Vijay Reena Durai, Krithica Srinivasan

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Introduction: The two fundamental skills involved in the growth and wellbeing of any child can be categorized into visual motor and perceptual skills. Visual stress is a disorder which is characterized by visual discomfort, blurred vision, misspelling words, skipping lines, letters bunching together. There is a need to understand the deficits in perceptual skills among children with visual stress. Aim: To estimate the association between visual stress and visual perceptual skills Objective: To compare visual perceptual skills of children with and without visual stress Methodology: Children between 8 to 15 years of age participated in this cross-sectional study. All children with monocular visual acuity better than or equal to 6/6 were included. Visual perceptual skills were measured using test for visual perceptual skills (TVPS) tool. Reading speed was measured with the chosen colored overlay using Wilkins reading chart and pattern glare score was estimated using a 3cpd gratings. Visual stress was defined as change in reading speed of greater than or equal to 10% and a pattern glare score of greater than or equal to 4. Results: 252 children participated in this study and the male: female ratio of 3:2. Majority of the children preferred Magenta (28%) and Yellow (25%) colored overlay for reading. There was a significant difference between the two groups (MD=1.24±0.6) (p<0.04, 95% CI 0.01-2.43) only in the sequential memory skills. The prevalence of visual stress in this group was found to be 31% (n=78). Binary logistic regression showed that odds ratio of having poor visual perceptual skills was OR: 2.85 (95% CI 1.08-7.49) among children with visual stress. Conclusion: Children with visual stress are found to have three times poorer visual perceptual skills than children without visual stress.

Keywords: visual stress, visual perceptual skills, colored overlay, pattern glare

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Authors: Cansu Gülser, Tuğce Ercan

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The construction sector is a key driver of the global economy, contributing significantly to growth and employment through a diverse array of sub-sectors. However, it faces challenges due to its project-based nature, which often hampers long-term collaboration and broader incentives beyond individual projects. These limitations are frequently discussed in scientific literature as obstacles to innovation and industry-wide change. Traditional practices and unwritten rules further hinder the adoption of new processes within the construction industry. The disadvantages of the construction industry’s project-based structure in fostering innovation and long-term relationships include limited continuity, fragmented collaborations, and a focus on short-term goals, which collectively hinder the development of sustained partnerships, inhibit the sharing of knowledge and best practices, and reduce incentives for investing in innovative processes and technologies. This structure typically emphasizes specific projects, which restricts broader collaborations and incentives that extend beyond individual projects, thus impeding innovation and change. The temporal complexities inherent in project-based sectors like construction make it difficult to address societal challenges through collaborative efforts. Traditional management approaches are inadequate for scaling up innovations and adapting to significant changes. For systemic transformation in the construction sector, there is a need for more collaborative relationships and activities beyond traditional supply chains. This study delves into the concept of an innovation ecosystem within the construction sector, highlighting various research findings. It aims to explore key questions about the components that enhance innovation capacity, the relationship between a robust innovation ecosystem and this capacity, and the reasons why innovation is less prevalent and implemented in this sector compared to others. Additionally, it examines the main factors hindering innovation within companies and identifies strategies to improve these efforts, particularly in developing countries. The innovation ecosystem in the construction sector generates various outputs through interactions between business resources and external components. These outputs include innovative value creation, sustainable practices, robust collaborations, knowledge sharing, competitiveness, and advanced project management, all of which contribute significantly to company market performance and competitive advantage. This article offers insights and strategic recommendations for industry professionals, policymakers, and researchers interested in developing and sustaining innovation ecosystems in the construction sector. Future research should focus on broader samples for generalization, comparative sector analysis, and application-focused studies addressing real industry challenges. Additionally, studying the long-term impacts of innovation ecosystems, integrating advanced technologies like AI and machine learning into project management, and developing future application strategies and policies are also important.

Keywords: construction industry, innovation ecosystem, innovation ecosystem components, project management

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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.

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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

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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

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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

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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

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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: 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: 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: Fei Sun, Meilan Xu, Jianghui Zhu, Maria Stefanie Dwiyanti, Cheolwoo Park, Fanjiang Kong, Baohui Liu, Tetsuya Yamada, Jun Abe

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Reduced or lack of sensitivity to long daylengths is a key character for soybean, a short-day crop, to adapt to higher latitudinal environments. However, the photoperiod-insensitivity often results in a reduction of the duration of vegetative growth and final yield. To overcome this limitation, a photoperiod insensitive line (RIL16) was developed in this study that delayed flowering from the recombinant inbred population derived from a cross between a photoperiod-insensitive cultivar AGS292 and a late-flowering Thai cultivar K3. Expression analyses under SD and LD conditions revealed that the expression levels of FLOWERING LOCUS T (FT) orthologues, FT2a and FT5a, were lowered in RIL16 relative to AGS292, although the expression of E1, a soybean-specific suppressor for FTs, was inhibited in both conditions. A soybean orthologue of TARGET OF EAT1 (TOE1), another suppressor of FT, showed an upregulated expression in RIL16, which appeared to reflect a lower expression of miR172a. Our data suggest that the delayed flowering of RIL16 most likely is controlled by genes involved in an age-dependent pathway in flowering. The QTL analysis based on 1,125 SNPs obtained from Restriction Site Associated DNA Sequencing revealed two major QTLs for flowering dates in Chromosome 16 and two minor QTLs in Chromosome 4, all of which accounted for 55% and 48% of the whole variations observed in natural day length and artificially-induced long day length conditions, respectively. The intervals of the major QTLs harbored FT2a and FT5a, respectively, on the basis of annotated genes in the Williams 82 reference genome. Sequencing analysis further revealed a nonsynonymous mutation in FT2a and an SNP in the 3′ UTR region of FT5a. A further study may elucidate a detailed mechanism underlying the QTL for late flowering. The alleles from K3 at the two QTLs can be used singly or in combination to retain an appropriate duration of vegetative growth to maximize the final yield of photoperiod-insensitive soybeans.

Keywords: FT genes, miR72a, photoperiod-insensitive, soybean flowering

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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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

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Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

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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

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

Abstract:

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

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Authors: Oyuna Weina

Abstract:

This study examines how musicians use visual and zoological metaphors for singing technique and voice quality in a genre of traditional music called urtiin duu (‘long song’) in Alshaa, Inner Mongolia, China. Previous studies have discussed melodic contour in Mongol music, but little study of the intersection of singing technique, visual and zoological metaphors has yet been undertaken. The purpose of this study is to address this lack by analysing urtiin duu itself, traditional pedagogy and performances, all of which have been inspired and are assessed by reference to nature and mobile pastoral herding practices. This study investigates the visual and zoological metaphors related to urtiin duu especially colour, the shape of the circle and animals in the Mongol community. Urtiin duu singing is associated with certain colours in song texts, in selection of repertoire and in the status of singers. Musicians also use colour to describe timbre. These colours in turn reference worship of nature, religions, and daily practices of most Mongols in Alshaa. Moreover, voice quality and singing technique are often related to the animals not only in song text but also in the approach to breathing and to melodic contour. Additionally, the concept of boronhoi (‘the shape of circle’), not only is applied to the melodic contour but also to the voice quality and singing technique. These three factors illustrate the connections among nature, spiritual world and everyday herding life of Mongols. These different connections provide evidence of multi-layered meanings. In contemporary Alshaa, urtiin duu singers received Western musical training from the city and returned to their homelands to perform urtiin duu. In doing so, they are also trying to reconnect with the history, nature and spiritual world in order to achieve their ideal sound. Within a multicultural society, singers negotiate amongst themselves, and with ethnic groups, audiences and government officials. The power of the metaphor therefore assists and reconnects the strength of regional identity and ethnic identity in Alshaa.

Keywords: Alshaa, urtiin duu, visual, zoological metaphors

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Authors: Mohammed Hussein, Abualseoud Hanani

Abstract:

In Low Earth Orbit (LEO) satellite constellation system, routing data from the source all the way to the destination constitutes a daunting challenge because LEO satellite constellation resources are spare and the high speed movement of LEO satellites results in a highly dynamic network topology. This situation limits the applicability of traditional routing approaches that rely on exchanging topology information upon change or setup of a connection. Consequently, in recent years, many routing algorithms and implementation strategies for satellite constellation networks with Inter Satellite Links (ISLs) have been proposed. In this article, we summarize and classify some of the most representative solutions according to their objectives, and discuss their advantages and disadvantages. Finally, with a look into the future, we present some of the new challenges and opportunities for LEO satellite constellations in general and routing protocols in particular.

Keywords: LEO satellite constellations, dynamic topology, IP routing, inter-satellite-links

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Authors: Asif Iqbal

Abstract:

Working capital management has its effect on liquidity as well as on profitability of a firm. In this research we have selected a sample of 100 respondents whose firms are listed on Karachi stock exchange. We have studied the effect of different variable s of working capital management. We find that organizations throughout the world as well as in Pakistan have to give immense recognition to the working capital management as it is an effective thing from their long term perspective especially to their shareholders to have a firm confidence over the companies for investment purpose.

Keywords: working capital management, Karachi stock exchange, shareholders, capital management

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