Search results for: delay tolerant networks

Authors: Hemant Kumar Pathak

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In 1994, Matthews (S.G. Matthews, Partial metric topology, in: Proc. 8th Summer Conference on General Topology and Applications, in: Ann. New York Acad. Sci., vol. 728, 1994, pp. 183-197) introduced the concept of a partial metric as a part of the study of denotational semantics of data flow networks. He gave a modified version of the Banach contraction principle, more suitable in this context. In fact, (complete) partial metric spaces constitute a suitable framework to model several distinguished examples of the theory of computation and also to model metric spaces via domain theory. In this paper, we introduce the concept of almost partial Hausdorff metric. We prove a fixed point theorem for multi-valued mappings on partial metric space using the concept of almost partial Hausdorff metric and prove an analogous to the well-known Nadler’s fixed point theorem. In the sequel, we derive a homotopy result as an application of our main result.

Keywords: fixed point, partial metric space, homotopy, physical sciences

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Authors: Suikinai Nobre Santos, Ranko Gacesa, Paul F. Long, Itamar Soares de Melo

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Extremophilic microorganism are adapted to biotopes combining several stress factors (temperature, pressure, radiation, salinity and pH), which indicate the richness valuable resource for the exploitation of novel biotechnological processes and constitute unique models for investigations their biomolecules (1, 2). The above information encourages us investigate bioprospecting synthesized compounds by a noval actinomycete, designated thermotolerant Streptomyces caatingaensis CMAA 1322, isolated from sample soil tropical dry forest (Caatinga) in the Brazilian semiarid region (3-17°S and 35-45°W). This set of constrating physical and climatic factores provide the unique conditions and a diversity of well adapted species, interesting site for biotechnological purposes. Preliminary studies have shown the great potential in the production of cytotoxic, pesticidal and antimicrobial molecules (3). Thus, to extend knowledge of the genes clusters responsible for producing biosynthetic pathways of natural products in strain CMAA1322, whole-genome shotgun (WGS) DNA sequencing was performed using paired-end long sequencing with PacBio RS (Pacific Biosciences). Genomic DNA was extracted from a pure culture grown overnight on LB medium using the PureLink genomic DNA kit (Life Technologies). An approximately 3- to 20-kb-insert PacBio library was constructed and sequenced on an 8 single-molecule real-time (SMRT) cell, yielding 116,269 reads (average length, 7,446 bp), which were allocated into 18 contigs, with 142.11x coverage and N50 value of 20.548 bp (BioProject number PRJNA288757). The assembled data were analyzed by Rapid Annotations using Subsystems Technology (RAST) (4) the genome size was found to be 7.055.077 bp, comprising 6167 open reading frames (ORFs) and 413 subsystems. The G+C content was estimated to be 72 mol%. The closest-neighbors tool, available in RAST through functional comparison of the genome, revealed that strain CMAA1322 is more closely related to Streptomyces hygroscopicus ATCC 53653 (similarity score value, 537), S. violaceusniger Tu 4113 (score value, 483), S. avermitilis MA-4680 (score value, 475), S. albus J1074 (score value, 447). The Streptomyces sp. CMAA1322 genome contains 98 tRNA genes and 135 genes copies related to stress response, mainly osmotic stress (14), heat shock (16), oxidative stress (49). Functional annotation by antiSMASH version 3.0 (5) identified 41 clusters for secondary metabolites (including two clusters for lanthipeptides, ten clusters for nonribosomal peptide synthetases [NRPS], three clusters for siderophores, fourteen for polyketide synthetase [PKS], six clusters encoding a terpene, two clusters encoding a bacteriocin, and one cluster encoding a phenazine). Our work provide in comparative analyse of genome and extract produced (data no published) by lineage CMAA1322, revealing the potential of microorganisms accessed from extreme environments as Caatinga” to produce a wide range of biotechnological relevant compounds.

Keywords: caatinga, streptomyces, environmental stresses, biosynthetic pathways

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Authors: Pablo Cid Galache, Laura Zamorano Bonilla

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Mauriac syndrome (MS) is a rare complication of type 1 diabetes mellitus (DM1). It is rela-ted to low insulin concentrations. Therefore is a complication mainly found in developing countries. The main clinical features are hepatomegaly, edema, growth and puberty delay, and the presence of elevated transaminases and serum lipids. The MS incidence is de-creasing due to the new types of insulin and intensive glycemic control. Therefore is a rare diagnosis in Europe nowadays, being described mainly in developing countries or with so-cioeconomic limitations to guarantee an adequate management of diabetes. Edema secondary to fluid retention is a rare complication of insulin treatment, especially in young patients. Its severity is variable and is mainly related to the start of a proper treatment and the improvement in glycemic control after diagnosis or after periods of poor metabolic control. Edema resolves spontaneously without requiring treatment in most cases. The Pediatric Endocrinology Unit of Hospital Motril could diagnose a 14-year-old girl who presented very poor metabolic control during the last 3 years as a consequence of the socioeconomic conditions of the country of origin during the last years. Presents up to 4 admissions for ketoacidosis during the last 12 months. After the family moved to Spain our patient began to be followed up in our Hospital. Initially presented glycated hemoglobin figures of 11%. One week after the start of treatment, the patient was admitted in the emergency room due to the appearance of generalized edema and pain in the limbs. The main laboratory abnormalities include: blood glucose 225mg/dl; HbA1C 10.8% triglycerides 543 mg/dl, total cholesterol 339 mg/dl (LDL 225) GOT 124 U/l, GPT 89U/l. Abdominal ultrasound shows mild hepatomegaly and no signs of ascites were shown. The patient presented a progressive improvement with resolution of the edema and analitical abnormalities during the next two weeks. During admission, the family received diabetes education, achieving adequate glycemic control at discharge. Nowadays the patient has a good glycemic control having glycated hemoglobin levels around 7%.

Keywords: Mauriac, diabetes, complication, developing countries

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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Authors: Birgit A. A. Solem, Kristin Bentsen

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Scholarly attention in entrepreneurship is currently directed towards understanding entrepreneurial venture creation as a process -the journey of new economic activities from nonexistence to existence often studied through flow- or network models. To complement existing research on entrepreneurial venture creation with more interactivity-based research of organized activities, this study examines two pop-up stores as anchor events involving on-site activities of fifteen participating entrepreneurs launching their new ventures. The pop-up stores were arranged in two middle-sized Norwegian cities and contained different brand stores that brought together actors of sub-networks and communities executing venture creation activities. The pop-up stores became on-site arenas for the entrepreneurs to create, maintain, and rejuvenate their networks, at the same time as becoming venues for temporal coordination of activities involving existing and potential customers in their venture creation. In this work, we apply a conceptual framework based on frequently addressed dilemmas within entrepreneurship theory (discovery/creation, causation/effectuation) to further shed light on the broad aspect of on-site anchor event activities and their venture creation outcomes. The dilemma-based concepts are applied as an analytic toolkit to pursue answers regarding the nature of anchor event activities typically found within entrepreneurial venture creation and how these anchor event activities affect entrepreneurial venture creation outcomes. Our study combines researcher participation with 200 hours of observation and twenty in-depth interviews. Data analysis followed established guidelines for hermeneutic analysis and was intimately intertwined with ongoing data collection. Data was coded and categorized in NVivo 12 software, and iterated several times as patterns were steadily developing. Our findings suggest that core anchor event activities typically found within entrepreneurial venture creation are; a concept- and product experimentation with visitors, arrangements to socialize (evening specials, auctions, and exhibitions), store-in-store concepts, arranged meeting places for peers and close connection with municipality and property owners. Further, this work points to four main entrepreneurial venture creation outcomes derived from the core anchor event activities; (1) venture attention, (2) venture idea-realization, (3) venture collaboration, and (4) venture extension. Our findings show that, depending on which anchor event activities are applied, the outcomes vary. Theoretically, this study offers two main implications. First, anchor event activities are both discovered and created, following the logic of causation, at the same time as being experimental, based on “learning by doing” principles of effectuation during the execution. Second, our research enriches prior studies on venture creation as a process. In this work, entrepreneurial venture creation activities and outcomes are understood through pop-up stores as on-site anchor event arenas, particularly suitable for interactivity-based research requested by the entrepreneurship field. This study also reveals important managerial implications, such as that entrepreneurs should allow themselves to find creative physical venture creation arenas (e.g., pop-up stores, showrooms), as well as collaborate with partners when discovering and creating concepts and activities based on new ideas. In this way, they allow themselves to both strategically plan for- and continually experiment with their venture.

Keywords: anchor event, interactivity-based research, pop-up store, entrepreneurial venture creation

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Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

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Authors: Mohadese Oghbaee, Borna Firouzi

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The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Sairoel Amertet, Girma Gebresenbet

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Smart mechatronics systems in agriculture can be traced back to the mid-1980s, when research into automated fruit harvesting systems began in Japan, Europe, and the United States. Since then, impressive advances have been made in smart mechatronics systems. Furthermore, smart mechatronics systems are promising areas, and as a result, we were intrigued to learn more about them. Consequently, the purpose of this study was to examine the smart mechatronic systems that have been applied to agricultural areas so far, with inspiration from the smart mechatronic system in other sectors. To get an overview of the current state of the art, benefits and drawbacks of smart mechatronics systems, various approaches were investigated. Moreover, smart mechatronic modules and various networks applied in agriculture processing were examined. Finally, we explored how the data retrieved using the one-way analysis of variance related to each other. The result showed that there were strongly related keywords for different journals. With the virtually limited use of sophisticated mechatronics in the agricultural industry and, at the same time, the low production rate, the demand for food security has fallen dramatically. Therefore, the application of smart mechatronics systems in agricultural sectors would be taken into consideration in order to overcome these issues.

Keywords: mechatronics, robotic, robotic system, automation, agriculture mechanism

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Authors: Elyce Cardonick, Shistri Dhar, Linsdey Seidman

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Background: When breast cancer is diagnosed during pregnancy, the prognosis is comparable to non-pregnant women matched for prognostic indicators when pregnant women receive treatment without delay. Chemotherapy, including taxanes, can be given during pregnancy with normal neonatal development in exposed fetuses. Methods: Cases of primary breast cancer were extracted from the Cancer and Pregnancy Registry and longitudinal study at Cooper Medical School, which collects cases of pregnant women diagnosed and treated for cancer into a single database. Obstetrical, oncology and pediatric records were reviewed, including annual neonatal developmental, behavioral and medical assessments. Results: 270 pregnant women were diagnosed with primary breast cancer at a mean gestational age of 14.7+9weeks. Mean maternal age at diagnosis 34.5+4.5 years. Receptor status is comparable to non-pregnant women of reproductive age. Forty-nine women were advised to terminate. Two hundred two women underwent surgery;244 women received chemotherapy in pregnancy after the first trimester; the majority of Doxorubucin/Cytoxan; 81 of the cases included a taxane. At a mean of 90 months, follow up obtained on 255 newborns.192/255 newborns are meeting developmental milestones. Respiratory illnesses, including asthma, and bronchiolitis, were reported in 64 newborns, the most common medical condition reported. Thirty-one children are undergoing treatment for GERD, 11 for urinary tract infections, and 7 are undergoing treatment for anemia. Twenty-six children with expressive or articulation language delays, 21/26 are mild. Eleven children with gross/ 7 with fine motor delays. Eight children are treated for ADHD, 4 for anxiety and 4 have social skill impairment. The majority of children with developmental, language or motor delays were born preterm. Conclusion: After chemotherapy exposure in utero for breast cancer, the majority of newborns are meeting developmental milestones and are medically healthy. The goal for treating pregnant women with breast cancer is to aim for delivery close to the term.

Keywords: breast cancer, pregnancy, chemotherapy, newborn

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Z. Olczykowski

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The paper presents the impact of work on the electric arc furnace. Arc equipment is one of the largest receivers powered by the power system. Electric arc disturbances arising during melting process occurring in these furnaces are the cause of an abrupt change of the passive power of furnaces. Currents drawn by these devices undergo an abrupt change, which in turn cause voltage fluctuations and light flicker. The quantitative evaluation of the voltage fluctuations is now the basic criterion of assessment of an influence of unquiet receiver on the supplying net. The paper presents the method of determination of range of voltage fluctuations and light flicker at parallel operation of arc devices. The results of measurements of voltage fluctuations and light flicker indicators recorded in power supply networks of steelworks were presented, with different number of parallel arc devices. Measurements of energy quality parameters were aimed at verifying the proposed method in practice. It was also analyzed changes in other parameters of electricity: the content of higher harmonics, asymmetry, voltage dips.

Keywords: power quality, arc furnaces, propagation of voltage fluctuations, disturbances

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Authors: Ali A. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression, salt and peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Abdulrahman T. Essa, Ahmed Aied, Omar Hamid, Felicity R. A. J. Rose, Kevin M. Shakesheff

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Biodegradable poly(ester amide)s are promising polymers for biomedical applications such as drug delivery and tissue engineering because of their optimized chemical and physical properties. In this study, we developed a biodegradable polyester amide elastomer poly(serinol sebacate) (PSS) composed of crosslinked networks based on serinol and sebacic acid. The synthesized polymers were characterized to evaluate their chemical structures, mechanical properties, degradation behaviors and in vitro cytocompatibility. Analysis of proton nuclear magnetic resonance and Fourier transform infrared spectroscopy revealed the structure of the polymer. The PSS exhibit excellent solubility in a variety of solvents such as methanol, dimethyl sulfoxide and dimethylformamide. More importantly, the mechanical properties of PSS could be tuned by changing the curing conditions. In addition, the 3T3 fibroblast cells cultured on the PSS demonstrated good cell attachment and high viability.

Keywords: biodegradable, biomaterial, elastomer, mechanical properties, poly(serinol sebacate)

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Zemenu Yohannes

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Introduction: The pandemic overstretched the weak health systems in developing countries, including Ethiopia. This study aims to assess and explore the effect of COVID-19 on antenatal care (ANC) provision. Methods: A concurrent mixed methods study was applied. An interrupted time series design was applied for the quantitative study, and in-depth interviews were implemented for the qualitative research to explore maternity care providers' perceptions of ANC provision during COVID-19. We used routine monthly collected data from the health management information system (HMIS) in fifteen hospitals in the Sidama region, Ethiopia, from March 2019 to February 2020 (12 months) before COVID-19 and from March to August 2020 (6 months) during COVID-19. We imported data into STATA V.17 for analysis. ANC provision's mean monthly incidence rate ratio (IRR) was calculated using Poisson regression with a 95% confidence interval. The qualitative data were analysed using thematic analysis. Findings from quantitative and qualitative elements were integrated with a contiguous approach. Results: Our findings indicate the rate of ANC provision significantly decreased in the first six months of COVID-19. This study has three identified main themes: barriers to ANC provision, inadequate COVID-19 prevention approach, and delay in providing ANC. Conclusion and recommendation: Based on our findings, the pandemic affected ANC provision in the study area. The health bureau and stakeholders should take a novel and sustainable approach to prevent future pandemics. The health bureau and hospital administrators should establish a task force that relies on financial self-reliance to close gaps in future pandemics of medical supply shortages. Pregnant women should receive their care promptly from maternity care providers. In order to foster contact and avoid discrimination the future pandemics, hospital administrators should set up a platform for community members and maternity care providers.

Keywords: ANC provision, COVID-19, mixed methods study, Ethiopia

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: Somesh Kumar Sharma, Sunanad Gupta

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The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization.

Keywords: fuel consumption, civil aviation industry, neural networking, optimization

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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Authors: Andrew Laghos

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Computer-assisted language learning (CALL) is defined as the use of computers to help learn languages. In this study we look at several different types of CALL tools and applications and how they can assist Adults and Young Learners in learning the English language as a foreign, second or additional language. It is important to identify the roles of the teacher and the learners, and what the learners’ motivations are for learning the language. Audio, video, interactive multimedia games, online translation services, conferencing, chat rooms, discussion forums, social networks, social media, email communication, songs and music video clips are just some of the many ways computers are currently being used to enhance language learning. CALL may be used for classroom teaching as well as for online and mobile learning. Advantages and disadvantages of CALL are discussed and the study ends with future predictions of CALL.

Keywords: computer-assisted language learning (CALL), teaching English as a foreign language (TEFL/EFL), adult learners, young learners

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Authors: Dilnee D. Suraweera, Tim Groom, Brian Chung, Brendan Bond, Andrew Schipp, Marc E. Nicolas

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Pyrethrum (Tanacetum cinerariifolium) is a perennial plant belongs to family Asteraceae. This is cultivated commercially for extraction of natural insecticide pyrethrins, which accumulates in their flower head achenes. Approximately 94% of the pyrethrins are produced within secretory ducts and trichomes of achenes of the mature pyrethrum flower. This is the most widely used botanical insecticide in the world and Australia is the current largest pyrethrum producer in the world. Rainfall in pyrethrum growing regions in Australia during pyrethrum flowering period, in late spring and early summer is significantly less. Due to lack of adequate soil moisture and under elevated temperature conditions during post-anthesis period, resulting in yield reductions. Therefore, understanding of yield responses of pyrethrum to irrigation is important for Pyrethrum as a commercial crop. Irrigation management has been identified as a key area of pyrethrum crop management strategies that could be manipulated to increase yield. Pyrethrum is a comparatively drought tolerant plant and it has some ability to survive in dry conditions due to deep rooting. But in dry areas and in dry seasons, the crop cannot reach to its full yield potential without adequate soil moisture. Therefore, irrigation is essential during the flowering period prevent crop water stress and maximise yield. Irrigation during the water deficit period results in an overall increased rate of water uptake and growth by the plant which is essential to achieve the maximum yield benefits from commercial crops. The effects of irrigation treatments applied at post-anthesis period on pyrethrum yield responses were studied in two irrigation methods. This was conducted in a first harvest commercial pyrethrum field in Waubra, Victoria, during 2012/2013 season. Drip irrigation and overhead sprinkler irrigation treatments applied during whole flowering period were compared with ‘rainfed’ treatment in relation to flower yield and pyrethrin yield responses. The results of this experiment showed that the application of 180mm of irrigation throughout the post-anthesis period, from early flowering stages to physiological maturity under drip irrigation treatment increased pyrethrin concentration by 32%, which combined with the 95 % increase in the flower yield to give a total pyrethrin yield increase of 157%, compared to the ‘rainfed’ treatment. In contrast to that overhead sprinkler irrigation treatment increased pyrethrin concentration by 19%, which combined with the 60 % increase in the flower yield to give a total pyrethrin yield increase of 91%, compared to the ‘rainfed’ treatment. Irrigation treatments applied throughout the post-anthesis period significantly increased flower yield as a result of enhancement of number of flowers and flower size. Irrigation provides adequate soil moisture for flower development in pyrethrum which slows the rate of flower development and increases the length of the flowering period, resulting in a delayed crop harvest (11 days) compared to the ‘rainfed’ treatment. Overall, irrigation has a major impact on pyrethrin accumulation which increases the rate and duration of pyrethrin accumulation resulting in higher pyrethrin yield per flower at physiological maturity. The findings of this study will be important for future yield predictions and to develop advanced agronomic strategies to maximise pyrethrin yield in pyrethrum.

Keywords: achene, drip irrigation, overhead irrigation, pyrethrin

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Authors: Stefanie Siebenhütter

Abstract:

Men and women use minority and majority languages differently and with varying confidence levels. This paper contrasts gendered differences in language use with socioeconomic status and age factors of minority language speakers in Southeast Asia. Language use and competence are conditioned by the variable of gender. Potential reasons for this variation by examining gendered language awareness and sociolinguistic attitudes will be given. Moreover, it is analyzed whether women in multilingual minority speakers’ society function as 'leaders of linguistic change', as represented in Labov’s sociolinguistic model. It is asked whether the societal role expectations in collectivistic cultures influence the model of linguistic change. The findings reveal speaking preferences and suggest predictions on the prospective language use, which is a stable situation of multilingualism. The study further exhibits differences between male and females identity-forming processes and shows why females are the leaders of (socio-) linguistic change.

Keywords: gender, identity construction, multilingual minorities, linguistic change, social networks

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Authors: Mohammad Parvaresh, Mahdi Babaee, Bahareh Arghand, Roushanak Fahimi Hanzaee, Davood Nourmohammadi

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Today, the intelligent network of water and wastewater as one of the key steps in realizing the smart city in the world. Use of pressure relief valves in urban water networks in order to reduce the pressure is necessary in Tehran city. But use these pressure relief valves lead to waste water, more power consumption, and environmental pollution because Tehran Province Water and Wastewater Co. use a quarter of industry 's electricity. In this regard, Tehran Province Water and Wastewater Co. identified solutions to reduce direct and indirect costs in energy use in the process of production, transmission and distribution of water because this company has extensive facilities and high capacity to realize green economy and industry. The aim of this study is to analyze the new project in water and wastewater industry to reach sustainable development.

Keywords: Tehran Province Water and Wastewater Company, water network efficiency, sustainable development, International Environmental Law

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Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

Abstract:

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

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Authors: Lamaa Sellami, Bechir Alaya

Abstract:

Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

Procedia PDF Downloads 117