Search results for: fuzzy genetic network programming

Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Dina Salem

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A variety of definitions and interpretations for sustainable development has been offered since the widely known definition of the World Commission on Environment and Development in 1987, the perspectives have ranged from deep ecology to better life quality for people. Sustainable landscape is widely understood as a key contributor to urban sustainability for the fact that all landscapes has a social, economic, cultural and ecological function for the community’s well-being and urban development, that was evident even before the emergence of sustainability concept. In this paper, the concepts of landscape planning and sustainable development are briefly reviewed; visions for landscape sustainability are demonstrated and classified. Challenges facing sustainable landscape planning are discussed. Finally, the paper investigates how our future urban open space could be sustainable and how does this contribute to urban sustainability, by creating urban landscapes that takes into account the social and cultural values of users of urban open space besides the ecological balance of urban open spaces as an integrated network.

Keywords: urban landscape, urban sustainability, resilience, open spaces

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Authors: Jaci Marie Mastrandrea, Rosario Haro

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening and intervention is directly associated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project was to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated, evidence-based PC referral criteria. The tool was initially implemented using paper forms, and data was collected over a period of eight weeks. Patients were screened by nurses on the SLCTC oncology treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher received an educational handout on the topic of PC and education about PC and symptom management. A score of five or higher indicates that PC referral is strongly recommended, and the patient’s EHR is flagged for the oncology provider to review orders for PC referral. The PSNA tool was approved by Sky Lakes administration for full integration into Epic-Beacon. The project lead collaborated with the Sky Lakes’ information systems team and representatives from Epic on the tool’s aesthetic and functionality within the Epic system. SLCTC nurses and physicians were educated on how to document the PSNA within Epic and where to view results. Results: Prior to the implementation of the PSNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the completed screening assessments of 100 patients under active treatment at the SLCTC. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting criteria were flagged in EPIC for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met the criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative and supportive care, symptom management, outpatient oncology, palliative screening tool

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: Georgios Boustras, Cleo Varianou Mikellidou, Christos Argyropoulos

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Summer 2021 was marked by a number of prolific fires in the EU (Greece, Cyprus, France) as well as outside the EU (USA, Turkey, Israel). This series of dramatic events have stretched national civil protection systems and first responders in particular. Despite the introduction of National, Regional and International frameworks (e.g. rescEU), a number of challenges have arisen, not only related to climate change. RESPOND-A (funded by the European Commission by Horizon 2020, Contract Number 883371) introduces a unique five-tier project architectural structure for best associating modern telecommunications technology with novel practices for First Responders of saving lives, while safeguarding themselves, more effectively and efficiently. The introduced architecture includes Perception, Network, Processing, Comprehension, and User Interface layers, which can be flexibly elaborated to support multiple levels and types of customization, so, the intended technologies and practices can adapt to any European Environment Agency (EEA)-type disaster scenario. During the preparation of the RESPOND-A proposal, some of our First Responder Partners expressed the need for an information management system that could boost existing emergency response tools, while some others envisioned a complete end-to-end network management system that would offer high Situational Awareness, Early Warning and Risk Mitigation capabilities. The intuition behind these needs and visions sits on the long-term experience of these Responders, as well, their smoldering worry that the evolving threat of climate change and the consequences of industrial accidents will become more frequent and severe. Three large-scale pilot studies are planned in order to illustrate the capabilities of the RESPOND-A system. The first pilot study will focus on the deployment and operation of all available technologies for continuous communications, enhanced Situational Awareness and improved health and safety conditions for First Responders, according to a big fire scenario in a Wildland Urban Interface zone (WUI). An important issue will be examined during the second pilot study. Unobstructed communication in the form of the flow of information is severely affected during a crisis; the flow of information between the wider public, from the first responders to the public and vice versa. Call centers are flooded with requests and communication is compromised or it breaks down on many occasions, which affects in turn – the effort to build a common operations picture for all firstr esponders. At the same time the information that reaches from the public to the operational centers is scarce, especially in the aftermath of an incident. Understandably traffic if disrupted leaves no other way to observe but only via aerial means, in order to perform rapid area surveys. Results and work in progress will be presented in detail and challenges in relation to civil protection will be discussed.

Keywords: first responders, safety, civil protection, new technologies

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: Laura M. F. Bertens

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There is a long tradition of visually representing the art historical canon, in schematic overviews and diagrams. This is indicative of the desire for scientific, ‘objective’ knowledge of the kind (seemingly) produced in the natural sciences. These diagrams will, however, always retain an element of subjectivity and the modelling methods colour our perception of the represented information. In recent decades visualisations of art historical data, such as hand-drawn diagrams in textbooks, have been extended to include digital, computational tools. These tools significantly increase modelling strength and functionality. As such, they might be used to deconstruct and amend the very problem caused by traditional visualisations of the canon. In this paper, the use of digital tools for modelling the art historical canon is studied, in order to draw attention to the artificial nature of the static models that art historians are presented with in textbooks and lectures, as well as to explore the potential of digital, dynamic tools in creating new models. To study the way diagrams of the canon mediate the represented information, two modelling methods have been used on two case studies of existing diagrams. The tree diagram Stammbaum der neudeutschen Kunst (1823) by Ferdinand Olivier has been translated to a social network using the program Visone, and the famous flow chart Cubism and Abstract Art (1936) by Alfred Barr has been translated to an ontological model using Protégé Ontology Editor. The implications of the modelling decisions have been analysed in an art historical context. The aim of this project has been twofold. On the one hand the translation process makes explicit the design choices in the original diagrams, which reflect hidden assumptions about the Western canon. Ways of organizing data (for instance ordering art according to artist) have come to feel natural and neutral and implicit biases and the historically uneven distribution of power have resulted in underrepresentation of groups of artists. Over the last decades, scholars from fields such as Feminist Studies, Postcolonial Studies and Gender Studies have considered this problem and tried to remedy it. The translation presented here adds to this deconstruction by defamiliarizing the traditional models and analysing the process of reconstructing new models, step by step, taking into account theoretical critiques of the canon, such as the feminist perspective discussed by Griselda Pollock, amongst others. On the other hand, the project has served as a pilot study for the use of digital modelling tools in creating dynamic visualisations of the canon for education and museum purposes. Dynamic computer models introduce functionalities that allow new ways of ordering and visualising the artworks in the canon. As such, they could form a powerful tool in the training of new art historians, introducing a broader and more diverse view on the traditional canon. Although modelling will always imply a simplification and therefore a distortion of reality, new modelling techniques can help us get a better sense of the limitations of earlier models and can provide new perspectives on already established knowledge.

Keywords: canon, ontological modelling, Protege Ontology Editor, social network modelling, Visone

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Authors: Kalidas Sarma

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Fraud is a social problem changing with social change and it has a regional and global impact. Introduction of private domain in higher education along with public institutions has led to commercialization of higher education which encourages unprecedented mushrooming of private institutions resulting in fraudulent activities in higher educational institutions in Assam, India. Presently, fraud has been noticed in in-service promotion, fake entry qualification by teachers in different levels of work-place by using fake master degrees, master of philosophy and doctor of philosophy degree certificates. The aim and objective of the study are to identify grey areas in maintenance of quality in higher educational institutions in Assam and also to draw the contour for planning and implementation. This study is based on both primary and secondary data collected through questionnaire and seeking information through Right to Information Act 2005. In Assam, there are 301 undergraduate and graduate colleges distributed in 27 (Twenty seven) administrative districts with 11000 (Eleven thousand) college teachers. Total 421 (Four hundred twenty one) college teachers from the 14 respondent colleges have been taken for analysis. Data collected has been analyzed by using 'Hypertext Pre-processor' (PhP) application with My Sequel Structure Query Language (MySQL) and Google Map Application Programming Interface (APIs). Graph has been generated by using open source tool Chart.js. Spatial distribution maps have been generated with the help of geo-references of the colleges. The result shows: (i) the violation of University Grants Commission's (UGCs) Regulation for the awards of M. Phil/Ph.D. clearly exhibits. (ii) There is a gap between apex regulatory bodies of higher education at national and as well as state level to check fraud. (iii) Mala fide 'No Objection Certificate' (NOC) issued by the Government of Assam have played pivotal role in the occurrence of fraudulent practices in higher educational institutions of Assam. (iv) Violation of verdict of the Hon'ble Supreme Court of India regarding territorial jurisdiction of Universities for the awards of Ph.D. and M. Phil degrees in distance mode/study centre is also a responsible factor for the spread of these academic frauds in Assam and other states. The challenges and mitigation of these issues have been discussed.

Keywords: Assam, fraud, higher education, mitigation

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Authors: M. S. Gaafar, S. Y. Marzouk, I. S. Mahmoud, S. Al-Zobaidi

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Makishima and Mackenzie model was used to simulation of acoustic properties (longitudinal and shear ultrasonic wave velocities, elastic moduli theoretically for many tellurite and borate glasses. The model was proposed mainly depending on the values of the experimentally measured density, which are obtained before. In this search work, we are trying to obtain the values of densities of amorphous glasses (as the density depends on the geometry of the network structure of these glasses). In addition, the problem of simulating the slope of linear regression between the experimentally determined bulk modulus and the product of packing density and experimental Young's modulus, were solved in this search work. The results showed good agreement between the experimentally measured values of densities and both ultrasonic wave velocities, and those theoretically determined.

Keywords: glasses, ultrasonic wave velocities, elastic modulus, Makishima & Mackenzie Model

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Authors: Hanan Mohamed Abd Elmoneim, Rawan Saleh AlJawi, Razan Saleh AlJawi, Aseel Abdullah AlMasoudi , Zyad Adnan Turkistani, Anas Abdulkarim Alkhoutani , Ohood Musaed AlJuhani , Hanan Attiyah AlZahrani

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Background Esophageal cancer is the eighth most common cancer worldwide. More than 90% of esophageal cancers are either squamous cell carcinoma or adenocarcinoma. Squamous dysplasia is a precancerous lesion for squamous cell carcinoma and Barrett's esophagus is the precancerous lesion for adenocarcinoma. Gastro-esophageal reflux disease (GERD) is the initiation factor for Barrett's esophagus. Cyclooxygenase-2 (COX-2) is a key enzyme in arachidonic metabolism. It appears to play an important role in gastrointestinal carcinogenesis. COX-2 activity may be a potential target for the prevention of cancer progression by selective COX-2 inhibitors, which decrease proliferation and increase apoptosis. Objectives To assess COX-2 expression in premalignant and malignant esophageal epitheliums changes and detect its roles in progression of these lesions. Materials and Methods We analyzed the expression of COX-2 immunohistochemically in 40 esophageal biopsies utilizing the streptavidin-biotin-peroxidase complex method on archival formalin fixed-paraffin embedded blocks. Histopathologically, 17 (42.5%) of cases were non-malignant cases which included GERD, Barrett's esophagus and squamous dysplasia. The malignant cases were 23 (57.5%) squamous cell carcinoma, adenocarcinoma and undifferentiated carcinoma. Results In non-malignant cases 7 (41.2%) out of 17 cases had high COX-2 expression. In squamous cell carcinoma 10 (83.3%) out of 12 cases had high COX-2 expression. The expression of COX-2 was high in all 9 (100%) cases of adenocarcinoma. COX-2 expression is significantly increased (P=0.005 and P=0.0001) in squamous cell carcinoma and adenocarcinoma respectively. There was a significant difference in COX-2 immunoreactivity between malignant and non-malignant lesions (P=0.0003). Conclusion COX-2 is responsible for the progression of esophageal diseases from benign to malignant. We recommend that COX-2 immunohistochemistry should be done routinely for premalignant and malignant esophageal lesions as selective COX-2 inhibitors will be helpful in the treatment. Further studies on molecular and genetic basis of COX-2 expression are needed to unmask its role and relation to progression of esophageal lesions.

Keywords: Cox-2, Esophageal adinocarcinoma, Esophageal squamous cell carcinoma, Immunohistochemistry.

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Authors: Sadaf Moeez, Madiha Khalid, Zoya Khalid, Sania Shaheen, Sumbul Khalid

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Background: Inter-individual variation in response to metformin, which has been considered as a first line therapy for T2DM treatment is considerable. In the current study, it was aimed to investigate the impact of two genetic variants Leu125Phe (rs77474263) and Gly64Asp (rs77630697) in gene SLC47A1 on the clinical efficacy of metformin in T2DM Pakistani patients. Methods: The study included 800 T2DM patients (400 metformin responders and 400 metformin non-responders) along with 400 ethnically matched healthy individuals. The genotypes were determined by allele-specific polymerase chain reaction. In-silico analysis was done to confirm the effect of the two SNPs on the structure of genes. Association was statistically determined using SPSS software. Results: Minor allele frequency for rs77474263 and rs77630697 was 0.13 and 0.12. For SLC47A1 rs77474263 the homozygotes of one mutant allele ‘T’ (CT) of rs77474263 variant were fewer in metformin responders than metformin non-responders (29.2% vs. 35.5 %). Likewise, the efficacy was further reduced (7.2% vs. 4.0 %) in homozygotes of two copies of ‘T’ allele (TT). Remarkably, T2DM cases with two copies of allele ‘C’ (CC) had 2.11 times more probability to respond towards metformin monotherapy. For SLC47A1 rs77630697 the homozygotes of one mutant allele ‘A’ (GA) of rs77630697 variant were fewer in metformin responders than metformin non-responders (33.5% vs. 43.0 %). Likewise, the efficacy was further reduced (8.5% vs. 4.5%) in homozygotes of two copies of ‘A’ allele (AA). Remarkably, T2DM cases with two copies of allele ‘G’ (GG) had 2.41 times more probability to respond towards metformin monotherapy. In-silico analysis revealed that these two variants affect the structure and stability of their corresponding proteins. Conclusion: The present data suggest that SLC47A1 Leu125Phe (rs77474263) and Gly64Asp (rs77630697) polymorphisms were associated with the therapeutic response of metformin in T2DM patients of Pakistan.

Keywords: diabetes, T2DM, SLC47A1, Pakistan, polymorphism

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Ramon Hernán, Maria Teresa Corzo

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This study examines the impact and contribution of the main journals in the discipline of behavioral finance to determine the state of the art of the discipline and the growth lines and concepts studied to date. This is a unique and novel study given that a review of the discipline has not been carried out through the keywords of the articles that allows visualizing through this component of the research, which are the main topics of discussion and the relationships that arise between the concepts discussed. To carry out this study, 3,876 articles have been taken as a reference, which includes 15,859 keywords from the main journals responsible for the growth of the discipline.; Journal of Behavioral Finance, Review of Behavioral Finance, Journal of Behavioral and Experimental Economics, Journal of Behavioral and Experimental Economics and Review of Behavioral Finance. The results indicate which are the topics most covered in the discipline throughout the period from 2000 to 2020, how these concepts have been dealt with on a recurring basis along with others throughout the aforementioned period and how the different concepts have been grouped based on the keywords established by the authors for the classification of their articles with a network diagram to complete the analysis.

Keywords: behavioral finance, keywords, co-words, top journals, data visualization

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Authors: Amal M. Alrayes, Hayat M. Ali

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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

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Authors: M. Soubadra Devy, Savitha Swamy, Chethana V. Casiker

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Sustainable smart cities are emerging as an important concept in response to the exponential rise in the world’s urbanizing population. While earlier, only technical, economic and governance based solutions were considered, more and more layers are being added in recent times. With the prefix of 'sustainability', solutions which help in judicious use of resources without negatively impacting the environment have become critical. We present a case study of Bangalore city which has transformed from being a garden city and pensioners' paradise to being an IT city with a huge, young population from different regions and diverse cultural backgrounds. This has had a big impact on the green spaces in the city and the biodiversity that they support, as well as on farming/gardening practices. Edible landscapes comprising farms lands, home gardens and neighbourhood parks (NPs henceforth) were examined. The land prices of areas having NPs were higher than those that did not indicate an appreciation of their aesthetic value. NPs were part of old and new residential areas largely managed by the municipality. They comprised manicured gardens which were similar in vegetation structure and composition. Results showed that NPs that occurred in higher density supported reasonable levels of biodiversity. In situations where NPs occurred in lower density, the presence of a larger green space such as a heritage park or botanical garden enhanced the biodiversity of these parks. In contrast, farm lands and home gardens which were common within the city are being lost at an unprecedented scale to developmental projects. However, there is also the emergence of a 'neo-culture' of home-gardening that promotes 'locovory' or consumption of locally grown food as a means to a sustainable living and reduced carbon footprint. This movement overcomes the space constraint by using vertical and terrace gardening techniques. Food that is grown within cities comprises of vegetables and fruits which are largely pollinator dependent. This goes hand in hand with our landscape-level study that has shown that cities support pollinator diversity. Maintaining and improving these man-made ecosystems requires analysing the functioning and characteristics of the existing structures of governance. Social network analysis tool was applied to NPs to examine relationships, between actors and ties. The management structures around NPs, gaps, and means to strengthen the networks from the current state to a near-ideal state were identified for enhanced services. Learnings from NPs were used to build a hypothetical governance structure and functioning of integrated governance of NPs and edible landscapes to enhance ecosystem services such as biodiversity support, food production, and aesthetic value. They also contribute to the sustainability axis of smart cities.

Keywords: biodiversity support, ecosystem services, edible green spaces, neighbourhood parks, sustainable smart city

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Authors: Samira Khalil, Adib Saad, Malek Ali

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The aim of this research is to determine fish species belonging to the order Pleuronectiforme fish found in Syrian marine water confirm or deny the continuity of the previously registered species, and record the unregistered species that appeared during this research for the first time. The research was carried out in the Laboratory of Marine Sciences, Faculty of Agriculture (Tishreen University); fish samples were collected periodically (bi-monthly) from fishermen in landing areas along the Syrian coast caught from depths (3m to 700m), using various mediums. An appropriate hand is available to fishermen on the Syrian coast (cliff bottom, fixed nets, enclosure nets, shelf nest, and manual disposal network; 451 individuals were captured and studied during the research period. During this study, it was found that the Syrian water includes 15 species, including one species recorded for the first time. On the eastern coast of the Mediterranean, it is Pegusa impar.

Keywords: pleuronectiformes, Syrian coast, flatfish, mediterranean

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Authors: Rida Pervaiz, Bushra Allah Rakha, Muhammad Sajjad Ansari, Shamim Akhter, Kainat Waseem, Sumiyyah Zuha, Tooba Javed

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Ring-necked pheasant (Phasianus colchicus) belongs to order Galliformes and family Phasianidae. It has been recognized as the most hunted bird due to its attractive colorful appearance and meat. Loss of habitat and hunting pressure has caused population fluctuations in the native range. Under these circumstances, this species can be conserved by employing ex-situ in vitro conservation techniques. Captive breeding, in combination with semen cryobanking is the most appropriate option to conserve/propagate this species without deteriorating the genetic diversity. Cryopreservation protocols of adequate efficiency are necessary to establish semen cryobanking for a species. Therefore, present study was designed to devise an efficient extender for cryopreservation of ring-necked pheasant semen. For this purpose, a range of extenders (Beltsville Poultry, red fowl, Lake, EK, Tselutin Poultry and Chicken semen extenders) were evaluated for cryopreservation of ring-necked pheasant semen. Semen collected from 10 cocks, diluted in the Beltsville Poultry (BPSE), Red Fowl (RFE), Lake (LE), EK (EKE), Tselutin Poultry (TPE) and Chicken Semen (CSE) extenders and cryopreserved. Glycerol (10%) was added to semen at 4°C, equilibrated for 10 min, filled in 0.5 mL French straws, kept over liquid nitrogen vapors for 10 min, cryopreserved in LN2 and stored. Sperm motility (%), viability (%), live/dead ratio (%), plasma membrane (%) and DNA Integrity (%) were evaluated at post-dilution, post-cooling, post-equilibration and post-thawing stage of cryopreservation. Sperm motility (83.8 ± 3.1; 81.3 ± 3.8; 73.8 ± 2.4; 62.5 ± 1.4), viability (79.0 ± 1.7; 75.5 ± 1.6; 69.5 ± 2.3; 65.5 ± 2.4), live/dead ratio (80.5 ± 5.7; 77.3 ± 4.9; 76.0 ± 2.7; 68.3 ± 2.3), plasma membrane (74.5 ± 2.9; 73.8 ± 3.4; 71.3 ± 2.3; 75.0 ± 3.4) and DNA integrity (78.3 ± 1.7; 73.0 ± 1.2; 68.0 ± 2.0; 63.0 ± 2.5) at all four stages of cryopreservation were recorded higher (P < 0.05) in red fowl extender compared to all experimental extenders. It is concluded that red fowl extender is the best extender for cryopreservation of ring-necked pheasant semen and can be used in establishing cryobank for ex situ conservation.

Keywords: ring-necked pheasant; extenders; cryopreservation; semen quality; DNA integrity

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Debora P. Arce, Flavia J. Krsticevic, Marco R. Bertolaccini, Joaquín Ezpeleta, Estela M. Valle, Sergio D. Ponce, Elizabeth Tapia

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Small Heat Shock Proteins (sHSPs) are low molecular weight chaperones that play an important role during stress response and development in all living organisms. Fruit maturation and oxidative stress can induce sHSP synthesis both in Arabidopsis and tomato plants. RNA-Seq technology is becoming widely used in various transcriptomics studies; however, analyzing and interpreting the RNA-Seq data face serious challenges. In the present work, we de novo assembled the Solanum lycopersicum transcriptome for three different maturation stages (mature green, breaker and red ripe). Differential gene expression analysis was carried out during tomato fruit development. We identified 12 sHSPs differentially expressed that might be involved in breaker and red ripe fruit maturation. Interestingly, these sHSPs have different subcellular localization and suggest a complex regulation of the fruit maturation network process.

Keywords: sHSPs, maturation, tomato, RNA-Seq, assembly

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Authors: Adekunle K. O, Adeniyi A. E, Kolawole E

Abstract:

One of the most dramatic trends in the communications market in recent years has been the growth of prepaid services. Today, prepaid no longer constitutes the low-revenue, basic-service segment. It is driven by a high margin, value-add service customers who view it as a convenient way of retaining control over their usage and communication spending while expecting high service levels. To service providers, prepaid services offer the advantage of reducing bad accounts while allowing them to predict usage and plan network resources. Yet, the real-time demands of prepaid services require a scalable, real-time platform to manage customers through their entire life cycle. It delivers integrated real-time rating, voucher management, recharge management, customer care and service provisioning for the generation of new prepaid services. It carries high scalability that can handle millions of prepaid customers in real-time through their entire life cycle.

Keywords: prepaid billing, voucher management, customers, automated, security

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Authors: Vangelis Papadimitropoulos

Abstract:

This paper is part of the research program “Techno-Social Innovation in the Collaborative Economy”, funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) for the years 2022-2024. The paper showcases the Open Food Network (OFN) as an open-sourced digital platform supporting short food supply chains in local agricultural production and consumption. The paper outlines the research hypothesis, the theoretical framework, and the methodology of research as well as the findings and conclusions. Research hypothesis: The model of open cooperativism as a vehicle for systemic change in the agricultural sector. Theoretical framework: The research reviews the OFN as an illustrative case study of the three-zoned model of open cooperativism. The OFN is considered a paradigmatic case of the model of open cooperativism inasmuch as it produces commons, it consists of multiple stakeholders including ethical market entities, and it is variously supported by local authorities across the globe, the latter prefiguring the mini role of a partner state. Methodology: Research employs Ernesto Laclau and Chantal Mouffe’s discourse analysis -elements, floating signifiers, nodal points, discourses, logics of equivalence and difference- to analyse the breadth of empirical data gathered through literature review, digital ethnography, a survey, and in-depth interviews with core OFN members. Discourse analysis classifies OFN floating signifiers, nodal points, and discourses into four themes: value proposition, governance, economic policy, and legal policy. Findings: OFN floating signifiers align around the following nodal points and discourses: “digital commons”, “short food supply chains”, “sustainability”, “local”, “the elimination of intermediaries” and “systemic change”. The current research identifies a lack of common ground of what the discourse of “systemic change” signifies on the premises of the OFN’s value proposition. The lack of a common mission may be detrimental to the formation of a common strategy that would be perhaps deemed necessary to bring about systemic change in agriculture. Conclusions: Drawing on Laclau and Mouffe’s discourse theory of hegemony, research introduces a chain of equivalence by aligning discourses such as “agro-ecology”, “commons-based peer production”, “partner state” and “ethical market entities” under the model of open cooperativism, juxtaposed against the current hegemony of neoliberalism, which articulates discourses such as “market fundamentalism”, “privatization”, “green growth” and “the capitalist state” to promote corporatism and entrepreneurship. Research makes the case that for OFN to further agroecology and challenge the current hegemony of industrial agriculture, it is vital that it opens up its supply chains into equivalent sectors of the economy, civil society, and politics to form a chain of equivalence linking together ethical market entities, the commons and a partner state around the model of open cooperativism.

Keywords: sustainability, the digital commons, open cooperativism, innovation

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Authors: Mahdi Bazarganigilani

Abstract:

Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Toushik Maiti, Saibal Chatterjee, Kamaljyoti Gogoi, Arijit Basuray

Abstract:

Eastern Regional(ER) Grid and North Eastern Regional (NER) Grid are two major grids of Eastern Part of India. Both of the grid consists of voltage level 765kV, 400 kV, 220 kV and numerous buses at lower voltage range. Eastern Regional Grid and North Eastern Regional Grid are not only connected among themselves but are also connected to various other grids of India. ER and NER Grid having various HVDC lines or back to back systems which form the total network. The studied system comprises of 340 buses of different voltage levels and transmission lines running over a length of 32089 km. The validation of load flow has been done using IEEE STANDARD 30 bus system. The power flow simulation analysis has been performed after synchronizing both the Eastern Grid and North-Eastern Regional Grid of India using Power System Simulators for Engineering (PSS®E) Important inferences has been drawn from the study.

Keywords: HVDC, load flow, PSS®E, unsymmetrical and symmetrical faults

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Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spread-sheet developers competency over a network. It is designed to automatically and autonomously monitor spread-sheet users and gather their development activities based on the utilization of the software Multi-Agent Technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spread-sheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: classification, design, MACS, MAS, prometheus

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

Abstract:

Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Kun Xue, Lvlan Miu, Jiarui Li

Abstract:

Jetting structures are widely found in particle rings or shells dispersed by the central explosion. In contrast, some explosive dispersal of particles only results in a dispersed cloud without distinctive structures. Employing the coupling method of the compressible computational fluid mechanics and discrete element method (CCFD-DEM), we reveal the underlying physics governing the formation of the jetting structure, which is related to the competition between the shock compaction and gas infiltration, two major processes during the shock interaction with the granular media. If the shock compaction exceeds the gas infiltration, the discernable jetting structures are expected, precipitated by the agglomerates of fast-moving particles induced by the heterogenous network of force chains. Otherwise, particles are uniformly accelerated by the interstitial flows, and no distinguishable jetting structures are formed. We proceed to devise the phase map of the jetting formation in the space defined by two dimensionless parameters which characterize the timescales of the shock compaction and the gas infiltration, respectively.

Keywords: compressible multiphase flows, DEM, granular jetting, pattern formation

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Authors: Samiah Alammari, Nassim Ammour

Abstract:

When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Ourn Vimoil, Kallaya Suntornvongsagul

Abstract:

Cambodia is considered as one of the most disaster prone countries in South East Asia, and most of natural disasters are related to floods. Cambodia, a developing country, faces significant impacts from floods, such as environmental, social, and economic losses. Using data accessed from focus group discussions and field surveys with villagers in Ba Baong commune, prey Veng province, Cambodia, the research would like to examine roles of social networks in raising community’s coping capacity with floods. The findings indicate that social capital play crucial roles in three stages of floods, namely preparedness, response, and recovery to overcome the crisis. People shared their information and resources, and extent their assistances to one another in order to adapt to floods. The study contribute to policy makers, national and international agencies working on this issue to pay attention on social networks as one factors to accelerate flood coping capacity at community level.

Keywords: social network, community, coping capacity, flood, Cambodia

Procedia PDF Downloads 351