Search results for: lymph nodes

Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

Procedia PDF Downloads 105

Authors: Wissam Saliba, Mandy Nicholson

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Secretory carcinoma (SC) is a rare type of salivary gland cancer. It was first realized as a distinct type of malignancy in 2010and wasinitially termed “mammary analogue secretory carcinoma” because of similarities with secretory breast cancer. The name was later changed to SC. Most SCs originate in parotid glands, and most harbour a rare gene mutation: ETV6-NTRK3. This mutation is rare in common cancers and common in rare cancers; it is present in most secretory carcinomas. Disease outcomes for SC are usually described as favourable as many cases of SC are lowgrade (LG), and cancer growth is slow. In early stages, localized therapy is usually indicated (surgery and/or radiation). Despitea favourable prognosis, a sub-set of casescan be much more aggressive.These cases tend to be of high-grade(HG).HG casesare associated with a poorer prognosis.Management of such cases can be challenging due to limited evidence for effective systemic therapy options. This case report describes the clinical management of a 46-year-oldmale patient with a unique case of SC. He was initially diagnosed with a low/intermediate grade carcinoma of the left parotid gland in 2009; he was treated with surgery and adjuvant radiation. Surgical pathology favoured primary salivary adenocarcinoma, and 2 lymph nodes were positive for malignancy. SC was not yet realized as a distinct type of cancerat the time of diagnosis, and the pathology reportvalidated this gap by stating that the specimen lacked features of the defined types of salivary carcinoma.Slow-growing pulmonary nodules were identified in 2017. In 2020, approximately 11 years after the initial diagnosis, the patient presented with malignant pleural effusion. Pathology from a pleural biopsy was consistent with metastatic poorly differentiated cancer of likely parotid origin, likely mammary analogue secretory carcinoma. The specimen was sent for Next Generation Sequencing (NGS); ETV6-NTRK3 gene fusion was confirmed, and systemic therapy was initiated.One cycle ofcarboplatin/paclitaxel was given in June 2020. He was switched to Larotrectinib (NTRK inhibitor (NTRKi)) later that month. Larotrectinib continued for approximately 9 months, with discontinuation in March 2021 due to disease progression. A second-generation NTRKi (Selitrectinib) was accessed and prescribedthrough a single patient study. Selitrectinib was well tolerated. The patient experienced a complete radiological response within~4 months. Disease progression occurred once again in October 2021. Progression was slow, and Selitrectinib continuedwhile the medical team performed a thorough search for additional treatment options. In January 2022, a liver lesion biopsy was performed, and NGS showed an NTRKG623R solvent-front resistance mutation. Various treatment pathways were considered. The patient pursuedanother investigational NTRKi through a clinical trial, and Selitrectinib was discontinued in July 2022. Excellent performance status was maintained throughout the entire course of treatment.It can be concluded that NTRK inhibitors provided satisfactory treatment efficacy and tolerance for this patient with high-grade transformation and NTRK gene fusion cancer. In the future, more clinical research is needed on systemic treatment options for high-grade transformations in NTRK gene fusion SCs.

Keywords: secretory carcinoma, high-grade transformations, NTRK gene fusion, NTRK inhibitor

Procedia PDF Downloads 92

Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

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Authors: Bsma Adel Bany Mohammad

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The University campuses are a small city containing basic city functions such as educational spaces, accommodations, services and transportation. They are spaces of functional and social life with different activities, different occupants. The campus designed and transformed like cities so both experienced and memorized in same way. Campus memory is the ability of individuals to maintain and reveal the spatial components of designed physical spaces, which form the understandings, experiences, sensations of the environment in all. ‘Cognitive mapping’ is used to decode the physical interaction and emotional relationship between individuals and the city; Cognitive maps are created graphically using geometric and verbal elements on paper by remembering the images of the Urban Environment. In this study, to determine the emotional urban identity belonging to Jordan University of science and technology Campus, architecture students Asked to identify the areas they interact with in the campus by drawing a cognitive map. ‘Campus memory items’ are identified by analyzing the cognitive maps of the campus, then the spatial identity result of such data. The analysis based on the five basic elements of Lynch: paths, districts, edges, nodes, and landmarks. As a result of this analysis, it found that Spatial Identity constructed by the shared elements of the maps. The memory of most students listed the gates structure- which is a large desirable structure, located at the main entrances within the campus defined as major landmarks, then the square spaces defined as nodes, in addition to both stairs and corridors defined as paths. Finally, the districts, edges of educational buildings and service spaces are listed correspondingly in cognitive maps. Findings suggest that the spatial identity of the campus design is related mainly to the gates structures, squares and stairs.

Keywords: cognitive maps, university campus, urban memory, identity

Procedia PDF Downloads 128

Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

Procedia PDF Downloads 238

Authors: Ghada Esheba, Bayan Hafiz, Ashwaq Al-Qarni, Abdulelah AlMalki, Esraa Kaheel

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Hydatid disease is caused by genus Echinococcus, it is transmitted to human through sheep and cattle. People who lived in an endemic area should be suspected to have the disease. Pulmonary hydatid disease can be presented by respiratory manifestations as in our case. We report a case of child, 13 years old, who was presented by shortness of breath and non-productive cough 2 months ago. The patient had an attack of hemoptysis 3 months ago but there is no history of fever, other constitutional symptoms or any medical illness. The patient has had a close contact with a horse. On examination, the patient was oriented and vitally stable. Both side of chest were moving equally with decrease air entry on the left side of the chest. Cervical lymph node enlargement was also detected. The case was provisionally diagnosed as tuberculosis. The x-ray was normal, while CT scan showed two cysts in the left side. The patient was treated surgically with resection of both cysts without lobectomy. Broncho-alveolar lavage was done and together with plural effusion and both cysts were sent for histopathology. The patient received the following medication: albendazole 200MG/BID/Orally for 30 days and Cefuroxime 250MG/Q12H/Orally for 10 days.

Keywords: Echinococcus granulosus, hydatid disease, pediatrics, pulmonary hydatid cyst

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Authors: Khalifa Kherafa

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This east project consists in studying beam–column joints concrete subjected to seismic loads. A bibliographical study was introduced to clarify the work undertaken by the researchers in the field during the three last decades and especially the two last year’s results which were to study for the determination of the method of calculating of transverse reinforcement in the various nodes of a structure. For application, the efforts in the posts el the beams of a building in R+4 in zone 3 were calculate according to the finite element method through the software .

Keywords: beam–column joints, cyclic loading, shearing force, damaged joint

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Authors: Boonsri Lertviriyachit

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The objective of this research is to investigate the treatment of psoriasis through Thai traditional medicine in the selected areas of 2 east coast provinces; Samudprakarn Province and Chantaburi Province. The informants in this study were two famous and accepted Thai traditional doctors, who have more than 20 year experiences. Data were collected by in depth interviews and participant-observation method. The research instrument included unstructured interviews, camera, and cassette tape to collect data analyzed by descriptive statistics. The results revealed that the 2 Thai traditional doctors were 54 and 85 years old with 25 and 45 years of treatment experiences. The knowledge of Thai traditional medicine was transferred from generations to generations in the family. The learning process was through close observation as an apprentice with the experience ones and assisted them in collecting herbs and learning by handling real case in individual situations. Before being doctors, they had to take exam to get the Thai traditional medical certificate. Knowledge of being Thai traditional doctors included diagnosis and find to the suitable way of treatment. They have to look into disorder physical fundamental factors such as blood circulation, lymph, emotion, and food consumption habit. It is important that the treatment needs to focus on balancing the fundamental factors and to observe contraindication.

Keywords: Thai traditional medicine, psoriasis, Samudprakarn Province, Chantaburi Province

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

Procedia PDF Downloads 362

Authors: Zimu Li, Zheng Wan

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The Suez Canal plays an important role in global shipping networks and is one of the most frequently used waterways in the world. The 2021 canal obstruction by ship Ever Given in March 2021, however, completed blocked the Suez Canal for a week and caused significant disruption to world trade. Therefore, it is very important to quantitatively analyze the impact of the accident on the robustness of the global shipping network. However, the current research on maritime transportation networks is usually limited to local or small-scale networks in a certain region. Based on the complex network theory, this study establishes a global shipping complex network covering 2713 nodes and 137830 edges by using the real trajectory data of the global marine transport ship automatic identification system in 2018. At the same time, two attack modes, deliberate (Suez Canal Blocking) and random, are defined to calculate the changes in network node degree, eccentricity, clustering coefficient, network density, network isolated nodes, betweenness centrality, and closeness centrality under the two attack modes, and quantitatively analyze the actual impact of Suez Canal Blocking on the robustness of global shipping network. The results of the network robustness analysis show that Suez Canal blocking was more destructive to the shipping network than random attacks of the same scale. The network connectivity and accessibility decreased significantly, and the decline decreased with the distance between the port and the canal, showing the phenomenon of distance attenuation. This study further analyzes the impact of the blocking of the Suez Canal on Chinese ports and finds that the blocking of the Suez Canal significantly interferes withChina's shipping network and seriously affects China's normal trade activities. Finally, the impact of the global supply chain is analyzed, and it is found that blocking the canal will seriously damage the normal operation of the global supply chain.

Keywords: global shipping networks, ship AIS trajectory data, main channel, complex network, eigenvalue change

Procedia PDF Downloads 152

Authors: Hamidreza Jahani, Zahra Salehzadeh, Ehsan Amini, Mohsen Tohidifar

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Calvarial Hyperostosis Syndrome (CHS) is a benign bone disease of the skull. It is a non-neoplastic and proliferative bone disease, and the main feature of the disease is progressive and asymmetrical bone involvement. CHS is mostly reported in young male and female bullmastiff dogs and less frequently in other breeds. The etiology of CHS is unknown. This is the first case report of CHS in Iran. A 3-month-old male Persian Mastiff was presented with chief complaints of multiple episodes of seizure, pacing, bizarre behavior, delayed growth, head pressing, and difficulty in opening the mouth. Central blindness and open fontanelles were observed in clinical examination. No abnormality was found in the complete blood count and routine blood biochemical tests. CT scan findings include cortical thickening of frontal and parietal bones and enlargement of the left retropharyngeal lymph node. For treatment, oral clindamycin for two weeks, prednisolone and phenobarbital for one month, respectively, were administrated, and the case showed improvement after a week and recovered after one month.

Keywords: calvarial hyperostosis, Persian Mastiff, frontal bone, seizure

Procedia PDF Downloads 117

Authors: Gabriela Wyszogrodzka, Przemyslaw Dorozynski, Barbara Gil, Maciej Strzempek, Bartosz Marszalek, Piotr Kulinowski, Wladyslaw Piotr Weglarz, Elzbieta Menaszek

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MOFs (Metal-Organic Frameworks) belong to a new group of porous materials with a hybrid organic-inorganic construction. Their structure is a network consisting of metal cations or clusters (acting as metallic centers, nodes) and the organic linkers between nodes. The interest in MOFs is primarily associated with the use of their well-developed surface and large porous. Possibility to build MOFs of biocompatible components let to use them as potential drug carriers. Furthermore, forming MOFs structure from cations possessing paramagnetic properties (e.g. iron cations) allows to use them as MRI (Magnetic Resonance Imaging) contrast agents. The concept of formation of particles that combine the ability to transfer active substance with imaging properties has been called theranostic (from words combination therapy and diagnostics). By building MOF structure from iron cations it is possible to use them as theranostic agents and monitoring the distribution of the active substance after administration in real time. In the study iron-MOF: Fe-MIL-101-NH2 was chosen, consisting of iron cluster in nodes of the structure and amino-terephthalic acid as a linker. The aim of the study was to investigate the possibility of applying Fe-MIL-101-NH2 as inhalable theranostic particulate system for the first-line anti-tuberculosis antibiotic – isoniazid. The drug content incorporated into Fe-MIL-101-NH2 was evaluated by dissolution study using spectrophotometric method. Results showed isoniazid encapsulation efficiency – ca. 12.5% wt. Possibility of Fe-MIL-101-NH2 application as the MRI contrast agent was demonstrated by magnetic resonance tomography. FeMIL-101-NH2 effectively shortening T1 and T2 relaxation times (increasing R1 and R2 relaxation rates) linearly with the concentrations of suspended material. Images obtained using multi-echo magnetic resonance imaging sequence revealed possibility to use FeMIL-101-NH2 as positive and negative contrasts depending on applied repetition time. MOFs micronization via ultrasound was evaluated by XRD, nitrogen adsorption, FTIR, SEM imaging and did not influence their crystal shape and size. Ultrasonication let to break the aggregates and achieve very homogeneously looking SEM images. MOFs cytotoxicity was evaluated in in vitro test with a highly sensitive resazurin based reagent PrestoBlue™ on L929 fibroblast cell line. After 24h no inhibition of cell proliferation was observed. All results proved potential possibility of application of ironMOFs as an isoniazid carrier and as MRI contrast agent in inhalatory treatment of tuberculosis. Acknowledgments: Authors gratefully acknowledge the National Science Center Poland for providing financial support, grant no 2014/15/B/ST5/04498.

Keywords: imaging agents, metal-organic frameworks, theranostics, tuberculosis

Procedia PDF Downloads 228

Authors: M. Regina Carreira-Lopez

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Lightweight ontologies seek to concrete union relationships between a parent node, and a secondary node, also called "child node". This logic relation (L) can be formally defined as a triple ontological relation (LO) equivalent to LO in ⟨LN, LE, LC⟩, and where LN represents a finite set of nodes (N); LE is a set of entities (E), each of which represents a relationship between nodes to form a rooted tree of ⟨LN, LE⟩; and LC is a finite set of concepts (C), encoded in a formal language (FL). Mondoc enables more refined searches on semantic and classified facets for retrieving specialized knowledge about Atlantic migrations, from the Declaration of Independence of the United States of America (1776) and to the end of the Spanish Civil War (1939). The model looks forward to increasing documentary relevance by applying an inverse frequency of co-ocurrent hypernymy phenomena for a concrete dataset of textual corpora, with RMySQL package. Mondoc profiles archival utilities implementing SQL programming code, and allows data export to XML schemas, for achieving semantic and faceted analysis of speech by analyzing keywords in context (KWIC). The methodology applies random and unrestricted sampling techniques with RMySQL to verify the resonance phenomena of inverse documentary relevance between the number of co-occurrences of the same term (t) in more than two documents of a set of texts (D). Secondly, the research also evidences co-associations between (t) and their corresponding synonyms and antonyms (synsets) are also inverse. The results from grouping facets or polysemic words with synsets in more than two textual corpora within their syntagmatic context (nouns, verbs, adjectives, etc.) state how to proceed with semantic indexing of hypernymy phenomena for subject-heading lists and for authority lists for documentary and archival purposes. Mondoc contributes to the development of web directories and seems to achieve a proper and more selective search of e-documents (classification ontology). It can also foster on-line catalogs production for semantic authorities, or concepts, through XML schemas, because its applications could be used for implementing data models, by a prior adaptation of the based-ontology to structured meta-languages, such as OWL, RDF (descriptive ontology). Mondoc serves to the classification of concepts and applies a semantic indexing approach of facets. It enables information retrieval, as well as quantitative and qualitative data interpretation. The model reproduces a triple tuple ⟨LN, LE, LT, LCF L, BKF⟩ where LN is a set of entities that connect with other nodes to concrete a rooted tree in ⟨LN, LE⟩. LT specifies a set of terms, and LCF acts as a finite set of concepts, encoded in a formal language, L. Mondoc only resolves partial problems of linguistic ambiguity (in case of synonymy and antonymy), but neither the pragmatic dimension of natural language nor the cognitive perspective is addressed. To achieve this goal, forthcoming programming developments should target at oriented meta-languages with structured documents in XML.

Keywords: hypernymy, information retrieval, lightweight ontology, resonance

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Authors: Mehmet Karaata

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Given two distinct vertices (nodes) source s and target t of a graph G = (V, E), the two node-disjoint paths problem is to identify two node-disjoint paths between s ∈ V and t ∈ V . Two paths are node-disjoint if they have no common intermediate vertices. In this paper, we present an algorithm with O(m)-time complexity for finding two node-disjoint paths between s and t in arbitrary graphs where m is the number of edges. The proposed algorithm has a wide range of applications in ensuring reliability and security of sensor, mobile and fixed communication networks.

Keywords: disjoint paths, distributed systems, fault-tolerance, network routing, security

Procedia PDF Downloads 422

Authors: Sara Alshehri, Bayan Alenzi, Atheer Alshehri, Samia Chelloug, Zainab Almry, Hussah Albugmai

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This paper concerns body area networks sensor that collect signals around a human body. The black hole attacks are the main security challenging problem because the data traffic can be dropped at any node. The focus of our proposed solution is to efficiently route data packets while detecting black hole nodes.

Keywords: body sensor networks, security, black hole, routing, broadcasting, OMNeT++

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

Procedia PDF Downloads 191

Authors: Christopher Meyer, Laima Gerlitz

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European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

Procedia PDF Downloads 59

Authors: Ji-yang Yu, Dan Huang, Guo-ping Feng, Xin Li, Lu-yuan Wang

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The navigation satellite network, especially the Beidou MEO Constellation, can relay data effectively with wide coverage and is applied in navigation, detection, and position widely. But the constellation has not been completed, and the amount of satellites on-board is not enough to cover the earth, which makes the data-relay disrupted or delayed in the transition process. The data-relay function needs to tolerant the delay or disruption in some extension, which make the Beidou MEO Constellation a delay/disruption-tolerant network (DTN). The traditional DTN designs mainly employ the relay table as the basic of data path schedule computing. But in practical application, especially in critical condition, such as the war-time or the infliction heavy losses on the constellation, parts of the nodes may become invalid, then the traditional DTN design could be useless. Furthermore, when transmitting the critical message in the navigation system, the maximum priority strategy is used, but the nodes still inquiry the relay table to design the path, which makes the delay more than minutes. Under this circumstances, it needs a function which could compute the optimum data path on-board in real-time according to the constellation states. The on-board critical message transmission design for navigation satellite delay/disruption-tolerant network (DTN) is proposed, according to the characteristics of navigation satellite network. With the real-time computation of parameters in the network link, the least-delay transition path is deduced to retransmit the critical message in urgent conditions. First, the DTN model for constellation is established based on the time-varying matrix (TVM) instead of the time-varying graph (TVG); then, the least transition delay data path is deduced with the parameters of the current node; at last, the critical message transits to the next best node. For the on-board real-time computing, the time delay and misjudges of constellation states in ground stations are eliminated, and the residual information channel for each node can be used flexibly. Compare with the minute’s delay of traditional DTN; the proposed transmits the critical message in seconds, which improves the re-transition efficiency. The hardware is implemented in FPGA based on the proposed model, and the tests prove the validity.

Keywords: critical message, DTN, navigation satellite, on-board, real-time

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Authors: Md Monir Hossain, Anne Staples, Kuya Takami, Tomonari Furukawa

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Tire noise has a significant impact on ride quality and vehicle interior comfort, even at low frequency. Reduction of tire noise is especially important due to strict state and federal environmental regulations. The primary sources of tire noise are the low frequency structure-borne noise and the noise that originates from the release of trapped air between the tire tread and road surface during each revolution of the tire. The frequency response of the tire changes at low and high frequency. At low frequency, the tension and bending moment become dominant, while the internal structure and local deformation become dominant at higher frequencies. Here, we analyze tire response in terms of deformation and rolling velocity at low revolution frequency. An Abaqus FEA finite element model is used to calculate the static and dynamic response of a rolling tire under different rolling conditions. The natural frequencies and mode shapes of a deformed tire are calculated with the FEA package where the subspace-based steady state dynamic analysis calculates dynamic response of tire subjected to harmonic excitation. The analysis was conducted on the dynamic response at the road (contact point of tire and road surface) and side nodes of a static and rolling tire when the tire was excited with 200 N vertical load for a frequency ranging from 20 to 200 Hz. The results show that frequency has little effect on tire deformation up to 80 Hz. But between 80 and 200 Hz, the radial and lateral components of displacement of the road and side nodes exhibited significant oscillation. For the static analysis, the fluctuation was sharp and frequent and decreased with frequency. In contrast, the fluctuation was periodic in nature for the dynamic response of the rolling tire. In addition to the dynamic analysis, a steady state rolling analysis was also performed on the tire traveling at ground velocity with a constant angular motion. The purpose of the computation was to demonstrate the effect of rotating motion on deformation and rolling velocity with respect to a fixed Newtonian reference point. The analysis showed a significant variation in deformation and rolling velocity due to centrifugal and Coriolis acceleration with respect to a fixed Newtonian point on ground.

Keywords: natural frequency, rotational motion, steady state rolling, subspace-based steady state dynamic analysis

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Authors: Krishnendra Shekhawat

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Given a graph G = (V, E), a rectangular dual of G represents the vertices of G by a set of interior-disjoint rectangles such that two rectangles touch if and only if there is an edge between the two corresponding vertices in G. Rectangular duals do not exist for every graph, so we can define maximal rectangular duals. A maximal rectangular dual is a rectangular dual of a graph G such that there exists no graph G ′ with a rectangular dual where G is a subgraph of G ′. In this paper, we enumerate all maximal rectangular duals (or, to be precise, the corresponding planar graphs) up to six nodes and presents a necessary condition for the existence of a rectangular dual. This work allegedly has applications in integrated circuit design and architectural floor plans.

Keywords: adjacency, degree sequence, dual graph, rectangular dual

Procedia PDF Downloads 241

Authors: Taleb L., Benarbia M., Brahmi M., Belmiloud H., Boukerche A.

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Introduction and purpose of the study: Cavum cancer in children and adolescents is rare and represents 8% of all nasopharyngeal cancers treated in our department. Our objective is to study its epidemiological, clinical, therapeutic, and evolutionary particularities. Material and methods: Retrospective study of 39 patients under 20 years old, treated for undifferentiated non-metastatic carcinoma of the nasopharynx at the Emir Abdelkader Cancer Center between 2014 and 2020. Results and statistical analysis: Median age was 14 years [7-19 years], with a sex ratio of 2.9. The median time to diagnosis was 5.6 months [1 to 14 months], the circumstances of the discovery of which were dominated by lymph node syndrome in 43.6% of cases (n=17) followed by a rhinological syndrome in 30.8% of cases (n=13). The tumor stage was T1 for two patients (5.1%), T2 for 8 (20.5%), T3 for 9 (23.1%), T4 for 20 (51.3%), N0 for 2 (5 .1%) N1 for 4 (10.3%), N2 for 28 (71.8%) and N3 for 5 (12.8%). All patients received induction chemotherapy followed by concomitant radiotherapy with cisplatin. The dose of irradiation delivered to the cavum and adenopathies was 66 Gy with fractionation of 2 Gy per session in 69.2% of cases (n=27) and 1.8 Gy in 30.8% of cases (n=12). With a median follow-up of 51 months (15 to 97 months), the locoregional, metastatic, specific, and overall relapse-free survival rates at five years were 91.1%, 73.5%, 66.1%, and 68.4, respectively. Conclusion: Chemotherapy and radiotherapy treatment of cavum cancer in children and adolescents has allowed excellent locoregional control despite the advanced stage of the disease. However, the frequency of metastatic relapses could justify the possible use of systemic maintenance treatment.

Keywords: cancer, nasopharynx, radiotherapy, chemotherapy, survival

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Authors: Md Fazlul Kader, Soo Young Shin

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In this paper, we consider a cognitive relay network (CRN) in which the primary receiver (PR) is protected by peak transmit power $\bar{P}_{ST}$ and/or peak interference power Q constraints. In addition, the interference effect from the primary transmitter (PT) is considered to show its impact on the performance of the CRN. We investigate the outage probability (OP) and outage capacity (OC) of the CRN by deriving closed-form expressions over Rayleigh fading channel. Results show that both the OP and OC improve by increasing the cooperative relay nodes as well as when the PT is far away from the SR.

Keywords: cognitive relay, outage, interference limited, decode-and-forward (DF)

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

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Authors: Keunhong Chae, Seokho Yoon

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This paper proposes a cooperative Alamouti space time transmission scheme with low relay complexity for the cooperative communication systems. In the proposed scheme, the source node combines the data symbols to construct the Alamouti-coded form at the destination node, while the conventional scheme performs the corresponding operations at the relay nodes. In simulation results, it is shown that the proposed scheme achieves the second order cooperative diversity while maintaining the same bit error rate (BER) performance as that of the conventional scheme.

Keywords: Space-time transmission, cooperative communication system, MIMO.

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Anca Radulescu, Danae Evans

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The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.

Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity

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Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

Abstract:

In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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Authors: Manoj Kumar

Abstract:

Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

Procedia PDF Downloads 493