Search results for: metastases in lymph nodes

Authors: T. Nalowa, L. Foncha, S. Eposi

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Prostate enlargement, prostate cancer are major global health problems affecting many men as they advance in age. It is highly recommended to encourage older men to get Prostate Specific Antigen test screening frequently. Conventional treatments like radiation, chemotherapy are associated with many side effects. And this situation is a call for concern. Traditional medicine is affordable, easily prepared with little or no side effects and it contains many phytochemicals. The study aims to find the cure for prostate cancer and prostate enlargement by extracting products from plant tissues of specific herbs to determine anti-inflammatory, anti-cancer, and anti-hematuria properties. Descriptive statistical analysis was applied to describe the data process. The commonly used method of preparation was extraction. Overall, 40 patients were classified based on their medical conditions on their underlying user report. Rural communities in Fako are rich sources of plants with medicinal properties. The used plants consequently provide basic information and aid to investigate the cure of prostate cancer and prostate enlargement, with great significance.

Keywords: cancer, enlargement, metastases, prostate

Procedia PDF Downloads 75

Authors: Pallavi Bhogaram, Xiaolong Wu, Min He, Onyedikachi Okenwa

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A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Keywords: critical path, transportation network, connectivity reliability, network model, Neo4j application, edge betweenness centrality index

Procedia PDF Downloads 134

Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

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Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

Procedia PDF Downloads 118

Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

Procedia PDF Downloads 504

Authors: Beverly Wang

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Background: Rosai-Dorfman disease (RDD), aka sinus histiocytosis with massive lymphadenopathy, is a rare, idiopathic histiocytic proliferative disorder. Although RDD can be seen involving the head and neck lymph nodes, rarely it can affect other extranodal sites. It present 3 unique cases of RDD affecting the nasal cavity, paranasal sinuses, and ear canal. The initial clinical presentation on two cases mimicked a malignant neoplasm. The 3rd case of RDD co-existed with a cholesteatoma of the ear canal. The clinical presentation, histology and immunohistochemical stains, and radiographic findings are discussed. Design: An overview of 3 cases of RDD affected sinonasal cavity and ear canal from UCI Medical Center was conducted. Case 1: A 61 year old male complaining of breathing difficulty presented with bilateral polypoid sinonasal masses and severe nasal obstruction. The masses elevated the nasal floor, and involved the anterior nasal septum to lateral wall. It was endoscopically excised. At intraoperative consultation, frozen section reported a pleomorphic spindle cell neoplasm with scattered large atypical spindle cells, resembling a high grade sarcoma. Case 2: A 46 year old male presented with recurrent bilateral maxillary chronic sinusitis with mass formation, clinically suspicious for malignant lymphoma. Excisional tissue sample showed large irregular spindled histiocytes with abundant granular and vacuolated cytoplasm. Case 3: A 36 year old female with a history of asthma initially presented with left-sided chronic otalgia, occasional nausea, vertigo, and fluctuating pain exacerbated by head movement and temperature changes. CT scan revealed an external auditory canal mass extending to the middle ear, coexisting with a small cholesteatoma. Results: The morphology of all cases revealed large atypical spindled histiocytes resembling fibrohistiocytic or myofibroblastic proliferative neoplasms. Scattered emperipolesis was seen. All 3 cases were confirmed as extranodal sinus RDD, confirmed by immunohistochemistry. The large atypical cells were positive for S100, CD68, and CD163. No evidence for malignancy was identified. Case 3 showed concurrent RDD co-existing with a cholesteatoma. Conclusion: Due to its rarity and variable clinical presentations, the diagnosis of RDD is seldom clinically considered. Extranodal sinus RDD morphologically can be pitfall as mimicker of spindly neoplasm, especially at intraoperative consultation. It can create diagnostic and therapeutic challenges. Correlation of radiological findings with histologic features will help to reach the diagnosis.

Keywords: head and neck, extranodal, rosai-dorfman disease, mimicker, immunohistochemistry

Procedia PDF Downloads 80

Authors: Kahlil Fredrick Cui, Marissa Pastor

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Earthquakes are complex phenomena, exhibiting complex correlations in space, time, and magnitude. Recently, the concept of complex networks has been used to shed light on the statistical and dynamical characteristics of regional seismicity. In this work, we study the relationships and interactions of seismic regions in Chile, Japan, and the Philippines through weighted and directed complex network analysis. Geographical areas are digitized into cells of fixed dimensions which in turn become the nodes of the network when an earthquake has occurred therein. Nodes are linked if a correlation exists between them as determined and measured by a correlation metric. The networks are found to be scale-free, exhibiting power-law behavior in the distributions of their different centrality measures: the in- and out-degree and the in- and out-strength. The evidence is also found of preferential interaction between seismically active regions through their degree-degree correlations suggesting that seismicity is dictated by the activity of a few active regions. The importance of a seismic region to the overall seismicity is measured using a generalized centrality metric taken to be an indicator of its activity or passivity. The spatial distribution of earthquake activity indicates the areas where strong earthquakes have occurred in the past while the passivity distribution points toward the likely locations an earthquake would occur whenever another one happens elsewhere. Finally, we propose a method that would project the location of the next possible earthquake using the generalized centralities coupled with correlations calculated between the latest earthquakes and a geographical point in the future.

Keywords: complex networks, correlations, earthquake, hazard assessment

Procedia PDF Downloads 212

Authors: Aydin Sipahioglu, Gokhan Celik

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Helicopter routing problem (HRP) is finding good tours for helicopter so as to pick up and deliver personnel or material among specified nodes, mutually. It can be encountered in case of being lots of supply and demand points for different commodities and requiring delivering commodities with helicopter. For instance, to deliver personnel or material from shore to oil rig is a good example. In fact, HRP is a branch of vehicle routing problem with pickup and delivery (VRPPD). However, it has additional constraints such that fuel capacity, performance of helicopter in different altitude and temperature, and the number of maximum takeoff and landing allowed. This kind of pickup and delivery problems can be classified into 3 groups, basically. 1-1 (one to one), M-M (many to many) and 1-M-1 (one to many to one). 1-1 means each commodity has only one supply and one demand point. M-M means there can be more than one supply and demand points for each kind of commodity. 1-M-1 means commodities at depot are delivered to demand points and commodities at customers are delivered to depot. In this case helicopter takes off from its own base, complete its tour and return to its own base. In this study, we define 1-M-M-1 type HRP. That means helicopter takes off from its home base, deliver commodities among the nodes as well as between depot and customers and return to its home base. These problems have NP-hard nature. Therefore, obtaining a good solution in a reasonable time is not easy. In this study, a model is offered for 1-M-M-1 type HRP. It is shown on small scale test instances that the model can find the optimal solution.

Keywords: helicopter routing problem, vehicle routing with pickup and delivery, integer programming

Procedia PDF Downloads 430

Authors: Mamouni Mohammed Dhiya Eddine

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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.

Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface

Procedia PDF Downloads 219

Authors: Nishant Shrivastava, D. K. Sehgal

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In Finite Element Technique nodal stresses are calculated through displacement as nodes. In this process, the displacement calculated at nodes is sufficiently good enough but stresses calculated at nodes are not sufficiently accurate. Therefore, the accuracy in the stress computation in FEM models based on the displacement technique is obviously matter of concern for computational time in shape optimization of engineering problems. In the present work same is focused to find out unique points within the element as well as the boundary of the element so, that good accuracy in stress computation can be achieved. Generally, major optimal stress points are located in domain of the element some points have been also located at boundary of the element where stresses are fairly accurate as compared to nodal values. Then, it is subsequently concluded that there is an existence of unique points within the element, where stresses have higher accuracy than other points in the elements. Therefore, it is main aim is to evolve a generalized procedure for the determination of the optimal stress location inside the element as well as at the boundaries of the element and verify the same with results from numerical experimentation. The results of quadratic 9 noded serendipity elements are presented and the location of distinct optimal stress points is determined inside the element, as well as at the boundaries. The theoretical results indicate various optimal stress locations are in local coordinates at origin and at a distance of 0.577 in both directions from origin. Also, at the boundaries optimal stress locations are at the midpoints of the element boundary and the locations are at a distance of 0.577 from the origin in both directions. The above findings were verified through experimentation and findings were authenticated. For numerical experimentation five engineering problems were identified and the numerical results of 9-noded element were compared to those obtained by using the same order of 25-noded quadratic Lagrangian elements, which are considered as standard. Then root mean square errors are plotted with respect to various locations within the elements as well as the boundaries and conclusions were drawn. After numerical verification it is noted that in a 9-noded element, origin and locations at a distance of 0.577 from origin in both directions are the best sampling points for the stresses. It was also noted that stresses calculated within line at boundary enclosed by 0.577 midpoints are also very good and the error found is very less. When sampling points move away from these points, then it causes line zone error to increase rapidly. Thus, it is established that there are unique points at boundary of element where stresses are accurate, which can be utilized in solving various engineering problems and are also useful in shape optimizations.

Keywords: finite elements, Lagrangian, optimal stress location, serendipity

Procedia PDF Downloads 105

Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

Procedia PDF Downloads 160

Authors: S. Ghalem, M. Mesmoudi, I. Daoudand, H. Allali

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The nitrogen-containing bisphosphonates (N-BPs) are well established as the treatments of choice for disorders of excessive bone resorption, myeloma and bone metastases, and osteoporosis. They inhibit farnesyl pyrophosphate synthase (FFPS), a key enzyme in the mevalonate pathway, resulting in inhibition of the prenylation of small GTP-binding proteins in osteoclasts and disruption of their cytoskeleton, adhesion/spreading, and invasion of cancer cells. A very few examples for synthesis of α-amino bisphosphonates based on several amino acids are known from the literature. In the present work, esters of aminoacid react with ketophsophonate (or their analog acid or acyl) to afford the desired products, α-iminophosphonates. The reaction of imine with dimethyl phosphate in the presence of catalytic amount of I2 give ester of α-aminobisphosphonate as sole product in good yield. Finally, we used computational docking methods to predict how several α-aminobisphosphonates bind to FPPS and how R and X influence. Pamidronate, β-aminobisphosphonate already marketed, was used as reference. These results are of interest since they represent a new and simple way to sythesize α-aminobisphosphonates with a free COOH group increased by R2 functionalisable and opening up the possibility of using the molecular docking to facilitate the design of other, novel FFPS inhibitors.

Keywords: drug research, cancer, α-amino bisphosphonates, molecular docking

Procedia PDF Downloads 271

Authors: Zafar Iqbal

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This study involved students of 6th semester enrolled in a Bachelor of Computer Science Program at university level. In this era of science and technology, e-learning can be helpful for grassroots in providing them access to education tenant in less developed areas. It is a potential substitute of face-to-face teaching being used in different countries. The purpose of the study was to explore the views of students about e-learning (Facebook) as an instructional tool. By using purposive sampling technique an intact class of 30 students included both male and female were selected where e-learning was used as an instructional tool. The views of students were explored through qualitative approach by using focus group interviews. The approach was helpful to develop comprehensive understanding of students’ views towards e- learning. In addition, probing questions were also asked and recorded. Data was transcribed, generated nodes and then coded text against these nodes. For this purpose and further analysis, NVivo 10 software was used. Themes were generated and tangibly presented through cluster analysis. Findings were interesting and provide sufficient evidence that face book is a subsequent e-learning source for students of higher education. Students acknowledged it as best source of learning and it was aligned with their academic and social behavior. It was not time specific and therefore, feasible for students who work day time and can get on line access to the material when they got free time. There were some distracters (time wasters) reported by the students but can be minimized by little effort. In short, e-learning is need of the day and potential learning source for every individual who have access to internet living at any part of the globe.

Keywords: e-learning, facebook, instructional tool, higher education

Procedia PDF Downloads 375

Authors: Maryam Tajadod

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The treatment of cancer is one of the main challenges of nuclear medicine; while cancer begins in an organ, such as the breast or prostate, it spreads to the bone, resulting in metastatic bone. In the treatment of cancer with radiotherapy, the determination of the involved tissues’ dose is one of the important steps in the treatment protocol. Comparing absorbed doses for Lu-177 and Ra-223 and Ac-225 in the bone marrow and soft tissue of bone phantom with evaluating energetic emitted particles of these radionuclides is the important aim of this research. By the use of MCNPX computer code, a model for bone phantom was designed and the values of absorbed dose for Ra-223 and Ac-225, which are Alpha emitters & Lu-177, which is a beta emitter, were calculated. As a result of research, in comparing gamma radiation for three radionuclides, Lu-177 released the highest dose in the bone marrow and Ra-223 achieved the lowest level. On the other hand, the result showed that although the figures of absorbed dose for Ra and Ac in the bone marrow are near to each other, Ra spread more energy in cortical bone. Moreover, The alpha component of the Ra-223 and Ac-225 have very little effect on bone marrow and soft tissue than a beta component of the lu-177 and it leaves the highest absorbed dose in the bone where the source is located.

Keywords: bone metastases, lutetium-177, radium-223, actinium-225, absorbed dose

Procedia PDF Downloads 112

Authors: N. A. Kazemi Sefat, M. M. Mohammadi, J. Hadjati, S. Talebi, M. Ajami, H. Daneshvar

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Colorectal cancer metastases result in a significant number of cancer related deaths. Histone deacetylase (HDAC) inhibitors induce growth arrest and apoptosis in a variety of human cancer cells. Sodium butyrate (SB) is a short chain fatty acid, belongs to HDAC inhibitors which is released in the colonic lumen as a consequence of fiber fermentation. In this study, we are about to assess the effect of sodium butyrate on HCT116 human colorectal carcinoma cell line. The viability of cells was measured by microscopic morphologic study and MTT assay. After 48 hours, treatments more than 10 mM lead to cell injury in HCT116 by increasing cell granulation and decreasing cell adhesion (p>0.05). After 72 hours, treatments at 10 mM and more lead to significant cell injury (p<0.05). Our results may suggest that the gene expression which is contributed in cell proliferation and apoptosis has been changed under pressure of HDAC inhibition.

Keywords: colorectal cancer, sodium butyrate, cytotoxicity, MTT

Procedia PDF Downloads 361

Authors: Bander Alzahrani

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Information-centric networking (ICN) using architectures such as Publish-Subscribe Internet Routing Paradigm (PSIRP) is one of the promising candidates for a future Internet, has recently been under the spotlight by the research community to investigate the possibility of redesigning the current Internet architecture to solve many issues such as routing scalability, security, and quality of services issues.. The Bloom filter-based forwarding is a source-routing approach that is used in the PSIRP architecture. This mechanism is vulnerable to brute force attacks which may lead to denial-of-service (DoS) attacks. In this work, we present a new forwarding approach that keeps the advantages of Bloom filter-based forwarding while mitigates attacks on the forwarding mechanism. In practice, we introduce a special type of forwarding nodes called Edge-FW to be placed at the edge of the network. The role of these node is to add an extra security layer by validating and inspecting packets at the edge of the network against brute-force attacks and check whether the packet contains a legitimate forwarding identifier (FId) or not. We leverage Certificateless Aggregate Signature (CLAS) scheme with a small size of 64-bit which is used to sign the FId. Hence, this signature becomes bound to a specific FId. Therefore, malicious nodes that inject packets with random FIds will be easily detected and dropped at the Edge-FW node when the signature verification fails. Our preliminary security analysis suggests that with the proposed approach, the forwarding plane is able to resist attacks such as DoS with very high probability.

Keywords: bloom filter, certificateless aggregate signature, denial-of-service, information centric network

Procedia PDF Downloads 198

Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

Procedia PDF Downloads 449

Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

Procedia PDF Downloads 314

Authors: Muccifora S., Rinallo C., Bellani L.

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Calcium (Ca²+) is an element essential to the plant being involved in plant growth and development. At high concentrations, it is toxic and can influence every stage, process and cellular activity of plant life. Given its toxicity, cells implement mechanisms to compartmentalize calcium in a vacuole, endoplasmic reticulum, mitochondria, plastids and cell wall. One of the most effective mechanisms to reduce the excess of calcium, thus avoiding cellular damage, is its complexation with oxalic acid to form calcium oxalate crystals that are no longer osmotically or physiologically active. However, the sequestered calcium can be mobilized when the plant needs it. Calcium crystals can be accumulated in the vacuole of specialized sink-cells called idioblasts, with different crystalline forms (druse, raphyde and styloid) of diverse physiological meanings. Actinidia deliciosa cv. Hayward presents raphydes and styloid localized in idioblasts in cells of photosynthetic and non-photosynthetic tissues. The purpose of this work was to understand if there is a relationship between the age of Actinidia leaves and the presence, distribution, dimension and shape of oxalate crystals by means of light, fluorescent, polarized and transmission electron microscopy. Three vines from female plants were chosen at the beginning of the season and used throughout the study. The leaves with petioles were collected at various stages of development from the bottom to the shoot of the plants monthly from April to July. The samples were taken in corresponding areas of the central and lateral parts of the leaves and of the basal portion of the petiole. The results showed that in the leaves, the number of raphyde idioblasts decreased with the progress of the growing season, while the styloid idioblasts increased progressively, becoming very numerous in the upper nodes of July. In June and in July samples, in the vacuoles of the highest nodes, a portion regular in shape strongly stained with rubeanic acid was present. Moreover, the chlortetracycline (CTC) staining for localization of free calcium marked the wall of the idioblasts and the wall of the cells near vascular bundles. In April petiole samples, moving towards the youngest nodes, the raphydes idioblast decreased in number and in the length of the single raphydes. Besides, crystals stained with rubeanic acid appeared in the vacuoles of some cells. In June samples, numerous raphyde idioblasts oriented parallel to vascular bundles were evident. Under the electron microscope, numerous idioblasts presented not homogeneous electrondense aggregates of material, in which a few crystals (styloids) in the form of regular holes were scattered. In July samples, an increase in the number of styloid idioblasts in the youngest nodes and little masses stained with CTC near styloids were observed. Peculiar cells stained with rubeanic acid were detected and hypothesized to be involved in the formation of the idioblasts. In conclusion, in Actinidia leaves and petioles, it seems to confirm the hypothesis that the formation of styloid idioblasts can be correlated to increasing calcium levels in growing tissues.

Keywords: calcium oxalate crystals, actinidia deliciosa, light and electron microscopy, idioblasts

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Authors: Andre F. A. Cyrino

Abstract:

Knowing that the technological advance is the focus on the efficient extraction of energy from wind, and therefore in the design of wind turbine structures, this work aims the study of the fluid-structure interaction of an idealized wind turbine. The blade was studied as a beam attached to a cylindrical Hub with rotation axis pointing the air flow that passes through the rotor. Using the calculus of variations and the finite difference method the blade will be simulated by a discrete number of nodes and the aerodynamic forces were evaluated. The study presented here was written on Matlab and performs a numeric simulation of a simplified model of windmill containing a Hub and three blades modeled as Euler-Bernoulli beams for small strains and under the constant and uniform wind. The mathematical approach is done by Hamilton’s Extended Principle with the aerodynamic loads applied on the nodes considering the local relative wind speed, angle of attack and aerodynamic lift and drag coefficients. Due to the wide range of angles of attack, a wind turbine blade operates, the airfoil used on the model was NREL SERI S809 which allowed obtaining equations for Cl and Cd as functions of the angle of attack, based on a NASA study. Tridimensional flow effects were no taken in part, as well as torsion of the beam, which only bends. The results showed the dynamic response of the system in terms of displacement and rotational speed as the turbine reached the final speed. Although the results were not compared to real windmills or more complete models, the resulting values were consistent with the size of the system and wind speed.

Keywords: blade aerodynamics, fluid–structure interaction, wind turbine aerodynamics, wind turbine blade

Procedia PDF Downloads 268

Authors: S. Zolghadri, H. Yousefnia, A. R. Jalilian

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Bone metastases are observed in a wide range of cancers leading to intolerable pain. While early detection can help the physicians in the decision of the type of treatment, various radiopharmaceuticals using phosphonates like ⁶⁸Ga-EDTMP have been developed. In this work, due to the importance of absorbed dose, human absorbed dose of this new agent was calculated for the first time based on biodistribution data in Wild-type rats. ⁶⁸Ga was obtained from ⁶⁸Ge/⁶⁸Ga generator with radionuclidic purity and radiochemical purity of higher than 99%. The radiolabeled complex was prepared in the optimized conditions. Radiochemical purity of the radiolabeled complex was checked by instant thin layer chromatography (ITLC) method using Whatman No. 2 paper and saline. The results indicated the radiochemical purity of higher than 99%. The radiolabelled complex was injected into the Wild-type rats and its biodistribution was studied up to 120 min. As expected, major accumulation was observed in the bone. Absorbed dose of each human organ was calculated based on biodistribution in the rats using RADAR method. Bone surface and bone marrow with 0.112 and 0.053 mSv/MBq, respectively, received the highest absorbed dose. According to these results, the radiolabeled complex is a suitable and safe option for PET bone imaging.

Keywords: absorbed dose, EDTMP, ⁶⁸Ga, rats

Procedia PDF Downloads 194

Authors: Cristian Pauna

Abstract:

Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

Procedia PDF Downloads 160

Authors: Ja’afar U., A. M. Gumi, Salisu N., Obadiah C. D.

Abstract:

Rice is susceptible to flooding due to its semi-aquatic characteristics, which enable it to thrive in wet or submerged environments. The development of aerenchyma allows for oxygen transfer, enabling faster lengthening of submerged shoot organs. Rice's germination and early seedling growth phases are highly intolerant of submersion, resulting in survival in low-oxygen environments. The research involved a study on rice plants treated with salicylic acid at different concentrations. Hypo was used for washing, while a reagent was used for submergence treatment. The plants were waterlogged for 11 days and submerged for 7 days, with control plants receiving distilled water. The study found a significant difference between Jirani Zawara's control and treated plants, with plants treated with 2 g/L of S.A. showing a 6.00 node increase per plant and Faro cultivars having more nodes. The study found significant differences between the control and treated plants, with the Jirani Zawara plant showing longer internode lengths and the Faro cultivar having longer internode lengths, while the B.G. cultivar had the longest. The research found that the Jirani Zawara cultivar treated with 3 g/L of S.A. produced tallest plants, with heights increasing from 14.43 cm to 15.50 cm in Faro cultivar S.A., and the highest height was 16.30 cm. The study reveals that salicylic acid significantly enhances the number of nodes, internode length, plant height, and root length in rice cultivars, thereby improving submerged stress recovery and promoting plant development.

Keywords: rice, submergence, stress, salicylic acid

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

Abstract:

Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: interconnection network, augmented cube, induced subgraph, bisection width

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

Procedia PDF Downloads 96

Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: energy consumption, IEEE 802.15.4, IoT security, security cost evaluation

Procedia PDF Downloads 168

Authors: Roland Benedict Reyes, Marc Edsel Ayes, Regina Berba, Cybele Lara Abad

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Background: Three AIDS-defining malignancies have been associated with the human immunodeficiency virus (HIV): Kaposi’s sarcoma, non-Hodgkin’s lymphoma, and cervical carcinoma. However, new cases of non-AIDS defining malignancies also have been increasingly associated with HIV. One of these is a rare intracranial malignancy, meningeal hemangiopericyotma. Case Description: A 32-year old HIV-positive male, not on highly active antiretroviral therapy, was admitted to our hospital due to generalized weakness and sudden onset hearing loss. Cranial MRI was done, which revealed a temporal nodule with the following considerations: granuloma, meningioma or metastases. A craniotomy was performed and the mass excised. Results from the biopsy showed meningeal hemangiopericytoma. The patient was then started on antiretroviral therapy (Lamivudine, Tenofovir, and Efavirenz) and was discharged for radiation therapy and metastatic work-up as an outpatient. On follow-up seven months later, metastatic work up revealed multiple hepatic foci not previously documented suggestive of metastasis short of biopsy sampling. Conclusions: This case of an intracranial hemangiopericytoma in an HIV-positive patient is the second case thus far presented, based on our systematic and extensive search of the literature.

Keywords: Hemangiopericytoma, Human Immunodeficiency Virus, Meningeal hemangiopericytoma, Neoplasm

Procedia PDF Downloads 463

Authors: Rishab Das, Arnab Banerjee, Bappaditya Manna

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Mono-pile foundations are often used in soft soils in order to support heavy mega-structures, whereby often these deep footings may undergo dynamic excitation due to many causes like earthquake, wind or wave loads acting on the superstructure, blasting, and unbalanced machines, etc. A comprehensive analytical study is performed to study the dynamics of the mono-pile system embedded in cohesion-less soil. The soil is considered homogeneous and visco-elastic in nature and is analytically modeled using complex springs. Considering the N number of the elements of the pile, the final global stiffness matrix is obtained by using the theories of the spectral element matrix method. Further, statically condensing the intermediate internal nodes of the global stiffness matrix results to a smaller sub matrix containing the nodes experiencing the external translation and rotation, and the stiffness and damping functions (impedance functions) of the embedded piles are determined. Proper plots showing the variation of the real and imaginary parts of these impedance functions with the dimensionless frequency parameter are obtained. The plots obtained from this study are validated by that provided by Novak,1974. Further, the dynamic analysis of the resonator impregnated pile is proposed within this study. Moreover, with the aid of Wood's 1g laboratory scaling law, a proper scaled-down resonator-pile model is 3D printed using PLA material. Dynamic analysis of the scaled model is carried out in the time domain, whereby the lateral loads are imposed on the pile head. The response obtained from the sensors through the LabView software is compared with the proposed theoretical data.

Keywords: mono-pile, visco-elastic, impedance, LabView

Procedia PDF Downloads 118

Authors: Rizky Oktaviana

Abstract:

The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

Procedia PDF Downloads 271

Authors: Raghavi C. Janaswamy

Abstract:

In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

Procedia PDF Downloads 86

Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

Abstract:

This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

Procedia PDF Downloads 167