Search results for: gold mining

Authors: Sally Ibrahim, Mohamed Hedia, Mohamed Taqi, Mohamed Derbala, Karima Mahmoud, Youssef Ahmed, Sayed Ismail, Mohamed El-Belely

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The identification and quantification of serum microRNA (miRNA) from mares with endometritis might serve as useful and implementable clinical biomarkers for the early diagnosis of endometiritis. Aims of the current study were (I) to study the expression pattern of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205, and (II) to determine the levels of interleukin 6 (IL-6), prostaglandins (PGF₂α and PGE₂), in the serum of Arabian mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares (4-14 years old). Mares were divided into 48 sub-fertile mares suspected of endometritis and 32 fertile at stud farms. The criteria for mares to be enrolled in the endometritis group were that they had been bred three or more times unsuccessfully in the breeding season or had a history of more than one year of reproductive failure. In addition, two or more of the following criteria on a checklist were present: abnormal clinical findings, transrectal ultrasonographic uterine examination showed abnormal fluid in the uterus (echogenic or ≥2 cm in diameter), positive endometrial cytology; and bacterial and/or fungal growth. Serum samples were collected for measuring IL-6, PGF₂α, and PGE₂ concentrations, as well as serum miRNA isolation and quantitative real-time PCR. Serum concentrations of IL-6, PGE₂, and PGF₂α were higher (P ≤ 0.001) in mares with endometritis compared to the control healthy ones. The expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 increased (P≤0.001) in mares with endometritis compared to the control ones. To the best of our knowledge, this is the first study that revealed that serum miRNA and serum inflammatory mediators (IL-6, PGE₂, and PGF₂α) could be used as non-invasive gold standard biomarkers, and therefore might be served as an important additional diagnostic tool for endometritis in Arabian mares. Moreover, estimation of the serum concentrations of serum miRNA, IL-6, PGE₂, and PGF₂α is a promising recommended tool during the breeding soundness examination in mares.

Keywords: Arabian Mares, endometritis, inflammatory mediators, serum miRNA

Procedia PDF Downloads 164

Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

Procedia PDF Downloads 111

Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

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Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

Procedia PDF Downloads 204

Authors: Reza Bahboodian

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One of the most important factors in the use of construction machinery is the fuel consumption cost of this equipment. The use of diesel engines in off-road vehicles is an important source of nitrogen oxides and particulate matter. Emissions of nitrogen oxides and particulate matter 10 in off-road vehicles (construction and mining) may be high. Due to the high cost of fuel, it is necessary to minimize fuel consumption. Factors affecting the fuel consumption of these cars are very diverse. Climate changes such as changes in pressure, temperature, humidity, fuel type selection, type of gearbox used in the car are effective in fuel consumption and pollution, and engine efficiency. In this paper, methods for reducing fuel consumption and pollutants by considering valid European and European standards are examined based on new methods such as hybridization, optimal gear change, adding hydrogen to diesel fuel, determining optimal working fluids, and using oxidation catalysts.

Keywords: improve fuel consumption, construction machinery, pollutant reduction, determining the optimal working cycle

Procedia PDF Downloads 142

Authors: D. He, Y. Pang, G. Lodewijks

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Belt conveyors play an important role in continuous dry bulk material transport, especially at the mining industry. Speed control is expected to reduce the energy consumption of belt conveyors. Transient operation is the operation of increasing or decreasing conveyor speed for speed control. According to literature review, current research rarely takes the conveyor dynamics in transient operation into account. However, in belt conveyor speed control, the conveyor dynamic behaviors are significantly important since the poor dynamics might result in risks. In this paper, the potential risks in transient operation will be analyzed. An existing finite element model will be applied to build a conveyor model, and simulations will be carried out to analyze the conveyor dynamics. In order to realize the soft speed regulation, Harrison’s sinusoid acceleration profile will be applied, and Lodewijks estimator will be built to approximate the required acceleration time. A long inclined belt conveyor will be studied with two major simulations. The conveyor dynamics will be given.

Keywords: belt conveyor , speed control, transient operation, dynamics

Procedia PDF Downloads 310

Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

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Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

Procedia PDF Downloads 102

Authors: Ewa Szarek-Gwiazda, Agata Z. Wojtal, Agnieszka Pociecha, Andrzej Kownacki, Dariusz Ciszewski

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Mining of metal ores is one of the largest sources of heavy metals, which deteriorate aquatic systems. The response of organisms to environmental changes can be well recorded in sediments of the affected water bodies and may be reconstructed based on analyses of organisms' remains. The present study aimed at the response of diatoms (Bacillariophyta), Cladocera, and Chironomidae communities to the impact of Zn-Pb mine water discharge recorded in sediment cores of small subsidence ponds on the Chechło River floodplain (Silesia–Krakow Region, southern Poland). We hypothesize various responses of the above groups to high metal concentrations (Cd, Pb, Zn, and Cu). The investigated ponds were formed either during the peak of the ore exploitation (DOWN) or after mining cessation (UP). Currently, the concentrations of dissolved metals (in µg g⁻¹) in water reached up to 0.53 for Cd, 7.3 for Pb, and up to 47.1 for Zn. All the sediment cores from subsidence ponds were heavily polluted with Cd 6.7–612 μg g⁻¹, Pb 0.1–10.2 mg g⁻¹, and Zn 0.5–23.1 mg g⁻¹. Core sediments varied also in respect to pH 5.8-7.1 and concentrations of organic matter (5.7-39.8%). The impact of high metal concentrations was expressed by the occurrence of metal-tolerant taxa like diatoms – Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii; Cladocera – Chydorus sphaericus (dominated in cores from all ponds), and Chironomidae – Chironomus and Cricotopus especially in the DOWN ponds. Statistical analysis exhibited a negative impact of metals on some taxa of diatoms and Cladocera but only on Polypedilum sp. from Chironomidae. The abundance of such diatoms like Gomphonema utae, Staurosirella pinnata, Eunotia bilunaris, and Cladocera like Alona, Chydorus, Graptoleberis, and Pleuroxus decreased with increasing Pb concentration. However, the occurrence or dominance of more sensitive species of diatoms and Cladocera indicates their adaptation to higher metal loads, which was facilitated by neutral pH and slightly alkaline waters. Diatom assemblages were generally resistant to Zn, Pb, Cu, and Cd pollution, as indicated by their large similarity to populations from non-contaminated waters. Comparison with reference objects clearly indicates the dominance of Achnanthidium minutissimum, Staurosira venter, and Fragilaria gracilis in very diverse assemblages of unpolluted waters. The distribution of the Cladocera and Chironomidae taxa depended on the habitat type. The DOWN ponds with stagnant water and overgrown with macrophytes were more suitable for cladocerans (14 taxa, higher diversity) than the UP ponds with river water flowing through their centre and with a small share of macrophytes (8 taxa). The Chironominae, mainly Chironomus and Microspectra, were abundant in cores from the UP ponds with muddy bottoms. Inversely, the density of Orthocladiinae, especially genus Cricotopus, was related to the organic matter content and dominated in cores from the DOWN ponds. The presence of diatoms like Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii, cladocerans: Bosmina longirostris, Chydorus sphaericus, Alona affinis, and A. rectangularis as well as Chironomidae Chironomus sp. (UP ponds) and Psecrotanypus varius (DOWN ponds) indicate the influence of the water trophy on their distribution.

Keywords: Chironomidae, Cladocera, diatoms, metals, Zn-Pb mine, sediment cores, subsidence ponds

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: early warning system, knowledge management, market prediction, topic modeling.

Procedia PDF Downloads 322

Authors: Yuhong Zhang, Dan Lu, Chenyang Bu, Peipei Li, Kui Yu, Xindong Wu

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The Cross-Lingual Entity Alignment (CLEA) task aims to find the aligned entities that refer to the same identity from two knowledge graphs (KGs) in different languages. It is an effective way to enhance the performance of data mining for KGs with scarce resources. In real-world applications, the neighborhood structures of the same entities in different KGs tend to be non-isomorphic, which makes the representation of entities contain diverse semantic information and then poses a great challenge for CLEA. In this paper, we try to address this challenge from two perspectives. On the one hand, the cross-KG relation completion rules are designed with the alignment constraint of entities and relations to improve the topology isomorphism of two KGs. On the other hand, a representation method combining isomorphic weights is designed to include more isomorphic semantics for counterpart entities, which will benefit the CLEA. Experiments show that our model can improve the isomorphism of two KGs and the alignment performance, especially for two non-isomorphic KGs.

Keywords: knowledge graphs, cross-lingual entity alignment, non-isomorphic, relation completion

Procedia PDF Downloads 108

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

Procedia PDF Downloads 238

Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

Procedia PDF Downloads 265

Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

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In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: association rules, rule-based classification, classification quality, validation

Procedia PDF Downloads 419

Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

Procedia PDF Downloads 379

Authors: Saad Al-Shibli, Nasser Amjad, Muna Al Kubaisi, Norra Harun, Shaikh Mizan

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Leptin is a multifunctional hormone produced mainly by adipocyte. Leptin and its receptor have long been found associated with breast cancer. The main aim of this study is to investigate the correlation between Leptin/Leptin receptor and the clinicopathological features of breast cancer. Blood samples for ELISA, tissue samples from tumors and adjacent breast tissue were taken from 51 women with breast cancer with a control group of 40 women with a negative mammogram. Leptin and Leptin receptor in the tissues were estimated by immunohistochemistry (IHC). They were localized at the subcellular level by immunocytochemistry using transmission electron microscopy (TEM). Our results showed significant difference in serum leptin level between control and the patient group, but no difference between pre and post-operative serum leptin levels in the patient group. By IHC, we found that the majority of the breast cancer cells studied, stained positively for leptin and leptin receptors with co-expression of leptin and its receptors. No significant correlation was found between leptin/leptin receptors expression with the race, menopausal status, lymph node metastasis, estrogen receptor expression, progesterone receptor expression, HER2 expression and tumor size. Majority of the patients with distant metastasis were associated with high leptin and leptin receptor expression. TEM views both Leptin and Leptin receptor were found highly concentrated within and around the nucleus of the cancer breast cells, indicating nucleus is their principal seat of actions while the adjacent breast epithelial cells showed that leptin gold particles are scattered all over the cell with much less than that of the cancerous cells. However, presence of high concentration of leptin does not necessarily prove its over-expression, because it could be internalized from outside by leptin receptor in the cells. In contrast, leptin receptor is definitely over-expressed in the ductal breast cancer cells. We conclude that reducing leptin levels, blocking its downstream tissue specific signal transduction, and/or blocking the upstream leptin receptor pathway might help in prevention and therapy of breast cancer.

Keywords: breast cancer, expression, leptin, leptin receptors

Procedia PDF Downloads 118

Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

Procedia PDF Downloads 348

Authors: Pamela Tancsik

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The stage production in 2018, titled ‘From‘Marikana to Mahagonny’, began with a prologue in the form of the award-winning documentary ‘Miners Shot Down' by Rehad Desai, followed by Brecht/Weill’s song play or scenic cantata ‘Mahagonny’, premièred in Baden-Baden 1927. The central directorial concept of the DUT musical production ‘From Marikana to Mahagonny’ was to show a connection between the socio-political alienation of mineworkers in present-day South Africa and Brecht’s alienation effect in his scenic cantata ‘Mahagonny’. Marikana is a mining town about 50 km west of South Africa’s capital Pretoria. Mahagonny is a fantasy name for a utopian mining town in the United States. The characters, setting, and lyrics refer to America with of songs like ‘Benares’ and ‘Moon of Alabama’ and the use of typical American inventions such as dollars, saloons, and the telephone. The six singing characters in ‘Mahagonny’ all have typical American names: Charlie, Billy, Bobby, Jimmy, and the two girls they meet later are called Jessie and Bessie. The four men set off to seek Mahagonny. For them, it is the ultimate dream destination promising the fulfilment of all their desires, such as girls, alcohol, and dollars – in short, materialistic goals. Instead of finding a paradise, they experience how money and the practice of exploitive capitalism, and the lack of any moral and humanity is destroying their lives. In the end, Mahagonny gets demolished by a hurricane, an event which happened in 1926 in the United States. ‘God’ in person arrives disillusioned and bitter, complaining about violent and immoral mankind. In the end, he sends them all to hell. Charlie, Billy, Bobby, and Jimmy reply that this punishment does not mean anything to them because they have already been in hell for a long time – hell on earth is a reality, so the threat of hell after life is meaningless. Human life was also taken during the stand-off between striking mineworkers and the South African police on 16 August 2012. Miners from the Lonmin Platinum Mine went on an illegal strike, equipped with bush knives and spears. They were striking because their living conditions had never improved; they still lived in muddy shacks with no running water and electricity. Wages were as low as R4,000 (South African Rands), equivalent to just over 200 Euro per month. By August 2012, the negotiations between Lonmin management and the mineworkers’ unions, asking for a minimum wage of R12,500 per month, had failed. Police were sent in by the Government, and when the miners did not withdraw, the police shot at them. 34 were killed, some by bullets in their backs while running away and trying to hide behind rocks. In the musical play ‘From Marikana to Mahagonny’ audiences in South Africa are confronted with a documentary about Marikana, followed by Brecht/Weill’s scenic cantata, highlighting the tragic parallels between the Mahagonny story and characters from 1927 America and the Lonmin workers today in South Africa, showing that in 95 years, capitalism has not changed.

Keywords: alienation, brecht/Weill, mahagonny, marikana/South Africa, musical theatre

Procedia PDF Downloads 86

Authors: Breno M. Castilho

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The Iron Ore Quadrangle, located in the state of Minas Gerais, Brazil is responsible for most of the country’s iron ore production. As a result, some of the biggest tailings dams in the country are located in this area. In recent years, several major failure events have happened in Tailings Storage Facilities (TSF) located in the Iron Ore Quadrangle. Some of these failures were found to be caused by liquefaction flowslides. This paper presents Piezocone Penetration Test (CPTu) data that was used, by applying Olson and Peterson methods, for the liquefaction susceptibility assessment of the iron ore tailings that are typically found in most TSF in the area. Piezocone data was also used to determine the steady-state strength of the tailings so as to allow for comparison with its drained strength. Results have shown great susceptibility for liquefaction to occur in the studied tailings and, more importantly, a large reduction in its strength. These results are key to understanding the failures that took place over the last few years.

Keywords: Piezocone Penetration Test CPTu, iron ore tailings, mining, liquefaction susceptibility assessment

Procedia PDF Downloads 217

Authors: M. S. R. Waas, S. G. U. S. Chandrarathne, U. A. Kumara

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The purpose of this quantitative study is to identify the impact of the destination attributes of Negombo on the coastal tourists’ visitor experience. As an island nation, Sri Lanka is identified and well renowned for its gold sandy beaches and natural scenic beauty. Among many tourist attractions, Negombo is identified as a developed beach centric tourist destination in the country. Yet, it is identified that there are low positive reviews on the internet for Negombo compared to other beach centric tourist attractions in Sri Lanka. Therefore, this study would help the policymakers and tourism service providers to identify the impact of destination attributes on international visitor satisfaction and to understand the visitors comprehensively so as to develop Negombo as a stable tourist destination while offering a memorable and satisfying experience for its visitors. In support, a self-administered questionnaire survey study was performed with 150 respondents (international tourists) in Negombo. The questions were designed based on the selected dimensions of destination attributes such as tourism service quality, infrastructure and superstructure developments, tourist information facilities and destination aesthetics and developments. The results showed that the overall satisfaction level of the international tourists who visit Sri Lanka is significantly affected by the destination attributes of Negombo. Yet, the dimensions of destination aesthetics and developments and tourist information facilities indicated a low level of mean satisfaction, paving the critique that Negombo as a beach centric tourist attraction is not serving well with its natural beauty and its destination management. Further, it is advocated that the policymakers and tourism service providers have a significant role in leading the way to attract more potential visitors to enhance their destination satisfaction and to encourage them to revisit Sri Lanka while recommending it to others. The survey was done during the off-peak season of the industry and it is suggested that the survey would have been conducted throughout a complete year.

Keywords: destination attributes, coastal tourism, tourism development, tourist satisfaction

Procedia PDF Downloads 372

Authors: Harley Stephens

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Although fiducial marker insertion is regarded as the ‘gold standard’ in terms of image guided radiotherapy (IGRT), its application must be considered carefully as the procedure can be invasive, time-consuming, and reliant on consultant expertise. Precision of the fiducials is dependent on these markers remaining in the same location and on the prostate not changing shape during the course treatment. To facilitate the acquirement of non-ionising IGRT and intra-fractional prostate tracking, Clarity TPUS was developed as an alternative imaging system. The main benefits of Clarity TPUS are that it is non-invasive, non-ionising and cost-effective. Other studies have compared fiducials to transabdominal ultrasound, which has since been proven to not be as accurate as trans-perineal imaging, as included in this study. CBCT fiducial translations and Clarity TPUS translations for 120 images as part of the PACE-C prostate SABR trial were retrospectively evaluated by three imaging specialists. Differences were analysed using correlation and Bland-Altman plots. Inter-observer matches agreed within 3mm 88.3 % of the time in left/right direction, 86.7 % of the time in in superior/inferior direction, and 91.7% of the time in ant/post direction. They agreed within 5mm more than 98.3 % of the time in all directions. The intra-class correlation co-efficient was calculated for each direction to show agreement between imaging specialist for inter-observer variability. Each was 0.95 or above, with 1 indicating perfect reliability. Agreement between observers was slightly higher for CBCT and fiducials at 98.7% agreement within 5 mm, compared to clarity TPUS where 96.7% agreement was seen within 5mm. Clarity TPUS has the benefit of no additional dose and intra-fractional monitoring, and results show a good correlation between the different modalities. Inter-observer variability is to be considered, and further research with a larger population would be of benefit.

Keywords: oncology, prostate radiotherapy, image guided radiotherapy, IGRT

Procedia PDF Downloads 93

Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

Procedia PDF Downloads 89

Authors: Olagunju John Olusesan-Remi

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The study area Ijero-Ekiti falls within the Ilesha-Ekiti Schist belt, originating from the long year of the Pan-Africa orogenic events and various cataclysmic tectonic activities in history. Ijero-Ekiti is situated within latitude 7 degree 45N and 7 Degree 55N. Ijero Ekiti is bordered between the Dahomean Basin and the southern Bida/Benue basin on the Geological map of Nigeria. This research work centers on majorly on investigating the chemical composition and as well as the mineralogical distribution of the various mineral-bearing rocks that composed the study area. This work is essentially carried out with a view to assessing and at the same time ascertaining the economic potentials and or the industrial significance of the area to Ekiti-south western region and the Nigeria nation as a whole. The mineralogical distribution pattern is of particular interest to us in this study. In this regard essential focus is put on the mostly the economic gemstones distributions within the various mineral bearing rocks in the zone, some of which includes the tourmaline formation, cassiterite deposit, tin-ore, tantalum columbite, smoky quartz, amethyst, polychrome and emerald variety beryl among others as they occurred within the older granite of the Precambrian rocks. To this end, samples of the major rock types were taken from various locations within the study area for detail scientific analysis as follows: The Igemo pegmatite of Ijero west, the epidiorite of Idaho, the biotitic hornblende gneiss of Ikoro-Ijero north and the beryl crystalline rock types to mention a few. The slides of the each rock from the aforementioned zones were later prepared and viewed under a cross Nichol petro graphic microscope with a particular focus on the light reflection ability of the constituent minerals in each rock samples. The results from the physical analysis viewed from the colour had it that the pegmatite samples ranges from pure milky white to fairly pinkish coloration. Other physical properties investigated include the streak, luster, form, specific gravity, cleavage/fracture pattern etc. The optical examination carried out centers on the refractive indices and pleochroism of the minerals present while the chemical analysis reveals from the tourmaline samples a differing correlation coefficient of the various oxides in each samples collected through which the mineral presence was established. In conclusion, it was inferred that the various minerals outlined above were in reasonable quantity within the Ijero area. With the above discoveries, therefore, we strongly recommend a detailed scientific investigation to be carried out such that will lead to a comprehensive mining of the area. Above all, it is our conclusion that a comprehensive mineralogical exploitation of this area will not only boost the socio-economic potential of the area but at the same time will go a long way contributing immensely to the socio-economic growth and development of the Nation-Nigeria at large.

Keywords: Ijero Ekiti, Southwestern Nigeria, economic minerals, pegmatite of the pan African origin, cataclastic tectonic activities, Ilesha Schistbelt, precambrian formations

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Authors: DEVASHISH KHULBE, MANU PATHAK

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

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

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Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel

Abstract:

Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.

Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 132

Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

Procedia PDF Downloads 137

Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

Abstract:

A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

Procedia PDF Downloads 178

Authors: Yu Hung Chiang, Hei Chia Wang

Abstract:

Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

Procedia PDF Downloads 317

Authors: Hyun-Woo Cho

Abstract:

Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

Procedia PDF Downloads 387

Authors: Gayani K. Nandasiri, Tilak Dias, William Hurley

Abstract:

Venous disease of human lower limb could range from minor asymptomatic incompetence of venous valves to chronic venous ulceration. The sheer prevalence of varicose veins and its associated significant costs of treating late complications such as chronic ulcers contribute to a higher burden on health care resources. In most of western countries with developed health care systems, treatment costs associated with Venous disease accounts for a considerable portion of their total health care budget, and it has become a high-cost burden to National Health Service (NHS), UK. The established gold standard of treatment for the venous disease is the graduated compression, where the pressure at the ankle being highest and decreasing towards the knee and thigh. Currently, medical practitioners use two main methods to treat venous disease; i.e. compression bandaging and compression stockings. Both these systems have their own disadvantages which lead to the current programme of research. The aim of the present study is to revolutionize the compression therapy by using a novel active compression system to deliver a controllable and more accurate pressure profiles using a series of inflatable mini bladders. Two types of commercially available silicones were tested for the application. The mini bladders were designed with a special fabrication procedure to provide required pressure profiles, and a series of experiments were conducted to characterise the mini bladders. The inflation/deflation heights of these mini bladders were investigated experimentally and using a finite element model (FEM), and the experimental data were compared to the results obtained from FEM simulations, which showed 70-80% agreement. Finally, the mini bladders were tested for its pressure transmittance characteristics, and the results showed a 70-80% of inlet air pressure transmitted onto the treated surface.

Keywords: finite element analysis, graduated compression, inflatable bladders, venous disease

Procedia PDF Downloads 171

Authors: Issa M. Shehabat, Huda F. Y. Nimri

Abstract:

This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

Procedia PDF Downloads 127