Search results for: international ovarian tumor analysis classification

Authors: Nasar Aldian Ambark Shashoa

Abstract:

Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

Procedia PDF Downloads 506

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 539

Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

Abstract:

Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

Procedia PDF Downloads 485

Authors: J. R. Ashrapov, G. A. Alihodzhaeva, D. E. Abdullaev, N. R. Kadirbekov

Abstract:

Diagnosis of brain tumors is one of the challenges, as several central nervous system diseases run the same symptoms. Modern diagnostic techniques such as CT, MRI helps to significantly improve the surgery in the operating period, after surgery, after allowing time to identify postoperative complications in neurosurgery. Purpose: To study the MRI characteristics and localization of brain tumors in children and to detect the postoperative complications in the postoperative period. Materials and methods: A retrospective study of treatment of 62 children with brain tumors in age from 2 to 5 years was performed. Results of the review: MRI scan of the brain of the 62 patients 52 (83.8%) case revealed a brain tumor. Distribution on MRI of brain tumors found in 15 (24.1%) - glioblastomas, 21 (33.8%) - astrocytomas, 7 (11.2%) - medulloblastomas, 9 (14.5%) - a tumor origin (craniopharyngiomas, chordoma of the skull base). MRI revealed the following characteristic features: an additional sign of the heterogeneous MRI signal of hyper and hypointensive T1 and T2 modes with a different perifocal swelling degree with involvement in the process of brain vessels. The main objectives of postoperative MRI study are the identification of early or late postoperative complications, evaluation of radical surgery, the identification of the extended-growing tumor that (in terms of 3-4 weeks). MRI performed in the following cases: 1. Suspicion of a hematoma (3 days or more) 2. Suspicion continued tumor growth (in terms of 3-4 weeks). Conclusions: Magnetic resonance tomography is a highly informative method of diagnostics of brain tumors in children. MRI also helps to determine the effectiveness and tactics of treatment and the follow up in the postoperative period.

Keywords: brain tumors, children, MRI, treatment

Procedia PDF Downloads 124

Authors: Ali Asheibi

Abstract:

The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 225

Authors: Liane Marcia Freitas Silva, Fernando Augusto Silva Marins, Maria Silene Alexandre Leite

Abstract:

The adoption of a network structure, like in the supply chains, favors the increase of dependence between companies and, by consequence, their vulnerability. Environment disasters, sociopolitical and economical events, and the dynamics of supply chains elevate the uncertainty of their operation, favoring the occurrence of events that can generate break up in the operations and other undesired consequences. Thus, supply chains are exposed to various risks that can influence the profitability of companies involved, and there are several previous studies that have proposed risk classification models in order to categorize the risks and to manage them. The objective of this paper is to analyze and discuss thirty of these risk classification models by means a theoretical survey. The research method adopted for analyzing and discussion includes three phases: The identification of the types of risks proposed in each one of the thirty models, the grouping of them considering equivalent concepts associated to their definitions, and, the analysis of these risks groups, evaluating their similarities and differences. After these analyses, it was possible to conclude that, in fact, there is more than thirty risks types identified in the literature of Supply Chains, but some of them are identical despite of be used distinct terms to characterize them, because different criteria for risk classification are adopted by researchers. In short, it is observed that some types of risks are identified as risk source for supply chains, such as, demand risk, environmental risk and safety risk. On the other hand, other types of risks are identified by the consequences that they can generate for the supply chains, such as, the reputation risk, the asset depreciation risk and the competitive risk. These results are consequence of the disagreements between researchers on risk classification, mainly about what is risk event and about what is the consequence of risk occurrence. An additional study is in developing in order to clarify how the risks can be generated, and which are the characteristics of the components in a Supply Chain that leads to occurrence of risk.

Keywords: sisks classification, survey, supply chain management, theoretical discussion

Procedia PDF Downloads 605

Authors: Indu Poornima

Abstract:

This paper aims at understanding the Socio-historical, political and economic dimensions of Female Genital Mutilation in Africa. After throwing light on the definition of FGM and scrutinizing the misconceptions associated with it, the paper progresses to analyze the following questions. a) How do communities performing FGM rationalize their act? b) Are the victims (women) themselves the strongest proponents of FGM ? and c) Are legislations against FGM by international organizations counter-productive?

Keywords: female genital mutilation, Africa, rationalizing the act, international legislations

Procedia PDF Downloads 193

Authors: M. A. H. Barry

Abstract:

The concept of Good faith (husn al-niyyah) and fair-dealing (Nadl) are the fundamental guiding elements in all contracts and other agreements under Islamic law. The preaching of Al-Quran and Prophet Muhammad’s (Peace Be upon Him) firmly command people to act in good faith in all dealings. There are several Quran verses and the Prophet’s saying which stressed the significance of dealing honestly and fairly in all transactions. Under the English law, the good faith is not considered a fundamental requirement for the formation of a legal contract. However, the concept of Good Faith in private contracts is recognized by the civil law system and in Article 7(1) of the Convention on International Sale of Goods (CISG-Vienna Convention-1980). It took several centuries for the international trading community to recognize the significance of the concept of good faith for the international sale of goods transactions. Nevertheless, the recognition of good faith in Civil law is only confined for the commercial contracts. Subsequently to the CISG, this concept has made inroads into the private international law. There are submissions in favour of applying the good faith concept to public international law based on tacit recognition by the international conventions and International Tribunals. However, under public international law the concept of good faith is not recognized as a source of rights or obligations. This weakens the spirit of the good faith concept, particularly when determining the international disputes. This also creates a fundamental flaw because the absence of good faith application means the breaches tainted by bad faith are tolerated. The objective of this research is to evaluate, examine and analyze the application of the concept of good faith in the modern laws and identify its limitation, in comparison with Islamic concept of good faith. This paper also identifies the problems and issues connected with the non-application of this concept to public international law. This research consists of three key components (1) the preliminary inquiry (2) subject analysis and discovery of research results, and (3) examining the challenging problems, and concluding with proposals. The preliminary inquiry is based on both the primary and secondary sources. The same sources are used for the subject analysis. This research also has both inductive and deductive features. The Islamic concept of good faith covers all situations and circumstances where the bad faith causes unfairness to the affected parties, especially the weak parties. Under the Islamic law, the concept of good faith is a source of rights and obligations as Islam prohibits any person committing wrongful or delinquent acts in any dealing whether in a private or public life. This rule is applicable not only for individuals but also for institutions, states, and international organizations. This paper explains how the unfairness is caused by non-recognition of the good faith concept as a source of rights or obligations under public international law and provides legal and non-legal reasons to show why the Islamic formulation is important.

Keywords: good faith, the civil law system, the Islamic concept, public international law

Procedia PDF Downloads 116

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 209

Authors: D. Maryama AG. Daud, Zuliana Bacho, Stephanie Chok, DG. Mashitah PG. Baharuddin, Mohd Hatta Tarmizi, Nathira Abdul Majeed, Helen Lasimbang

Abstract:

Lifestyle, physical activity, food intake, genetics and medication are contributing factors for people getting obese. Which in some of the obese people were a low or non-responder to exercise. And obesity is very common clinical feature in women affected by Polycystic Ovarian Syndrome (PCOS). Labisia pumila var. alata (LP) is a local herb which had been widely used by Malay women in treating menstrual irregularities, painful menstruation and postpartum well-being. Therefore, this study was carried out to investigate the effect of LP with a structured exercise program on anthropometric, body composition and physical fitness performance of PCOS patients. By using a single blind and parallel study design, where by subjects were assigned into a 16-wk structured exercise program (3 times a week) interventions; (LP and exercise; LPE, and exercise only; E). All subjects in the LPE group were prescribed 200mg LP; once a day, for 16 weeks. The training heart rate (HR) was monitored based on a percentage of the maximum HR (HRmax) achieved during submaximal exercise test that was conducted at wk-0 and wk-8. The progression of aerobic exercise intensity from 25–30 min at 60 – 65% HRmax during the first week to 45 min at 75–80% HRmax by the end of this study. Anthropometric (body weight, Wt; waist circumference, WC; and hip circumference, HC), body composition (fat mass, FM; percentage body fat, %BF; Fat Free Mass, FFM) and physical fitness performance (push up to failure, PU; 1-minute Sit Up, SU; and aerobic step test, PVO2max) were measured at wk-0, wk-4, wk-8, wk-12, and wk-16. This study found that LP does not have a significant effect on body composition, anthropometric and physical fitness performance of PCOS patients underwent a structured exercise program. It means LP does not improve exercise responses of PCOS patients towards anthropometric, body composition and physical fitness performance. The overall data shows exercise responses of PCOS patients is by increasing their aerobic endurance and muscle endurance performances, there is a significant reduction in FM, PBF, HC, and Wt significantly. Therefore, exercise program for PCOS patients have to focus on aerobic fitness, and muscle endurance.

Keywords: polycystic ovarian syndrome, Labisia pumila var. alata, body composition, aerobic endurance, muscle endurance, anthropometric

Procedia PDF Downloads 191

Authors: Mohammad Hossein Habibi, Atena Sadat Hosseini

Abstract:

Colorectal cancer is the third leading cause of cancer-related death in the world. Colorectal cancer screening, early detection, and treatment programs could benefit from the most up-to-date information on the disease's burden, given the present worldwide trend of increasing colorectal cancer incidence. Tumor recurrence and resistance are exacerbated by the presence of chemotherapy-resistant cancer stem cells that can generate rapidly proliferating tumor cells. In addition, tumor cells can evolve chemoresistance through adaptation mechanisms. In this work, we used in silico analysis to select suitable GEO datasets. In this study, we compared slow-growing cancer stem cells with high-growth colorectal cancer-derived cancer stem cells. We then evaluated the signal pathways, transcription factors, and kinases associated with these two types of cancer stem cells. A total of 980 upregulated genes and 870 downregulated genes were clustered. MAPK signaling pathway, AGE-RAGE signaling pathway in diabetic complications, Fc gamma R-mediated phagocytosis, and Steroid biosynthesis signaling pathways were observed in upregulated genes. Also, caffeine metabolism, amino sugar and nucleotide sugar metabolism, TNF signaling pathway, and cytosolic DNA-sensing pathway were involved in downregulated genes. In the next step, we evaluated the best transcription factors and kinases in two types of cancer stem cells. In this regard, NR2F2, ZEB2, HEY1, and HDGF as transcription factors and PRDM5, SMAD, CBP, and KDM2B as critical kinases in upregulated genes. On the other hand, IRF1, SPDEF, NCOA1, and STAT1 transcription factors and CTNNB1 and CDH7 kinases were regulated low expression genes. Using bioinformatics analysis in the present study, we conducted an in-depth study of colorectal cancer stem cells at low and high growth rates so that we could take further steps to detect and even target these cells. Naturally, more additional tests are needed in this direction.

Keywords: colorectal cancer, bioinformatics analysis, transcription factor, kinases, cancer stem cells

Procedia PDF Downloads 101

Authors: Dechen Tshering Vogel, Johannes T. Heverhagen, Bernard Kiss, Spyridon Arampatzis

Abstract:

In addition to computed tomography (CT), contrast enhanced ultrasound (CEUS), and magnetic resonance imaging (MRI) are being increasingly used for imaging of renal lesions. The aim of this prospective study was to compare the classification of complex cystic renal lesions using the Bosniak classification with CEUS and MRI to CT. Forty-eight patients with 65 cystic renal lesions were included in this study. All participants signed written informed consent. The agreement between the Bosniak classifications of complex renal lesions ( ≥ BII-F) on CEUS and MRI were compared to that of CT and were tested using Cohen’s Kappa. Sensitivity, specificity, positive and negative predictive values (PPV/NPV) and the accuracy of CEUS and MRI compared to CT in the detection of complex renal lesions were calculated. Twenty-nine (45%) out of 65 cystic renal lesions were classified as complex using CT. The agreement between CEUS and CT in the classification of complex cysts was fair (agreement 50.8%, Kappa 0.31), and was excellent between MRI and CT (agreement 93.9%, Kappa 0.88). Compared to CT, MRI had a sensitivity of 96.6%, specificity of 91.7%, a PPV of 54.7%, and an NPV of 54.7% with an accuracy of 63.1%. The corresponding values for CEUS were sensitivity 100.0%, specificity 33.3%, PPV 90.3%, and NPV 97.1% with an accuracy 93.8%. The classification of complex renal cysts based on MRI and CT scans correlated well, and MRI can be used instead of CT for this purpose. CEUS can exclude complex lesions, but due to higher sensitivity, cystic lesions tend to be upgraded. However, it is useful for initial imaging, for follow up of lesions and in those patients with contraindications to CT and MRI.

Keywords: Bosniak classification, computed tomography, contrast enhanced ultrasound, cystic renal lesions, magnetic resonance imaging

Procedia PDF Downloads 119

Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

Procedia PDF Downloads 82

Authors: Jumanah S. Alawfi

Abstract:

Polycystic ovary syndrome (PCOS) is a common endocrinopathy among females in their reproductive years. The incidence cases are nearly 1.55 million among females across the globe, with 0.43 million associated disability-adjusted life-years (DALYs). This syndrome is associated with intricate mechanisms typically characterized by insulin resistance (IR), infertility, overweight and/or obesity. Lifestyle interventions are often prescribed as an adjective treatment. Nonetheless, obesity is a complex disease that encompasses multiple dimensions, such as excessive energy intake and genetics. The melanocortin 4 receptor mutation (MC4R) is an important mediator in appetite. There is emerging evidence that suggests its role in the Body Mass Index (BMI) among PCOS subjects, which poses the question of obesity and/or overweight among the PCOS patients who carry the MC4R variants may be caused by overconsumption. Thereby, using other satiety techniques may be beneficial as a part of personalized nutrition. Therefore, the aim of the current mini-review is to discuss the effect of the vegan low glycemic diet on reducing appetite among PCOS patients. The review shows that there is a gap in the knowledge of the effect of the vegan diet on PCOS patients who carry MC4R variants which need further research.

Keywords: polycystic ovarian syndrome (PCOS), Appetite, Melanocortin 4 Receptor Mutation (MC4R)., Obesity

Procedia PDF Downloads 100

Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

Abstract:

DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

Procedia PDF Downloads 294

Authors: Adrian-Gabriel Chifu, Sebastien Fournier

Abstract:

One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

Procedia PDF Downloads 56

Authors: Kaewkarn Phuangsombat, Arthit Phuangsombat, Anupun Terdwongworakul

Abstract:

Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.

Keywords: mung bean, near infrared, germinatability, hard seed

Procedia PDF Downloads 279

Authors: Patsorn Worawattananutai, Srisopa Ruangnoo, Arunporn Itharat

Abstract:

Hibiscus sabdariffa (HS) leaves are vegetables which are extensively used as blood tonic and laxatives in Thai traditional medicine. They are popularly used as healthy sour soup for prevention of chronic diseases such as cancer. Therefore, the cytotoxic activity of different extracts of fresh and dried Hibiscus sabdariffa leaves were investigated via the sulforhodamine B (SRB) assay against three types of women’s cancer cell lines, namely the human cervical adenocarcinoma cell line (HeLa), the human ovarian adenocarcinoma cell line (SKOV-3), and the human breast adenocarcinoma cell line (MCF-7). Extraction methods were squeezing, boiling with water and maceration with 95% or 50% ethanol. The 95% ethanolic extracts of Hibiscus sabdariffa dry leaves (HSDE95) showed the highest cytotoxicity against all types of women’s cancer cell lines with the IC50 values in range 7.51±0.33 to 12.13±1.85 µg/ml. Its IC50 values against SKOV-3, HeLa and MCF-7 were 7.51±0.33, 9.44±1.41 and 12.13±1.85 µg/ml, respectively. In these results, this extract can be classified as “active” according to the NCI guideline which indicated that IC50 values of the active cytotoxic plant extracts have to be beneath 20 µg/ml. Thus, HSDE95 was concluded to be a potent cytotoxic drug for all women’s cancer cells. This extract should be further investigated to isolate active compounds against women’s cancer cells.

Keywords: breast adenocarcinoma, cervical adenocarcinoma, cytotoxic activity, Hibiscus sabdariffa, ovarian adenocarcinoma

Procedia PDF Downloads 581

Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno

Abstract:

Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.

Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement

Procedia PDF Downloads 176

Authors: Jean Gray C. Achapero, Mary Margareth P. Ancheta, Patricia Anjelika A. Angeles, Shannon Denzel S. Ao Tai, Carl Brandon C. Barlis, Chrislen Mae B. Benavidez

Abstract:

Health literacy and awareness of Polycystic ovarian syndrome (PCOS) is a global issue that is under-addressed in the Philippines. Conducting a thorough review of the country's ability to recognize and comprehend the severity of the syndrome should be undertaken, as early treatment is essential to avoid further disorder complications. This research aims to assess the health literacy and awareness of the female residents of Barangay Dagatan, Sabang, and Marauoy Lipa, Batangas on PCOS. It followed a cross-sectional study, and data gathering was done through a pre-assessment using the Single Item Literacy Screener (SILS) and an online population-based survey questionnaire about PCOS awareness. The participants, as based on the objectives and purposive sampling method, were females aged 18-45 years old. Data were analyzed statistically using STATA 13.1 software. The study showed that 339 (76%) out of 444 respondents passed the SILS meaning the residents have proficient health literacy. Among the 339 respondents, 87% (287) had previous knowledge about PCOS. The respondents showed minimal awareness of PCOS symptoms which could be attributed to its broad spectrum of information. Respondents were shown to be most knowledgeable about PCOS physiology, treatment, beliefs, and its remedies. The respondents’ age had no significant association with their health literacy (p=0.31) and PCOS awareness (p=0.60). A significant association was noted, however, in their educational attainment linked with their health literacy (p=<0.0001) and PCOS awareness (p=0.001). It is suggested that reproductive health education even in the lower year levels must be optimized and Local Government Unit (LGU)/Non-Government Organization (NGO)-held seminars should be conducted for knowledge reinforcement. Reliable health information should be more accessible to the public and clinicians must emphasize the importance of the majority of early screening as part of routine physical examination for women of reproductive age to increase health literacy and awareness about PCOS and actively engage in the management of the disease.

Keywords: age, awareness, educational attainment, health literacy, polycystic ovarian syndrome

Procedia PDF Downloads 196

Authors: Aisha Iddrsiu

Abstract:

Public Relations (PR) has rapidly evolved around the world, just as companies have expanded to reach other parts of the world. With most multinational corporations conducting businesses in more than one country, only a few of these Multinational Corporations (MNC’s) are actual public relations firms, many have public relations departments or divisions that conduct public relations practices internationally. Hence international public relations is seen as a fast-growing specialty in the field of Public Relations. Multinational companies have devised strategies to effectively communicate and execute their roles within and between foreign publics and other cultures in which they operate through various means including the internet which is among the major inventions that have enabled corporations to establish their presents while targeting anonymous and diverse publics from varied cultures. International public relations practitioners rely on strategies coupled with internet use to communicate among and with foreign publics. Corporate websites and various social media handles have served as an important channel for public relations activities targeting both internal and international publics. In an incessant expansion of corporations and interactions with the publics from different cultures, it has become eminent to understand the public relation strategies used by MNCs in their international communication. This study therefore seeks to establish the international public relation strategies or models employed by Multinational Corporations specifically Arcelik Global in the management of its subsidiaries and communicating with international public. This study analyses both Arçelik global’s (one of the largest multinational companies in Turkey) website and social media accounts to understand the management strategy used with it subsidiary as well as strategies used to communicate with its global and local publics. Other underlying objective of this study are, 1. To examine the dominant international public relations models used by Multinational Corporations (Arcelik global). 2. To understand how Multinational Corporations manage (Arcelik global) its subsidiaries. 3. To understand how Multinational Corporations (Arcelik global) communicate with international or global publics. Research Questions 1. The main global PR strategies employed by multinational corporations (Arcelik global) 2. How subsidiaries of multinational corporations like Arcelik Global are managed. 3. How multinational corporations, like Arcelik worldwide, interact with international publics.

Keywords: multinational corporation, ethnocentric model, polycentric model, international public relations

Procedia PDF Downloads 60

Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

Abstract:

Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

Procedia PDF Downloads 212

Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

Abstract:

Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

Procedia PDF Downloads 258

Authors: Jerzy Banski

Abstract:

The basic aim of this study is to discuss and assess different classifications and research approaches to small towns that take their social and economic functions into account, as well as relations with surrounding areas. The subject literature typically includes three types of approaches to the classification of small towns: 1) the structural, 2) the location-related, and 3) the mixed. The structural approach allows for the grouping of towns from the point of view of the social, cultural and economic functions they discharge. The location-related approach draws on the idea of there being a continuum between the center and the periphery. A mixed classification making simultaneous use of the different approaches to research brings the most information to bear in regard to categories of the urban locality. Bearing in mind the approaches to classification, it is possible to propose a synthetic method for classifying small towns that takes account of economic structure, location and the relationship between the towns and their surroundings. In the case of economic structure, the small centers may be divided into two basic groups – those featuring a multi-branch structure and those that are specialized economically. A second element of the classification reflects the locations of urban centers. Two basic types can be identified – the small town within the range of impact of a large agglomeration, or else the town outside such areas, which is to say located peripherally. The third component of the classification arises out of small towns’ relations with their surroundings. In consequence, it is possible to indicate 8 types of small-town: from local centers enjoying good accessibility and a multi-branch economic structure to peripheral supra-local centers characterised by a specialized economic structure.

Keywords: small towns, classification, functional structure, localization

Procedia PDF Downloads 165

Authors: D. Suman, M. Venkateshwara Rao

Abstract:

Cancer is a disease caused by an uncontrolled division of abnormal cells in a part of the body, which is affecting millions of people leading to death. Even though there have been tremendous developments taken place over the last few decades the effective therapy for cancer is still not a reality. The existing techniques of cancer therapy are chemotherapy and radio therapy which are having their limitations in terms of the side effects, patient discomfort, radiation hazards and the localization of treatment. This paper describes a novel method for cancer therapy by using RF-hyperthermia application of nanoparticles. We have synthesized ferromagnetic nanoparticles and characterized by using XRD and TEM. These nanoparticles after the biocompatibility studies will be injected in to the body with a suitable tracer element having affinity to the specific tumor site. When RF energy is applied to the nanoparticles at the tumor site it produces heat of excess room temperature and nearly 41-45°C is sufficient to kill the tumor cells. We have designed a RF source generator provided with a temperature feedback controller to control the radiation induced temperature of the tumor site. The temperature control is achieved through a negative feedback mechanism of the thermocouple and a relay connected to the power source of the RF generator. This method has advantages in terms of its effect like localized therapy, less radiation, and no side effects. It has several challenges in designing the RF source provided with coils suitable for the tumour site, biocompatibility of the nanomaterials, cooling system design for the RF coil. If we can overcome these challenges this method will be a huge benefit for the society.

Keywords: hyperthermia, cancer therapy, RF source generator, nanoparticles

Procedia PDF Downloads 444

Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

Procedia PDF Downloads 344

Authors: Nouf A. Aldarmahi, Nesrin I. Tarbiah, Nuha A. Alkhattabi, Huda F. Alshaibi

Abstract:

Nigella sativa which is known as dark cumin is a well-known example for a widely applicable herbal medicine. Nigella sativa can be effective in a variety of diseases such as hypertension, diabetes, bronchitis, gastrointestinal upset, and cancer. The anticancer effect of Nigella sativa appeared to be mediated by immune-modulatory effect through stimulating human natural killer (NK) cells. This is a type of lymphocytes which is part of the innate immunity, also known as the first line of defense in the body against pathogens. This study investigated the effect of thymoquinone as a major component of Nigella sativa on the molecular cytotoxic pathway of NK cell and the role of thymoquinone therapeutic effect on NK cells. NK cells were cultured with breast tumor cells in different ways and cultured media was collected and the concentration of perforin, granzyme B and interferon-α were measured by ELISA. The cytotoxic effect of NK cells on breast tumor cells was enhanced in the presence of thymoquinone, with increased activity of perforin in NK cells. This improved anticancer effect of thymoquinone on breast cancer cells.

Keywords: breast cancer, cancer cells, natural killer cells, thymoquinone

Procedia PDF Downloads 219

Authors: Paul J Yazaki, Michael Bouvet, John Shively

Abstract:

Surgery for solid gastrointestinal (GI) cancers such as pancreatic, colorectal, and gastric adenocarcinoma remains the mainstay of curative therapy. Complete resection of the primary tumor with negative margins (R0 resection), its draining lymph nodes, and distant metastases offers the optimal surgical benefit. Real-time fluorescence guided surgery (FGS) promises to improve GI cancer outcomes and is rapidly advancing with tumor-specific antibody conjugated fluorophores that can be imaged using near infrared (NIR) technology. Carcinoembryonic Antigen (CEA) is a non-internalizing tumor antigen validated as a surface tumor marker expressed in >95% of colorectal, 80% of gastric, and 60% of pancreatic adenocarcinomas. Our humanized anti-CEA hT84.66-M5A (M5A) monoclonal antibody (mAb)was conjugated with the NHS-IRDye800CW fluorophore and shown it can rapidly and effectively NIRoptical imageorthotopically implanted human colon and pancreatic cancer in mouse models. A limitation observed is that these NIR-800 dye conjugated mAbs have a rapid clearance from the blood, leading to a narrow timeframe for FGS and requiring high doses for effective optical imaging. We developed a novel antibody-fluorophore conjugate by incorporating a PEGylated sidearm linker to shield or mask the IR800 dye’s hydrophobicity which effectively extended the agent’s blood circulation half-life leading to increased tumor sensitivity and lowered normal hepatic uptake. We hypothesized that our unique anti-CEA linked to the fluorophore, IR800 by PEGylated sidewinder, M5A-SW-IR800 will become the next generation optical imaging agent, safe, effective, and widely applicable for intraoperative image guided surgery in CEA expressing GI cancers.

Keywords: optical imaging, anti-CEA, cancer, fluorescence-guided surgery

Procedia PDF Downloads 128

Authors: Vishwa Joshi

Abstract:

The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

Procedia PDF Downloads 477

Authors: H. Nakamura

Abstract:

This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: database business, electronic library, international strategic alliances, partner selection

Procedia PDF Downloads 353