Search results for: feature detection

Authors: Anželika Teresė

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In order to solve issues in sign language linguistics, address matters pertaining to maintaining high quality of sign language (SL) translation, contribute to dispelling misconceptions about SL and deaf people, and raise awareness and understanding of the deaf community heritage, this presentation discusses literature in Lithuanian Sign Language (LSL) and inherent metaphors that are created by using the phonological parameter –handshape, location, movement, palm orientation and nonmanual features. The study covered in this presentation is twofold, involving both the micro-level analysis of metaphors in terms of phonological parameters as a sub-lexical feature and the macro-level analysis of the poetic context. Cognitive theories underlie research of metaphors in sign language literature in a range of SL. The study follows this practice. The presentation covers the qualitative analysis of 34 pieces of LSL literature. The analysis employs ELAN software widely used in SL research. The target is to examine how specific types of each phonological parameter are used for the creation of metaphors in LSL literature and what metaphors are created. The results of the study show that LSL literature employs a range of metaphors created by using classifier signs and by modifying the established signs. The study also reveals that LSL literature tends to create reference metaphors indicating status and power. As the study shows, LSL poets metaphorically encode status by encoding another meaning in the same sign, which results in creating double metaphors. The metaphor of identity has been determined. Notably, the poetic context has revealed that the latter metaphor can also be identified as a metaphor for life. The study goes on to note that deaf poets create metaphors related to the importance of various phenomena significance of the lyrical subject. Notably, the study has allowed detecting locations, nonmanual features and etc., never mentioned in previous SL research as used for the creation of metaphors.

Keywords: Lithuanian sign language, sign language literature, sign language metaphor, metaphor at the phonological level, cognitive linguistics

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Claudio Clemente, Valentina Gargiulo, Alessio Occhicone, Giovanni Piero Pepe, Giovanni Ausanio, Michela Alfè

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Volatile organic compound (VOC) emissions represent a serious risk to human health and the integrity of the ecosystems, especially at high concentrations. For this reason, it is very important to continuously monitor environmental quality and develop fast and reliable portable sensors to allow analysis on site. Chemiresistors have become promising candidates for VOC sensing as their ease of fabrication, variety of suitable sensitive materials, and simple sensing data. A chemoresistive gas sensor is a transducer that allows to measure the concentration of an analyte in the gas phase because the changes in resistance are proportional to the amount of the analyte present. The selection of the sensitive material, which interacts with the target analyte, is very important for the sensor performance. The most used VOC detection materials are metal oxides (MOx) for their rapid recovery, high sensitivity to various gas molecules, easy fabrication. Their sensing performance can be improved in terms of operating temperature, selectivity, and detection limit. Metal-organic frameworks (MOFs) have attracted a lot of attention also in the field of gas sensing due to their high porosity, high surface area, tunable morphologies, structural variety. MOFs are generated by the self-assembly of multidentate organic ligands connecting with adjacent multivalent metal nodes via strong coordination interactions, producing stable and highly ordered crystalline porous materials with well-designed structures. However, most MOFs intrinsically exhibit low electrical conductivity. To improve this property, MOFs can be combined with organic and inorganic materials in a hybrid fashion to produce composite materials or can be transformed into more stable structures. MOFs, indeed, can be employed as the precursors of metal oxides with well-designed architectures via the calcination method. The MOF-derived MOx partially preserved the original structure with high surface area and intrinsic open pores, which act as trapping centers for gas molecules, and showed a higher electrical conductivity. Core-shell heterostructures, in which the surface of a metal oxide core is completely coated by a MOF shell, forming a junction at the core-shell heterointerface, can also be synthesized. Also, nanocomposite in which MOF structures are intercalated with graphene related materials can also be produced, and the conductivity increases thanks to the high mobility of electrons of carbon materials. As MOF structures, zinc-based MOFs belonging to the ZIF family were selected in this work. Several Zn-based materials based and/or derived from MOFs were produced, structurally characterized, and arranged in a chemo resistive architecture, also exploring the potentiality of different approaches of sensing layer deposition based on PLD (pulsed laser deposition) and, in case of thermally labile materials, MAPLE (Matrix Assisted Pulsed Laser Evaporation) to enhance the adhesion to the support. The sensors were tested in a controlled humidity chamber, allowing for the possibility of varying the concentration of ethanol, a typical analyte chosen among the VOCs for a first survey. The effect of heating the chemiresistor to improve sensing performances was also explored. Future research will focus on exploring new manufacturing processes for MOF-based gas sensors with the aim to improve sensitivity, selectivity and reduce operating temperatures.

Keywords: chemiresistors, gas sensors, graphene related materials, laser deposition, MAPLE, metal-organic frameworks, metal oxides, nanocomposites, sensing performance, transduction mechanism, volatile organic compounds

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Authors: Giacomo Ciani

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This paper reviews the impact of quantum noise on modern gravitational wave interferometers and explains how squeezed vacuum states are used to push the noise below the standard quantum limit. With the first detection of gravitational waves from a pair of colliding black holes in September 2015 and subsequent detections including that of gravitational waves from a pair of colliding neutron stars, the ground-based interferometric gravitational wave observatories LIGO and VIRGO have opened the era of gravitational-wave and multi-messenger astronomy. Improving the sensitivity of the detectors is of paramount importance to increase the number and quality of the detections, fully exploiting this new information channel about the universe. Although still in the commissioning phase and not at nominal sensitivity, these interferometers are designed to be ultimately limited by a combination of shot noise and quantum radiation pressure noise, which define an envelope known as the standard quantum limit. Despite the name, this limit can be beaten with the use of advanced quantum measurement techniques, with the use of squeezed vacuum states being currently the most mature and promising. Different strategies for implementation of the technology in the large-scale detectors, in both their frequency-independent and frequency-dependent variations, are presented, together with an analysis of the main technological issues and expected sensitivity gain.

Keywords: gravitational waves, interferometers, squeezed vacuum, standard quantum limit

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Authors: Mahan Qwamizadeh, Kun Zhou, Zuoqi Zhang, Yong Wei Zhang

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Typical load-bearing biological materials like bone, mineralized tendon and shell, are biocomposites made from both organic (collagen) and inorganic (biomineral) materials. This amazing class of materials with intrinsic internally designed hierarchical structures show superior mechanical properties with regard to their weak components from which they are formed. Extensive investigations concentrating on static loading conditions have been done to study the biological materials failure. However, most of the damage and failure mechanisms in load-bearing biological materials will occur whenever their structures are exposed to dynamic loading conditions. The main question needed to be answered here is: What is the relation between the layout and architecture of the load-bearing biological materials and their dynamic behavior? In this work, a staggered model has been developed based on the structure of natural materials at nanoscale and Finite Element Analysis (FEA) has been used to study the dynamic behavior of the structure of load-bearing biological materials to answer why the staggered arrangement has been selected by nature to make the nanocomposite structure of most of the biological materials. The results showed that the staggered structures will efficiently attenuate the stress wave rather than the layered structure. Furthermore, such staggered architecture is effectively in charge of utilizing the capacity of the biostructure to resist both normal and shear loads. In this work, the geometrical parameters of the model like the thickness and aspect ratio of the mineral inclusions selected from the typical range of the experimentally observed feature sizes and layout dimensions of the biological materials such as bone and mineralized tendon. Furthermore, the numerical results validated with existing theoretical solutions. Findings of the present work emphasize on the significant effects of dynamic behavior on the natural evolution of load-bearing biological materials and can help scientists to design bioinspired materials in the laboratories.

Keywords: load-bearing biological materials, nanostructure, staggered structure, stress wave decay

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Authors: Rasha Elhawari

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Heritage language learners (HLL) are part of the linguistic reality in Foreign Language Learning (FLL). These learners present several characteristics that are different from non-heritage language learners. They have a personal connection with the language and their motivation to learn the language is partly because of this personal connection. In Canada there is a large diversity in the foreign language learning classroom; the Arabic language classroom is no exception. The Arabic HLL is unique for more than one reason. First, is the fact that the Arabic language is spoken across twenty-two Arab countries across the Arab World. Across the Arab World there is a standard variation and a local dialect that co-exist side by side, i.e. diaglossia exists in a strong and unique way as a feature of Arabic. Second, Arabic is the language that all Muslims across the Muslim World use for their prayers. This raises a number of points when we consider Arabic as a Heritage Language; namely the role of diaglossia, culture and religion. The fact that there is a group of leaners that can be regarded as HLL who are not of Arabic speaking background but are Muslims and use the language for religious purposes is unique, thus course developers and language instructors need take this into consideration. The paper takes a closer look at this distinction and establishes sub-groups the Arabic HLLs in a language and/or culture specific way related mainly to the Arabic HLL. It looks at the learners at the beginners’ Arabic class at the undergraduate university level over a period of three years in order to define this learner. Learners belong to different groups and backgrounds but they all share common characteristics. The paper presents a detailed look at the learner types present at this class in order to help prepare and develop material for this specific learner group. The paper shows that separate HLL and non-HLL courses, especially at the introductory and intermediate level, is successful in resolving some of the pedagogical problems that occur in the Arabic as a Foreign Language classroom. In conclusion, the paper recommends the development of HLL courses at the early levels of language learning. It calls for a change in the pedagogical practices to overcome some of the challenges learner in the introductory Arabic class can face.

Keywords: Arabic, Heritage Language, langauge learner, teaching

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Authors: Khaliun Nyambayar, Nomindari Azzaya, Batkhuyag Purevjav

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Pharmacovigilance was officially introduced in Mongolia in 2003, in accordance with the Health Minister Order 183 for the registry of adverse drug reactions (ADR), approved in 2006 and was reviewed in 2010. This study was designed to evaluate the incidence and common types of adverse drug reactions among hospitalized children, the frequency of adverse drug reaction reported by health care providers, and the follow-up processes resulting from adverse drug reactions. A retrospective study of paediatric patients who experienced an adverse drug reaction from 2015 to 2019, extracted from the “yellow” card at the State Research Center for Maternal and Child Health, (city). A total of 417 adverse drug reactions were reported with an overall incidence was 80 (21.5%). Adverse reactions resulting from the use of antibiotics (particularly gentamycin, cephalosporins, and vancomycin) were usually mild. ADR’s were reported by physicians and nurses (93.8%), pharmacists (6.25%). Although documentation of physician notification occurred for 93% of adverse drug reactions, only 29% of cases were documented in the patient's medical chart, 13% included follow-up education for individuals involved, and 10% were updated in the allergy profile of the hospital computer system. Measures to improve the detection and reporting of adverse drug reactions by all health care professionals should be improved, to enhance our understanding of the nature and impact of these reactions in children.

Keywords: adverse drug reaction, pediatric, yellow card, Mongolia

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Authors: Qinghua Xing, Noha M. Mesbah, Haisheng Wang, Jun Li, Baisuo Zhao

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Droplet digital PCR (ddPCR) is being increasingly adopted for gene detection and quantification because of its higher sensitivity and specificity. According to previous observations and our lab data, it is essential to use endogenous reference genes (RGs) when investigating gene expression at the mRNA level under salt stress. This study aimed to select and validate suitable RGs for gene expression under salt stress using ddPCR. Six candidate RGs were selected based on the tandem mass tag (TMT)-labeled quantitative proteomics of Alkalicoccus halolimnae at four salinities. The expression stability of these candidate genes was evaluated using statistical algorithms (geNorm, NormFinder, BestKeeper and RefFinder). There was a small fluctuation in cycle threshold (Ct) value and copy number of the pdp gene. Its expression stability was ranked in the vanguard of all algorithms, and was the most suitable RG for quantification of expression by both qPCR and ddPCR of A. halolimnae under salt stress. Single RG pdp and RG combinations were used to normalize the expression of ectA, ectB, ectC, and ectD under four salinities. The present study constitutes the first systematic analysis of endogenous RG selection for halophiles responding to salt stress. This work provides a valuable theory and an approach reference of internal control identification for ddPCR-based stress response models.

Keywords: endogenous reference gene, salt stress, ddPCR, RT-qPCR, Alkalicoccus halolimnae

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Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

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Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

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Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R.M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

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Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool have been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will provide consistent, regular and reliable information regarding natural and anthropogenic ground motion phenomena all over Europe.

Keywords: ground displacements, InSAR, natural hazards, satellite imagery

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: Khalid Mahmud

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In this paper, an analytic approach is presented to evaluate the Bit Error Rate (BER) and round trip distance for a UWB chipless RFID system using diversity technique at the reader receiver using different modulation technique. The analysis is carried out with multiresonator based chipless RFID tags using frequency range from 3 GHz − 6 GHz and bandwidth of 500 M Hz in outdoor non-line-of-sight (NLOS) environment. SISO configuration is used to communicate from the reader to the tag and SIMO configuration is used do vice versa. Maximal Ratio Combining (MRC) technique is used in the reader. MPSK, DQPSK, DBPSK, BPSK, QPSK and DMPSK modulation techniques are considered with coherent demodulation to evaluate the BER performance. From the numerical analysis of the results, it is found that at a given BER maximum possible round trip distance can be achieved using DMPSK modulation technique. In addition, it has been proved that, while using DMPSK modulation technique, the application of diversity has very little effect on the overall improvement in reader receiver sensitivity and achievable distance. Finally the method not only proves to be a very good way for tag detection in case of a chipless RFID system but also gives a clear insight regarding the interrelationship between BER, read range, reader received power, number of receiving antenna in outdoor NLOS environment.

Keywords: EGC, MRC, BER, read range, diversity

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Authors: Malik Abdul Jabbar Zen, Wiwik Misaco Yuniarti, Azisya Amalia Karimasari, Novita Priandini

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Zoonos is as an infectiontransmitted froma nimals to human sand vice versa currently having increased in the last 20 years. The experts/scientists predict that zoonosis will be a threat to the community in the future since it leads on 70% emerging infectious diseases (EID) and the high mortality of 50%-90%. The zoonosis’ spread from animal to human is caused by contaminated food known as foodborne disease. One World One Health, as the conceptual prevention toward zoonosis, requires the crossed disciplines cooperation to accelerate and streamlinethe handling ofanimal-based disease. E-Vet Smart Rapid System is an integrated innovation in the veterinary expertise application is able to facilitate the prevention, treatment, and educationagainst pandemic diseases and zoonosis. This system is constructed by Decision Support System (DSS) method provides a database of knowledge that is expected to facilitate the identification of disease rapidly, precisely, and accurately as well as to identify the deduction. The testingis conducted through a black box test case and questionnaire (N=30) by validity and reliability approach. Based on the black box test case reveals that E-Vet Rapid System is able to deliver the results in accordance with system design, and questionnaire shows that this system is valid (r > 0.361) and has a reliability (α > 0.3610).

Keywords: diagnosis, disease, expert systems, livestock, zoonosis

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Maria Ashitko

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The Constitution of the Republic of Belarus is based on the principle of the unity of rights and obligations, including those of the child. The constitutional status of the child is aspecific system of constitutional elements established and guaranteed by the state through the current legislation and regulatory acts that ensure the special legal status of the child, his or her constitutional legal capacity, implementation of the principles of the constitutional and legal status of the child, constitutional rights of the child and their safeguards. Under the principles of the constitutional status of the child, we consider the general, normative, social-volitional rules of behavior established by the Constitution of the Republic of Belarus, laws and other regulatory acts that determine the content and social purpose of the legal status of the child. The constitutional and legal status of the child is characterized by the following special principles, which form a feature of the state legal system:1) Ensuring the interests of the child means providing for the child in accordance with his or her age, state of health, characteristics of development, life experience, family life, cultural traditions, ethnicity. 2) The principle of equal responsibility of both parents or their substitutes characterized by caring for the next generation as one of the priority tasks of the state and society, and all issues related to the implementation of children’s rights should be addressed at the constitutional level. 3) We would like to highlight such a special principle as the subprinciple of safeguards, which is the principle of ensuring the safety of the child. It is also worth noting that in legal studies, there is no relationship between safety and constitutional rights as general safeguards of individual rights and freedoms, and as special safeguards for the right to life. 4) The principle of justice is expressed by the fact that in modern conditions, the quality of life is determined not only by material wealth but also by the ability of the state to ensure the harmonization of social relations and social harmony on the basis of humanism and justice. Thus, the specificity of the constitutional status of the child is the age boundary between adulthood and minority; therefore, we propose to highlight the age characteristics of the child as an additional element. It is advisable to highlight such a special principle as the subprinciple of safeguards, which is the principle of ensuring the safety of the child.

Keywords: children’s rights, constitutional status, constitutional principles, constitutional rights

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Authors: Abdullah Mohammad, Abdullah Alshemali, Esmaeil Alsaleh

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The chemical composition of desalinated water is modified to make it more acceptable to the end-user. Sometimes, this modification is approached by mixing with brackish water that is known to contain a variety of minerals. Expectedly, besides minerals, brackish water indigenous bacterial communities access the final mixture hence reaching the end consumer. The current project examined the safety of using brackish water as an ingredient in potable water. Pseudomonas aeruginosa strains were detected in potable and brackish water samples collected from storage facilities in residential areas as well as from main water distribution and storage tanks. The application of molecular and biochemical fingerprinting methods, including phylogeny, RFLP (restriction fragment length polymorphism), MLST (multilocus sequence typing) and substrate specificity testing, suggested that the potable water P. aeruginosa strains were most probably originated from brackish water. Additionally, all the sixty-four isolates showed multi-drug resistance (MDR) phenotype and harboured the three genes responsible for biofilm formation. These virulence factors represent serious health hazards compelling the scientific community to revise the WHO (World Health Organization) and USEP (US Environmental Protection Agency) A potable water quality guidelines, particularly those related to the types of bacterial genera that evade the current water quality guidelines.

Keywords: potable water, brackish water, pseudomonas aeroginosa, multidrug resistance

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Authors: Naila Sher, Mushtaq Ahmed, Nadia Mushtaq, Rahmat Ali Khan

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In cancer therapy, nanoparticles (NPs) shall be applied possibly by inoculation in the veins of humans. This action will connect them with white (WBCs) and red blood cells (RBCs) in the bloodstream before they reach their main targeted cancer cells. However, possible effects of silver, gold, and silver/gold bimetallic NPs (Ag, Au, and Ag/Au BNPs) on baby hamster kidney-21 (BHK-21) cells were studied by MTT assay. Here, Ag, Au, and their Ag/Au BNPs (bimetallic nanoparticles) were synthesized by using Hippeastrum hybridum (HH) extract. These NPs were characterized by UV-visible spectroscopy, FT-IR, XRD, and EDX, and SEM analysis. XRD analysis conferring the crystal structure with an average size of 13.3, 10.72, and 8.34nm of Ag, Au, and Ag/Au BNPs, respectively. SEM showed that Ag, Au, and Ag/Au BNPs had irregular morphologies, with nano measures calculated sizes of 40, 30, and 20 nm respectively. EDX spectrometers confirmed the presence of elemental Ag signal of the AgNPs with 22.75%, Au signal of the AuNPs with 48.08%, Ag signal with 12%, and Au signal with 38.26% of the Ag/Au BNPs. The BHK-21cells were incubated in the existence of doxorubicin, plant extract, Ag, Au, and Ag/Au BNPs. The cytotoxic effects could be observed in a dose-dependent mode; doxorubicin and Ag/Au BNPs were more toxic than plant extract, Ag, and Au NPs. It is demonstrated that NPs interact with BHK-21cells and significantly reduce cell viability in a concentration-dependent manner. However, to reduce the potential threats of NPs further studies are recommended.

Keywords: hippeastrum hybridum, nanoparticle, BHK-21cells

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Authors: Nasser A. Al-Shabib

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Food allergens are most common non-native form when exposed to the immune system. Most food proteins undergo various treatments (e.g. thermal or proteolytic processing) during food manufacturing. Such treatments have the potential to impact the chemical structure of food allergens so as to convert them to more denatured or unfolded forms. The conformational changes in the proteins may affect the allergenicity of treated-allergens. However, most allergenic proteins possess high resistance against thermal modification or digestive enzymes. In the present study, ovomucoid (a major allergenic protein of egg white) was heated in phosphate-buffered saline (pH 7.4) at different temperatures, aqueous solutions and on different surfaces for various times. The results indicated that different antibody-based methods had different sensitivities in detecting the heated ovomucoid. When using one particular immunoassay‚ the immunoreactivity of ovomucoid increased rapidly after heating in water whereas immunoreactivity declined after heating in alkaline buffer (pH 10). Ovomucoid appeared more immunoreactive when dissolved in PBS (pH 7.4) and heated on a stainless steel surface. To the best of our knowledge‚ this is the first time that antibody-based methods have been applied for the detection of ovomucoid adsorbed onto different surfaces under various conditions. The results obtained suggest that use of antibodies to detect ovomucoid after food processing may be problematic. False assurance will be given with the use of inappropriate‚ non-validated immunoassays such as those available commercially as ‘Swab’ tests. A greater understanding of antibody-protein interaction after processing of a protein is required.

Keywords: ovomucoid, thermal treatment, solutions, surfaces

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Authors: Nina Tsvetkova, Rumen Harizanov, Aleksandra Ivanova, Iskra Rainova, Nina Yancheva-Petrova, Dimitar Strashimirov, Raina Enikova, Mihaela Videnova, Eleonora Kaneva, Iskren Kaftandjiev, Viktoria Levterova, Ivan Simeonovski, Nikolay Yanev, Georgi Hinkov

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The Pneumocystis jirovecii (P. jirovecii) and protozoan of the genera Acanthamoeba, Cryptosporidium, and Toxoplasma gondii are opportunistic pathogens that can cause life-threatening infections in immunocompromised patients. Aim of the study was to evaluate the coinfection rate with opportunistic protozoal agents among Bulgarian patients diagnosed with P. jirovecii pneumonia. Thirty-eight pulmonary samples were collected from 38 patients (28 HIV-infected) with P. jirovecii infection. P. jirovecii DNA was detected by real-time PCR targeting the large mitochondrial subunit ribosomal RNA gene. Acanthamoeba was determined by genus-specific conventional PCR assay. Real-time PCR for the detection of a Toxoplasma gondii and Cryptosporidium DNA fragment was used. Pneumocystis DNA was detected in all 38 specimens; 28 (73.7%) were from HIV-infected patients. Three (10,7%) of them were co-infected with T. gondii and 1 (3.6%) with Cryptosporidium. In the group of non-HIV-infected (n=10), Cryptosporidium DNA was detected in an infant (10%). Acanthamoeba DNA was not found in the tested samples. The current study showed a relatively low rate of coinfections of Cryptosporidium spp./T. gondii and P. jirovecii in the Bulgarian patients studied.

Keywords: coinfection, opportunistic protozoal agents, Pneumocystis jirovecii, pulmonary infections

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Authors: Mona Marzouk, Nesrine Hegazi, Aliaa Ragheb, Mona El Shabrawy, Salwa Kawashty

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The whole plant of Matthiola longipetala (Brassicaceae) was extracted by 70% methanol to give the total aqueous methanol extract (AME), which was defatted by hexane yielded hexane extract (HE) and defatted AME (DAME). HE was analyzed through GC/MS assay and revealed the detection of 28 non-polar compounds. In addition, the chemical investigation of DAME led to the isolation and purification of twelve flavonoids and three chlorogenic acids. Their structures were interpreted through chemical (complete and partial acid hydrolysis) and spectroscopic analysis (MS, UV, 1D and 2D NMR). Among them, nine compounds have been isolated for the first time from M. longipetala. Moreover, LC-ESI-MS analysis of DAME was achieved to detect additional 46 metabolites, including phospholipids, organic acids, phenolic acids and flavonoids. The biological activity of AME, HE and DAME against alloxan inducing oxidative stress and diabetes in male rats was investigated. Diabetes was induced using a single dose of Alloxan (150 mg/kg b.wt.). HE and DAME significantly increased serum GSH content in rats (37.3±0.7 and 35.9±0.6 mmol/l) compared to diabetic rats (21.8±0.3) and vitamin E (36.2±1.1) at P<0.01. Also, HE, DAME and AME revealed a significant acute anti-hyperglycemic effect potentiated after four weeks of treatment with blood glucose levels of 96.2±5.4, 98.7±6.1 and 98.9±8.6 mg/dl, respectively, compared to diabetic rats (263.4±7.8) and metaformin group (81.9±2.4) at P<0.01.

Keywords: Brassicaceae, Flavonoid, LCMS/MS, Matthiola

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Authors: Aqeela Ashraf, Muhammad Imran, Tahir Yaqub, Muhammad Tayyab, Yung Fu Chang

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For the identification of bovine mastitic pathogen, an economical, rapid and sensitive molecular diagnostic assay is developed by PCR multiplexing of gene and pathogenic species specific DNA sequences. The multiplex PCR assay is developed for detecting nine important bacterial pathogens causing mastitis Worldwide. The bacterial species selected for this study are Streptococcus agalactiae, Streptococcus dysagalactiae, Streptococcus uberis, Staphylococcus aureus, Escherichia coli, Staphylococcus haemolyticus, Staphylococcus chromogenes Mycoplasma bovis and Staphylococcus epidermidis. A single reaction assay was developed and validated by 27 reference strains and further tested on 276 bacterial strains obtained from culturing mastitic milk. The multiplex PCR assay developed here is further evaluated by applying directly on genomic DNA isolated from 200 mastitic milk samples. It is compared with bacterial culturing method and proved to be more sensitive, rapid, economical and can specifically identify 9 bacterial pathogens in a single reaction. It has detected the pathogens in few culture negative mastitic samples. Recognition of disease is the foundation of disease control and prevention. This assay can be very helpful for maintaining the udder health and milk monitoring.

Keywords: multiplex PCR, bacteria, mastitis, milk

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Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

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Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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Authors: Saif Ullah, Zaigham Hasan, Muhammad Ali, Qaisar Jamal, Kiran Salahuddin, Muhammad Awais

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Survey of avian fauna of Bara Gali Summer Campus, University of Peshawar situated in Abbottabad was conducted from April to October, 2013. A total of 21 species belonging to 5 orders and 15 families were recorded. Out of these, 6 were resident, 12 summer visitor and 3 rare. Order Passeriformes was represented by 16 species which are Certhia himalayana, Megalaima virens, Phylloscopus trochiloides, Garrulax lineatus, Passer rutilans, Corvus macrorhynchos, Hypsipetes leucocephalus, Acridotheres tristis, Delichon dasypus cashmeriensis, Hirundo rustica, Muscicapa thalassina, Saxicola ferrea, Myiophoneus caeruleus, Parus melonolophus, Parus rufonuchalis, Parus monticolus, belonging to 11 families. Two species Dendrocopos himalayansis and Picus squamatus belong to only one family Picidae of order Piciformes. Among rest of the three orders each is represented by only a single species; Accipitriformes by Accipiter virgatus, Coraciformes by Upupa epops while order Psittaciformes has been represented by Psittacula himalayana. The distribution and abundance varied with season and maximum number of species were found during the monsoon season when most of the birds migrate for breeding. Some habits and behaviors like nesting, feeding, breeding and vocalizations were also studied which are very unique from other birds found at lower elevations. Among bird species adapted to diverse habitat in the field, Himalayan Jungle Crow, Common Mynas, Bulbuls, Barn Swallows, barbets were prominent. Interesting feature of the avian fauna is its familiarity with flora, was also observed during the present studies that some birds are very quick and active in their movement on a tree surface i.e Certhia himalayana.

Keywords: avifauna diversity, distribution, Bara Gali, Abbottabad

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Authors: Fatemeh Nokhodchi Bonab

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Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 107

Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Bertakalswa Hermawati

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The double burden of nutrition problem must be faced by Indonesia as developing country. The implemented program did not improve the nutritional status, therefore need to consider to utilize local potential. The objective of this research was to find out the effectivity of magnification model of early detect through local potential utilization in urban region, Semarang, Central Java, Indonesia. The research used an experimental design with the quantitative-qualitative approach. The population was all toddlers under five within the research region, sample determination by purposive sampling, as many as 216 toddlers. Quantitative data analysis used effectively criteria by Sugiono. Qualitative data was analyzed using NVivo. The optimization of local potential in the effort of nutrition status improvement shows number of nutrition case found was increased 225% (very effective), number of cases treated was increased 175% (very effective), number of cases counselled was increased 200% (effective), and number of cases that have improvement increase 75% (effective). The local potential need to be utilized in the effort of nutrition program improvement one of it is through the community empowerment, particularly health care and health high education institution as partner.

Keywords: early detection, nutrition status, local potential, health cadre

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Authors: Gloria Chen

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When offering conventional level-appropriate ESL classes for adults is not feasible, a multilevel adult ESL class can be formed to benefit those who need to learn English for daily function. This paper examines the rationale, the process, the contents, and the outcomes of a multilevel ESL class for adults. The action research discusses a variety of assessments, lesson plans, teaching strategies that facilitate lifelong language learning. In small towns where adult ESL learners are only a handful, often advanced students and inexperienced students have to be placed in one class. Such class might not be viewed as desirable, but with on-going assessments, careful lesson plans, and purposeful strategies, a multilevel ESL class for adults can overcome the obstacles and help learners to reach a higher level of English proficiency. This research explores some hand-on strategies, such as group rotating, cooperative learning, and modifying textbook contents for practical purpose, and evaluate their effectiveness. The data collected in this research include Needs Assessment (beginning of class term), Mid-term Self-Assessment (5 months into class term), End-of-term Student Reflection (10 months into class), and End-of-term Assessment from the Instructor (10 months into class). A descriptive analysis of the data explains the practice of this particular learning community, and reveal the areas for improvement and enrichment. This research answers the following questions: (1) How do the assessments positively help both learners and instructors? (2) How do the learning strategies prepare students to become independent, life-long English learners? (3) How do materials, grouping, and class schedule enhance the learning? The result of the research contributes to the field of teaching and learning in language, not limited in English, by (a) examining strategies of conducting a multilevel adult class, (b) involving adult language learners with various backgrounds and learning styles for reflection and feedback, and (c) improving teaching and learning strategies upon research methods and results. One unique feature of this research is how students can work together with the instructor to form a learning community, seeking and exploring resources available to them, to become lifelong language learners.

Keywords: adult language learning, assessment, multilevel, teaching strategies

Procedia PDF Downloads 337

Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

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Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

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Authors: T. Bryan , V. Kepuska, I. Kostnaic

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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.

Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit

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Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

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Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

Procedia PDF Downloads 297