Search results for: male infertility detection

Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

Procedia PDF Downloads 283

Authors: Zoe M. G. Skalkos, Sam N. Dowland, James U. Van Dyke, Camilla. M. Whittington

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Syngnathid fishes (seahorses, pipefishes, and seadragons) are unique because embryos develop on or in the male in a specialised brooding structure. Many seahorse species are endangered or vulnerable, while others are popular in the ornamental fish trade. Seahorses are capable of nutrient provisioning (patrotrophy) of lipids during pregnancy via their fully enclosed brood pouch. Protein is vital for gene regulation and tissue growth during embryogenesis. We tested the hypothesis that protein is paternally transported to developing embryos during pregnancy in the Australian Pot-bellied seahorse, Hippocampus abdominalis. We compared the dry masses and nitrogen content in recently fertilised H. abdominalis embryos and newborns. We calculated an updated patrotrophy index, 1.34, but without a significant difference in dry mass between the two developmental stages. There was, however, a significant increase in total protein content from recently fertilised embryos to neonates. This suggests paternal protein transport is essential for H. abdominalis embryogenesis because protein yolk reserves are depleted by embryonic metabolism, and supplementation is required. This study is the first to provide evidence for paternal protein transport during pregnancy in seahorses. It furthers our understanding of the paternal influence on embryonic development in male pregnancy and how a protein-deficient diet during pregnancy may limit the allocation of resources to embryos, reducing offspring fitness. This research contributes to a deeper understanding of the fundamental reproductive biology of seahorses, which can help improve conservation and farming production outcomes.

Keywords: brood pouch, embryonic provisioning, nitrogen, parentotrophy, paternal investment, reproduction

Procedia PDF Downloads 81

Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya, Harsha Pola

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In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: physical health, athletic trainers, fitness monitoring, technology driven solutions, Google’s MediaPipe, landmark detection, angle computation, real-time feedback

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Authors: Endang Lukitaningsih, Fathul Jannah, Arief R. Hakim, Ratna D. Puspita, Zullies Ikawati

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Rifampicin is a semisynthetic antibiotic derivative of rifamycin B produced by Streptomyces mediterranei. RIF has been used worldwide as first line drug-prescribed throughout tuberculosis therapy. This study aims to develop and to validate an HPLC method couple with a UV detection for determination of rifampicin in spiked human plasma and its application for bioequivalence study. The chromatographic separation was achieved on an RP-C18 column (LachromHitachi, 250 x 4.6 mm., 5μm), utilizing a mobile phase of phosphate buffer/acetonitrile (55:45, v/v, pH 6.8 ± 0.1) at a flow of 1.5 mL/min. Detection was carried out at 337 nm by using spectrophotometer. The developed method was statistically validated for the linearity, accuracy, limit of detection, limit of quantitation, precise and specifity. The specifity of the method was ascertained by comparing chromatograms of blank plasma and plasma containing rifampicin; the matrix and rifampicin were well separated. The limit of detection and limit of quantification were 0.7 µg/mL and 2.3 µg/mL, respectively. The regression curve of standard was linear (r > 0.999) over a range concentration of 20.0 – 100.0 µg/mL. The mean recovery of the method was 96.68 ± 8.06 %. Both intraday and interday precision data showed reproducibility (R.S.D. 2.98% and 1.13 %, respectively). Therefore, the method can be used for routine analysis of rifampicin in human plasma and in bioequivalence study. The validated method was successfully applied in pharmacokinetic and bioequivalence study of rifampicin tablet in a limited number of subjects (under an Ethical Clearance No. KE/FK/6201/EC/2015). The mean values of Cmax, Tmax, AUC(0-24) and AUC(o-∞) for the test formulation of rifampicin were 5.81 ± 0.88 µg/mL, 1.25 hour, 29.16 ± 4.05 µg/mL. h. and 29.41 ± 4.07 µg/mL. h., respectively. Meanwhile for the reference formulation, the values were 5.04 ± 0.54 µg/mL, 1.31 hour, 27.20 ± 3.98 µg/mL.h. and 27.49 ± 4.01 µg/mL.h. From bioequivalence study, the 90% CIs for the test formulation/reference formulation ratio for the logarithmic transformations of Cmax and AUC(0-24) were 97.96-129.48% and 99.13-120.02%, respectively. According to the bioequivamence test guidelines of the European Commission-European Medicines Agency, it can be concluded that the test formulation of rifampicin is bioequivalence with the reference formulation.

Keywords: validation, HPLC, plasma, bioequivalence

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Leah Wilck

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Eyewitness identification is arguably one of the most utilized practices within our legal system; however, exoneration cases indicate that this practice may lead to accuracy and conviction errors. The purpose of this study was to examine the effects of the cross-race effect, the phenomena in which people are able to more easily and accurately identify faces from within their racial category, on the accuracy of eyewitness identification. Participants watched three separate videos of a perpetrator trying to steal a bicycle. In each video, the perpetrator was of a different race and gender. Participants watched a video where the perpetrator was a Black male, a White male, and a White female. Following the completion of watching each video, participants were asked to recall everything they could about the perpetrator they witnessed. The initial results of the study did not find the expected cross-race effect impacted the eyewitness identification accuracy. These surprising results are discussed in terms of cross-race bias and recognition theory as well as applied implications.

Keywords: cross race effect, eyewitness identification, own-race bias, racial profiling

Procedia PDF Downloads 147

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm

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Authors: Denis V. Axenov-Gribanov, Irina V. Voytsekhovskaya, Evgenii S. Protasov, Maxim A. Timofeyev

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Isolated ecosystems existing under specific environmental conditions have been shown to be promising sources of new strains of actinobacteria. The taiga forest of Baikal Siberia has not been well studied, and its actinobacterial population remains uncharacterized. The proximity between the huge water mass of Lake Baikal and high mountain ranges influences the structure and diversity of the plant world in Siberia. Here, we report the isolation of eighteen actinobacterial strains from male cones of Pinus sylvestris trees growing on the shore of the ancient Lake Baikal in Siberia. The actinobacterial strains were isolated on solid nutrient MS media and Czapek agar supplemented with cycloheximide and phosphomycin. Identification of actinobacteria was carried out by 16S rRNA gene sequencing and further analysis of the evolutionary history. Four different liquid and solid media (NL19, DNPM, SG and ISP) were tested for metabolite production. The metabolite extracts produced by the isolated strains were tested for antibacterial and antifungal activities. Also, antiradical activity of crude extracts was carried out. Strain Streptomyces sp. IB 2014 I 74-3 that active against Gram-negative bacteria was selected for dereplication analysis with using the high-yield liquid chromatography with mass-spectrometry. Mass detection was performed in both positive and negative modes, with the detection range set to 160–2500 m/z. Data were collected and analyzed using Bruker Compass Data Analysis software, version 4.1. Dereplication was performed using the Dictionary of Natural Products (DNP) database version 6.1 with the following search parameters: accurate molecular mass, absorption spectra and source of compound isolation. Thus, in addition to more common representative strains of Streptomyces, several species belonging to the genera Rhodococcus, Amycolatopsis, and Micromonospora were isolated. Several of the selected strains were deposited in the Russian Collection of Agricultural Microorganisms (RCAM), St. Petersburg, Russia. All isolated strains exhibited antibacterial and antifungal activities. We identified several strains that inhibited the growth of the pathogen Candida albicans but did not hinder the growth of Saccharomyces cerevisiae. Several isolates were active against Gram-positive and Gram-negative bacteria. Moreover, extracts of several strains demonstrated high antioxidant activity. The high proportion of biologically active strains producing antibacterial and specific antifungal compounds may reflect their role in protecting pollen against phytopathogens. Dereplication of the secondary metabolites of the strain Streptomyces sp. IB 2014 I 74-3 was resulted in the fact that a total of 59 major compounds were detected in the culture liquid extract of strain cultivated in ISP medium. Eight compounds were preliminarily identified based on characteristics described in the Dictionary of Natural Products database, using the search parameters Streptomyces sp. IB 2014 I 74-3 was found to produce saframycin A, Y3 and S; 2-amino-3-oxo-3H-phenoxazine-1,8-dicarboxylic acid; galtamycinone; platencin A4-13R and A4-4S; ganefromycin d1; the antibiotic SS 8201B; and streptothricin D, 40-decarbamoyl, 60-carbamoyl. Moreover, forty-nine of the 59 compounds detected in the extract examined in the present study did not result in any positive hits when searching within the DNP database and could not be identified based on available mass-spec data. Thus, these compounds might represent new findings.

Keywords: actinobacteria, Baikal Lake, biodiversity, male cones, Pinus sylvestris

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

Procedia PDF Downloads 172

Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: N. Hammid, F. Bouarab-Dahmani, T. Berkane

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Since its appearance, the MOOC (massive open online course) is gaining more and more intention of the educational communities over the world. Apart from the current MOOCs design and purposes, the creators of MOOC focused on the importance of the connection and knowledge exchange between individuals in learning. In this paper, we present a conceptual model for massive open online blended courses where teachers over the world can collaborate and exchange their experience to get a common efficient content designed as a MOOC opened to their students to live a better learning experience. This model is based on disciplines’ concepts capitalization and the detection of the obstacles met by their students when faced with problem situations (exercises, projects, case studies, etc.). This detection is possible by analyzing the frequently of semantic errors committed by the students. The participation of teachers in the design of the course and the attendance by their students can guarantee an efficient and extensive participation (an important number of participants) in the course, the learners’ motivation and the evaluation issues, in the way that the teachers designing the course assess their students. Thus, the teachers review, together with their knowledge, offer a better assessment and efficient connections to their students.

Keywords: massive open online course, MOOC, online learning, e-learning

Procedia PDF Downloads 255

Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

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Authors: Duygu Alptekin

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Patriarchal social structure is based on a gender-based discrimination. Due to confrontational nature of discrimination; in a patriarchal society men and women exists in a based on contrasts and inequalities interaction patterns and this situation continues as socio-cultural with dominant gender perception in society. In this context gender perception of youth is a required vision tool for multidimensional understanding and resolving of gender discrimination problem and making projections about future. The aim of the study is explaining the gender discrimination by helping of Ambivalent Sexism Inventory and hostile benevolent sexism which are subdimensions of (ASI). Additionally the sexism perception of youth will be try to analyse ın the context of conflict of conventionalism and modernism. For that purpose survey have carried aout with the participation of students at the Selcuk University and the conclusions revealed that reached ampirically Young people's perceptions about the hierarchy of power revealed between men and women; sexual, economic and occupational segregation by pointing to statements about male-female relationships commitment, guardianship, gratitude, expressions containing highlights the superiority of socio-psychological (ASI) where results are determined by the application. The results of the factor analysis performed in this direction with the detection of the previous studies were evaluated by blending.

Keywords: ambivalent sexism inventory, gender discrimination, youth, conventionalism

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Authors: Chairussyuhur Arman, Totti Tjiptosumirat, Muhammad Gunawan, Mastur, Joko Priyono, Baiq Tri Ratna Erawati

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The present study was undertaken to synchronize oestrus of bali cattle and artificially inseminated with frozen-thawed sexed-semen. The experiment was carried out at District AI Station. Four pluriparous cows and four nulliparous heifers were used in this study and they were housed in free stall barns. The heifers fed with corn silage supplemented with UMMB, while the cows fed with green fodder. All animals were given 500 mg cloprostenolum i.m. injections PGF2α twice, 11 days apart, to synchronize the occurrence of estrus. Estrus was detected by visual observation twice a day and determined if all cattle accepted mount from other females. All animals were inseminated twice with Bali sexed-semen at 72 and 76 h after observed oestrus. Results suggested that the percentage of calving rate either for pluriparous cows or nulliparous heifers were recorded to be 75 percent. One cow and one heifer did not produce calves because of embryonic lost. Regardless the sex of calves, the mean of birth weight of calves in cows was higher than that of heifers (18.50 ± 2.60 kg vs 13.83 ± 5.20 kg). One female calf from heifer with lower birth weight (8.0 kg) was dead one day after born. In pluriparous group, two cows delivered male calves and the other delivered female calf. Conversely in nulliparous group, two heifers delivered female calves and the other male calf. It is concluded that under the conditions of this preliminary trials, the sex ratio between pluriparous and nulliparous groups was found to be 50:50 (male:female).

Keywords: artificial insemination, bali cattle, calves, sexed sperm

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Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Anindita Sen

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Oral fluid is a promising diagnostic matrix for drugs of abuse compared to urine and serum. Detection of methamphetamine in oral fluid would pave way for the easy evaluation of impairment in drivers during roadside drug testing as well as ensure safe working environments by facilitating evaluation of impairment in employees at workplaces. A membrane-based point-of-care (POC) friendly pre-treatment technique has been developed which aided elimination of interferences caused by salivary proteins and facilitated the demonstration of methamphetamine detection in saliva using a gold nanoparticle based colorimetric aptasensor platform. It was found that the colorimetric response in saliva was always suppressed owing to the matrix effects. By navigating the challenging interfering issues in saliva, we were successfully able to detect methamphetamine at nanomolar levels in saliva offering immense promise for the translation of these platforms for on-site diagnostic systems. This subsequently motivated the development of a handheld portable light meter device that can reliably transduce the aptasensors colorimetric response into absorbance, facilitating quantitative detection of analyte concentrations on-site. This is crucial due to the prevalent unreliability and sensitivity problems of the conventional drug testing kits. The fabricated light meter device response was validated against a standard UV-Vis spectrometer to confirm reliability. The portable and cost-effective handheld detector device features sensitivity comparable to the well-established UV-Vis benchtop instrument and the easy-to-use device could potentially serve as a prototype for a commercial device in the future.

Keywords: aptasensors, colorimetric gold nanoparticle assay, point-of-care, oral fluid

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Authors: William L. Whitehouse, Louisa H. Y. Lo, Andrew B. Kinghorn, Simon C. C. Shiu, Julian. A. Tanner

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C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome (SIRS). Currently, clinical turn-around times for established CRP detection methods take between 30 minutes to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers functionalized onto cheap, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 minute. The aptasensor dynamic range spans 5-1000nM (R=0.97) or 5-500nM (R=0.99) in 50% diluted human serum, with a LOD of 3nM, corresponding to 2-orders of magnitude sensitivity under the clinically relevant cut-off for CRP. The sensor is stable for up to one week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors (SS-EABs) provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of an SS-EAB for reagentless CRP detection. We hope this study can inspire further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for use more broadly by the public.

Keywords: structure-switching, C-reactive protein, electrochemical, biosensor, aptasensor.

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Hanaa Sameen Ameen Bajilan

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Gender statuses are inherently unequal; it is difficult to establish equality between men and women in the light of traditional inequalities across the world. This research focuses on the similarities and differences among women from different generations different kinds of educational backgrounds and highlights the conflict experiences of the characters in Githa Hariharan's novel ‘The Thousand Faces of Night’ The purpose is to show how women are suffering and are being humiliated in a male-dominated society. The paper depicts how women in India grapple from male domination aggressiveness as well as the cultural, social and religious controlling in the society they live in. The paper also seeks to explore the importance of Knowledge as a powerful component that produces positive effects at the level of desire. The paper is based on the theories of Simone Beauvoir, Pierre Bourdieu, Edward Said, Rene Descartes and Amy Bhatt. Finally, the paper emphasizes on survival against hegemonic regimes and Indian women's hope for a better life.

Keywords: equality, gender, Githa Hariharan, humiliation

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Authors: Sethu Lekshmi, Shahanas, Prettha P.

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All existing protocols in wireless networks are mainly based on Carrier Sense Multiple Access with Collision avoidance. By applying collision detection in wireless networks, the time spent on collision can be reduced and thus improves system throughput. However in a real WLAN scenario due to the use of nonlinear modulation techniques only receiver can decided whether a packet loss take place, even there are multiple transmissions. In this proposed method, the receiver or Access Point detects the collision when multiple data packets are transmitted from different wireless stations. Whenever the receiver detects a collision, it transmits a jamming signal to all the transmitting stations so that they can immediately stop their on-going transmissions. We also provide preferential access to all collided packet to reduce unfairness and to increase system throughput by reducing contention. However, this preferential access will not block the channel for the long time. Here, an in-band transmission is considered in which both the data frames and control frames are transmitted in the same channel. We also provide a simple mathematical model for the proposed protocol and give the simulation result of WLAN scenario under various capture thresholds.

Keywords: 802.11, WLAN, capture effect, collision detection, collision resolution, receiver initiated

Procedia PDF Downloads 344

Authors: Olomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr, Zekeriya Aliyazicioglu, H. K. Hwang

Abstract:

Multiple Input Multiple Output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection, resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO Uniformly-Spaced Linear Array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, Pseudo Random (PN) sequence length, number of snapshots, and Signal to Noise Ratio (SNR). The results of MIMO are compared to a traditional array antenna.

Keywords: MIMO radar, phased array antenna, target detection, radar signal processing

Procedia PDF Downloads 526

Authors: Johanna Goeß

Abstract:

In this field study, it is hypothesised that affiliation motivation is relevant to dark terminal technology readiness. The theoretical basis for this work was the TAM 2, focusing on the social process variables and the short-scale technology readiness. Two hypotheses to be tested are the focus of consideration:
 H1: The TAM constructs are independently positively related to dark device use. H2: Sense of social belonging is positively related to dark device use.
 In this quantitative study, 30 male subjects participated with their dark devices. Using a post-basket exercise, affiliation is manipulated by content items on the website to investigate whether affiliation between computers and people and smartphones and people leads to similar effects as an affiliation between people. The entire scientific study, including the questionnaire, took about 30 minutes. This study contributes to the current literature and draws attention to the fact that male users' terminal devices have an influence in the form of affiliation effects.

Keywords: human-computer-interaction, computers, smartphones, addiction, social affiliation effects, TAM 2, pyramid of needs, social actors

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

Abstract:

To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

Abstract:

Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

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Authors: Abdulsallam A. Bakdash, Aiyshah M. Alshehri, Hind M. Alenzi

Abstract:

Benzatropine (benztropine) is used to treat symptoms of Parkinson's disease or involuntary movements due to the side effects of certain psychiatric drugs. We report in this study, results of a procedure for the determination of benzatropine in hair using LLE, once with methanol and second with phosphate buffer (pH 6.0), followed by filtration and then re-extraction with dichloromethane. A GC/MS method was developed and validated for this determination using selected ion monitoring (SIM) detection without derivatization. Linearity established over the concentration range 0.1-20.0 ng/mg hair, and the correlation coefficients were greater than 0.99. Recoveries were 52.2% and 21.1% using methanol and phosphate buffer extraction, respectively. Detection limits of benzatropine in hair were between 0.65 and 3.0 ng/mg hair, while the accuracy were 10.4% and 18.5% (RSD), respectively. We also applied this method to the analysis of soaked hair samples and demonstrated that the LLE using methanol meets the requirement for the analysis of benzatropine in hair.

Keywords: hair analysis, benzatropine, liquid-liquid extraction, GC/MS

Procedia PDF Downloads 390

Authors: Muhammad Solikhudin Nafi, Wahyu Afif Mufida, Mita Erna Wati, Fitri Setyani Rokim, M. Al-Rizqi Dharma Fauzi

Abstract:

High dose activity without any pre-exercise will impact Delayed Onset Muscle Soreness (DOMS). DOMS known as delayed pain post-exercise and induce skeletal injury which will decrease athletes’ performances. From now on, post-exercise muscle damage can be detected by measuring skeletal troponin I (sTnI) concentration in serum using ELISA but this method needs more time and cost. To prevent decreased athletes performances, screening need to be done rapidly. We want to introduce our new prototype to detect DOMS acutely. Rapid detection tests are based on immunological reaction between skeletal troponin I antibodies and sTnI in human serum or whole blood. Chemical methods that are used in the manufacture of diagnostic test is lateral flow immunoassay. The material used is rat monoclonal antibody sTnI, colloidal gold, anti-mouse IgG, nitrocellulose membrane, conjugate pad, sample pad, wick and backing card. The procedure are made conjugate (colloidal gold and mAb sTnI) and insert into the conjugate pad, gives spray sTnI mAb and anti-mouse IgG into nitrocellulose membrane, and assemble RDT. RDT had been evaluated by measuring the sensitivity of positive human serum (n = 30) and negative human serum (n = 30). Overall sensitivity value was 93% and specificity value was 90%. ADCOR as the first rapid detection test qualitatively showed antigen-antibody reaction and showed good overall performances for screening of muscle damage. Furthermore, these finding still need more improvements to get best results.

Keywords: DOMS, sTnI, rapid detection test, ELISA

Procedia PDF Downloads 498

Authors: Nelson Igaba, C. Onaga, S. Hlongwane

Abstract:

Background: Medical Male Circumcision (MMC) is part of a comprehensive HIV prevention strategy. The quality of MMC done at Right To Care (RtC) sites is maintained by Continuous Quality Improvement (CQI) based on findings of assessments by internal and independent external assessors who evaluate such parameters as the quality of the surgical procedure, infection control, etc. There are 12 RtC MMC teams in Mpumalanga, two of which are headed by Medical Officers and 10 by Clinical Associates (Clin A). Objectives: To compare the quality (i) of care rendered at doctor headed sites (DHS) versus Clin A headed sites (CHS); (ii) of CQI assessments (external versus internal). Methodology: A retrospective review of data from RightMax™ (a novel RtC data management system) and CQI reports (external and internal) was done. CQI assessment scores of October 2015 and October 2016 were taken as the baseline and latest respectively. Four sites with 745-810 circumcisions per annum were purposively selected; the two DHS (group A) and two CHS (group B). Statistical analyses were conducted using R (2017 version). Results: There were no significant difference in latest CQI scores between the two groups (DHS and CHS) (Anova, F = 1.97, df = 1, P = 0.165); between internal and external CQI assessment scores (Anova, F = 2.251, df = 1, P = 0.139) or among the individual sites (Anova, F = 1.095, df = 2, P = 0.341). Of the total of 16 adverse events reported by the four sites in the 12 months reviewed (all were infections), there was no statistical evidence that the documented severity of the infection was different for DHS and CHS (Fisher’s exact test, p-value = 0.269). Conclusion: At RtC VMMC sites in Mpumalanga, internal and external/independent CQI assessments are comparable, and quality of care of VMMC is standardized with the performance of well-supervised clinical associates comparing well with those of medical officers.

Keywords: adverse events, Right to Care, male medical circumcision, continuous quality improvement

Procedia PDF Downloads 156

Authors: Ruziana Masiran, Hamidin Awang, Cheah Y. T. Jun, Nor Fauziah Hashim, Archana Premkumar, Mohd. Feizel Aisiddiq, Mohd. Fakharuddin

Abstract:

Risk behaviours among secondary school students are common and show an increasing trend over the years. Existing attachment styles between the students and their parents influence the psychosocial development of this group of population hence contributing to the adoption of risk behaviours. The aim of this study was to determine the associations between three risk behaviours; smoking, bullying and being bullied among secondary school students and their styles of attachment to parents in a district in Malaysia. Using multistage simple random sampling, a cross-sectional study was designed with the level of significance, α set at 0.05. The validated self-administered Inventory of Parent and Peer Attachment (IPPA) and Youth Risk Behaviours Surveillance Questionnaire focusing on smoking and bullying were utilized. Secondary school students aged 13 to 17 years old from ten schools in the district of Hulu Langat, Malaysia were sampled. Prevalence of smoking was 15.8%, bullying 8.5% and being bully victims 19.0%. It was found that male gender was a significant risk factor for smoking (p < 0.001), while being Chinese (OR=0.156, 95%CI=0.029-0.837, p=0.030) and having married parents (OR=0.490, 95%CI=0.302-0.796, p=0.490) are protective against smoking. Students with insecure attachment to mothers (OR=1.650, 95%CI=1.018-2.675, p=0.042) and fathers (OR=2.039, 95%CI=1.285-3.234, p=0.002) are at 1.6 and 2 times risk respectively to smoke compared to those with secure attachment. The odds of male students bullying is almost twice than that for female students (OR=2.017, 95%CI=1.416-2.873, p < 0.001), and the odds of being bullied is 1.5 times higher for male students (OR=1.519, 95%CI=1.183-1.950, p=0.001). Those who are insecurely attached to fathers are at 1.8 times higher risk to be bullies (OR=1.867, 95%CI=1.272-2.740, p < 0.001) and 1.5 times higher risk to be bullied (OR=1.546, 95%CI=1.026-2.329, p=0.037). In conclusion, insecure attachment shows a strong association with smoking, bullying and being bullied among secondary school students in Malaysia.

Keywords: attachment styles, bullied, bullying, insecure attachment, risk behaviours, smoking and attachment

Procedia PDF Downloads 316