Search results for: human activity detection

Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Adel Fathy Sadek Abdalla

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The issue of respect for human rights in Southeast Asia has become a major concern and is attracting the attention of the international community. Basically, the Association of Southeast Asian Nations (ASEAN) made human rights one of its main issues and in the ASEAN Charter in 2008. Subsequently, the Intergovernmental Commission on Human Rights ASEAN Human Rights (AICHR) was established. AICHR is the Southeast Asia Human Rights Enforcement Commission charged with the responsibilities, functions and powers to promote and protect human rights. However, at the end of 2016, the protective function assigned to the AICHR was not yet fulfilled. This is shown by several cases of human rights violations that are still ongoing and have not yet been solved. One case that has recently come to light is human rights violations against the Rohingya people in Myanmar. Using a legal-normative approach, the study examines the urgency of establishing a human rights tribunal in Southeast Asia capable of making a decision binding on ASEAN members or guilty parties. Data shows ASEAN needs regional courts to deal with human rights abuses in the ASEAN region. In addition, the study also highlights three important factors that ASEAN should consider when establishing a human rights tribunal, namely: Volume. a significant difference in terms of democracy and human rights development among the members, a consistent implementation of the principle of non-interference and the financial issue of the continuation of the court.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

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Authors: Y. L. Chang, Y. H. Huang

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This study designed a mobile guide system that integrates the design principles of guidance and interpretation with augmented reality (AR) as an auxiliary tool for National Taiwan Science Education Center guidance and explored the learning performance of participants who were divided into two visiting groups: AR-guided mode and non-guided mode (without carrying any auxiliary devices). The study included 96 college students as participants and employed a quasi-experimental research design. This study evaluated the learning performance of education center students aided with different guided modes, including their flow experience, activity involvement, learning effects, as well as their attitude and acceptance of using the guide systems. The results showed that (a) the AR guide promoted visitors’ flow experience; (b) the AR-guidance activity involvement and flow experience having a significant positive effect; (c) most of the visitors of mobile guide system with AR elicited a positive response and acceptance attitude. These results confirm the necessity of human–computer–context interaction. Future research can continue exploring the advantages of enhanced learning effectiveness, activity involvement, and flow experience through application of the results of this study.

Keywords: augmented reality, mobile guide system, informal learning, flow experience, activity involvement

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Authors: Cheng-Yen Lu, Chin-Yuan Hsu

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Ambient temperature reduction (ATR) can extend the lifespan of an annual fish (Nothobranchius rachovii), but the underlying mechanism is unknown. In this study, the expression, concentration, and activity of cellular-degraded molecules were evaluated in the muscle of N. rachovii reared under high (30 °C), moderate (25 °C), and low (20 °C) ambient temperatures by biochemical techniques. The results showed that (i) the activity of the 20S proteasome, the expression of microtubule-associated protein 1 light chain 3-II (LC3-II), the expression of lysosome-associated membrane protein type 2a (Lamp 2a), and lysosome activity increased with ATR; (ii) the expression of the 70 kD heat shock cognate protein (Hsc 70) decreased with ATR; (iii) the expression of the 20S proteasome, the expression of lysosome-associated membrane protein type 1 (Lamp 1), the expression of molecular target of rapamycin (mTOR), the expression of phosphorylated mTOR (p-mTOR), and the p-mTOR/mTOR ratio did not change with ATR. These findings indicated that ATR activated the activity of proteasome, macroautophagy, and chaperone-mediated autophagy. Taken together these data reveal that ATR likely activates cellular degradation activity to extend the lifespan of N. rachovii.

Keywords: ambient temperature reduction, autophagy, degradation activity, lifespan, proteasome

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: image detection, forgery image, copy-paste, attack detection

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Authors: Benyapa Suksuwan

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Introduction: Oxidative stress is identified as the root cause of the development and progression of several diseases as the disproportion of free radicals in the body leads to tissue or cell damage. Polyphenols are the most common antioxidant found in plants and are efficient in capturing oxidative free radicals. Aim of the Study: This study focused on the antioxidant activity of polyphenols extracted from Phyllanthus Emblica L. as oxidative stress plays a vital role in developing and progressing many diseases, including cardiovascular diseases and cancer. Materials and Methods: The plant was extracted using a mixture solvent (ethyl alcohol: water in ratio 8:2). The total phenolic content of P. Emblica extract was determined using the Folin-Cioucalteu method and calculated as gallic acid equivalents (GAE) and various antioxidant assays DPPH and ABTS radical scavenging capacity assays. Results and Discussion: The findings exhibited a strong correlation between antioxidant activity and the total phenol contents. In addition, the IC₅₀ of P. Emblica extract via DPPH and ABTS assays were 68.10 μg/mL ± 0.455, and 49.24 μg/mL ± 0.716, respectively. Furthermore, P. Emblica extract showed antioxidant activities in a concentration-dependent manner. Vitamin C was used as a positive control in the DPPH assay, while Trolox was used as a positive control in the ABTS assay. Conclusions: In conclusion, P. Emblica extract consisted of a high amount of total phenolic content, which possesses potent antioxidant activity. However, further antioxidant activity assays using human cell lines such as SOD, ROS, and RNS scavenging assays and in vitro antioxidant experiments should be performed in order.

Keywords: antioxidant, ABTS scavenging, DPPH scavenging assay, total phenol contents assay, Phyllanthus Emblica L

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Authors: Nasibeh Azizi Khereshki

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Olive leaf (OL) extract as a green reductant agent was utilized for the biogenic synthesis of silver nanoparticles (Ag NPs) for the first time in this study, and then its performance was evaluated for colorimetric detection of Fe3+ in different media. Some analytical methods were used to characterize the nanosensor. The effective sensing parameters were optimized by central composite design (CCD) combined with response surface methodology (RSM) application. Then, the prepared material's applicability in antibacterial and optical chemical sensing for naked-eye detection of Fe3+ ions in aqueous solutions were evaluated. Furthermore, OL-Ag NPs-loaded paper strips were successfully applied to the colorimetric visualization of Fe3+. The colorimetric probe based on OL-AgNPs illustrated excellent selectivity and sensitivity towards Fe3+ ions, with LOD and LOQ of 0.81 μM and 2.7 μM, respectively. In addition, the developed method was applied to detect Fe3+ ions in real water samples and validated with a 95% confidence level against a reference spectroscopic method.

Keywords: Ag NPs, colorimetric detection, Fe(III) ions, green synthesis, olive leaves

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Tareq M. Aziz Elven

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The issue of Human Rights enforcement in Southeast Asia has become the serious problem and attract the attention of international community. Principally, Association of Southeast Asian Nations (ASEAN) has mentioned the Human Rights as one of the focus and be a part of the ASEAN Charter in 2008. It was followed by the establishment of ASEAN Inter-Governmental Commission on Human Rights (AICHR). AICHR is the commission of Human Rights enforcement in Southeast Asia which has a duty, function, and an authority to conduct dissemination and protection of Human Rights. In the end of 2016, however, the function of protection mandated to AICHR have not achieved yet. It can be proved by several cases of Human Rights violation which still exist and have not settled yet. One of case which attracts the public attention recently is human rights violation towards Rohingya in Myanmar. Using the juridical-normative method, the research aims to examine the urgency of Human Rights court establishment in Southeast Asia region which able to issue the decision that binds the ASEAN members or the violating parties. The data shows that ASEAN needs to establish a regional court which intended to settle the Human Rights violations in ASEAN region. Furthermore, the research also highlights three strong factors should be settled by ASEAN for establishing human rights court i.e. the significant distinction of democracy and human rights development among the members, the strong implementation of non-intervention principle, and the financial matter to sustain the court.

Keywords: AICHR, ASEAN, human rights, human rights court

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Authors: Richu J. Babu, Sony Mathew, Sharon Rony Jacob, Soney C. George, Jibin C. Jacob

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Human hair is a non-biodegradable waste available in plenty throughout the world but is rarely explored for applications in engineering fields. Tensile strength of human hair ranges from 170 to 220 MPa. This property of human hair can be made use in the field of making bio-composites[1]. The composite is prepared by commixing the human hair and natural rubber in a two roll mill along with additives followed by vulcanization. Here the concentration of the human hair is varied by fine-tuning the fiber length as 20 mm and sundry tests like tensile, abrasion, tear and hardness were conducted. While incrementing the fiber length up to a certain range the mechanical properties shows superior amendments.

Keywords: human hair, natural rubber, composite, vulcanization, fiber loading

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Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

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As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

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Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

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A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

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Authors: Kyung Hwa Hong

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The objective of this study was to evaluate the ability of spent coffee extract to enhance the antioxidant and antimicrobial properties of cotton fabrics. The emergence and spread of infectious diseases has raised a global interest in the antimicrobial substances. The safety of chemical agents, such as antimicrobials and dyes, which may irritate the skin, cause cellular and organ damage, and have adverse environmental impacts during their manufacturing, in relation to the human body has not been established. Nevertheless, there is a growing interest in natural antimicrobials that kill microorganisms or stop their growth without dangerous effects on human health. Spent coffee is the by-product of coffee brewing and amounted to 96,000 tons worldwide in 2015. Coffee components such as caffeine, melanoidins, and chlorogenic acid have been reported to possess multifunctional properties, including antimicrobial, antioxidant, and anti-inflammatory activities. Therefore, the current study examined the possibility of applying spent coffee in functional textile finishing. Spent coffee was extracted with 60% methanol solution, and the major components of the extract were quantified. In addition, cotton fabrics treated with spent coffee extract through a pad-dry-cure process were investigated for antioxidant and antimicrobial activities. The cotton fabrics finished with the spent coffee extract showed an increase in yellowness, which is an unfavorable outcome from the fabric finishing process. However, the cotton fabrics finished with the spent coffee extract exhibited considerable antioxidant activity. In particular, the antioxidant ability significantly increased with increasing concentrations of the spent coffee extract. The finished cotton fabrics showed antimicrobial ability against S. aureus but relatively low antimicrobial ability against K. pneumoniae. Therefore, further investigations are needed to determine the appropriate concentration of spent coffee extract to inhibit the growth of various pathogenic bacteria.

Keywords: spent coffee grounds, cotton, natural finishing agent, antioxidant activity, antimicrobial activity

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: In-Geun Lim, Sung-Woong Ra

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As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically.

Keywords: facility detection, satellite image, object, mathematical morphology

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

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As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

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Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Catarina Bento, Ana Carolina Gonçalves, Fábio Jesus, Luís Rodrigues Silva

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Increasing evidence suggests that a diet rich in fruits and vegetables plays important roles in the prevention of chronic diseases, such as heart disease, cancer, stroke, diabetes, Alzheimer’s disease, among others. Fruits and vegetables gained prominence due their richness in bioactive compounds, being the focus of many studies due to their biological properties acting as health promoters. Prunus avium Linnaeus (L.), commonly known as sweet cherry has been the centre of attention due to its health benefits, and has been highly studied. In Portugal, most of the cherry production comes from the Fundão region. The Saco is one of the most important cultivar produced in this region, attributed with geographical protection. In this work, we prepared 3 extracts through solid-phase extraction (SPE): a whole extract, fraction I (non-coloured phenolics) and fraction II (coloured phenolics). The three extracts were used to determine the phenolic profile of Saco cultivar by liquid chromatography with diode array detection (LC-DAD) technique. This was followed by the evaluation of their biological potential, testing the extracts’ capacity to scavenge free-radicals (DPPH•, nitric oxide (•NO) and superoxide radical (O2●-)) and to inhibit α-glucosidase enzyme of all extracts. Additionally, we evaluated, for the first time, the protective effects against peroxyl radical (ROO•)-induced hemoglobin oxidation and hemolysis in human erythrocytes. A total of 16 non-coloured phenolics were detected, 3-O-caffeoylquinic and ρ-coumaroylquinic acids were the main ones, and 6 anthocyanins were found, among which cyanidin-3-O-rutinoside represented the majority. In respect to antioxidant activity, Saco showed great antioxidant potential in a concentration-dependent manner, demonstrated through the DPPH•,•NO and O2●-radicals, and greater ability to inhibit the α-glucosidase enzyme in comparison to the regular drug acarbose used to treat diabetes. Additionally, Saco proved to be effective to protect erythrocytes against oxidative damage in a concentration-dependent manner against hemoglobin oxidation and hemolysis. Our work demonstrated that Saco cultivar is an excellent source of phenolic compounds which are natural antioxidants that easily capture reactive species, such as ROO• before they can attack the erythrocytes’ membrane. In a general way, the whole extract showed the best efficiency, most likely due to a synergetic interaction between the different compounds. Finally, comparing the two separate fractions, the coloured fraction showed the most activity in all the assays, proving to be the biggest contributor of Saco cherries’ biological activity.

Keywords: biological potential, coloured phenolics, non-coloured phenolics, sweet cherry

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Authors: Farshad Badie

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The central focus of this article is on the fact that knowledge is constructed from an interaction between humans’ experiences and over their conceptions of constructed concepts. Logical characterisation of ‘human inductive learning over human’s constructed concepts’ within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. This research connects with the topics ‘human learning’, ‘epistemology’, ‘cognitive modelling’, ‘knowledge representation’ and ‘ontological reasoning’.

Keywords: human concept learning, concept construction, knowledge construction, terminological systems

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Authors: Joanna Maj

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Awe inspiring is the idea that emotions could be present in human-machine interactions, both on the human side as well as the machine side. Human factors present intriguing components and are examined in detail while discussing this controversial topic. Mood, attention, memory, performance, assessment, causes of emotion, and neurological responses are analyzed as components of the interaction. Problems in computer-based technology, revenge of the system on its users and design, and applications comprise a major part of all descriptions and examples throughout this paper. It also allows for critical thinking while challenging intriguing questions regarding future directions in research, dealing with emotion in human-machine interactions.

Keywords: biocomputing, biomedical engineering, emotions, human-machine interaction, interfaces

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Authors: Naoki Ohshima, Ken Kaminishi

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Four types of dependencies, which are 'Finish-to-start', 'Finish-to-finish', 'Start-to-start' and 'Start-to-finish (S-F)' as logical relationship are modeled based on the definition by 'the predecessor activity is defined as an activity to come before a dependent activity in a schedule' in PMBOK. However, it is found a self-contradiction in the precedence diagram for S-F relationship by PMBOK. In this paper, author would like to validate logical relationship of S-F by Graph Theory and propose a new interpretation of the precedence diagram for S-F relationship.

Keywords: project time management, sequence activity, start-to-finish relationship, precedence diagram, PMBOK

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Authors: Juliana A. Galhardi, Daniel M. Bonotto

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Coal is an important non-renewable energy source of and can be associated with radioactive elements. In Figueira city, Paraná state, Brazil, it was recorded high uranium activity near the coal mine that supplies a local thermoelectric power plant. In this context, the radon activity (Rn-222, produced by the Ra-226 decay in the U-238 natural series) was evaluated in groundwater, river water and effluents produced from the acid mine drainage in the coal reject dumps. The samples were collected in August 2013 and in February 2014 and analyzed at LABIDRO (Laboratory of Isotope and Hydrochemistry), UNESP, Rio Claro city, Brazil, using an alpha spectrometer (AlphaGuard) adjusted to evaluate the mean radon activity concentration in five cycles of 10 minutes. No radon activity concentration above 100 Bq.L-1, which was a previous critic value established by the World Health Organization. The average radon activity concentration in groundwater was higher than in surface water and in effluent samples, possibly due to the accumulation of uranium and radium in the aquifer layers that favors the radon trapping. The lower value in the river waters can indicate dilution and the intermediate value in the effluents may indicate radon absorption in the coal particles of the reject dumps. The results also indicate that the radon activities in the effluents increase with the sample acidification, possibly due to the higher radium leaching and the subsequent radon transport to the drainage flow. The water samples of Laranjinha River and Ribeirão das Pedras stream, which, respectively, supply Figueira city and receive the mining effluent, exhibited higher pH values upstream the mine, reflecting the acid mine drainage discharge. The radionuclides transport indicates the importance of monitoring their activity concentration in natural waters due to the risks that the radioactivity can represent to human health.

Keywords: radon, radium, acid mine drainage, coal

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Authors: Shivankar Agrawal, Indira Sarangthem

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Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus (MRSA) remains one of the major causes of healthcare-associated and community-onset infections worldwide. Hence the search for non-toxic natural compounds having antibacterial activity has intensified for future drug development. The exploration of less studied niches of Earth can highly increase the possibility to discover novel bioactive compounds. Therefore, in this study, the cultivable fraction of fungi from the sediments of natural hot springs has been studied to mine potential fungal candidates with antibacterial activity against the human pathogen Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus. We isolated diverse strains of thermophilic fungi from a collection of samples from sediment. Following a standard method, we isolated a promising thermophilic fungus strain IBSD19, identified as Acrophialophora levis, possessing the potential to produce an anti-Staphylococcus aureus agent. The growth conditions were optimized and scaled to fermentation, and its produced extract was subjected to chemical extraction. The ethyl acetate fraction was found to display significant activity against Staphylococcus aureus and MRSA with a minimum inhibitory concentration (MIC) of 0.5 mg/ml and 4 mg/ml, respectively. The cell membrane integrity assay and SEM suggested that the fungal metabolites cause bacteria clustering and further lysis of the cell.

Keywords: antibacterial activity, antioxidant, fungi, Staphylococcus aureus, MRSA, thermophiles

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Authors: Drashti G. Daraji, Rosa E. Moo-Puc, Hitesh D. Patel

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Substituted 2-Thioimidazole analogues have been synthesized and confirmed by advanced spectroscopic techniques. Among them, ten compounds have been selected and evaluated for their in vitro anti-cancer activity at the National Cancer Institute (NCI) for testing against a panel of 60 different human tumor cell lines derived from nine neoplastic cancer types. Furthermore, synthesized compounds were tested for their in vitro antiprotozoal activity, and none of them exhibited significant potency against antiprotozoans. It was observed that the tested all compounds seem effective on the UACC-62 melanoma cancer cell line as compared to other cancer cell lines and also exhibited the least potent in the Non-Small Cell Lung Cancer cell line in one-dose screening. In silico studies of these derivatives were carried out by molecular docking techniques and Absorption, Distribution, Metabolism, and Excretion (ADME) using Schrödinger software to find potent B-Raf kinase inhibitor (PDB ID: 3OG7). All the compounds have been performed for docking study; Compound D4 has a good docking score for melanoma cancer as compared with other.

Keywords: anticancer activity, cancer cell line, 2-thio imidazole, one-dose assay, molecular docking

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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Authors: A. Kistaubayeva, I. Savitskaya, D. Ibrayeva, M. Abdulzhanova, N. Voronova

Abstract:

36 strains of sulfur-oxidizing bacteria were isolated in Southern Kazakhstan soda-saline soils and identified. Screening of strains according bio-oxidation (destruction thiosulfate to sulfate) and enzymatic (Thiosulfate dehydrogenises and thiosulfate reductase) activity was conducted. There were selected modes of aeration and culture conditions (pH, temperature), which provide optimum harvest cells. These strains can be used in bio-melioration technology.

Keywords: elemental sulfur, oxidation activity, Тhiobacilli, fertilizers, heterotrophic S-oxidizers

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Authors: Monthon Tangjitmungman

Abstract:

Numerous diseases have been linked to oxidative stress, in which a disproportion of free radicals in the body leads to tissue or cell damage. Polyphenols are the most abundant antioxidants found in plants, and they are highly effective at scavenging oxidative free radicals. Due to the presence of phenolic compounds in Caesalpinia sappan has been discovered to have antioxidant activity. It has several health benefits, the most important of which is preventing cardiovascular and cancer diseases. This study aimed to determine the phenolic content and antioxidant activity of C. sappan extract using a variety of antioxidant assays. The extract of C. sappan was made using a mixture of solvents (ethyl alcohol: water in ratio 8:2). The total phenolic content of C. sappan extract was determined and expressed as gallic acid equivalents using the Folin-Cioucalteu method (GAE). The antioxidant activity of C. sappan extract was assessed using the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay and the ABTS radical scavenging capacity assay. An association was found between antioxidant activity and total phenol content. The antioxidant activity of C. sappan extract was also determined by DPPH and ABTS assays. The IC50 values for C. sappan extract from DPPH and ABTS assays were 54.48 μg/mL ± 0.545 and 25.46 μg/mL ± 0.790, respectively, in the DPPH assay. In the DPPH assay, vitamin C was used as a positive control, whereas Trolox was used as a positive control in the ABTS assay. In conclusion, C. sappan extract contains a high level of total phenolics and exhibits significant antioxidant activity. Nevertheless, more research should be done on the antioxidant activity, such as SOD and ROS scavenging assays and in vivo experiments, to determine whether the compound has antioxidant activity.

Keywords: ABTS assay, antioxidant activity, Caesalpinia sappan, DPPH assays, total phenolic content

Procedia PDF Downloads 368