Search results for: Human detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3245

Search results for: Human detection

2045 Intelligent Dynamic Decision-making Model Using in Robot's Movement

Authors: Yufang Cheng, Hsiu-Hua Yang

Abstract:

This work develops a novel intelligent “model of dynamic decision-making" usingcell assemblies network architecture in robot's movement. The “model of dynamic decision-making" simulates human decision-making, and follows commands to make the correct decisions. The cell assemblies approach consisting of fLIF neurons was used to implement tasks for finding targets and avoiding obstacles. Experimental results show that the cell assemblies approach of can be employed to efficiently complete finding targets and avoiding obstacles tasks and can simulate the human thinking and the mode of information transactions.

Keywords: Cell assemblies, fLIF, Hebbian learning rule.

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2044 Separation of Dissolved Gases from Water for a Portable Underwater Breathing

Authors: Pil Woo Heo, In Sub Park

Abstract:

Water contains oxygen which may make a human breathe under water like a fish. Centrifugal separator can separate dissolved gases from water. Carrier solution can increase the separation of dissolved oxygen from water. But, to develop an breathing device for a human under water, the enhancement of separation of dissolved gases including oxygen and portable devices which have dc battery based device and proper size are needed. In this study, we set up experimental device for analyzing separation characteristics of dissolved gases including oxygen from water using a battery based portable vacuum pump. We characterized vacuum state, flow rate of separation of dissolved gases and oxygen concentration which were influenced by the manufactured vacuum pump.

Keywords: Portable, breathing, water, separation, battery.

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2043 Efficiency Based Model for Solar Urban Planning

Authors: Amado, M. P., Amado, A., Poggi, F., Correia de Freitas, J.

Abstract:

Today is widely understood that global energy consumption patterns are directly related to the urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals.

In this paper a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities and economic development and the local and global environment while safeguarding fairness in the energy sector.

Keywords: Solar urban planning, solar smart city, urban development, energy efficiency.

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2042 Robotic Hands: Design Review and Proposal of New Design Process

Authors: Jimmy W. Soto Martell, Giuseppina Gini

Abstract:

In this paper we intend to ascertain the state of the art on multifingered end-effectors, also known as robotic hands or dexterous robot hands, and propose an experimental setup for an innovative task based design approach, involving cutting edge technologies in motion capture. After an initial description of the capabilities and complexity of a human hand when grasping objects, in order to point out the importance of replicating it, we analyze the mechanical and kinematical structure of some important works carried out all around the world in the last three decades and also review the actuators and sensing technologies used. Finally we describe a new design philosophy proposing an experimental setup for the first stage using recent developments in human body motion capture systems that might lead to lighter and always more dexterous robotic hands.

Keywords: Dexterous manipulation, grasp, multifingered endeffector, robotic hand.

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2041 Pervasiveness of Aflatoxin in Peanuts Growing in the Area of Pothohar, Pakistan

Authors: Mateen Abbas, Abdul Muqeet Khan, Muhammad Rafique Asi, Javed Akhtar

Abstract:

Mycotoxin (aflatoxins) contamination of peanuts is a great concern for human health. A total of 72 samples of unripe, roasted, and salty peanuts were collected randomly from Pothohar plateau of Pakistan for the assessment of aflatoxin. Samples were dried, ground and extracted by acetonitrile (84%). The filtered extracts were cleaned up by MycoSep-226 and analyzed by high performance liquid chromatography with flourescence detector. Quantification limit of Aflatoxin was 1 μg/kg and 70% Recovery was observed in spiked samples in the range 1–10 μg/kg. The screening of mycotoxins indicated that aflatoxins were present in most of the samples being detected in 82%, in concentrations from 14.25 μg/kg to 98.80 μg/kg. Optimal conditions for mycotoxin production and fungal growth are frequently found in the crop fields as well as in store houses. Human exposure of such toxin can be controlled by pointed out such awareness and implemented the regulations.

Keywords: Aflatoxin, HPLC, Pakistan, Peanuts, Punjab

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2040 Machine Learning Techniques for COVID-19 Detection: A Comparative Analysis

Authors: Abeer Aljohani

Abstract:

The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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2039 Risk and Uncertainty in Aviation: A Thorough Analysis of System Vulnerabilities

Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

Abstract:

Hazard assessment and risks quantification are key components for estimating the impact of existing regulations. But since regulatory compliance cannot cover all risks in aviation, the authors point out that by studying causal factors and eliminating uncertainty, an accurate analysis can be outlined. The research debuts by making delimitations on notions, as confusion on the terms over time has reflected in less rigorous analysis. Throughout this paper, it will be emphasized the fact that the variation in human performance and organizational factors represent the biggest threat from an operational perspective. Therefore, advanced risk assessment methods analyzed by the authors aim to understand vulnerabilities of the system given by a nonlinear behavior. Ultimately, the mathematical modeling of existing hazards and risks by eliminating uncertainty implies establishing an optimal solution (i.e. risk minimization).

Keywords: Control, human factor, optimization, risk management, uncertainty.

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2038 Trend Analysis of Annual Total Precipitation Data in Konya

Authors: Naci Büyükkaracığan

Abstract:

Hydroclimatic observation values ​​are used in the planning of the project of water resources. Climate variables are the first of the values ​​used in planning projects. At the same time, the climate system is a complex and interactive system involving the atmosphere, land surfaces, snow and bubbles, the oceans and other water structures. The amount and distribution of precipitation, which is an important climate parameter, is a limiting environmental factor for dispersed living things. Trend analysis is applied to the detection of the presence of a pattern or trend in the data set. Many trends work in different parts of the world are usually made for the determination of climate change. The detection and attribution of past trends and variability in climatic variables is essential for explaining potential future alteration resulting from anthropogenic activities. Parametric and non-parametric tests are used for determining the trends in climatic variables. In this study, trend tests were applied to annual total precipitation data obtained in period of 1972 and 2012, in the Konya Basin. Non-parametric trend tests, (Sen’s T, Spearman’s Rho, Mann-Kendal, Sen’s T trend, Wald-Wolfowitz) and parametric test (mean square) were applied to annual total precipitations of 15 stations for trend analysis. The linear slopes (change per unit time) of trends are calculated by using a non-parametric estimator developed by Sen. The beginning of trends is determined by using the Mann-Kendall rank correlation test. In addition, homogeneities in precipitation trends are tested by using a method developed by Van Belle and Hughes. As a result of tests, negative linear slopes were found in annual total precipitations in Konya.

Keywords: Trend analysis, precipitation, hydroclimatology, Konya, Turkey.

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2037 Securing Message in Wireless Sensor Network by using New Method of Code Conversions

Authors: Ahmed Chalak Shakir, GuXuemai, Jia Min

Abstract:

Recently, wireless sensor networks have been paid more interest, are widely used in a lot of commercial and military applications, and may be deployed in critical scenarios (e.g. when a malfunctioning network results in danger to human life or great financial loss). Such networks must be protected against human intrusion by using the secret keys to encrypt the exchange messages between communicating nodes. Both the symmetric and asymmetric methods have their own drawbacks for use in key management. Thus, we avoid the weakness of these two cryptosystems and make use of their advantages to establish a secure environment by developing the new method for encryption depending on the idea of code conversion. The code conversion-s equations are used as the key for designing the proposed system based on the basics of logic gate-s principals. Using our security architecture, we show how to reduce significant attacks on wireless sensor networks.

Keywords: logic gates, code conversions, Gray-code, and clustering.

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2036 The Oxidative Damage Marker for Sodium Formate Exposure on Lymphocytes

Authors: Malinee Pongsavee

Abstract:

Sodium formate is the chemical substance used for food additive. Catalase is the important antioxidative enzyme in protecting the cell from oxidative damage by reactive oxygen species (ROS). The resultant level of oxidative stress in sodium formatetreated lymphocytes was investigated. The sodium formate concentrations of 0.05, 0.1, 0.2, 0.4 and 0.6 mg/mL were treated in human lymphocytes for 12 hours. After 12 treated hours, catalase activity change was measured in sodium formate-treated lymphocytes. The results showed that the sodium formate concentrations of 0.4 and 0.6 mg/mL significantly decreased catalase activities in lymphocytes (P < 0.05). The change of catalase activity in sodium formate-treated lymphocytes may be the oxidative damage marker for detect sodium formate exposure in human.

Keywords: Sodium formate, catalase activity, oxidative damage marker, toxicity.

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2035 Domestic Violence against Children and Trafficking in Human Beings: Two Worrying Phenomena in Kosovo

Authors: Adile Shaqiri, Arjeta Shaqiri Latifi

Abstract:

Domestic violence, trafficking with human beings especially violence against children, is a worldwide problem. Hence, it remains one of the most widespread forms of violence in Kosovo and which often continues to be described as a "closed door issue". Recognition, acceptance and prioritization of cases of domestic violence definitely require a much greater awareness of individuals in institutions for the risks, consequences and costs that the lack of such a well-coordinated response brings to the country. Considering that children are the future and the wealth of the country, violence and neglect against them should be treated as carefully as possible. The purpose of this paper is to identify steps towards prevention of the domestic violence and trafficking with human beings, so that the reflection of the consequences and the psychological flow do not reflect to a large extent in society. In this study is described: How is the phenomenon of domestic violence related to trafficking in human beings? The methods used are: historical, comparative, qualitative. Data derived from the relevant institutions were presented, i.e., by the actors who are the first reactors as well as the policy makers. Although these phenomena are present in all countries of the world, Kosovo is no exception and therefore comparisons of the development of child abuse have been made with other countries in the region as well. Since Kosovo is a country in transition, a country with a relatively high level of education, low economic development, high unemployment, political instability, dysfunctional legal infrastructure, it can be concluded that the potential for the development of negative phenomena is present and inevitable. Thus, during the research, the stages of development of these phenomena are analyzed, determining the causes and consequences which come from abuse, neglect of children and the impact on trafficking in human beings. The Kosovar family (parental responsibility), culture and religion, social services, the dignity of the abused child, etc. were analyzed. The review was also done on the legislation, educational institutions (curricula), governmental and non-governmental institutions their responsibilities and cooperation towards combating child abuse and trafficking. It is worth noting that during the work on paper, recommendations and conclusions have been drawn where it is concluded that we need an environment with educational reforms, stability in the political environment, economic development, a review of social policies, greater awareness of society, more adequate information through media, so that information and awareness could penetrate even in the most remote places of Kosovo society.

Keywords: Awareness, education, information, society, violence.

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2034 High Sensitivity Crack Detection and Locating with Optimized Spatial Wavelet Analysis

Authors: A. Ghanbari Mardasi, N. Wu, C. Wu

Abstract:

In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.

Keywords: Edge effect, scale optimization, small crack locating, spatial wavelet.

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2033 Non-negative Principal Component Analysis for Face Recognition

Authors: Zhang Yan, Yu Bin

Abstract:

Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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2032 Effects of Sprint Training on Athletic Performance Related Physiological, Cardiovascular, and Neuromuscular Parameters

Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp

Abstract:

Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.

Keywords: Sprint, training, performance, exercise.

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2031 Automatic Deactivation in Phased Array Probe for Human Prostate Magnetic Resonance Imaging at 1.5T

Authors: Fotios N. Vlachos, Anastasios D. Garetsos, Nikolaos K. Uzunoglu, Efstathios D. Gotsis

Abstract:

A four element prototype phased array surface probe has been designed and constructed to improve clinical human prostate spectroscopic data. The probe consists of two pairs of adjacent rectangular coils with an optimum overlap to reduce the mutual inductance. The two pairs are positioned on the anterior and the posterior pelvic region and two couples of varactors at the input of each coil undertake the procedures of tuning and matching. The probe switches off and on automatically during the consecutive phases of the MR experiment with the use of an analog switch that is triggered by a microcontroller. Experimental tests that were carried out resulted in high levels of tuning accuracy. Also, the switching mechanism functions properly for various applied loads and pulse sequence characteristics, producing only 10 μs of latency.

Keywords: Automatic tuning, prostate imaging, phased array, spectroscopy.

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2030 Performance Analysis of Artificial Neural Network with Decision Tree in Prediction of Diabetes Mellitus

Authors: J. K. Alhassan, B. Attah, S. Misra

Abstract:

Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

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2029 Heart-Rate Resistance Electrocardiogram Identification Based on Slope-Oriented Neural Networks

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: High-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network.

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2028 The Effect of Fixing Kinesiology Tape onto the Plantar Surface during the Loading Phase of Gait

Authors: Albert K. Chong, Jasim Ahmed Ali Al-Baghdadi, Peter B. Milburn

Abstract:

Precise capture of plantar 3D surface of the foot at the loading gait phases on rigid substrates was found to be valuable for the assessment of the physiology, health and problems of the feet. Photogrammetry, a precision 3D spatial data capture technique is suitable for this type of dynamic application. In this research, the technique is utilised to study the plantar deformation as a result of having a strip of kinesiology tape on the plantar surface during the loading phase of gait. For this pilot study, one healthy adult male subject was recruited under the University’s human research ethics guidelines for this preliminary study. The 3D plantar deformation data with and without applying the tape were analysed. The results and analyses are presented together with detailed findings.

Keywords: Gait, human plantar, loading, Kinesiology Tape.

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2027 Evaluation of the Antifungal and Antioxidant Activities of the Leaf Extract of Aloe vera(Aloe barbadensis Miller)

Authors: Tin A. Khaing

Abstract:

Aloe vera has been used worldwide both for pharmaceutical, food, and cosmetic industries due to the plethora of biological activities of some of its metabolites. The aim of this study was to evaluate the antifungal and antioxidant activities of the leaf extract. The antifungal activity was determined by the agar-well diffusion method against plant and human fungal pathogens. The methanol and ethanol portions of the extracts studied were more bioactive than ethyl acetate portion. It was also observed that the activity was more pronounced on plant pathogen than human pathogen except Candida albicans. This is an indication that the extract has the potential to treat plant fungal infections. The Aloe extract showed the significant antioxidant activity by the DPPH radical scavenging method. Therefore, the Aloe extract provided as natural antioxidant has been used in health foods for medical and preservative purposes.

Keywords: Aloe vera, antifungal, antioxidant, DPPH

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2026 Why We Are Taller in the Morning than Going to Bed at Night – An in vivo and in vitro Study

Authors: Harcharan Singh Ranu

Abstract:

Intradiscal and intervertebral pressure transducers were developed. They were used to map the pressures in the nucleus and within the annulus of the human spinal segments. Their stressrelaxation were recorded over a period of time for nucleus pressure, applied load, and peripherial strain against time. The results show that for normal discs, pressures in the nucleus are viscoelastic in nature with the applied compressive load. Mechanical strains which develop around the periphery of the vertebral body are also viscoelastic with the applied compressive load. Applied compressive load against time also shows viscoelastic behavior. However, annulus does not respond viscoelastically with the applied load. It showed a linear response to compressive loading.

Keywords: Intradiscal pressure transducer (IDPT), intervertebral pressure transducer (IVPT), mechanical strains of vertebral bone, viscoelasticity of human spinal disc.

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2025 Motivations for Engaging in Consensual Non-Monogamous Relationships in North America: McClelland's Human Motivation Theory

Authors: Alisha Fisher

Abstract:

Exploring and engaging in intimate, sexual, and romantic relationships carries the opportunity of personal growth, pleasure, connection, and enhancement of well-being. As more and more North Americans begin to consider and engage in romantic and sexual orientations outside of monogamy, the question of their motivations arises. We utilize McClelland's human motivation theory to investigate the intersections of motivational attributes for North Americans engaging in consensual non-monogamous (CNM) relationships. The need for achievement, power, and affiliation all influence and interact with each other within CNM relationships. The interplay of these motivations is vital for CNM relational structures to operate and effectively navigate conflict. Further studies should explore these motivational components within the individuals who practice CNM and examining the differences in various CNM relational structures.

Keywords: Consensual non-monogamy, motivations for non-monogamy, McClelland Motivation theory, CNM.

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2024 Surface Water Pollution by Open Refuse Dumpsite in North Central of Nigeria

Authors: Abimbola Motunrayo Folami, Ibironke Titilayo Enitan, Feroz Mohomed Swalaha

Abstract:

Water is a vital resource that is important in ensuring the growth and development of any country. To sustain the basic human needs and the demands for agriculture, industry, conservational and ecosystem, enough quality and quantity water is needed. Contamination of water resources is now a global and public health concern. Hence, this study assessed the water quality of Ndawuse River by measuring the physicochemical parameters and heavy metals concentrations of the river using standard methods. In total, 16 surface water samples were obtained from five locations along the river, from upstream to downstream as well as samples from the dumpsite. The results obtained were compared with the standard limits set by both the World Health Organization and the Federal Environmental Protection Agency for domestic purposes. The results of the measured parameters indicated that biological oxygen demand (85.88 mg/L), turbidity (44.51 NTU), Iron (0.014 - 3.511 mg /L) and chromium (0.078 - 0.14 mg /L) were all above the standard limits. The results further showed that the quality of surface water is being significantly affected by human activities around the Ndawuse River which could pose an adverse health risk to several communities that rely on this river as their primary source of water. Therefore, there is a need for strict enforcement of environmental laws to protect the aquatic ecosystem and to avoid long term cumulative exposure risk that heavy metals may pose on human health.

Keywords: Abuja, contaminants, heavy metals, Ndawuse River, Nigeria, surface water.

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2023 CBIR Using Multi-Resolution Transform for Brain Tumour Detection and Stages Identification

Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

Abstract:

Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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2022 Performance Analysis of MT Evaluation Measures and Test Suites

Authors: Yao Jian-Min, Lv Qiang, Zhang Jing

Abstract:

Many measures have been proposed for machine translation evaluation (MTE) while little research has been done on the performance of MTE methods. This paper is an effort for MTE performance analysis. A general frame is proposed for the description of the MTE measure and the test suite, including whether the automatic measure is consistent with human evaluation, whether different results from various measures or test suites are consistent, whether the content of the test suite is suitable for performance evaluation, the degree of difficulty of the test suite and its influence on the MTE, the relationship of MTE result significance and the size of the test suite, etc. For a better clarification of the frame, several experiment results are analyzed relating human evaluation, BLEU evaluation, and typological MTE. A visualization method is introduced for better presentation of the results. The study aims for aid in construction of test suite and method selection in MTE practice.

Keywords: Machine translation, natural language processing, visualization.

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2021 Critical Analysis of Decision Making Experience with a Machine Learning Approach in Playing Ayo Game

Authors: Ibidapo O. Akinyemi, Ezekiel F. Adebiyi, Harrison O. D. Longe

Abstract:

The major goal in defining and examining game scenarios is to find good strategies as solutions to the game. A plausible solution is a recommendation to the players on how to play the game, which is represented as strategies guided by the various choices available to the players. These choices invariably compel the players (decision makers) to execute an action following some conscious tactics. In this paper, we proposed a refinement-based heuristic as a machine learning technique for human-like decision making in playing Ayo game. The result showed that our machine learning technique is more adaptable and more responsive in making decision than human intelligence. The technique has the advantage that a search is astutely conducted in a shallow horizon game tree. Our simulation was tested against Awale shareware and an appealing result was obtained.

Keywords: Decision making, Machine learning, Strategy, Ayo game.

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2020 Tracking Activity of Real Individuals in Web Logs

Authors: Sándor Juhász, Renáta Iváncsy

Abstract:

This paper describes an enhanced cookie-based method for counting the visitors of web sites by using a web log processing system that aims to cope with the ambitious goal of creating countrywide statistics about the browsing practices of real human individuals. The focus is put on describing a new more efficient way of detecting human beings behind web users by placing different identifiers on the client computers. We briefly introduce our processing system designed to handle the massive amount of data records continuously gathered from the most important content providers of the Hungary. We conclude by showing statistics of different time spans comparing the efficiency of multiple visitor counting methods to the one presented here, and some interesting charts about content providers and web usage based on real data recorded in 2007 will also be presented.

Keywords: Cookie based identification, real data, user activitytracking, web auditing, web log processing

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2019 Nutrient Modelling to Fabricate Dairy Milk Constituents: Let Milk Serve More Than a Food Item

Authors: M.Aasif Shahzad, N.Mukhtar, M.Sarwar

Abstract:

Dietary macro and micro nutrients in their respective proportion and fractions present a practical potential tool to fabricate milk constituents since cells of lactating mammary glands obtain about 80 % of milk synthesis nutrients from blood, reflecting the existence of an isotonic equilibrium between blood and milk. Diverting milk biosynthetic activities through manipulation of nutrients towards producing milk not only keeping in view its significance as natural food but also as food item which prevents or dilutes the adverse effects of some diseases (like cardiovascular problem by saturated milk fat intake) has been area of interest in the last decade. Nutritional modification / supplementation has been reported to enhance conjugated linoleic acid, fatty acid type and concentration, essential fatty acid concentration, vitamin B12& C, Se, Cu, I and Fe which are involved to counter the health threats to human well being. Synchronizing dietary nutrients aimed to modify rumen dynamics towards synthesis of nutrients or their precursors to make their drive towards formulated milk constituents presents a practical option. Formulating dietary constituents to design milk constituents will let the farmers, consumers and investors know about the real potential and profit margins associated with this enterprise. This article briefly recapitulates the ways and means to modify milk constituents keeping an eye on human health and well being issues, which allows milk to serve more than a food item.

Keywords: Nutritional modification, fabricating milk composition, human health.

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2018 Hemodynamic Characteristics in the Human Carotid Artery Model Induced by Blood-Arterial Wall Interactions

Authors: Taewon Seo

Abstract:

The characteristics of physiological blood flow in human carotid arterial bifurcation model have been numerically studied using a fully coupled fluid-structure interaction (FSI) analysis. This computational model with the fluid-structure interaction is constructed to investigate the flow characteristics and wall shear stress in the carotid artery. As the flow begins to decelerate after the peak flow, a large recirculation zone develops at the non-divider wall of both internal carotid artery (ICA) and external carotid artery (ECA) in FSI model due to the elastic energy stored in the expanding compliant wall. The calculated difference in wall shear stress (WSS) in both Non-FSI and FSI models is a range of between 5 and 11% at the mean WSS. The low WSS corresponds to regions of carotid artery that are more susceptible to atherosclerosis.

Keywords: Carotid artery, Fluid-structure interaction, Hemodynamics, Wall shear stress.

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2017 Bioinformatic Analysis of Retroelement-Associated Sequences in Human and Mouse Promoters

Authors: Nadezhda M. Usmanova, Nikolai V. Tomilin

Abstract:

Mammalian genomes contain large number of retroelements (SINEs, LINEs and LTRs) which could affect expression of protein coding genes through associated transcription factor binding sites (TFBS). Activity of the retroelement-associated TFBS in many genes is confirmed experimentally but their global functional impact remains unclear. Human SINEs (Alu repeats) and mouse SINEs (B1 and B2 repeats) are known to be clustered in GCrich gene rich genome segments consistent with the view that they can contribute to regulation of gene expression. We have shown earlier that Alu are involved in formation of cis-regulatory modules (clusters of TFBS) in human promoters, and other authors reported that Alu located near promoter CpG islands have an increased frequency of CpG dinucleotides suggesting that these Alu are undermethylated. Human Alu and mouse B1/B2 elements have an internal bipartite promoter for RNA polymerase III containing conserved sequence motif called B-box which can bind basal transcription complex TFIIIC. It has been recently shown that TFIIIC binding to B-box leads to formation of a boundary which limits spread of repressive chromatin modifications in S. pombe. SINEassociated B-boxes may have similar function but conservation of TFIIIC binding sites in SINEs located near mammalian promoters has not been studied earlier. Here we analysed abundance and distribution of retroelements (SINEs, LINEs and LTRs) in annotated sequences of the Database of mammalian transcription start sites (DBTSS). Fractions of SINEs in human and mouse promoters are slightly lower than in all genome but >40% of human and mouse promoters contain Alu or B1/B2 elements within -1000 to +200 bp interval relative to transcription start site (TSS). Most of these SINEs is associated with distal segments of promoters (-1000 to -200 bp relative to TSS) indicating that their insertion at distances >200 bp upstream of TSS is tolerated during evolution. Distribution of SINEs in promoters correlates negatively with the distribution of CpG sequences. Using analysis of abundance of 12-mer motifs from the B1 and Alu consensus sequences in genome and DBTSS it has been confirmed that some subsegments of Alu and B1 elements are poorly conserved which depends in part on the presence of CpG dinucleotides. One of these CpG-containing subsegments in B1 elements overlaps with SINE-associated B-box and it shows better conservation in DBTSS compared to genomic sequences. It has been also studied conservation in DBTSS and genome of the B-box containing segments of old (AluJ, AluS) and young (AluY) Alu repeats and found that CpG sequence of the B-box of old Alu is better conserved in DBTSS than in genome. This indicates that Bbox- associated CpGs in promoters are better protected from methylation and mutation than B-box-associated CpGs in genomic SINEs. These results are consistent with the view that potential TFIIIC binding motifs in SINEs associated with human and mouse promoters may be functionally important. These motifs may protect promoters from repressive histone modifications which spread from adjacent sequences. This can potentially explain well known clustering of SINEs in GC-rich gene rich genome compartments and existence of unmethylated CpG islands.

Keywords: Retroelement, promoter, CpG island, DNAmethylation.

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2016 Landcover Mapping Using Lidar Data and Aerial Image and Soil Fertility Degradation Assessment for Rice Production Area in Quezon, Nueva Ecija, Philippines

Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

Abstract:

Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: Aerial image, land-cover, LiDAR, soil fertility degradation.

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