Search results for: client identification

Authors: Chia-Ju Peng, Shih-Jui Chen

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This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

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Authors: Hyo-In Koh, Anders Nordborg, Alex Sievi, Chun-Kwon Park

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The noise source for the interior room of the high speed train is constituted by the rolling contact between the wheel and the rail, aerodynamic noise and structure-borne sound generated through the vibrations of bogie, connection points to the carbody. Air-borne sound is radiated through the panels and structures into the interior room of the trains. The high-speed lines are constructed with slab track systems and many tunnels. The interior noise level and the frequency characteristics vary according to types of the track structure and the infrastructure. In this paper the main sound sources and the transfer paths are studied to find out the contribution characteristics of the sources to the interior noise of a high-speed rail vehicle. For the identification of the acoustic power of each parts of the rolling noise sources a calculation model of wheel/rail noise is developed and used. For the analysis of the transmission of the sources to the interior noise noise and vibration are measured during the operation of the vehicle. According to operation speeds, the mainly contributed sources and the paths could be analyzed. Results of the calculations on the source generation and the results of the measurement with a high-speed train are shown and discussed.

Keywords: rail vehicle, high-speed, interior noise, noise source

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Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: Jiangping Wang

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This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

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Authors: Charles Mothobiso

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This study attempts to identify the client’s main priority when delivering green projects. The aim is to compare whether clients’ interests are similar when delivering conventional buildings as compared to green buildings. Private clients invest more in green buildings as compared to government and parastatal entities. Private clients prioritize on maximizing a return on investment and they mainly invest in energy-saving buildings that have low life cycle costs. Private clients are perceived to be more knowledgeable about the benefits of green building projects as compared to government and parastatal clients. A shortage of expertise and managerial skill leads to the low adaptation of green buildings in government and parastatal projects. Other factors that seem to prevent the adoption of green buildings are the preparedness of the supply chain within the industry and inappropriate procurement strategies adopted by clients.

Keywords: construction clients, design team, green buildings, procurement

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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Authors: Liang Zhao, Guangwen Wang, Guichang Liu

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Constant potometer is an important component of pipeline anti-corrosion systems in the chemical industry. Based on Internet of Things (IoT) technology, Programmable Logic Controller (PLC) technology and database technology, this paper developed a set of a constant potometer remote monitoring management system. The remote monitoring and remote adjustment of the working status of the constant potometer are realized. The system has real-time data display, historical data query, alarm push management, user permission management, and supporting Web access and mobile client application (APP) access. The actual engineering project test results show the stability of the system, which can be widely used in cathodic protection systems.

Keywords: internet of things, pipe corrosion protection, potentiostat, remote monitoring

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Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Mohammad Javad Seddighi, Avar Almukhtar

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Sustainable urban planning and design (SUPD) play a critical role in achieving the United Nations Sustainable Development Goals (UN SDGs). While there are many rating systems and standards available to assess the sustainability of the built environment, there is still a lack of a comprehensive framework that can assess the quality of SUPD in a specific context. In this paper, we present a framework for assessing the quality of SUPD in Iranian cities, considering their unique cultural, social, and environmental contexts. The aim of this study is to develop a framework for assessing the quality of SUPD in Iranian cities. To achieve this aim, the following objectives are pursued review and synthesis of relevant literature on SUPD, identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities application of the framework to case studies of Iranian cities and evaluation and refinement of the framework based on the results of the case studies. The framework is developed based on a review and synthesis of relevant literature on SUPD, and the identification of key indicators and criteria for assessing the quality of SUPD in Iranian cities. The framework is then applied to case studies of Iranian cities and the results are evaluated and refined. The data for this study are collected through a review of relevant literature on SUPD, including academic journals, conference proceedings, and books. The case studies of Iranian cities are selected based on their relevance and availability of data. The data are collected through interviews, site visits, and document analysis. This paper presents a framework for assessing the quality of SUPD in Iranian cities. The framework is developed based on a review and synthesis of relevant literature, identification of key indicators and criteria, application to case studies, and evaluation and refinement. The framework provides a comprehensive and context-specific approach to assessing the quality of SUPD in Iranian cities. It can be used by urban planners, designers, and policymakers to improve the sustainability and liveability of Iranian cities, and it can be adapted for use in other contexts.

Keywords: sustainable urban planning and design, framework, quality assessment, Iranian cities, case studies

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Authors: Omar Shakra

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This paper contains a huge number of benefits that we can use it in several places and times in fire safety protection in the Middle East especially in Egypt . People here in Egypt did not consider the safety and fire protection as important as it is. But on the other hand, its very important for them to contain the fire systems and safety in every facility, the companies , hospitals , police stations , and even the super markets must use the fire system. It makes the facility safe to the visitors while they are using it.From my point of view as the owner Fire Safety Company called Deluge Egypt , i can say that not all of the companies use the fire system protection according to the high cost they prefer to build their company without the protection, and this is make the building totally unsafe to be used from the visitors or client.So, i am looking for new methods and technology to invest in Egypt, and this is through attending this Conference and let the audiences know more about the services i provide and [to let them know about the importance of the Fire Safety in Egypt. The Objectives of my research 1- The system that i used in my Company. 2- The benefits of the Fire System Protection. 3-The importance of the Fire System and safety. 4-The use of the new Technologies. 5-The hardships that i found while having new deals with new clients.

Keywords: fire, system, protection, fire hydrants, security, alarms

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Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

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Authors: Michael Saad Thabet Azrek

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Experiential advertising method is an unforgettable revel that remains deeply anchored within the customer's memory. Furthermore, client pleasure is defined as the emotional reaction to the stories provided that relate to precise products or services bought. Consequently, experiential advertising sports can influence the extent of consumer pleasure and loyalty. In this context, they have a look at pursuits to observe the connection between experiential advertising, purchaser satisfaction and loyalty to splendor merchandise in Konya. The outcomes of this examination confirmed that experiential marketing is an important indicator of consumer pride and loyalty, and that experiential advertising and marketing have a large positive impact on patron satisfaction and loyalty.

Keywords: sponsorship, marketing communication theories, marketing communication tools internet, marketing, tourism, tourism management corporate responsibility, employee organizational performance, internal marketing, internal customer experiential marketing, customer satisfaction, customer loyalty, social sciences.

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Authors: Samiyah Tasleem, Muhammad Abdul Haq, Syed Baqir Shyum Naqvi, Muhammad Abid Husnain, Sajjad Haider Naqvi

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The objective of the present study was: a) to investigate the antimicrobial activity of honey samples of different floral sources of Pakistan, b) to recover the phenolic acids in them as a possible contributing factor of antimicrobial activity. Six honey samples from different floral sources, namely: Trachysperm copticum, Acacia species, Helianthus annuus, Carissa opaca, Zizyphus and Magnifera indica were used. The antimicrobial activity was investigated by the disc diffusion method against eight freshly isolated clinical isolates (Staphylococci aureus, Staphylococci epidermidis, Streptococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumonia, Escherichia coli, Proteus vulgaris and Candida albicans). Antimicrobial activity of honey was compared with five commercial antibiotics, namely: doxycycline (DO-30ug/mL), oxytetracycline (OT-30ug/mL), clarithromycin (CLR–15ug/mL), moxifloxacin (MXF-5ug/mL) and nystatin (NT – 100 UT). The fractions responsible for antimicrobial activity were extracted using ethyl acetate. Solid phase extraction (SPE) was used to recover the phenolic acids of honey samples. Identification was carried out via High-Performance Liquid Chromatography (HPLC). The results indicated that antimicrobial activity was present in all honey samples and found comparable to the antibiotics used in the study. In the microbiological assay, the ethyl acetate honey extract was found to exhibit a very promising antimicrobial activity against all the microorganisms tested, indicating the existence of phenolic compounds. Six phenolic acids, namely: gallic, caffeic, ferulic, vanillic, benzoic and cinnamic acids were identified besides some unknown substance by HPLC. In conclusion, Pakistani honey samples showed a broad spectrum antibacterial and promising antifungal activity. Identification of six different phenolic acids showed that Pakistani honey samples are rich sources of phenolic compounds that could be the contributing factor of antimicrobial activity.

Keywords: Pakistani honey, antimicrobial activity, Phenolic acids eg.gallic, caffeic, ferulic, vanillic, benzoic and cinnamic acids

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Authors: Adjebli Ahmed, Messis Abdelaziz, Ayeche Riad, Tighilet Karim, Talbi Melissa, Smaili Yanis, Lehri Mokrane, Louardiane Mustapha

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Colorectal cancer is one of the most common types of cancer worldwide, and its incidence has been increasing in recent years. Data and fecal samples from colorectal cancer patients were collected at the Amizour Public Hospital's oncology department (Bejaia, Algeria). Microbiological and cohort study were conducted at the Biological Engineering of Cancers laboratory at the Faculty of Medicine of the University of Bejaia. All the data showed that patients aged between 50 and 70 years were the most affected by colorectal cancer, while the age categories of [30-40] and [40-50] were the least affected. Males were more likely to be at risk of contracting colorectal cancer than females. The most common types of colorectal cancer among the studied population were sigmoid cancer, rectal cancer, transverse colon cancer, and ascending colon cancer. The hereditary factor was found to be more dominant than other risk factors. Bacterial identification revealed the presence of certain pathogenic and opportunistic bacterial genera, such as E. coli, K. pneumoniae, Shigella sp, and Streptococcus group D. These results led us to conclude that dysbiosis of the intestinal microbiome is strongly present in colorectal cancer patients at the EPH of Amizour.

Keywords: microbiome, colorectal cancer, risk factors, bacterial identification

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Jingyuan Hu, Zhandong Liu

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CRISPR genome editing technology has transformed molecular biology by accurately targeting and altering an organism’s DNA. Despite the state-of-art precision of CRISPR genome editing, the imprecise mutation outcome and off-target effects present considerable risk, potentially leading to unintended genetic changes. Targeted deep sequencing, combined with bioinformatics sequence alignment, can detect such unwanted mutations. Nevertheless, the classical method, Needleman-Wunsch (NW) algorithm may produce false alignment outcomes, resulting in inaccurate mutation identification. The key to precisely identifying CRISPR-induced mutations lies in determining optimal parameters for the sequence alignment algorithm. Hidden Markov models (HMM) are ideally suited for this task, offering flexibility across CRISPR systems by leveraging forward-backward algorithms for parameter estimation. In this study, we introduce CRISPR-HMM, a statistical software to precisely call CRISPR-induced mutations. We demonstrate that the software significantly improves precision in identifying CRISPR-induced mutations compared to NW-based alignment, thereby enhancing the overall understanding of the CRISPR gene-editing process.

Keywords: CRISPR, HMM, sequence alignment, gene editing

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Sara Seyfi

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DDT and petroleum contamination in coastal sand alters the physical and mechanical properties of contaminated soils. This article aims to understand the effects of DDT pollution on the geotechnical characteristics of sand groups, including sand, silty sand, and clay sand. First, the studies conducted on the topic of the article will be reviewed. In the initial stage of the tests, this article deals with the identification of the used sands (sand, silty sand, clay sand) by FTIR, µ-XRF and SEM methods. Then, the geotechnical characteristics of these sand groups, including density, permeability, shear strength, compaction, and plasticity, are investigated using a sand cone, head permeability test, Vane shear test, strain gauge penetrometer, and plastic limit test. Sand groups are artificially contaminated with petroleum substances with 1, 2, 4, 8, 10, 12% by weight. In a separate experiment, amounts of 2, 4, 8, 12, 16, 20 mg/liter of DDT were added to the sand groups. Geotechnical characteristics and identification analysis are performed on the contaminated samples. In the final tests, the mentioned amounts of oil pollution and DDT are simultaneously added to the sand groups, and identification and measurement processes are carried out. The results of the tests showed that petroleum contamination had reduced the optimal moisture content, permeability, and plasticity of all samples. Except silty sand’s plasticity, which petroleum increased it by 1-4% and decreased it by 8-12%. The dry density of sand and clay sand increased, but that of silty sand decreased. Also, the shear strength of sand and silty sand increased, but that of clay sand decreased. DDT contamination increased the maximum dry density and decreased the permeability of all samples. It also reduced the optimum moisture content of the sand. The shear resistance of silty sand and clayey sand decreased, and plasticity of clayey sand increased, and silty sand decreased. The simultaneous effect of petroleum and DDT pollution on the maximum dry density of sand and clayey sand has been synergistic, on the plasticity of clayey sand and silty sand, there has been antagonism. This process has caused antagonism of optimal sand content, shear strength of silty sand and clay sand. In other cases, the effect of synergy or antagonism is not observed.

Keywords: DDT contamination, geotechnical characteristics, petroleum contamination, sand

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Authors: Haixu Yu, Wenhui Cao

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Tailoring Large Language Models (LLMs) to perform legal reasoning has been a popular trend in the study of AI and law. Researchers have mainly employed two methods to unlock the potential of LLMs, namely by finetuning the LLMs to expand their knowledge of law and by restructuring the prompts (In-Context Learning) to optimize the LLMs’ understanding of the legal questions. Although claiming the finetuning and renovated prompting can make LLMs more competent in legal reasoning, most state-of-the-art studies show quite limited improvements of practicability. In this paper, drawing on the study of the complexity and low interpretability of legal texts, we propose a prompting strategy based on the Chain of Thought (CoT) method. Instead of merely instructing the LLM to reason “step by step”, the prompting strategy requires the tested LLM to identify the ambiguity in the questions as the first step and then allows the LLM to generate corresponding answers in line with different understandings of the identified terms as the following step. The proposed prompting strategy attempts to encourage LLMs to "interpret" the given text from various aspects. Experiments that require the LLMs to answer “case analysis” questions of bar examination with general LLMs such as GPT 4 and legal LLMs such as LawGPT show that the prompting strategy can improve LLMs’ ability to better understand complex legal texts.

Keywords: ambiguity-identification, prompt, large language model, legal text understanding

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Muneeba Butt

Abstract:

One of the most important physical evidence which leaves suspects at the crime scene is footprints. Analysis of footprints, which can provide useful information for personal identification, is helpful in crime scene investigation. For the current study, 200 samples collected (144 male and 56 female) from Pakistani population with a consent form. The footprints were collected by using black ink with an ink pad. The entire samples were photographed, and then the magnifying glass was used for visualization of individual characteristics including detail of toes, humps, phalange mark, and flat foot cracks in footprint patterns. The descriptive results of individualizing characteristics features were presented in tabular form with respective frequency and percentage. In the result in the male population, the prevalence of tibialis type (T-type) is highest. In the female population, the prevalence of midularis type (M-type) is highest. Humps on the first toe are more found in the male population rather than other humps. In the female population, humps on the third toe are more found rather than other humps. In the male population, the prevalence of phalange mark by toe 1 is highest followed by toe 3, toe 5, toe 2, toe 4 and in female population the prevalence of phalange mark by toe 1 is highest followed by toe 5, 4, 3 and 2. Creases marks are found highest in male population as compared to the female population.

Keywords: foot prints, toes, humps, cracks

Procedia PDF Downloads 154

Authors: Shayma Mohammed, Adel Trabelsi

Abstract:

Radiopharmacy is the art of preparing high-quality, radioactive, medicinal products for use in diagnosis and therapy. Radiopharmaceuticals unlike normal medicines, this dual aspect (radioactive, medical) makes their management highly critical. One of the most convincing applications of modern technologies is the ability to delegate the execution of repetitive tasks to programming scripts. Automation has found its way to the most skilled jobs, to improve the company's overall performance by allowing human workers to focus on more important tasks than document filling. This project aims to contribute to implement a comprehensive system to insure rigorous management of radiopharmaceuticals through the use of a platform that links the Nuclear Medicine Service Management System to the Nuclear Radio-pharmacy Management System in accordance with the recommendations of World Health Organization (WHO) and International Atomic Energy Agency (IAEA). In this project we attempt to build a web application that targets radiopharmacies, the platform is built atop the inherently compatible web stack which allows it to work in virtually any environment. Different technologies are used in this project (PHP, Symfony, MySQL Workbench, Bootstrap, Angular 7, Visual Studio Code and TypeScript). The operating principle of the platform is mainly based on two parts: Radiopharmaceutical Backoffice for the Radiopharmacian, who is responsible for the realization of radiopharmaceutical preparations and their delivery and Medical Backoffice for the Doctor, who holds the authorization for the possession and use of radionuclides and he/she is responsible for ordering radioactive products. The application consists of sven modules: Production, Quality Control/Quality Assurance, Release, General Management, References, Transport and Stock Management. It allows 8 classes of users: The Production Manager (PM), Quality Control Manager (QCM), Stock Manager (SM), General Manager (GM), Client (Doctor), Parking and Transport Manager (PTM), Qualified Person (QP) and Technical and Production Staff. Digital platform bringing together all players involved in the use of radiopharmaceuticals and integrating the stages of preparation, production and distribution, Web technologies, in particular, promise to offer all the benefits of automation while requiring no more than a web browser to act as a user client, which is a strength because the web stack is by nature multi-platform. This platform will provide a traceability system for radiopharmaceuticals products to ensure the safety and radioprotection of actors and of patients. The new integrated platform is an alternative to write all the boilerplate paperwork manually, which is a tedious and error-prone task. It would minimize manual human manipulation, which has proven to be the main source of error in nuclear medicine. A codified electronic transfer of information from radiopharmaceutical preparation to delivery will further reduce the risk of maladministration.

Keywords: automated system, management, radiopharmacy, technical papers

Procedia PDF Downloads 149

Authors: Niki K. Burns, James R. Pearson, Paul G. Stevenson, Xavier A. Conlan

Abstract:

In Australian state Victoria, synthetic cannabinoids have recently been made illegal under an amendment to the drugs, poisons and controlled substances act 1981. Identification of synthetic cannabinoids in popular brands of ‘incense’ and ‘potpourri’ has been a difficult and challenging task due to the sample complexity and changes observed in the chemical composition of the cannabinoids of interest. This study has developed analytical methodology for the targeted extraction and determination of synthetic cannabinoids available pre-ban. A simple solvent extraction and solid phase extraction methodology was developed that selectively extracted the cannabinoid of interest. High performance liquid chromatography coupled with UV‐visible and chemiluminescence detection (acidic potassium permanganate and tris (2,2‐bipyridine) ruthenium(III)) were used to interrogate the synthetic cannabinoid products. Mass spectrometry and nuclear magnetic resonance spectroscopy were used for structural elucidation of the synthetic cannabinoids. The tris(2,2‐bipyridine)ruthenium(III) detection was found to offer better sensitivity than the permanganate based reagents. In twelve different brands of herbal incense, cannabinoids were extracted and identified including UR‐144, XLR 11, AM2201, 5‐F‐AKB48 and A796‐260.

Keywords: electrospray mass spectrometry, high performance liquid chromatography, solid phase extraction, synthetic cannabinoids

Procedia PDF Downloads 456

Authors: Farid Benkaci-Alia, Abdelhamid Neggada, Sophie Laurentb

Abstract:

A new extraction method of polyphenols from honey using a biodegradable resin was developed and compared with the common commercial resin amberlite XAD2. For this purpose, three honey samples of Algerian origin were selected for the different physico-chemical and biochemical parameters study. After extraction of the target compounds by both resins, the polyphenol content was determined, the antioxidant activity was tested, and LC-MS analyses were performed for identification and quantification. The results showed that physico-chemical and biochemical parameters meet the norms of the International Honey commission, and the H1 sample seemed to be of high quality. The optimal conditions of extraction by biodegradable resin were a pH of 3, an adsorption dose of 40 g/L, a contact time of 50 min, an extraction temperature of 60°C and no stirring. The regeneration and reuse number of both resins was three cycles. The polyphenol contents demonstrated a higher extraction efficiency of biosorbent than of XAD2, especially in H1. LC-MS analyses allowed for the identification and quantification of fifteen compounds in the different honey samples extracted using both resins and the most abundant compound was 3,4,5-trimethoxybenzoic acid. In addition, the biosorbent extracts showed stronger antioxidant activities than the XAD2 extracts.

Keywords: extraction, polyphénols, biosorbent, resin amberlite, HPLC-MS

Procedia PDF Downloads 97

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river

Procedia PDF Downloads 281