Search results for: data sensitivity

Authors: Muhammad Usman

Abstract:

Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

Procedia PDF Downloads 223

Authors: Agampodi Promoda Perera, Yong Shin, Mi Kyoung Park

Abstract:

The successful detection of pathogenic bacteria in blood provides important information for early detection, diagnosis and the prevention and treatment of infectious diseases. Silicon microring resonators are refractive-index-based optical biosensors that provide highly sensitive, label-free, real-time multiplexed detection of biomolecules. We demonstrate the technique of using GO (graphene oxide) to enhance the signal output of the silicon microring optical sensor. The activated carboxylic groups in GO molecules bind directly to single stranded DNA with an amino modified 5’ end. This conjugation amplifies the shift in resonant wavelength in a real-time manner. We designed a capture probe for strain Staphylococcus aureus of 21 bp and a longer complementary target sequence of 70 bp. The mismatched target sequence we used was of Streptococcus agalactiae of 70 bp. GO is added after the complementary binding of the probe and target. GO conjugates to the unbound single stranded segment of the target and increase the wavelength shift on the silicon microring resonator. Furthermore, our results show that GO could successfully differentiate between the mismatched DNA sequences from the complementary DNA sequence. Therefore, the proposed concept could effectively enhance sensitivity of pathogen detection sensors.

Keywords: label free biosensor, pathogenic bacteria, graphene oxide, diagnosis

Procedia PDF Downloads 468

Authors: A. M. T. Jacinto, M.O. Osi

Abstract:

Tamarind has various medicinal properties among which is its antibacterial property. Its bark contains saponins, alkaloids, sesquiterpenes and tannins. It is rich in phlobapenes which is responsible for antibacterial property. The objective of the study was to determine which bark will produce the highest antibacterial property, develop it into a topical cream and evaluate its quality and characteristics. Powdered barks of Tamarind were extracted by soxhlet method using 70% acetone. Stem bark produced a higher yield than trunk bark (5.85 g vs. 4.73 g). It was found that the trunk bark was more sensitive than stem bark to microorganisms namely Staphylococcus aureus, Corynebacterium minutissimum, and Streptococcus spp. Sensitivity of trunk bark can be attributed to a more developed phytoconstituents. Dermal sensitization test on both sexes of rabbits using the following concentrations: 100%, 40% and 20% of extract showed that Tamarind has no irritating property and therefore safe for formulation into an antibacterial cream. Excipients used for formulation such as methyl paraben, propyl paraben, stearyl alcohol and white petrolatum were compatible with the Tamarind acetone extract through Differential Scanning Calorimetry except sodium lauryl sulfate that exhibited crystallization when subjected at 200˚C. The method of manufacture used in cream is fusion, therefore strict compliance of processing temperature should be observed to prevent polymorphism. Quality control tests of formulated cream based on USP 30 and Philippine Pharmacopeia were satisfactory.

Keywords: antibacterial, differential scanning calorimetry, tannins, dermal sensitization

Procedia PDF Downloads 486

Authors: Majid Samiee Zonoozian

Abstract:

For such important constructions as jacket type platforms, scrupulous attention in analysis, design and calculation processes is needed. The reliability assessment method has been established into an extensively used method to behavior safety calculation of jacket platforms. In the present study, a methodology for the reliability calculation of an offshore jacket platform in contradiction of the extreme wave loading state is available. Therefore, sensitivity analyses are applied to acquire the nonlinear response of jacket-type platforms against extreme waves. The jacket structure is modeled by applying a nonlinear finite-element model with regards to the tubular members' behave. The probability of a member’s failure under extreme wave loading is figured by a finite-element reliability code. The FORM and SORM approaches are applied for the calculation of safety directories and reliability indexes have been detected. A case study for a fixed jacket-type structure positioned in the Persian Gulf is studied by means of the planned method. Furthermore, to define the failure standards, equations suggested by the 21st version of the API RP 2A-WSD for The jacket-type structures’ tubular members designing by applying the mixed axial bending and axial pressure. Consequently, the effect of wave Loades in the reliability index was considered.

Keywords: Jacket-Type structure, reliability, failure probability, tubular members

Procedia PDF Downloads 172

Authors: Zhan Panpan, Lu Lan, Sun Yong, He Xiongwen, Yan Dong, Gu Ming

Abstract:

The function of the two spacecraft docking network, the communication and control of a docking target with various spacecrafts is realized in the space lab data management system. In order to solve the problem of the complex data communication mode between the space lab and various spaceships, and the problem of software reuse caused by non-standard protocol, a data management software system supporting rendezvous and docking with various spaceships has been designed. The software system is based on CCSDS Spcecraft Onboard Interface Service(SOIS). It consists of Software Driver Layer, Middleware Layer and Appliaction Layer. The Software Driver Layer hides the various device interfaces using the uniform device driver framework. The Middleware Layer is divided into three lays, including transfer layer, application support layer and system business layer. The communication of space lab plaform bus and the docking bus is realized in transfer layer. Application support layer provides the inter tasks communitaion and the function of unified time management for the software system. The data management software functions are realized in system business layer, which contains telemetry management service, telecontrol management service, flight status management service, rendezvous and docking management service and so on. The Appliaction Layer accomplishes the space lab data management system defined tasks using the standard interface supplied by the Middleware Layer. On the basis of layered architecture, rendezvous and docking tasks and the rendezvous and docking management service are independent in the software system. The rendezvous and docking tasks will be activated and executed according to the different spaceships. In this way, the communication management functions in the independent flight mode, the combination mode of the manned spaceship and the combination mode of the cargo spaceship are achieved separately. The software architecture designed standard appliction interface for the services in each layer. Different requirements of the space lab can be supported by the use of standard services per layer, and the scalability and flexibility of the data management software can be effectively improved. It can also dynamically expand the number and adapt to the protocol of visiting spaceships. The software system has been applied in the data management subsystem of the space lab, and has been verified in the flight of the space lab. The research results of this paper can provide the basis for the design of the data manage system in the future space station.

Keywords: space lab, rendezvous and docking, data management, software system

Procedia PDF Downloads 368

Authors: Jui-Chien Hsieh

Abstract:

Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

Procedia PDF Downloads 114

Authors: Hiroki Takiguchi, Masahiro Furuya, Takahiro Arai

Abstract:

In order to quantitatively comprehend thermal flow for some industrial applications such as nuclear and chemical reactors, detailed measurements for temperature and abundance (concentration) of materials at high temporal and spatial resolution are required. Additionally, rigorous evaluation of the size effect is also important for practical realization. This paper introduces a real-time spectroscopic imaging method in micro scale field, which visualizes temperature and concentration distribution of a liquid or mix liquids with near-infrared (NIR) wavelength region. This imaging principle is based on absorption of pre-selected narrow band from absorption spectrum peak or its dependence property of target liquid in NIR region. For example, water has a positive temperature sensitivity in the wavelength at 1905 nm, therefore the temperature of water can be measured using the wavelength band. In the experiment, the real-time imaging observation of concentration distribution in micro channel was demonstrated to investigate the applicability of micro-scale diffusion coefficient and temperature measurement technique using this proposed method. The effect of thermal diffusion and binary mutual diffusion was evaluated with the time-series visualizations of concentration distribution.

Keywords: near-infrared spectroscopic imaging, micro fluid channel, concentration distribution, diffusion phenomenon

Procedia PDF Downloads 161

Authors: Youhang Zhou, Weimin Zeng, Qi Xie

Abstract:

Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

Procedia PDF Downloads 519

Authors: Nikhil Kewalkrishna Mehta

Abstract:

In the past researchers have questioned the effectiveness of ethics training in higher education. Also, there are observations that support the view that ethical behaviour (range of actions)/ethical decision making models used in the past make use of vignettes to explain ethical behaviour. The understanding remains in the perspective that these vignettes play a limited role in determining individual intentions and not actions. Some authors have also agreed that there are possibilities of differences in one’s intentions and actions. This paper makes an attempt to fill those gaps by evaluating real actions rather than intentions. In a way this study suggests the use of an experiential methodology to explore Berlo’s model of communication as an action along with orchestration of various principles. To this endeavor, an attempt was made to use conversational analysis in the pursuance of evaluating ethical decision making behaviour among students and middle level managers. The process was repeated six times with the set of an average of 15 participants. Similarities have been observed in the behaviour of students and middle level managers that calls for understanding that both the groups of individuals have no cognizance of their actual actions. The deliberations derived out of conversation were taken a step forward for meta-ethical evaluations to portray a clear picture of ethical behaviour among participants. This study provides insights for understanding demonstrated unconscious human behaviour which may fortuitously be termed both ethical and unethical.

Keywords: ethical behaviour, unethical behavior, ethical decision making, intentions and actions, conversational analysis, human actions, sensitivity

Procedia PDF Downloads 249

Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

Procedia PDF Downloads 229

Authors: Ebrahim Alrashed

Abstract:

Wireless sensor networks are vulnerable to attacks from adversaries attempting to disrupt their operations. Sink-hole attacks are a type of attack where an adversary node drops data forwarded through it and hence affecting the reliability and accuracy of the network. Since sensor nodes have limited battery power, it is essential that any solution to the sinkhole attack problem be very energy-aware. In this paper, we present a reliable and energy efficient scheme to forward data from source nodes to the base station while under sink-hole attack. The scheme also detects sink-hole attack nodes and avoid paths that includes them.

Keywords: energy-aware routing, reliability, sink-hole attack, WSN

Procedia PDF Downloads 396

Authors: Abdelaziz Fellah, Allaoua Maamir

Abstract:

We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

Procedia PDF Downloads 387

Authors: S. H. Liao, J. M. Huang

Abstract:

The delivery service business model is the final link in logistics for both online-and-offline businesses. The online-and-offline business model focuses on the entire customer purchasing process online and offline, placing greater emphasis on the importance of data to optimize overall retail operations. For the retail industry, it is an important task of information and management to strengthen the collection and investigation of consumers' online and offline purchasing data to better understand customers and then recommend products. This study implements two-stage data mining analytics for clustering and association rules analysis to investigate Taiwanese consumers' (n=2,209) preferences for delivery service. This process clarifies online-and-offline purchasing behaviors and preferences to find knowledge profiles/patterns/rules for cross-channel collaborative recommendations. Finally, theoretical and practical implications for methodology and enterprise are presented.

Keywords: delivery service, online-and-offline purchasing, retail cross-channel, collaborative recommendations, data mining analytics

Procedia PDF Downloads 31

Authors: Xin Li, Ji-Yang Yu, Yue-Hua Niu, Lu-Yuan Wang

Abstract:

As an inevitable chain of the space data acquirement system, space-borne storage system based on Nand Flash has gradually been implemented in spacecraft. In face of massive, parallel and varied data on board, efficient data management become an important issue of storage research. Face to the requirements of high-performance and reliability in Nand Flash storage system, a combination of hardware and file system design can drastically increase system dependability, even for missions with a very long duration. More sophisticated flash storage concepts with advanced operating systems have been researched to improve the reliability of Nand Flash storage system on satellites. In this paper, architecture of file system with multi-channel data acquisition and storage on board is proposed, which obtains large-capacity and high-performance with the combine of intra-channel pipeline and device partition in Nand Flash. Multi-channel data in different rate are stored as independent files with parallel-storage system in device partition, which assures the high-effective and reliable throughput of file treatments. For massive and high-speed data storage, an efficiency assessment model is established to calculate the bandwidth formula of intra-channel pipeline. Information tables designed in Magnetoresistive RAM (MRAM) hold the management of bad block in Nand Flash and the arrangement of file system address for the high-reliability of data storage. During the full-load test, the throughput of 3D PLUS Module 160Gb Nand Flash can reach 120Mbps for store and reach 120Mbps for playback, which efficiently satisfies the requirement of multi-channel data acquisition in Satellite. Compared with previous literature, the results of experiments verify the advantages of the proposed system.

Keywords: device partition architecture, intra-channel pipelining, nand flash, parallel storage

Procedia PDF Downloads 289

Authors: Najmeh Abedzadeh, Matthew Jacobs

Abstract:

An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, imbalanced datasets, sampling algorithms, big data

Procedia PDF Downloads 328

Authors: Rajeev Kumar, Harishankar Kumar

Abstract:

Fragmented data silos within enterprises impede the extraction of meaningful insights and hinder efficiency in tasks such as product development, client understanding, and meeting preparation. To address this, we propose a system-agnostic framework that leverages large language models (LLMs) to unify diverse data sources into a cohesive, user-centered knowledge graph. By automating entity extraction, relationship inference, and semantic enrichment, the framework maps interactions, behaviors, and data around the user, enabling intelligent querying and reasoning across various data types, including emails, calendars, chats, documents, and logs. Its domain adaptability supports applications in contextual search, task prioritization, expertise identification, and personalized recommendations, all rooted in user-centric insights. Experimental results demonstrate its effectiveness in generating actionable insights, enhancing workflows such as trip planning, meeting preparation, and daily task management. This work advances the integration of knowledge graphs and LLMs, bridging the gap between fragmented data systems and intelligent, unified enterprise solutions focused on user interactions.

Keywords: knowledge graph, entity extraction, relation extraction, LLM, activity graph, enterprise intelligence

Procedia PDF Downloads 3

Authors: Anne-Margré C. Vink

Abstract:

Background: Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according to ‘Golden Standard’ of elimination efficiency are time-consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated. Method: As we developed Medisynx IgG Human Screening Test ELISA before and the dog’s immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this study, 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring the efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results: The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs(44 out of 47 dogs =93.6%). Conclusion: Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: allergy, canine atopic dermatitis, CAD, food allergens, IgG-ELISA, food-incompatibility

Procedia PDF Downloads 321

Authors: Pappas Theodoros, Mihail Diakomihalis

Abstract:

Measuring the economic impact of tourism in a benchmark economy is a global concern, with previous measurements being partial and not fully integrated. Tourism is a phenomenon that requires individual consumption of visitors and which should be observed and measured to reveal, thus, the overall contribution of tourism to an economy. The Tourism Satellite Account (TSA) is a critical tool for assessing the annual growth of tourism, providing reliable measurements. This article introduces a system of TSA information that encompasses all the works of the TSA, including input, storage, management, and analysis of data, as well as additional future functions and enhances the efficiency of tourism data management and TSA collection utility. The methodology and results presented offer insights into the development and implementation of TSA.

Keywords: tourism satellite account, information system, data-based tourist account, relation database

Procedia PDF Downloads 85

Authors: Fabiano Amorim Vaz, Camila Gonzaga de Araujo

Abstract:

With the growing number of personal devices such as smartphones, tablets, smart watches, among others, in addition to recent devices designed for IoT, it is observed that residential environment has potential to generate important information about our daily lives. Therefore, this work is focused on showing and evaluating a system that integrates all these technologies considering the context of a smart house. To achieve this, we define an architecture capable of supporting the amount of data generated and consumed at a residence and, mainly, the variety of this data presents. We organize it in a particular cloud containing information about robots, recreational vehicles, weather, in addition to data from the house, such as lighting, energy, security, among others. The proposed architecture can be extrapolated to various scenarios and applications. Through the core of this work, we can define new functionality for residences integrating them with more resources.

Keywords: cloud computing, IoT, robotics, smart house

Procedia PDF Downloads 381

Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

Abstract:

This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

Procedia PDF Downloads 397

Authors: Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Widjojo Suprapto

Abstract:

The ERP is integrating all data from various departments within the company into one data base. One department inputs the data and many other departments can access and use the data through the connected information system. As many manufacturing companies in Indonesia implement the ERP technology, many adjustments are to be made to align with the business process in the companies, especially the management policy and the competitive advantages. For companies that are successful in the initial implementation, they still have to maintain the process so that the initial success can develop along with the changing of business processes of the company. For companies which have already implemented the ERP successfully, they are still in need to maintain the system so that it can match up with the business development and changes. The continued success of the extended ERP implementation aims to achieve efficient and effective performance for the company. This research is distributing 100 questionnaires to manufacturing companies in East Java, Indonesia, which have implemented and have going live ERP for over five years. There are 90 returned questionnaires with ten disqualified questionnaires because they are from companies that implement ERP less than five years. There are only 80 questionnaires used as the data, with the response rate of 80%. Based on the data results and analysis with PLS (Partial Least Square), it is obtained that the organization commitment brings impacts to the user’s effectiveness and provides the adequate IT infrastructure. The user’s effectiveness brings impacts to the adequate IT infrastructure. The information quality of the company increases the implementation of the extended ERP in manufacturing companies in East Java, Indonesia.

Keywords: organization commitment, adequate IT infrastructure, information quality, extended ERP implementation

Procedia PDF Downloads 168

Authors: Khodzhaberdi Allaberdiev

Abstract:

Substituted phenols are widely used for the synthesis of advanced polycondensation polymers. In terms of the structure regularity and practical value of obtained polymers are of special interest the p-substituted phenols. The lanthanide induced shifts (LIS) of the aromatic ring and the OH protons by addition Eu(fod)3 to various p-substituted phenols in CDCL3 solvent were measured Nuclear Magnetic Resonance spectroscopy. A linear relationship has been observed between the LIS of protons (∆=δcomplex –δsubstrate) and Eu(fod)3/substrate molar ratios. The LIS protons of the investigated phenols decreases in the following order: ОН > ortho > meta. The LIS of these protons also depends on both steric and electronic effects of p-substituents. The effect on the LIS of protons steric hindrance of substituents by way of example p-substituted alkyl phenols was studied. Alkyl phenols exhibit pronounced europium- induced shifts, their sensitivity increasing in the order: CH3 > C2H5 > sym-C5H11 > tert-C5H11 > tert-C4H9, i.e. in parallel with decreasing steric hindrance. The influence steric hindrance p-substituents of phenols on the LIS of protons in sequence following decreases: OH> meta >ortho. Contrary to the expectations, it is found that the LIS of the ortho protons an excellent linear correlation with meta-substituent constants, σm for 14 p-substituted phenols: ∆H2, 6=8.165-9.896 σm (r2=0,999). Moreover, a linear correlation between the LIS of the ortho protons and ionization constants, РКa of p-substituted phenols has been revealed. Similarly, the linear relationships for the LIS of the meta and the OH protons were obtained. Use the LIS of the phenolic hydroxyl groups for linear relationships is necessary with care, because of the signal broadening of the OH protons. New constants may be determinate with unusual case by this approach.

Keywords: novel correlations, NMR spectroscopy, phenols, shift reagent

Procedia PDF Downloads 301

Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

Procedia PDF Downloads 105

Authors: Jay P. Sipani, Riki H. Patel, Trushit Upadhyaya

Abstract:

Today there is a demand to monitor environmental factors almost in all research institutes and industries and even for domestic uses. The analog data measurement requires manual effort to note readings, and there may be a possibility of human error. Such type of systems fails to provide and store precise values of parameters with high accuracy. Analog systems are having drawback of storage/memory. Therefore, there is a requirement of a smart system which is fully automated, accurate and capable enough to monitor all the environmental parameters with utmost possible accuracy. Besides, it should be cost-effective as well as portable too. This paper represents the Wireless Sensor (WS) data communication using DHT11, Arduino, SIM900A GSM module, a mobile device and Liquid Crystal Display (LCD). Experimental setup includes the heating arrangement of DHT11 and transmission of its data using Arduino and SIM900A GSM shield. The mobile device receives the data using Arduino, GSM shield and displays it on LCD too. Heating arrangement is used to heat and cool the temperature sensor to study its characteristics.

Keywords: wireless communication, Arduino, DHT11, LCD, SIM900A GSM module, mobile phone SMS

Procedia PDF Downloads 282

Authors: A. Venkatakrishnan, M. Juneja, S. Kapoor

Abstract:

Background: Gastrointestinal dysfunction is an emerging co morbidity seen in autism and may further strengthen the association between autism and celiac disease. This is supported by increased rates (22-70%) of gastrointestinal symptoms like diarrhea, constipation, abdominal discomfort/pain, and gastrointestinal inflammation in children with the etiology of autism is still elusive. In addition to genetic factors, environmental factors such as toxin exposure, intrauterine exposure to certain teratogenic drugs, are being proposed as possible contributing factors in the etiology of Autism Spectrum Disorders (ASD) in cognizance with reports of increased gut permeability and high rates of gastrointestinal symptoms noted in children with ASD, celiac disease has also been proposed as a possible etiological factor. Despite insufficient evidence regarding the benefit of restricted diets in Autism, GFD has been promoted as an alternative treatment for ASD. This study attempts to discern any correlation between ASD and celiac disease. Objective: This cross sectional study aims to determine the proportion of celiac disease in children with ASD. Methods: Study included 155 participants aged 2-12 yrs, diagnosed as ASD as per DSM-5 attending the child development center at a tertiary care hospital in Northern India. Those on gluten free diet or having other autoimmune conditions were excluded. A detailed Performa was filled which included sociodemographic details, history of gastrointestinal symptoms, anthropometry, systemic examination, and pertinent psychological testing was done using was assessed using Developmental Profile-3(DP-3) for Developmental Quotient, Childhood Autism Rating Scale-2 (CARS-2) for severity of ASD, Vineland Adaptive Behavior Scales (VABS) for adaptive behavior, Child Behavior Checklist (CBCL) for behavioral problems and BAMBI (Brief Autism Mealtime Behavior Scales) for feeding problems. Screening for celiac was done by TTG-IgA levels, and total serum IgA levels were measured to exclude IgA deficiency. Those with positive screen were further planned for HLA typing and endoscopic biopsy. Results: A total of 155 cases were included, out of which 5 had low IgA levels and were hence excluded from the study. The rest 150 children had TTG levels below the ULN and normal total serum IgA level. History of Gastrointestinal symptoms was present in 51 (34%) cases abdominal pain was the most frequent complaint (16.6%), followed by constipation (12.6%). Diarrhea was seen in 8 %. Gastrointestinal symptoms were significantly more common in children with ASD above 5 yrs (p-value 0.006) and those who were verbal (p = 0.000). There was no significant association between socio-demographic factors, anthropometric data, or severity of autism with gastrointestinal symptoms. Conclusion: None of the150 patients with ASD had raised TTG levels; hence no association was found between ASD and celiac disease. There is no justification for routine screening for celiac disease in children with ASD. Further studies are warranted to evaluate association of Non Celiac Gluten Sensitivity with ASD and any role of gluten-free diet in such patients.

Keywords: autism, celiac, gastrointestinal, gluten

Procedia PDF Downloads 120

Authors: Nguyen Lan, Le Tan Kien, Nguyen Pham Gia Bao

Abstract:

The cable-stayed bridge belongs to the combined system, in which the cables is a major strutual element. Cable-stayed bridges with large spans are often arranged with structural health monitoring systems to collect data for bridge health diagnosis. Cables tension monitoring is a structural monitoring content. It is common to measure cable tension by a direct force sensor or cable vibration accelerometer sensor, thereby inferring the indirect cable tension through the cable vibration frequency. To translate cable-stayed vibration acceleration data to real-time tension requires some necessary calculations and programming. This paper introduces the algorithm, labview program that converts cable-stayed vibration acceleration data to real-time tension. The research results are applied to the monitoring system of Tran Thi Ly cable-stayed bridge and Song Hieu cable-stayed bridge in Vietnam.

Keywords: cable-stayed bridge, cable fore, structural heath monitoring (SHM), fast fourie transformed (FFT), real time, vibrations

Procedia PDF Downloads 71

Authors: Bin Su

Abstract:

This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.

Keywords: building energy efficiency, building thermal design, building thermal performance, school building design

Procedia PDF Downloads 444

Authors: Panwasn Mahalawalert

Abstract:

The objective of this study was to meta-evaluation of Master Degree theses in Science Program of Evaluation Methodology at Srinakharinwirot University, published during 2008-2011. This study was summative meta-evaluation that evaluated all theses of Master Degree in Science Program of Evaluation Methodology. Data were collected using the theses characteristics recording form and the evaluation meta-evaluation checklist. The collected data were analyzed by two parts: 1) Quantitative data were analyzed by descriptive statistics presented in frequency, percentages, mean, and standard deviation and 2) Qualitative data were analyzed by content analysis. The results of this study were found the theses characteristics was results revealed that most of theses were published in 2011. The largest group of theses researcher were female and were from the government office. The evaluation model of all theses were Decision-Oriented Evaluation Model. The objective of all theses were evaluate the project or curriculum. The most sampling technique were used the multistage random sampling technique. The most tool were used to gathering the data were questionnaires. All of the theses were analysed by descriptive statistics. The meta-evaluation results revealed that most of theses had fair on Utility Standards and Feasibility Standards, good on Propriety Standards and Accuracy Standards.

Keywords: meta-evaluation, evaluation, master degree theses, Srinakharinwirot University

Procedia PDF Downloads 536

Authors: Yunfeng Shan, Xiaoliang Wang, Youjun Zhou

Abstract:

Whole-genome data from two lungfish species, along with other species, present a valuable opportunity to re-investigate the longstanding debate regarding the evolutionary relationships among tetrapods, lungfishes, and coelacanths. However, the use of bootstrap support has become outdated for large-scale phylogenomic data. Without robust phylogenetic support, the phylogenetic trees become meaningless. Therefore, it is necessary to re-evaluate the phylogenies of tetrapods, lungfishes, and coelacanths using novel measures of phylogenetic support specifically designed for phylogenomic data, as the previous phylogenies were based on 100% bootstrap support. Our findings consistently provide strong evidence favoring lungfish as the closest living relative of tetrapods. This conclusion is based on high internode certainty, relative gene support, and high gene concordance factor. The evidence stems from five previous datasets derived from lungfish transcriptomes. These results yield fresh insights into the three hypotheses regarding the phylogenies of tetrapods, lungfishes, and coelacanths. Importantly, these hypotheses are not mere conjectures but are substantiated by a significant number of genes. Analyzing real biological data further demonstrates that the inclusion of additional taxa leads to more diverse tree topologies. Consequently, gene trees and species trees may not be identical even when whole-genome sequencing data is utilized. However, it is worth noting that many gene trees can accurately reflect the species tree if an appropriate number of taxa, typically ranging from six to ten, are sampled. Therefore, it is crucial to carefully select the number of taxa and an appropriate outgroup, such as slow-evolving species, while excluding fast-evolving taxa as outgroups to mitigate the adverse effects of long-branch attraction and achieve an accurate reconstruction of the species tree. This is particularly important as more whole-genome sequencing data becomes available.

Keywords: novel measures of phylogenetic support for phylogenomic data, gene concordance factor confidence, relative gene support, internode certainty, origin of tetrapods

Procedia PDF Downloads 60

Authors: Shreya Goyal

Abstract:

The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

Procedia PDF Downloads 65