Search results for: calibration data requirements

Authors: Ahmed Barakat, Nourhan Ahmed Saad, Mahmoud Hammad

Abstract:

Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: agriculture sector, cold chain management, export companies, non-traded goods, supply chain management

Procedia PDF Downloads 138

Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

Abstract:

The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

Procedia PDF Downloads 57

Authors: A. Sathiya Susuman, Hamisi F. Hamisi

Abstract:

Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

Procedia PDF Downloads 460

Authors: Alfonso Sepulveda, Brecht Put, Nouha Labyedh, Philippe M. Vereecken

Abstract:

High energy and power density are the main requirements of today’s high demanding applications in consumer electronics. Lithium ion batteries (LIB) have the highest energy density of all known systems and are thus the best choice for rechargeable micro-batteries. Liquid electrolyte LIBs present limitations in safety, size and design, thus thin film all-solid state batteries are predominantly considered to overcome these restrictions in small devices. Although planar all-solid state thin film LIBs are at present commercially available they have low capacity (<1mAh/cm2) which limits their application scenario. By using micro-or nanostructured surfaces (i.e. 3D batteries) and appropriate conformal coating technology (i.e. electrochemical deposition, ALD) the capacity can be increased while still keeping a high rate performance. The main challenges in the introduction of solid-state LIBs are low ionic conductance and limited cycle life time due to mechanical stress and shearing interfaces. Novel materials and innovative nanostructures have to be explored in order to overcome these limitations. Thin film 3D compatible materials need to provide with the necessary requirements for functional and viable thin-film stacks. Thin film electrodes offer shorter Li-diffusion paths and high gravimetric and volumetric energy densities which allow them to be used at ultra-fast charging rates while keeping their complete capacities. Thin film electrolytes with intrinsically high ion conductivity (~10-3 S.cm) do exist, but are not electrochemically stable. On the other hand, electronically insulating electrolytes with a large electrochemical window and good chemical stability are known, but typically have intrinsically low ionic conductivities (<10-6 S cm). In addition, there is the need for conformal deposition techniques which can offer pinhole-free coverage over large surface areas with large aspect ratio features for electrode, electrolyte and buffer layers. To tackle the scaling of electrodes and the conformal deposition requirements on future 3D batteries we study LiMn2O4 (LMO) and Li4Ti5O12 (LTO). These materials are among the most interesting electrode candidates for thin film batteries offering low cost, low toxicity, high voltage and high capacity. LMO and LTO are considered 3D compatible materials since they can be prepared through conformal deposition techniques. Here, we show the scaling effects on rate performance and cycle stability of thin film cathode layers of LMO created by RF-sputtering. Planar LMO thin films below 100 nm have been electrochemically characterized. The thinnest films show the highest volumetric capacity and the best cycling stability. The increased stability of the films below 50 nm allows cycling in both the 4 and 3V potential region, resulting in a high volumetric capacity of 1.2Ah/cm3. Also, the creation of LTO anode layers through a post-lithiation process of TiO2 is demonstrated here. Planar LTO thin films below 100 nm have been electrochemically characterized. A 70 nm film retains 85% of its original capacity after 100 (dis)charging cycles at 10C. These layers can be implemented into a high aspect ratio structures. IMEC develops high aspect Si pillars arrays which is the base for the advance of 3D thin film all-solid state batteries of future technologies.

Keywords: Li-ion rechargeable batteries, thin film, nanostructures, rate performance, 3D batteries, all-solid state

Procedia PDF Downloads 323

Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove

Abstract:

Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.

Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor

Procedia PDF Downloads 57

Authors: Sandra Christina Gressler

Abstract:

Resting is essentially the physical and mental relaxation. So, can behaviors that go beyond the merely physical relaxation to some extent be understood as a behavior of restoration? Studies on restorative environments emphasize the physical, mental and social benefits that some environments can provide and suggest that activities in natural environments reduce the stress of daily lives, promoting recovery against the daily wear. These studies, though specific in their results, do not unify the different possibilities of restoration. Considering the importance of restorative environments by promoting well-being, this research aims to verify the applicability of the theory on restorative environments in a Brazilian context, inquiring about the environment/behavior of rest. The research sought to achieve its goals by; a) identifying daily ways of how participants interact/connect with nature; b) identifying the resting environments/behavior; c) verifying if rest strategies match the restorative environments suggested by restorative studies; and d) verifying different rest strategies related to time. Workers from different companies in which certain functions require focused attention, and high school students from different schools, participated in this study. An interview was used to collect data and information. The data obtained were compared with studies of attention restoration theory and stress recovery. The collected data were analyzed through the basic descriptive inductive statistics and the use of the software ALCESTE® (Analyse Lexicale par Contexte d'un Ensemble de Segments de Texte). The open questions investigate perception of nature on a daily basis – analysis using ALCESTE; rest periods – daily, weekends and holidays – analysis using ALCESTE with tri-croisé; and resting environments and activities – analysis using a simple descriptive statistics. According to the results, environments with natural characteristics that are compatible with personal desires (physical aspects and distance) and residential environments when they fulfill the characteristics of refuge, safety, and self-expression, characteristics of primary territory, meet the requirements of restoration. Analyzes suggest that the perception of nature has a wide range that goes beyond the objects nearby and possible to be touched, as well as observation and contemplation of details. The restoration processes described in the studies of attention restoration theory occur gradually (hierarchically), starting with being away, following compatibility, fascination, and extent. They are also associated with the time that is available for rest. The relation between rest behaviors and the bio-demographic characteristics of the participants are noted. It reinforces, in studies of restoration, the need to insert not only investigations regarding the physical characteristics of the environment but also behavior, social relationship, subjective reactions, distance and time available. The complexity of the theme indicates the necessity for multimethod studies. Practical contributions provide subsidies for developing strategies to promote the welfare of the population.

Keywords: attention restoration theory, environmental psychology, rest behavior, restorative environments

Procedia PDF Downloads 168

Authors: Shweh Fern Loo, Jun Yin Ong, Than Zaw Oo

Abstract:

Acute respiratory distress syndrome (ARDS) is a common serious condition of bilateral lung infiltrates that develops secondary to various underlying conditions such as diseases or injuries. ARDS with severe hypercapnia is associated with higher ICU mortality and morbidity. Venovenous Extracorporeal membrane oxygenation (VV-ECMO) support has been established to avert life-threatening hypoxemia and hypercapnic respiratory failure despite optimal conventional mechanical ventilation. However, VV-ECMO is relatively not advisable in particular groups of patients, especially in multi-organ failure, advanced age, hemorrhagic complications and irreversible central nervous system pathology. We presented a case of a 79-year-old Chinese lady without any pre-existing lung disease admitted to our hospital intensive care unit (ICU) after acute presentation of breathlessness and chest pain. After extensive workup, she was diagnosed with rapidly progressing acute interstitial pneumonia with ARDS and hypercapnia respiratory failure. The patient received lung protective strategies of mechanical ventilation and neuromuscular blockage therapy as per clinical guidelines. However, hypercapnia respiratory failure was refractory, and she was deemed not a good candidate for VV-ECMO support given her advanced age and high vasopressor requirements from shock. Alternative therapy with extracorporeal CO2 removal (ECCO2R) was considered and implemented. The patient received 12 days of ECCO2R paired with muscle paralysis, optimization of lung-protective mechanical ventilation and dialysis. Unfortunately, the patient still had refractory hypercapnic respiratory failure with dual vasopressor support despite prolonged therapy. Given failed and futile medical treatment, the family opted for withdrawal of care, a conservative approach, and comfort care, which led to her demise. The effectivity of extracorporeal CO2 removal may depend on disease burden, involvement and severity of the disease. There is insufficient data to make strong recommendations about its benefit-risk ratio for ECCO2R devices, and further studies and data would be required. Nonetheless, ECCO2R can be considered an alternative treatment for refractory hypercapnic respiratory failure patients who are unsuitable for initiating venovenous ECMO.

Keywords: extracorporeal CO2 removal (ECCO2R), acute respiratory distress syndrome (ARDS), acute interstitial pneumonia (AIP), hypercapnic respiratory failure

Procedia PDF Downloads 48

Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

Abstract:

This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

Procedia PDF Downloads 413

Authors: Eirini Petratou, Pezirkianidis Christos, Anastassios Stalikas

Abstract:

Nostalgia is characterized as a mental state of human’s emotional longing for the past that activates both positive and negative emotions. The bittersweet emotions that are activated by nostalgia aid psychological functions to humans and are depended on the type of stimuli that evoke nostalgia but also on the nostalgia activation context. In general, despite that nostalgia can be activated and experienced by all people; however, it differs both in terms of nostalgia experience but also nostalgia frequency. As a matter of fact, nostalgia experience along with nostalgia frequency differs according to the level of the nostalgia proneness. People with high nostalgia proneness tend to experience nostalgia more intensely and frequently than people with low nostalgia proneness. Nostalgia proneness is considered as a basic individual difference that affects the experience of nostalgia, and it can be measured by the Southampton Nostalgia Scale (SNS); a psychometric instrument that measures human’s nostalgia proneness consisting of seven questions that assess a person’s attitude towards nostalgia, the degree of experience or tendency to nostalgic feelings and the nostalgia frequency. In the current study, we translated, validated and calibrated the SNS in Greek population (N = 267). For the calibration process, we used several scales relevant to positive dimensions, such as life satisfaction, positive and negative emotions, time perspective and wellbeing. A confirmatory factor analysis revealed the factors that provide a good Southampton Nostalgia Proneness model fit for young adult Greek population.

Keywords: nostalgia proneness, nostalgia, psychometric instruments, psychometric properties

Procedia PDF Downloads 135

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

Procedia PDF Downloads 48

Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

Abstract:

Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

Procedia PDF Downloads 498

Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

Abstract:

In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

Procedia PDF Downloads 92

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

Procedia PDF Downloads 317

Authors: Tanapat Chongkamunkong

Abstract:

The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

Procedia PDF Downloads 180

Authors: Vinod Kumar Jaysaval, Prateek Agarwal

Abstract:

Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

Procedia PDF Downloads 454

Authors: Young Gil Kim, Hye Min Park, Chan Jong Park, Koan Sik Joo

Abstract:

A personal gamma spectrometer has to be sensitive, pocket-sized, and carriable on the users. To serve these requirements, we developed the SiPM-based portable radiation detectors. The prototype uses a Ce:GAGG scintillator coupled to a silicon photomultiplier and a radio frequency(RF) module to measure gamma-ray, and can be accessed wirelessly or remotely by mobile equipment. The prototype device consumes roughly 4.4W, weighs about 180g (including battery), and measures 5.0 7.0. It is able to achieve 5.8% FWHM energy resolution at 662keV.

Keywords: Ce:GAGG, gamma-ray, radio frequency, silicon photomultiplier

Procedia PDF Downloads 313

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

Procedia PDF Downloads 194

Authors: M. R. Akshaya, Veena Rao

Abstract:

Pet population in India is increasing phenomenally owing to the changes in urban lifestyle with increasing number of single professionals, single parents, delayed parenthood etc. The animal companionship as a means of reducing stress levels, deriving emotional support, and unconditional love provided by dogs are a few reasons attributed for increasing pet ownership. The consequence is the booming of the pet care products and dog care centers catering to the different requirements of rearing the pets. Dog care centers quite popular in tier 1 metros of India cater to the requirement of the dog owners providing space for the dogs in absence of the owner. However, it is often reported that the absence of the owner leads to destructive and exploratory behavior issues; the main being the anxiety disorders. In the above context, it becomes imperative for a designer to design dog boarding centers that help in reducing the separation anxiety in dogs keeping in mind the different interior design parameters. An exploratory research with focus group discussion is employed involving a group of dog owners, behaviorists, proprietors of day care as well as boarding centers, and veterinarians to understand their perception on the significance of different interior parameters of color, texture, ventilation, aroma therapy and acoustics as a means of reducing the stress levels in dogs sent to the boarding centers. The data collected is organized as thematic networks thus enabling the listing of the interior design parameters that needs to be considered in designing dog boarding centers. 

Keywords: behavioral response, design parameters, dog boarding centers, interior environment

Procedia PDF Downloads 186

Authors: Pan Hongxia, Wang Zhenhua

Abstract:

In this paper, the EMD decomposition in the process of endpoint effect adopted data based on AR model to predict the continuation and window function method of combining the two effective inhibition. Proven by simulation of the simulation signal obtained the ideal effect, then, apply this method to the gearbox test data is also achieved good effect in the process, for the analysis of the subsequent data processing to improve the calculation accuracy. In the end, under various working conditions for the gearbox fault diagnosis laid a good foundation.

Keywords: gearbox, fault diagnosis, ar model, end effect

Procedia PDF Downloads 353

Authors: Maria Jędrzejczak, Patryk Pieniążek

Abstract:

The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

Procedia PDF Downloads 46

Authors: Handie Pramana Putra, Ani Dijah Rahajoe

Abstract:

The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

Procedia PDF Downloads 38

Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

Procedia PDF Downloads 392

Authors: Amal Mohammed Alqahatni

Abstract:

This paper is a non-empirical analysis of existing literature on digital leadership competency, data-driven organizations, and dealing with AI technology (big data). This paper will provide insights into the importance of developing the leader’s analytical skills and style to be more effective for high-quality decision-making in a data-driven organization and achieve creativity during the organization's transformation to be digitalized. Despite the enormous potential that big data has, there are not enough experts in the field. Many organizations faced an issue with leadership style, which was considered an obstacle to organizational improvement. It investigates the obstacles to leadership style in this context and the challenges leaders face in coaching and development. The leader's lack of analytical skill with AI technology, such as big data tools, was noticed, as was the lack of understanding of the value of that data, resulting in poor communication with others, especially in meetings when the decision should be made. By acknowledging the different dynamics of work competency and organizational structure and culture, organizations can make the necessary adjustments to best support their leaders. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how analytical leadership will assist in overcoming challenges in a data-driven organization's work environment.

Keywords: digital leadership, big data, leadership style, digital leadership challenge

Procedia PDF Downloads 52

Authors: Chaitanya Varma, Arpan Mehar

Abstract:

The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

Procedia PDF Downloads 452

Authors: Adel H. Hejaaji

Abstract:

The need for organisations to be flexible to meet the rapidly changing requirements of their customers is now well appreciated and can be witnessed within companies with their use of techniques such as single-minute exchange of die (SMED) for machine change-over or Kanban as the visual production and inventory control for Just-in-time manufacture and delivery. What is not so well appreciated by companies is the need for agility. Put simply it is the need to be alert for a new and unexpected opportunity and quick to respond with the changes necessary in order to profit from it. This paper aims to study the literature of agility in manufacturing to understand the concept of agility and how it is important and critical for the small and medium size manufacturing organisations (SMEs), and to defined the specific benefits of moving towards agility, and thus what benefit it can bring to an organisation.

Keywords: SMEs, agile manufacturing, manufacturing, industrial engineering

Procedia PDF Downloads 591

Authors: Thi Phuong Lan Nguyen

Abstract:

Alongside technical skills, the employability is crucial for any graduates in the fast-evolving 21st century. It is reported that 78% of Australian students believe soft skills give advantages in the changing workforce due to technological automation (Oxford, 2020), which motivated to investigate how students whose English as a foreign or second language (EFL/ESL) are ready for the employability requirements in the new normal. Literature review, document analysis, and Interviews with EFL teachers are used in this research. The results of this research are helpful in preparing international EFL/ESL students to achieve the best preparation for currently increasing demanding employment markets, which are also meaningful for students themselves to be ready of being global citizens in the new normal.

Keywords: readiness, employability, EFL, ESL

Procedia PDF Downloads 14

Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang

Abstract:

Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.

Keywords: human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing

Procedia PDF Downloads 649

Authors: Nishiyama Toshiaki, Tadayuki Kyountani, Nguyen Huu Phuc, Shigeyuki Haruyama, Oke Oktavianty

Abstract:

It is important to clarify the company’s core technology in product development process to strengthen their power in providing technology that meets the customer requirement. QFD method is adopted to clarify the core technology through identifying the high element technologies that are related to the voice of customer, and offer the most delightful features for customer. AHP is used to determine the importance of evaluating factors. A case study was conducted by using this approach in Japan’s Monozukuri Company (so called manufacturing company) to clarify their core technology based on customer requirements.

Keywords: core technology, QFD, voices of customer, analysis procedure

Procedia PDF Downloads 369

Authors: Ade Dwi Utami

Abstract:

Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

Procedia PDF Downloads 238

Authors: S. S. Dol

Abstract:

Improvement in vehicle efficiency can reduce global fossil fuels consumptions. For that sole reason, Shell Global Corporation introduces Shell Eco-marathon where student teams require to design, build and test energy-efficient vehicles. Hence, this paper will focus on design processes and the development of a fuel economic vehicle which satisfying the requirements of the competition. In this project, three components are designed and analyzed, which are the body, chassis and powertrain of the vehicle. Optimum design for each component is produced through simulation analysis and theoretical calculation in which improvement is made as the project progresses.

Keywords: energy efficient, drag force, chassis, powertrain

Procedia PDF Downloads 314