Search results for: secure data aggregation

Authors: Baris Can Yalcin

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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

Procedia PDF Downloads 588

Authors: Shalini Saini, Sharmila Ahuja

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Anaesthesia for caesarean section poses challenges unique to the obstetric patient due to changes in the airway and respiratory system. The choice of anaesthesia for caesarean section depends on various factors however general anaesthesia (GA) is necessary for certain situations. Supraglottic airway devices are an emerging method to secure airway, especially in difficult situations. Of these devices, proseal –LMA (PLMA) is designed to provide better protection of the airway. The use of PLMA has been reported successfully as a rescue device in difficult intubation situations and in patients undergoing elective caesarean section without any complications. The study was prospective and randomised and was designed to compare PLMA in patients undergoing elective lower segment caesarean section (LSCS) with the endotracheal tube (ETT). Patients undergoing LSCS under GA belonging to ASA grade 1 and 2 were included. Patients with the history of fewer than 6 hrs of fasting, known/predicted difficult airway, obesity, gastroesophageal reflux disease, hypertensive disorder were excluded. A standard anaesthesia protocol was followed. All patients received aspiration prophylaxis. The airway was secured with either PLMA or ETT. Parameters noted were- ease of insertion, adequacy of ventilation, hemodynamic changes at insertion and removal of device, incidence of regurgitation and aspiration. Data was analysed by unpaired t- test, Chi-square /Fisher’s test. The findings of our study indicated that PLMA was easy to insert (20.67±6.835 sec) with comparable insertion time to TT (18.33 ± 4.971, p 0.136) and adequate ventilation was achieved with very minimal hemodynamic changes seen with PLMA as compared to ETT at insertion and removal of devices (p 0.01). There was no incidence of regurgitation with the use of PLMA. The incidence of a postoperative sore throat was minimal (6.7%) with PLMA (p<0.05). PLMA appears to be a safe alternative to ETT for selected obstetric patients undergoing elective LSCS. Further study with a larger group of patients is required to establish the safety of PLMA in obstetric patients.

Keywords: caesarean section, general anaesthesia, proseal LMA, endotracheal tube

Procedia PDF Downloads 374

Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

Procedia PDF Downloads 423

Authors: Ming Wei

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Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

Procedia PDF Downloads 286

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Yiyang Su, Jörg Neumann, Jan Wetzlich, Florian Thiel

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Smart grid is a term used to describe the next generation power grid. New challenges such as integration of renewable and decentralized energy sources, the requirement for continuous grid estimation and optimization, as well as the use of two-way flows of energy have been brought to the power gird. In order to achieve efficient, reliable, sustainable, as well as secure delivery of electric power more and more information and communication technologies are used for the monitoring and the control of power grids. Consequently, the need for cybersecurity is dramatically increased and has converged into several standards which will be presented here. These standards for the smart grid must be designed to satisfy both performance and reliability requirements. An in depth investigation of the effect of retrospectively embedded security in existing grids on it’s dynamic behavior is required. Therefore, a retrofitting plan for existing meters is offered, and it’s performance in a test low voltage microgrid is investigated. As a result of this, integration of security measures into measurement architectures of smart grids at the design phase is strongly recommended.

Keywords: cyber security, performance, protocols, security standards, smart grid

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Authors: Mehrab Masayeed Habib, Tasneem Sanjana, Ahmed Amin Rumel

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Automated car anti-collision system is a trending technology of science. A car anti-collision system is an automobile safety system. The aim of this paper was to describe designing a car anti-collision system device to reduce the severity of an accident. The purpose of this device is to prevent collision among cars and objects to reduce the accidental death of human. This project gives an overview of secure & smooth journey of car as well as the certainty of human life. This system is controlled by microcontroller PIC. Sharp distance sensor is used to detect any object within the danger range. A crystal oscillator is used to produce the oscillation and generates the clock pulse of the microcontroller. An LCD is used to give information about the safe distance and a buzzer is used as alarm. An actuator is used as automatic break and inside the actuator; there is a motor driver that runs the actuator. For coding ‘microC PRO for PIC’ was used and ’Proteus Design Suite version 8 Software’ was used for simulation.

Keywords: sharp distance sensor, microcontroller, MicroC PRO for PIC, proteus, actuator, automobile anti-collision system

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Authors: Ali Essam El Shazly

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The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

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Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Jürgen Fleischer, Woramon Pangboonyanon, Dominic Lesage

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Non-metallic lightweight materials such as fiber reinforced plastics (FRP) become very significant at present. Prepregs e.g. SMC and unidirectional tape (UD-tape) are one of raw materials used to produce FRP. This study concerns with the manufacturing steps of handling and preforming of this UD-SMC and focuses on the investigation of gripper characteristics regarding gripping forces in normal and lateral direction, in order to identify suitable operating pressures for a secure gripping operation. A reliable handling and preforming operation results in a higher adding value of the overall process chain. As a result, the suitable operating pressures depending on travelling direction for each material type could be shown. Moreover, system boundary conditions regarding allowable pulling force in normal and lateral directions during preforming could be measured.

Keywords: continuous-discontinuous fiber reinforced plastics, UD-SMC-prepreg, handling, preforming, prepregs, sheet moulding compounds, surface suction gripper

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Authors: Maryam Aloshan, Imam Mohammad Ibn Saud, Ahmad Khudair

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This study assesses the data governance maturity of nonprofit organizations in Riyadh, Saudi Arabia, using the National Data Maturity Index (NDI) framework developed by the Saudi Data and Artificial Intelligence Authority (SDAIA). Employing a survey designed around the NDI model, data maturity levels were evaluated across 14 dimensions using a 5-point Likert scale. The results reveal a spectrum of maturity levels among the organizations surveyed: while some medium-sized associations reached the ‘Defined’ stage, others, including large associations, fell within the ‘Absence of Capabilities’ or ‘Building’ phases, with no organizations achieving the advanced ‘Established’ or ‘Pioneering’ levels. This variation suggests an emerging recognition of data governance but underscores the need for targeted interventions to bridge the maturity gap. The findings point to a significant opportunity to elevate data governance capabilities in Saudi nonprofits through customized capacity-building initiatives, including training, mentorship, and best practice sharing. This study contributes valuable insights into the digital transformation journey of the Saudi nonprofit sector, aligning with national goals for data-driven governance and organizational efficiency.

Keywords: nonprofit organizations-national data maturity index (NDI), Saudi Arabia- SDAIA, data governance, data maturity

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 307

Authors: S. Bahrami, A. Rezaie, Z. Boroumand, S. Ghavami

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Neospora caninum is protozoan parasite which can cause a serious disease in dogs and cattle. It has been shown that birds may be a permissive intermediate host for N. caninum since parasite DNA has been detected in tissues from birds. It is showed that embryonated chicken egg can be used as an animal model for experimental infection. The aim of present study was to compare experimental infection of Neospora in chicken and pigeons embryonated eggs. An infection with N. caninum Nc1 isolate was conducted in chicken and pigeons embryonated eggs to evaluate LD50. After calculation of LD50, 2LD50 of tachyzoites were injected to eggs. Macroscopic changes of each embryo were noticed and to investigate the parasite distribution in tissues immunohistochemistry (IHC) and molecular methods were used. In the present study, histopathological changes were considered and sections to those used for histopathological examination including heart, liver, brain and chorioallantoic (CA) membrane were subjected to IHC, too. For PCR procedure, primer pair Np21/Np6 was used for amplification of the Nc5 gene. Pigeon's embryo showed more macroscopic changes than chicken embryo. A hemorrhage of the CA was the main grass lesion. All the infected tissues had histopathological changes. Microscopic examination of tissues revealed acute neosporosis due to hemorrhage, necrosis and infiltration of mononuclear inflammatory cells. Based on IHC and molecular results, the parasite aggregation in the heart was more predominant than in the other tissues. These results reinforce that there is genetic susceptibility to N. caninum in pigeons embryonated eggs like chickens embryonated eggs and provide new insights to research an inexpensive and available animal model for N. caninum.

Keywords: immunohistochemistry, Neospora caninum, PCR, pigeon embryonated egg

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Authors: Boguslaw Schreyer

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The paper investigates the application of the Kohonen’s Self-Organizing Map (SOM) to the wheeled robot starting and braking dynamic states. In securing wheeled robot stability as well as minimum starting and braking time, it is important to ensure correct torque distribution as well as proper slope of braking and driving moments. In this paper, a correct movement distribution has been formulated, securing optimum adhesion coefficient and good transversal stability of a wheeled robot. A neural tuner has been proposed to secure the above properties, although most of the attention is attached to the SOM network application. If the delay of the torque application or torque release is not negligible, it is important to change the rising and falling slopes of the torque. The road/surface condition is also paramount in robot dynamic states control. As the road conditions may randomly change in time, application of the SOM network has been suggested in order to classify the actual road conditions.

Keywords: slip control, SOM network, torque distribution, wheeled Robot

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Authors: Maruf Farhan, Abdul Salih, Sikandar Ali Tahir

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Protecting patient information's confidentiality is paramount considering the widespread use of Internet of Things (IoT) gadgets in medical settings. This study's subjects are decentralized identifiers (DIDs) and verifiable credentials (VCs) in conjunction with an OAuth-based authorization framework, as they are the key to protecting IoT healthcare devices. DIDs enable autonomous authentication and trust formation between IoT devices and other entities. To authorize users and enforce access controls based on verified claims, VCs offer a secure and adaptable solution. Through the proposed method, medical facilities can improve the privacy and security of their IoT devices while streamlining access control administration. A Smart pill dispenser in a hospital setting is used to illustrate the advantages of this method. The findings demonstrate the value of DIDs, VCs, and OAuth-based delegation in protecting the IoT devices. Improved processes for authorizing and controlling access to IoT devices are possible thanks to the research findings, which also help ensure patient confidentiality in the healthcare sector.

Keywords: Iot, DID, authorization, verifiable credentials

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Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Mohd Sidek Ahmad, Zainon Mohd Noor, Zaidah Zainal Ariffin

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Fibrin degradation is an important part in prevention or treatment of intravascular thrombosis and cardiovascular diseases. Plasmin like fibrinolytic enzymes has given new hope to patient with cardiovascular diseases by treating fibrin aggregation related diseases with traditional plasminogen activator which have many side effects. Various researches involving wide range of sources for production of fibrinolytic proteases, from bacteria, fungi, insects and fermented foods. But few have looked into endophytic fungi as a potential source. Sixteen (16) endophytic fungi were isolated from Hibiscus sp. leaves from six different locations in Shah Alam, Selangor. Only two endophytic fungi, FH3 and S13 showed positive fibrinolytic protease activities. FH3 produced 5.78cm and S13 produced 4.48cm on Skim Milk Agar after 4 days of incubation at 27°C. Fibrinolytic activity was observed; 3.87cm and 1.82cm diameter clear zone on fibrin plate of FH3 and S13 respectively. 18srRNA was done for identification of the isolated fungi with positive fibrinolytic protease. S13 had the highest similarity (100%) to that of Penicillium citrinum strain TG2 and FH3 had the highest similarity (99%) to that of Fusarium sp. FW2PhC1, Fusarium sp. 13002, Fusarium sp. 08006, Fusarium equiseti strain Salicorn 8 and Fungal sp. FCASAn-2. Media composition variation showed the effects of carbon nitrogen on protein concentration, where the decrement of 50% of media composition caused drastic decrease in protease of FH3 from 1.081 to 0.056 and also S13 from 2.946 to 0.198.

Keywords: isolation, identification, fibrinolytic protease, endophytic fungi, Hibiscus leaves

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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Authors: Dicky R. Munaf, Ayu Bulan Tisna

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Competitive intelligence (business intelligence) is the process of observing the external environment which often conducted by many organizations to get the relevant information which will be used to create the organization policy, whereas, security intelligence is related to the function of the officers who have the duties to protect the country and its people from every criminal actions that might harm the national and individual security. Therefore, the intelligence dimension of maritime security is associated with all the intelligence activities including the subject and the object that connected to the maritime issues. The concept of intelligence business regarding the maritime security perspective is the efforts to protect the maritime security using the analysis of economic movements as the basic strategic plan. Clearly, a weak maritime security will cause high operational cost to all the economic activities which uses the sea as its media. Thus, it affects the competitiveness of a country compared to the other countries that are able to maintain the maritime law enforcement and secure their marine territory. So, the intelligence business within the security intelligence is important to conduct as the beginning process of the identification against the opponent strategy that might happen in the present or in the future. Thereby, the scenario of the potential impact of all the illegal maritime activities, as well as the strategy in preventing the opponent maneuver can be made.

Keywords: competitive intelligence, maritime security intelligence, intelligent systems, information technology

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Rainner Roweder

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Theme: The present paper aims to analyze the specificity of the judicial evidence linked to the subjects of dignity and personality rights, otherwise known as moral rights, in the determination of the truth and formation of the judicial reasoning in cases concerning these areas. This research is about the way courts in Brazilian domestic law search for truth and handles evidence in cases involving moral rights that are abundant and important in Brazil. The main object of the paper is to analyze the effectiveness of the evidence in the formation of judicial conviction in matters related to morally controverted rights, based on the Brazilian, and as a comparison, the Latin American legal systems. In short, the rights of dignity and personality are moral. However, the evidential legal system expects a rational demonstration of moral rights that generate judicial conviction or persuasion. Moral, in turn, tends to be difficult or impossible to demonstrate in court, generating the problem considered in this paper, that is, the study of the moral demonstration problem as proof in court. In this sense, the more linked to moral, the more difficult to be demonstrated in court that right is, expanding the field of judicial discretion, generating legal uncertainty. More specifically, the new personality rights, such as gender, and their possibility of alteration, further amplify the problem being essentially an intimate manner, which does not exist in the objective, rational evidential system, as normally occurs in other categories, such as contracts. Therefore, evidencing this legal category in court, with the level of security required by the law, is a herculean task. It becomes virtually impossible to use the same evidentiary system when judging the rights researched here; therefore, it generates the need for a new design of the evidential task regarding the rights of the personality, a central effort of the present paper. Methodology: Concerning the methodology, the Method used in the Investigation phase was Inductive, with the use of the comparative law method; in the data treatment phase, the Inductive Method was also used. Doctrine, Legislative, and jurisprudential comparison was the technique research used. Results: In addition to the peculiar characteristics of personality rights that are not found in other rights, part of them are essentially linked to morale and are not objectively verifiable by design, and it is necessary to use specific argumentative theories for their secure confirmation, such as interdisciplinary support. The traditional pragmatic theory of proof, for having an obvious objective character, when applied in the rights linked to the morale, aggravates decisionism and generates legal insecurity, being necessary its reconstruction for morally charged cases, with the possible use of the “predictive theory” ( and predictive facts) through algorithms in data collection and treatment.

Keywords: moral rights, proof, pragmatic proof theory, insufficiency, Brazil

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Raana Babadi Fathipour

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Over the past decades, the climatic CO2 concentration and worldwide normal temperature have been expanding, and this drift is anticipated to before long gotten to be more extreme. This situation of climate alter escalate abiotic stretch components (such as dry spell, flooding, saltiness, and bright radiation) that debilitate timberland and related environments as well as trim generation. These variables can contrarily influence plant development and advancement with a ensuing lessening in plant biomass aggregation and surrender, in expansion to expanding plant defenselessness to biotic stresses. As of late, biostimulants have ended up a hotspot as an viable and economical elective to reduce the negative impacts of stresses on plants. In any case, the larger part of biostimulants has destitute solidness beneath natural conditions, which leads to untimely debasement, shortening their organic movement. To unravel these bottlenecks, small scale- and nano-based definitions containing biostimulant atoms and/or microorganisms are picking up consideration as they illustrate a few points of interest over their routine details. In this survey, we center on the embodiment of plant development controllers and plant acquainted microorganisms as a technique to boost their application for plant assurance against abiotic stresses. We moreover address the potential restrictions and challenges confronted for the execution of this innovation, as well as conceivable outcomes with respect to future inquire about.

Keywords: bio stimulants, Seed priming, nano biotechnology, plant growth-promoting, rhizobacteria, plant growth regulators, microencapsulation

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Authors: Srinivas Vangari

Abstract:

In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Mochamad Beta Auditama, Yusuf Kurniawan

Abstract:

A smartphone or tablet require a strong randomness to establish secure encrypted communication, encrypt files, etc. Therefore, random number generation is one of the main keys to provide secrecy. Android devices are equipped with hardware-based sensors, such as accelerometer, gyroscope, etc. Each of these sensors provides a stochastic process which has a potential to be used as an extra randomness source, in addition to /dev/random and /dev/urandom pseudorandom number generators. Android sensors can provide randomness automatically. To obtain randomness from Android sensors, each one of Android sensors shall be used to construct an entropy source. After all entropy sources are constructed, output from these entropy sources are combined to provide more entropy. Then, a deterministic process is used to produces a sequence of random bits from the combined output. All of these processes are done in accordance with NIST SP 800-22 and the series of NIST SP 800-90. The operation conditions are done 1) on Android user-space, and 2) the Android device is placed motionless on a desk.

Keywords: Android hardware-based sensor, deterministic process, entropy source, random number generation/generators

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Authors: Inigo de Miguel Beriain

Abstract:

Genetic data of deceased persons are of great interest for both biomedical research and clinical use. This is due to several reasons. On the one hand, many of our diseases have a genetic component; on the other hand, we share genes with a good part of our biological family. Therefore, it would be possible to improve our response considerably to these pathologies if we could use these data. Unfortunately, at the present moment, the status of data on the deceased is far from being satisfactorily resolved by the EU data protection regulation. Indeed, the General Data Protection Regulation has explicitly excluded these data from the category of personal data. This decision has given rise to a fragmented legal framework on this issue. Consequently, each EU member state offers very different solutions. For instance, Denmark considers the data as personal data of the deceased person for a set period of time while some others, such as Spain, do not consider this data as such, but have introduced some specifically focused regulations on this type of data and their access by relatives. This is an extremely dysfunctional scenario from multiple angles, not least of which is scientific cooperation at the EU level. This contribution attempts to outline a solution to this dilemma through an alternative proposal. Its main hypothesis is that, in reality, health data are, in a sense, a rara avis within data in general because they do not refer to one person but to several. Hence, it is possible to think that all of them can be considered data subjects (although not all of them can exercise the corresponding rights in the same way). When the person from whom the data were obtained dies, the data remain as personal data of his or her biological relatives. Hence, the general regime provided for in the GDPR may apply to them. As these are personal data, we could go back to thinking in terms of a general prohibition of data processing, with the exceptions provided for in Article 9.2 and on the legal bases included in Article 6. This may be complicated in practice, given that, since we are dealing with data that refer to several data subjects, it may be complex to refer to some of these bases, such as consent. Furthermore, there are theoretical arguments that may oppose this hypothesis. In this contribution, it is shown, however, that none of these objections is of sufficient substance to delegitimize the argument exposed. Therefore, the conclusion of this contribution is that we can indeed build a general framework on the processing of personal data of deceased persons in the context of the GDPR. This would constitute a considerable improvement over the current regulatory framework, although it is true that some clarifications will be necessary for its practical application.

Keywords: collective data conceptual issues, data from deceased people, genetic data protection issues, GDPR and deceased people

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Authors: Angela T. H. Kwan, Saman Arfaie, Joseph Therriault, Zahra Azizi, Firoza Z. Lussier, Cecile Tissot, Mira Chamoun, Gleb Bezgin, Stijn Servaes, Jenna Stevenon, Nesrine Rahmouni, Vanessa Pallen, Serge Gauthier, Pedro Rosa-Neto

Abstract:

Alzheimer’s disease (AD) can be detected in living people using in vivo biomarkers of amyloid-β (Aβ) and tau, even in the absence of cognitive impairment during the preclinical phase. [¹⁸F]-MK-6420 is a high affinity positron emission tomography (PET) tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early AD symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the Translational Biomarkers in Aging and Dementia (TRIAD) study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau PET with [¹⁸F]-MK-6420 and Aβ PET with [¹⁸F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke, or other neurological disorders. There were 111 eligible participants who were chosen based on the availability of Aβ PET, tau PET, magnetic resonance imaging (MRI), and APOEε4 genotyping. Among these participants, the mean (SD) age was 70.1 (8.6) years; 20 (18%) were tau PET positive, and 71 of 111 (63.9%) were women. A significant association between baseline Braak I-II [¹⁸F]-MK-6240 SUVR positivity and change in composite memory score was observed at the 12-month follow-up, after correcting for age, sex, and years of education (Logical Memory and RAVLT, standardized beta = -0.52 (-0.82-0.21), p < 0.001, for dichotomized tau PET and -1.22 (-1.84-(-0.61)), p < 0.0001, for continuous tau PET). Moderate cognitive decline was observed for A+T+ over the follow-up period, whereas no significant change was observed for A-T+, A+T-, and A-T-, though it should be noted that the A-T+ group was small.Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [¹⁸F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [¹⁸F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of AD defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [¹⁸F]-MK-6420 PET provides us with the hope that living patients with AD may be diagnosed during the preclinical phase before it is too late.

Keywords: alzheimer’s disease, braak I-II, in vivo biomarkers, memory, PET, tau

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