Search results for: Support vector data description

Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

Abstract:

This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, Traffic, Weigh-in-Motion, Axle load Distribution.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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The Sensor Network consists of densely deployed sensor nodes. Energy optimization is one of the most important aspects of sensor application design. Data acquisition and aggregation techniques for processing data in-network should be energy efficient. Due to the cross-layer design, resource-limited and noisy nature of Wireless Sensor Networks(WSNs), it is challenging to study the performance of these systems in a realistic setting. In this paper, we propose optimizing queries by aggregation of data and data redundancy to reduce energy consumption without requiring all sensed data and directed diffusion communication paradigm to achieve power savings, robust communication and processing data in-network. To estimate the per-node power consumption POWERTossim mica2 energy model is used, which provides scalable and accurate results. The performance analysis shows that the proposed methods overcomes the existing methods in the aspects of energy consumption in wireless sensor networks.

Keywords: Data Aggregation, Directed Diffusion, Partial Aggregation, Packet Merging, Query Plan.

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Authors: Xiaoshu Lu, Tao Lu, Matias Remes, Martti Viljanen

Abstract:

As the data-driven economy is growing faster than ever and the demand for energy is being spurred, we are facing unprecedented challenges of improving energy efficiency in data centers. Effectively maximizing energy efficiency or minimising the cooling energy demand is becoming pervasive for data centers. This paper investigates overall energy consumption and the energy efficiency of cooling system for a data center in Finland as a case study. The power, cooling and energy consumption characteristics and operation condition of facilities are examined and analysed. Potential energy and cooling saving opportunities are identified and further suggestions for improving the performance of cooling system are put forward. Results are presented as a comprehensive evaluation of both the energy performance and good practices of energy efficient cooling operations for the data center. Utilization of an energy recovery concept for cooling system is proposed. The conclusion we can draw is that even though the analysed data center demonstrated relatively high energy efficiency, based on its power usage effectiveness value, there is still a significant potential for energy saving from its cooling systems.

Keywords: Data center, case study, cooling system, energyefficiency.

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Authors: Urska Cvek, Marjan Trutschl, Randolph Stone II, Zanobia Syed, John L. Clifford, Anita L. Sabichi

Abstract:

Expression data analysis is based mostly on the statistical approaches that are indispensable for the study of biological systems. Large amounts of multidimensional data resulting from the high-throughput technologies are not completely served by biostatistical techniques and are usually complemented with visual, knowledge discovery and other computational tools. In many cases, in biological systems we only speculate on the processes that are causing the changes, and it is the visual explorative analysis of data during which a hypothesis is formed. We would like to show the usability of multidimensional visualization tools and promote their use in life sciences. We survey and show some of the multidimensional visualization tools in the process of data exploration, such as parallel coordinates and radviz and we extend them by combining them with the self-organizing map algorithm. We use a time course data set of transitional cell carcinoma of the bladder in our examples. Analysis of data with these tools has the potential to uncover additional relationships and non-trivial structures.

Keywords: microarrays, visualization, parallel coordinates, radviz, self-organizing maps.

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Authors: Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

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Many-core GPUs provide high computing ability and substantial bandwidth; however, optimizing irregular applications like SpMV on GPUs becomes a difficult but meaningful task. In this paper, we propose a novel method to improve the performance of SpMV on GPUs. A new storage format called HYB-R is proposed to exploit GPU architecture more efficiently. The COO portion of the matrix is partitioned recursively into a ELL portion and a COO portion in the process of creating HYB-R format to ensure that there are as many non-zeros as possible in ELL format. The method of partitioning the matrix is an important problem for HYB-R kernel, so we also try to tune the parameters to partition the matrix for higher performance. Experimental results show that our method can get better performance than the fastest kernel (HYB) in NVIDIA-s SpMV library with as high as 17% speedup.

Keywords: GPU, HYB-R, Many-core, Performance Tuning, SpMV

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Authors: A. S. Haruna, M. U. Tambawal, A. A. Salawu

Abstract:

The psychological impact of peer influence on its individual group members, can make them resist HIV/AIDS counselling and testing. This study investigated the correlate of peer influence and resistance to HIV/AIDS counselling and testing among students in tertiary institutions in Kano state, Nigeria. To achieve this, three null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841.Simple Random Sampling was used in the selection. A self-developed 20-item scale called Peer Influence and Psychological Resistance Inventory (PIPRI) was used for data collection. Pearson Product Moment Correlation (PPMCC) via test-retest method was applied to estimate a reliability coefficient of 0.86 for the scale. Data obtained was analyzed using t-test and PPMCC at 0.05 level of confidence. Results reveal 26.3% (397) of the respondents being influenced by their peer group, while 39.8% showed resistance. Also, the t-tests and PPMCC statistics were greater than their respective critical values. This shows that there was a significant gender difference in peer influence and a difference between peer influence and resistance to HIV/AIDS counselling and testing. However, a positive relationship between peer influence and resistance to HIV/AIDS counselling and testing was shown. A major recommendation offered suggests the use of reinforcement and social support for positive attitudes and maintenance of safe behaviour among students who patronize HIV/AIDS counselling.

Keywords: Peer influence, HIV/AIDS counselling and testing, Resistance.

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Authors: Tayfun Çay, Yaşar İnceyol, Abdurrahman Özbeyaz

Abstract:

Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: Genetic algorithm, land consolidation, landholding, land reallocation.

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Authors: Katarzyna Czubak

Abstract:

The aim of this paper is description of the notion of the death for prisoners and the ways of deal with. They express indifference, coldness, inability to accept the blame, they have no shame and no empathy. Is it enough to perform acts verging on the death. In this paper we described mechanisms and regularities of selfdestructive behaviour in the view of the relevant literature? The explanation of the phenomenon is of a biological and sociopsychological nature. It must be clearly stated that all forms of selfdestructive behaviour result from various impulses, conflicts and deficits. That is why they should be treated differently in terms of motivation and functions which they perform in a given group of people. Behind self-destruction there seems to be a motivational mechanism which forces prisoners to rebel and fight against the hated law and penitentiary systems. The imprisoned believe that pain and suffering inflicted on them by themselves are better than passive acceptance of repression. The variety of self-destruction acts is wide, and some of them take strange forms. We assume that a life-death barrier is a kind of game for them. If they cannot change the degrading situation, their life loses sense.

Keywords: Self- destruction, Simulation, Negative emotions, Consequences of conviction.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: Shaun Cox, Michael Oakes, Stefan Wermter, Maurice Hawthorne

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We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.

Keywords: Audiology, data mining, chi-squared, self-organizing maps

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Authors: Fan Yang, Ye-lu Wang, Yang Zhao

Abstract:

The dynamic load allowance, as an application result of the vehicle-bridge coupled vibration theory, is an important parameter for bridge design and evaluation. Based on the coupled vehicle-bridge vibration theory, the current work establishes a full girder model of a dynamic load allowance, selects a planar five-degree-of-freedom three-axis vehicle model, solves the coupled vehicle-bridge dynamic response using the APDL language in the spatial finite element program ANSYS, selects the pivot point 2 sections as the representative of the negative moment section, and analyzes the effects of parameters such as travel speed, unevenness, vehicle frequency, span diameter, span number and forced displacement of the support on the negative moment dynamic load allowance through orthogonal tests. The influence of parameters such as vehicle speed, unevenness, vehicle frequency, span diameter, span number, and forced displacement of the support on the negative moment dynamic load allowance is analyzed by orthogonal tests, and the influence law of each influencing parameter is summarized. It is found that the effects of vehicle frequency, unevenness, and speed on the negative moment dynamic load allowance are significant, among which vehicle frequency has the greatest effect on the negative moment dynamic load allowance; the effects of span number and span diameter on the negative moment dynamic load allowance are relatively small; the effects of forced displacement of the support on the negative moment dynamic load allowance are negligible.

Keywords: Continuous T-girder bridge, dynamic load allowance, sensitivity analysis, vehicle-bridge coupling.

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Authors: R. Leelaruji, V. Knazkins

Abstract:

This paper proposes a methodology for mitigating the occurrence of cascading failure in stressed power systems. The methodology is essentially based on predicting voltage instability in the power system using a voltage stability index and then devising a corrective action in order to increase the voltage stability margin. The paper starts with a brief description of the cascading failure mechanism which is probable root cause of severe blackouts. Then, the voltage instability indices are introduced in order to evaluate stability limit. The aim of the analysis is to assure that the coordination of protection, by adopting load shedding scheme, capable of enhancing performance of the system after the major location of instability is determined. Finally, the proposed method to generate instability prediction is introduced.

Keywords: Blackouts, cascading failure, voltage stability indices, singular value decomposition, load shedding.

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Authors: Gia Surguladze, Lily Petriashvili, Nino Topuria, Giorgi Surguladze

Abstract:

Modelling of building processes of a multimodal freight transportation support information system is discussed based on modern CASE technologies. Functional efficiencies of ports in the eastern part of the Black Sea are analyzed taking into account their ecological, seasonal, resource usage parameters. By resources, we mean capacities of berths, cranes, automotive transport, as well as work crews and neighbouring airports. For the purpose of designing database of computer support system for Managerial (Logistics) function, using Object-Role Modeling (ORM) tool (NORMA–Natural ORM Architecture) is proposed, after which Entity Relationship Model (ERM) is generated in automated process. Software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.

Keywords: Seaport resources, business-processes, multimodal transportation, CASE technology, object-role model, entity relationship model, SOA.

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Authors: A. Eui Koog Ahn, B. Gi-Nam Wang, C. Sang C. Park

Abstract:

Higher productivity and less cost in the ship manufacturing process are required to maintain the international competitiveness of morden manufacturing industries. In shipbuilding, however, the Engineering To Order (ETO) production method and production process is very difficult. Thus, designs change frequently. In accordance with production, planning should be set up according to scene changes. Therefore, fixed production planning is very difficult. Thus, a scheduler must first make sketchy plans, then change the plans based on the work progress and modifications. Thus, data sharing in a shipbuilding block assembly shop is very important. In this paper, we proposed to scheduling method applicable to the shipbuilding industry and decision making support system through web based visualization system.

Keywords: Shipbuilding, Monitoring, Block assembly shop, Visualization

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Authors: Seo Young Kim, Tai Myong Choi

Abstract:

The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others.

Keywords: Clustering, microarray data, Fuzzy-type clustering, Validation

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Authors: Mabel A. Leva

Abstract:

This study defines a methodology to compute unitary costs for freight transportation modes. The main objective was to gather relevant costs data to support the formulation and evaluation of railway, road, pipelines and port projects. This article will concentrate on the following steps: Compilation and analysis of relevant modal cost studies, Methodological adjustments to make cost figures comparable between studies, Definition of typology and scope of transportation modes, Analysis and validation of cost values for relevant freight transportation modes in Chile. In order to define the comparison methodology for the costs between the different transportation modes, it was necessary to consider that the relevant cost depends on who performs the comparison. Thus, for the transportation user (e.g. exporter) the pertinent costs are the mode tariffs, whereas from the operators perspective (e.g. rail manager), the pertinent costs are the operating costs of each mode.

Keywords: Intermodal costs, Logistics, Transportation costs.

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Authors: H. Sediki, S. Djennoune

Abstract:

The switching lag-time and the voltage drop across the power devices cause serious waveform distortions and fundamental voltage drop in pulse width-modulated inverter output. These phenomenons are conspicuous when both the output frequency and voltage are low. To estimate the output voltage from the PWM reference signal it is essential to take account of these imperfections and to correct them. In this paper, on-line compensation method is presented. It needs three simple blocs to add at the ideal reference voltages. This method does not require any additional hardware circuit and off- line experimental measurement. The paper includes experimental results to demonstrate the validity of the proposed method. It is applied, finally, in case of indirect vector controlled induction machine and implemented using dSpace card.

Keywords: Dead time, field-oriented control, Induction motor, PWM inverter, voltage drop.

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Authors: C. M. Balaceanu, G. Suciu, C. S. Bosoc, O. Orza, C. Fernandez, Z. Viniczay

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The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.

Keywords: Blockchain, IoT, smart agriculture, vineyard.

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Authors: Goodarz Sabetian, Sajjad Moshfe

Abstract:

Control system for hi-tech industries could be realized generally and deeply by a special document. Vast heavy industries such as power plants with a large number of I/O signals are controlled by a distributed control system (DCS). This system comprises of so many parts from field level to high control level, and junior instrument engineers may be confused by this enormous information. The key document which can solve this problem is “control configuration system diagram” for each type of DCS. This is a road map that covers all of activities respect to control system in each industrial plant and inevitable to be studied by whom corresponded. It plays an important role from designing control system start point until the end; deliver the system to operate. This should be inserted in bid documents, contracts, purchasing specification and used in different periods of project EPC (engineering, procurement, and construction). Separate parts of DCS are categorized here in order of importance and a brief description and some practical plan is offered. This article could be useful for all instrument and control engineers who worked is EPC projects.

Keywords: Control, configuration, DCS, power plant, bus.

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

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This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: MicroRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM.

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

Abstract:

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: Data grids, fault tolerance, chandy-lamport, clustering.

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Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mohamad Teshnelab, Ehsan Shahamatnia

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The anti-lock braking systems installed on vehicles for safe and effective braking, are high-order nonlinear and timevariant. Using fuzzy logic controllers increase efficiency of such systems, but impose a high computational complexity as well. The main concept introduced by this paper is reducing computational complexity of fuzzy controllers by deploying problem-solution data structure. Unlike conventional methods that are based on calculations, this approach is based on data oriented modeling.

Keywords: ABS, Fuzzy controller, PSDS, Time-Memory tradeoff, Data oriented modeling.

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Authors: P. Hajyalikhani, B. Hudson, D. Boll, L. Boren, Z. Sparks, M. Ward

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Wood Light frame construction is one of the most common types of construction methods for residential and light commercial building in North America and parts of Europe. The typical roof framing for wood framed building is sloped and consists of several structural members such as rafters, hips, and valleys which are connected to the ridge and ceiling joists. The common slopes for roofs are 3/12, 8/12, and 12/12. Wood framed residential roof failure is most commonly caused by wind damage in such buildings. In the recent study, one of the weaknesses of wood framed roofs is long unsupported structural member lengths, such as hips and valleys. The purpose of this research is to find the critical support location for long hips and valleys with different slopes. ForteWeb software is used to find the critical location. The analysis results demonstrating the maximum unbraced hip and valley length are from 8.5 to 10.25 ft. dependent on the slope and roof type.

Keywords: Light wood framed, bracing, construction, hip, valley, slope.

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, these projects propose AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project present the best-in-school techniques used to preserve data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptography techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures, and identifies potential correction/mitigation measures.

Keywords: Data privacy, artificial intelligence, healthcare AI, data sharing, healthcare organizations.

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Authors: Goh Yen Nee

Abstract:

This research aimed to find out the determining factors for ISO 14001 EMS implementation among SMEs in Malaysia from the Resource based view. A cross-sectional approach using survey was conducted. A research model been proposed which comprises of ISO 14001 EMS implementation as the criterion variable while physical capital resources (i.e. environmental performance tracking and organizational infrastructures), human capital resources (i.e. top management commitment and support, training and education, employee empowerment and teamwork) and organizational capital resources (i.e. recognition and reward, organizational culture and organizational communication) as the explanatory variables. The research findings show that only environmental performance tracking, top management commitment and support and organizational culture are found to be positively and significantly associated with ISO 14001 EMS implementation. It is expected that this research will shed new knowledge and provide a base for future studies about the role played by firm-s internal resources.

Keywords: ISO 14001 Environmental Management System, Malaysia, Resource based view, SMEs

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Authors: M. Tajdari, A. R. Nezamabadi, M. Naeemi, P. Pirali

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Mechanical buckling analysis of rectangular plates with central circular cutout is performed in this paper. The finiteelement method is used to study the effects of plate-support conditions, aspect ratio, and hole size on the mechanical buckling strength of the perforated plates subjected to linearly varying loading. Results show that increasing the hole size does not necessarily reduce the mechanical buckling strength of the perforated plates. It is also concluded that the clamped boundary condition increases the mechanical buckling strength of the perforated plates more than the simply-supported boundary condition and the free boundary conditions enhance the mechanical buckling strength of the perforated plates more effectively than the fixed boundary conditions. Furthermore, for the bending cases, the critical buckling load of perforated plates with free edges is less than perforated plates with fixed edges.

Keywords: Buckling, Perforated plates, Boundary condition, Rectangular plates

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung, Jae-Cheol Ryou

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Cell phone forensics to acquire and analyze data in the cellular phone is nowadays being used in a national investigation organization and a private company. In order to collect cellular phone flash memory data, we have two methods. Firstly, it is a logical method which acquires files and directories from the file system of the cell phone flash memory. Secondly, we can get all data from bit-by-bit copy of entire physical memory using a low level access method. In this paper, we describe a forensic tool to acquire cell phone flash memory data using a logical level approach. By our tool, we can get EFS file system and peek memory data with an arbitrary region from Korea CDMA cell phone.

Keywords: Forensics, logical method, acquisition, cell phone, flash memory.

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Authors: Muhammad Umair Shahid, Abdul Rehman, Mudassir Mukhtar, Muhammad Nauman

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The smart antenna is the prominent technology that has become known in recent years to meet the growing demands of wireless communications. In an overcrowded atmosphere, its application is growing gradually. A methodical evaluation of the performance of Fixed Beamforming algorithms for smart antennas such as Multiple Sidelobe Canceller (MSC), Maximum Signal-to-interference ratio (MSIR) and minimum variance (MVDR) has been comprehensively presented in this paper. Simulation results show that beamforming is helpful in providing optimized response towards desired directions. MVDR beamformer provides the most optimal solution.

Keywords: Fixed weight beamforming, array pattern, signal to interference ratio, power efficiency, element spacing, array elements, optimum weight vector.

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