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Generative AI applications have played an increasingly significant role in real-time tracking applications in many domains including, for example, healthcare, consultancy, dialog boxes (common types of window in a graphical user interface of operating systems), monitoring systems, and emergency response. This paper considers generative AI and presents an approach which combines hedge algebra and a multilingual large language model to find hidden rules in big data for ChatGPT. We present a novel method for extracting natural language knowledge from large datasets by leveraging fuzzy sets and hedge algebra to extract these rules, presented in meta data for ChatGPT and generative AI applications. The proposed model has been developed to minimize the computational and staff costs for medium-sized enterprises which are typically resource and time limited. The proposed model has been designed to automate question–response interactions for rules extracted from large data in a multiplicity of domains. The experimental results show that the proposed model performs well using datasets associated with specific domains in healthcare to validate the effectiveness of the proposed model. The ChatGPT application in case studies of healthcare is tested using datasets for English and Vietnamese languages. In comparative experimental testing, the proposed model outperformed the state of the art, achieving in the range of 96.70–97.50% performance using a heart dataset. [ABSTRACT FROM AUTHOR]

Streaming video in real time from one device to another is a challenging issue for many purposes. One of them is that both sides must initialize the connection at relatively short period of time, another issue is happened if the systems work on different platforms or different Operating Systems (OS). Network status also plays an important role in streaming quality. This paper proposes streaming live video using Real Time Protocol (RTP) form mobile camera (Android system) to a computer (Windows system). Six Streaming metrics has been taken into consideration to measure the results. These metrics are video Jitter, frame Latency, Network Throughput, Peek Signal to Noisy Ratio, and CPU usage. The results shows that network bandwidth effect on these metrics with different perspectives. [ABSTRACT FROM AUTHOR]

Semantic-Web Recommender System (SWRS) evaluation over different operating systems (OSs) used to facilitate and improve human electronic recommendation management (HERM). The HERM is address the needs of user and dataset of movie in our proposed system through internetworking means which increase the speed of automated recommendation and enhance the goodness of SWRS and services also electronically to select right movies-title to user demand. Furthermore, it will be a benefit for selection a right favor by user for right selection from (i.e., 3000 records in dataset of movie-Lens) in the backend. There are a direct relation between time-consume of selection movie-title, also the time-consume, and accuracy. The two-mentioned parameters, namely, time-consume and accuracy over two different operation system (OSs) which designed by web technology Python. In our research, SWR system is proposed; it is provide with some recommendation methods. The system designed and improved using content-based algorithm (CBA). Investigational results indicate that the developed algorithm technique confident a reasonable performance such as accuracy and time consuming compared to other existing works with a testing average accuracy of 85.63 for windows and 88.35 for Linux operating system. In conclusion, SWRS investigated on two different operating platforms and could be seen that the Linux is faster than windows in accuracy and time consuming. [ABSTRACT FROM AUTHOR]

The cone aperture of 0.3 mm diameter is slightly larger than the footprint of the beam at normal emission ( I i 0.2 mm) and allows pressures up to 100 mbar in the analysis chamber while keeping the pressure in the detector section of the analyzer below 10 SP -6 sp mbar. It features a near ambient-pressure end station capable of performing XPS (X-ray photoelectron Spectroscopy) and NEXAFS (Near-edge X-ray absorption fine structure) spectroscopy experiments at gas pressures up to tens of mbar. Summary and outlook The two branches of the VerSoX (Versatile Soft X-ray) beamline B07 of Diamond Light Source cover an energy range from 45 eV (minimum energy of branch B) to 2800 eV (maximum energy of branch C) and currently provide endstations for near-ambient-pressure XPS/NEXAFS (10 SP -9 sp to I i 30 mbar) ambient-pressure NEXAFS (10 SP -7 sp to I i 1000 mbar). Inert and non-toxic gases are supplied via manual leak valves and toxic or flammable gases via a mobile gas delivery system that can be connected to the beamline's exhaust system and is equipped with mass flow controllers and full software control, similar to that of the ambient-pressure XPS/NEXAFS endstation. [Extracted from the article]

After several years, crypto‐ransomware attacks still constitute a principal threat for individuals and organisations worldwide. Despite the fact that a number of solutions are deployed to fight against this plague, one main challenge is that of early reaction, as merely detecting its occurrence can be useless to avoid the pernicious effects of the malware. With this aim, the authors introduced in a previous work a novel anti‐ransomware tool for Unix platforms named R‐Locker. The proposal is supported on a honeyfile‐based approach, where 'infinite' trap files are disseminated around the target filesystem for early detection and to effectively block the ransomware action. The authors extend here the tool with three main new contributions. First, R‐Locker is migrated to Windows platforms, where specific differences exist regarding FIFO handling. Second, the global management of the honeyfiles around the target filesystem is now improved to maximise protection. Finally, blocking suspicious ransomware is (semi)automated through the dynamic use of white‐/black‐lists. As in the original work for Unix systems, the new Windows version of R‐Locker shows high effectivity and efficiency in thwarting ransomware action. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Scientific & Technical Applications / Revista de Aplicación Científica & Técnica is the property of ECORFAN-Mexico S.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Process‐based models are becoming increasingly used tools for understanding how species are likely to respond to environmental changes and to potential management options. RangeShifter is one such modelling platform, which has been used to address a range of questions including identifying effective reintroduction strategies, understanding patterns of range expansion and assessing population viability of species across complex landscapes. Here we introduce a new version, RangeShifter 2.0, which incorporates important new functionality. It is now possible to simulate dynamics over user‐specified, temporally changing landscapes. Additionally, we integrated a new genetic module, notably introducing an explicit genetic modelling architecture, which allows for simulation of neutral and adaptive genetic processes. Furthermore, emigration, transfer and settlement traits can now all evolve, allowing for sophisticated simulation of the evolution of dispersal. We illustrate the potential application of RangeShifter 2.0's new functionality by two examples. The first illustrates the range expansion of a virtual species across a dynamically changing UK landscape. The second demonstrates how the software can be used to explore the concept of evolving connectivity in response to land‐use modification, by examining how movement rules come under selection over landscapes of different structure and composition. RangeShifter 2.0 is built using object‐oriented C++ providing computationally efficient simulation of complex individual‐based, eco‐evolutionary models. The code has been redeveloped to enable use across operating systems, including on high performance computing clusters, and the Windows graphical user interface has been enhanced. RangeShifter 2.0 will facilitate the development of in‐silico assessments of how species will respond to environmental changes and to potential management options for conserving or controlling them. By making the code available open source, we hope to inspire further collaborations and extensions by the ecological community. [ABSTRACT FROM AUTHOR]

Individual differences in male reproductive success drive genetic drift and natural selection, altering genetic variation and phenotypic trait distributions in future generations. Therefore, identifying the determinants of reproductive success is important for understanding the ecology and evolution of plants. Here, based on the spatially explicit mating model (the neighborhood model), we develop a hierarchical probability model that links co‐dominant genotypes of offspring and candidate parents with phenotypic determinants of male reproductive success. The model accounts for pollen dispersal, genotyping errors as well as individual variation in selfing, pollen immigration, and differentiation of immigrant pollen pools. Unlike the classic neighborhood model approach, our approach is specially designed to account for excessive variation (overdispersion) in male fecundity. We implemented a Bayesian estimation method (the Windows computer program available at: https://www.ukw.edu.pl/pracownicy/plik/igor%5fchybicki/1806/) that, among others, allows for selecting phenotypic variables important for male fecundity and assessing the fraction of variance in fecundity (R2) explained by selected variables. Simulations showed that our method outperforms both the classic neighborhood model and the two‐step approach, where fecundities and the effects of phenotypic variables are estimated separately. The analysis of two data examples showed that in wind‐pollinated trees, male fecundity depends on both the amount of produced pollen and the ability to pollen spread. However, despite that the tree size was positively correlated with male fecundity, it explained only a fraction of the total variance in fecundity, indicating the presence of additional factors. Finally, case studies highlighted the importance of accounting for pollen dispersal in the estimation of fecundity determinants. [ABSTRACT FROM AUTHOR]

The threats and risks that exist in socio-economic, financial, informative spheres of business subject’s activity compel to search new and perfect the real registration-financial instruments of watching, control and making decision in relation to certain connections, communications in internal and external environments of business. The purpose of the article are finding certain reasons, methods and instruments cooperation of business subjects co-operation in the different circumstances of its behaviour, to get most effective the account and financial results from general co-operation of all socio-economic development participants. Methodological basis of research became the modern normatively-legal and legislative aspects of communications and co-operation of business subjects. In research used methods of dialectics, methods and principles of scientific cognition, instruments of economic analysis with the aim of improvement the registrationfinancial methods of co-operation in the conditions of display of different types of subject’s social behavior. The basic hypothesis of research became a supposition of possibility of improvement the registration-financial instruments of co-operating with the aim of transformation of social reference-points and values, motivation of positive behavior of business subjects in the process of communications. Basic investigation became the reasons that induce the business subjects to fruitful, mutually beneficial co-operation. It is well-proven that the most powerful results can attain only at the terms of complete to account the interests of all subjects of mutual relations and personal interest in the achievement of the put aims of personnel, that depend on behavior of human and set of factors that determine the modern terms of socio-economic development of subject on local and global levels. It is offered that must effective can have if take in the account by financial instruments that influence on success of business subjects co-operation as control, analysis and leveling of nascent critical moments in the process of mutual relations. It is showing that for every separate case it follows to have the set of motivations, stimuli that must be variables depending from values that pull out modern global calls and progress of socio-economic relations trends in Ukraine. Further researches will be sent to the design of scenarios of overcoming the barriers in the process of innovative co-operation, evaluation of satisfaction level the interests of business subjects in the conditions of global calls and attained level of social and behaviors limitations. All authors are requested to observe the technical requirements for formatting the articles, which will be presented at the International conference “Education, science, economics and technologies”. The articles should be written using the computer program Word for Windows in a DOC format. The papers should be sent via e-mail to the conference organizers. [ABSTRACT FROM AUTHOR]

Smartphones are an indispensable tool in modern day-to-day life. Their widespread use has spawned numerous applications targeting diverse domains, such as biomedical, environment sensing, and infrastructure monitoring. In such applications, the accuracy of the sensors at the core of the system is still questionable since these devices are not originally designed for high-accuracy sensing purposes. In this article, we investigate the accuracy limits of one of the commonly used sensors, namely, smartphone accelerometer. We focus on the efficacy of a smartphone as an acceleration measuring device, rather than focusing only on the accuracy of its internal accelerometer chip. This holistic approach includes additional errors that arise from the device operating system, such as sampling time uncertainty. Hence, we propose a novel smart device accelerometer error model that includes the traditional additive noise as well as sampling time uncertainty errors represented by a white Gaussian process. The model is validated experimentally using shake table experiments, and the maximum likelihood estimation (MLE) is used to estimate the sampling time uncertainty standard deviation. Moreover, we derive the Cramer–Rao lower bound (CRLB) of acceleration estimation based on the proposed model. [ABSTRACT FROM AUTHOR]

The implementation of policies promoting the adoption of an open science (OS) culture must be accompanied by indicators that allow monitoring the uptake of such policies and their potential effects on research publishing and sharing practices. This study presents indicators of open access (OA) at the institutional level for universities worldwide. By combining data from Web of Science, Unpaywall and the Leiden Ranking disambiguation of institutions, we track OA coverage of universities' output for 963 institutions. This paper presents the methodological challenges, conceptual discrepancies and limitations and discusses further steps needed to move forward the discussion on fostering OA and OS practices and policies. [ABSTRACT FROM AUTHOR]

BCR-ABL-negative myeloproliferative neoplasms (MPNs) in transformation have a dismal prognosis, and allogeneic hematopoietic stem cell transplantation (allo-HSCT) is considered the sole curative therapeutic option. We retrospectively analyzed 53 molecularly annotated patients treated at Saint Louis Hospital, Paris, diagnosed with MPN in transformation between 2008 and 2018. The median patient age was 65 years, and the median interval between MPN diagnosis and MPN transformation was 46 months. The median overall survival (OS) of the entire cohort after transformation was 7.1 months. OS was better for patients treated with hypomethylating agents (HMAs) or with chemotherapy compared than for those treated by best supportive care or single-agent targeted therapy (median, 9.1 months versus 1.5 months; P <.001). Patients treated with chemotherapy more often achieved complete remission compared with those treated with HMAs (68% versus 29%; P =.02), and were more often candidates for transplantation (59% versus 14%; P =.02), but the median OS was similar in the 2 groups. We then compared the outcomes in transplant recipients and nonrecipients using the Mantel-Byar methodology and found that allo-HSCT did not improve survival. In multivariate analysis, independent factors in prognosis were performance status at transformation (P <.01), initial treatment with HMAs or chemotherapy (P =.02), and the ability to achieve complete remission during follow-up (P <.01). Our data demonstrate that the indication for allo-HSCT for high-risk MPN should be discussed before transformation, because transplantation rescues few patients after transformation. [ABSTRACT FROM AUTHOR]

Waveform data resulting from time-intensive longitudinal designs require careful treatment. In particular, the statistical properties of summary metrics in this area are crucial. We draw on event-related potential (ERP) studies, a field with a relatively long history of collecting and analyzing such data, to illustrate our points. In particular, three summary measures for a component in the average ERP waveform feature prominently in the literature: the maximum (or peak amplitude), the average (or mean amplitude) and a combination (or adaptive mean). We discuss the methodological divide associated with these summary measures. Through both analytic work and simulation study, we explore the properties (e.g., Type I and Type II errors) of these competing metrics for assessing the amplitude of an ERP component across experimental conditions. The theoretical and simulation-based arguments in this article illustrate how design (e.g., number of trials per condition) and analytic (e.g., window location) choices affect the behavior of these amplitude summary measures in statistical tests and highlight the need for transparency in reporting the analytic steps taken. There is an increased need for analytic tools for waveform data. As new analytic methods are developed to address these time-intensive longitudinal data, careful treatment of the statistical properties of summary metrics used for null hypothesis testing is crucial. [ABSTRACT FROM AUTHOR]

Introduction: An Australian case series study demonstrated the effectiveness of the REsilience and Activities for every DaY for people with multiple sclerosis (READY for MS), a resilience group training program based on Acceptance and Commitment Therapy, in improving quality of life in people with MS. This study aimed to evaluate the feasibility and acceptability of the Italian READY for MS program, and to preliminary assess its efficacy when compared to an active control intervention (group relaxation). Methods: Single-blind phase II randomized controlled trial (RCT) and nested qualitative study (ISRCTN registration number: 38971970). Health-related quality of life (primary study outcome), mood, resilience, psychological flexibility and its protective factors were measured at baseline, after seven, 12 and 24 weeks. READY participants completed the purpose-built satisfaction questionnaire after 12 weeks. After trial completion, the control group also received READY. One-to-one participant interviews were conducted within three months of finishing the READY groups. Results: Four intervention groups were conducted with 39 participants (20 READY, 19 relaxation). Two patients (READY) withdrew before beginning the intervention due to unexpected work commitments. Feasibility and acceptability of READY were good, with high participant engagement and satisfaction. No statistical effects of READY were detected vs relaxation. Thirty participants were interviewed (18 READY; 12 relaxation + READY). Content data analysis revealed seven overarching themes: "Attitudes towards participation"; "Perceptions of program composition"; "Program impacts on life domains"; "Program active elements"; "Program improvement trajectories"; "Program differences and similarities"; "Suggested READY improvements". Conclusion: READY was well accepted by MS patients with varied socio-demographic and clinical characteristics. Qualitative (but not quantitative) data provided evidence in favour of READY. Our findings will inform methodological and intervention refinements for the multi-centre RCT that will follow. [ABSTRACT FROM AUTHOR]

IoT is getting popular as it makes human life comfortable. The industry giants such as IBM, Microsoft, Cisco and Amazon have started offering IoT assistance in form of services. Numerous IoT applications exist today with different roles to play in day-to-day life. Because of application diversity and a good number of IoT service providers, it is difficult for IoT users to select the best one as per the requirement and expected quality of service, QoS. To address this, QoS metrics related to major IoT components, i.e., communication, computing and things, are designed to assess the alternative services. IoT users can express their requirements regarding QoS, while service providers exhibit their offerings. Because of three major IoT components, service selection is considered as multi-criteria group decision-making (MCGDM) problem. This work proposes a new MCGDM framework to rank the IoT services that considers rank reversal problem, judgments of decision makers in linguistic term and the uncertainty and risk-attitudinal characteristics in human decision-making. The proposed framework is validated by comparing it with an existing MCGDM model. A case study on IoT health-care application is provided besides the sensitivity analysis to demonstrate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

In this article, we propose a creation order reconstruction method of deleted files for the FAT32 file system with Windows operating systems. Creation order of files is established using a correlation between storage locations of the files and their directory entry locations. This method can be utilized to derive the creation-time bound of files recovered without the creation-time information. In this article, we first examine the file allocation behavior of Windows FAT32 file system. Next, based on the examined behavior, we propose a novel method that finds the creation order of deleted files after being recovered without the creation-time information. Due to complex behaviors of Windows FAT32 file system, the method may find multiple creation orders although the actual creation order is unique. In experiments with a commercial device, we confirm that the actual creation order of each recovered file belongs to one of the creation orders found by the method. [ABSTRACT FROM AUTHOR]

Featured Application: In this paper, we propose a lightweight key-value store for managing various types of data, which are generated from Big data applications, in a very simple form. The proposed technique can be used in any environments where Windows operating systems are running, which encompass from client environments (e.g., Windows 10) to server environments (e.g., Windows Server 2016), with the minimum effort for the installation. For the other environments without Windows operating systems, we can easily migrate data to the other any environments that support existing key-value stores by using the ETL (Extract-Transform-Load) method proposed by this paper. In this paper, we propose a method to construct a lightweight key-value store based on the Windows native features. The main idea is providing a thin wrapper for the key-value store on top of a built-in storage in Windows, called Windows registry. First, we define a mapping of the components in the key-value store onto the components in the Windows registry. Then, we present a hash-based multi-level registry index so as to distribute the key-value data balanced and to efficiently access them. Third, we implement basic operations of the key-value store (i.e., Get, Put, and Delete) by manipulating the Windows registry using the Windows native APIs. We call the proposed key-value store WR-Store. Finally, we propose an efficient ETL (Extract-Transform-Load) method to migrate data stored in WR-Store into any other environments that support existing key-value stores. Because the performance of the Windows registry has not been studied much, we perform the empirical study to understand the characteristics of WR-Store, and then, tune the performance of WR-Store to find the best parameter setting. Through extensive experiments using synthetic and real data sets, we show that the performance of WR-Store is comparable to or even better than the state-of-the-art systems (i.e., RocksDB, BerkeleyDB, and LevelDB). Especially, we show the scalability of WR-Store. That is, WR-Store becomes much more efficient than the other key-value stores as the size of data set increases. In addition, we show that the performance of WR-Store is maintained even in the case of intensive registry workloads where 1000 processes accessing to the registry actively are concurrently running. [ABSTRACT FROM AUTHOR]

File system forensics is an important part of Digital Forensics. Investigators of storage media have traditionally focused on the most commonly used file systems such as NTFS, FAT, ExFAT, Ext2-4, HFS+, APFS, etc. NTFS is the current file system used by Windows for the system volume, but this may change in the future. In this paper we will show the structure of the Resilient File System (ReFS), which has been available since Windows Server 2012 and Windows 8. The main purpose of ReFS is to be used on storage spaces in server systems, but it can also be used in Windows 8 or newer. Although ReFS is not the current standard file system in Windows, while users have the option to create ReFS file systems, digital forensic investigators need to investigate the file systems identified on a seized media. Further, we will focus on remnants of non-allocated metadata structures or attributes. This may allow metadata carving, which means searching for specific attributes that are not allocated. Attributes found can then be used for file recovery. ReFS uses superblocks and checkpoints in addition to a VBR, which is different from other Windows file systems. If the partition is reformatted with another file system, the backup superblocks can be used for partition recovery. Further, it is possible to search for checkpoints in order to recover both metadata and content. Another concept not seen for Windows file systems, is the sharing of blocks. When a file is copied, both the original and the new file will share the same content blocks. If the user changes the copy, new data runs will be created for the modified content, but unchanged blocks remain shared. This may impact file carving, because part of the blocks previously used by a deleted file might still be in use by another file. The large default cluster size, 64 KiB, in ReFS v1.2 is an advantage when carving for deleted files, since most deleted files are less than 64 KiB and therefore only use a single cluster. For ReFS v3.2 this advantage has decreased because the standard cluster size is 4 KiB. Preliminary support for ReFS v1.2 has been available in EnCase 7 and 8, but the implementation has not been documented or peer-reviewed. The same is true for Paragon Software, which recently added ReFS support to their forensic product. Our work documents how ReFS v1.2 and ReFS v3.2 are structured at an abstraction level that allows digital forensic investigation of this new file system. At the time of writing this paper, Paragon Software is the only digital forensic tool that supports ReFS v3.x. It is the most recent version of the ReFS file system that is most relevant for digital forensics, as Windows automatically updates the file system to the latest version on mount. This is why we have included information about ReFS v3.2. However, it is possible to change a registry value to avoid updating. The latest ReFS version observed is 3.4, but the information presented about 3.2 is still valid. In any criminal case, the investigator needs to investigate the file system version found. • Reverse engineering of the low level structures for the Resilient file system (ReFS) • Explains the meaning of ReFS structures in a digital forensic context • Introduces new approaches for metadata carving and new recovery techniques for data reconstruction • Provides the necessary knowledge to verify digital forensic tools implementation of ReFS [ABSTRACT FROM AUTHOR]

Fine-tuning of a model is a method that is most often required to cater the users’ explicit requirements. But the question remains whether the model is accurate enough to be used for a certain application. This paper strives to present the metrics used for performance evaluation of a Convolutional Neural Network (CNN) model. The evaluation is based on the training process which provides us with intermediate models after every 1000 iterations. While 1000 iterations is not substantial enough over the range of 490k iterations, the groups are sized with 100k iterations each. Now, the intention was to compare the recorded metrics to evaluate the model in terms of accuracy. The training model used the set of specific categories chosen from the Microsoft Common Objects in Context (MS COCO) dataset, while allowing users to use their own externally available images to test the model’s accuracy. Our trained model ensured that all the objects are detected that are present in the image to depict the effect of precision. [ABSTRACT FROM AUTHOR]

The rapid pace of change in consumer technology requires structures and mechanisms to ensure ongoing engagement of consumers with disabilities so that new and updated products and services are accessible and useful. This article reviews the rationale, creation, operation, and impact of the Accessibility User Research Collective (AURC), a partnership between Microsoft and Shepherd Center, a rehabilitation hospital for traumatic injury and neurodegenerative diseases, to create and maintain a national network of people with all types of disabilities to provide ongoing customer input and testing of Microsoft products and services. The AURC is modeled after the Consumer Advisory Network (CAN) concept developed by Shepherd Center staff under the Rehabilitation Engineering Research Center for Wireless Technologies (Wireless RERC) and continued in recent years by the LiveWell RERC. The concept is to build a national network of consumers with disabilities who can be recruited to participate in targeted usability and needs-discovery studies. [ABSTRACT FROM AUTHOR]

Abstract A sequence of apparently ad-hoc hand postures can generate meaningful dynamic gestures which can be utilized in interface controls for computer, television, or games. In order to develop deployable systems with these gestures, selected descriptors should be fast enough to meet the live recognition requirements. This paper proposes framework for a practical system capable of recognizing continuous dynamic gestures characterized by short-duration posture sequences. A depth-based modification to the shape matrix is devised to describe hand silhouettes, which gives a faster alternative to region-based descriptors. Postures are recognized using depth matrix and 1-nearest neighbor strategy. Posture sequence labels are predicted by a dynamic naive Bayes classifier which works in association with an adaptive windowing mechanism. The conducted experiments report up to 96.2% accurate results with mean accuracy of 95.2% on dynamic gesture dataset. Depth matrix computation takes a maximum of 2ms time. [ABSTRACT FROM AUTHOR]

Mining in data streams has been a hot research topic in the recent time. A main challenge in data stream mining lies in extracting knowledge in real time from a massive, dynamic data stream in only a single scan. Data stream clustering presents an important role in data stream processing. This paper proposes SCluStream an algorithm for tracking clusters over a sliding window to handle such challenges. The algorithm is an enhancement over CluStream which does not involve this sliding window concept. In the sliding window model, only the most recent data is used while the old data is eliminated, which allows for faster execution. A better clustering technique is also involved which managed to contribute to accuracy enhancement. The proposed algorithm has been tested on a dataset for Intrusion detection and the results showed that comparing SCluStream to CluStream has proven that the former algorithm is more efficient for online clusters generation for big data streaming in regard of the accuracy as well as the utilized time and memory resources. [ABSTRACT FROM AUTHOR]

Abstract As the applications of High-Density surface Electromyography (HDsEMG) expand in clinical research settings, three issues deserve deeper investigation and clarification: a) the effect of electrode size, b) the effect of sampling frequency in space (interelectrode distance), c) the effect of the size of the electrode grid. The individual effects of these three factors are discussed. Electrode size introduces averaging in space, which is acceptable for electrode diameter d < 3–5 mm. Sampling frequency in space must satisfy Nyquist criterion to avoid aliasing. This implies small interelectrode distances e < 5–10 mm (e = 10 mm is a questionable compromise between proper sampling and number of channels). The use of 1D electrode arrays or 2D electrode grids implies rectangular windowing of the signal distribution in space and generates unavoidable "truncation" effects resulting in spectral power "leakage" and aliasing. Standardization of procedures and education of the users of HDsEMG are badly needed to facilitate exchange and comparison of results. [ABSTRACT FROM AUTHOR]

In this paper, we derive an expression for computing the average window size of a single TCP CUBIC connection under random losses. For this we consider a throughput expression for TCP CUBIC computed earlier under deterministic periodic packet losses. We validate this expression theoretically. We then use insights from the deterministic loss-based model to scale appropriately a sequence of Markov chains with random losses indexed by the probability of loss p. We show that this sequence converges to a limiting Markov chain as p tends to 0. The stationary distribution of the limiting Markov chain is then used to derive the average window size for small packet error rates. We then use a simple approximation to extend our current results with negligible queuing to a setup with multiple connections and non-negligible queuing. We validate our model and approximations via simulations. [ABSTRACT FROM AUTHOR]

A hybrid image processing technique is described which combines traditional feature extraction and windowing with a new artificial intelligence technique based on weightless neural networks. This technique is a unique way of compressing and then analysing complex data. Described here is its application to the measuring of light scattered for machine surfaces as well as the inspection of complex and highly coloured images. These examples illustrate the distinctive nature of the system. It is called WISE (Windowed Image Shaped Extraction) because it describes the stages of image processing. [ABSTRACT FROM AUTHOR]