An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period

Performance evaluation of hierarchical clustering protocols with fuzzy C-means

The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters

A Model of Electronic Customer Relationship Management System Adoption In Telecommunication Companies

Employee satisfaction is key to electronic–customer relationship management (E-CRM) systems in telecommunication companies. The purpose of this study is to investigate the direct and indirect effect of technological factors, individual factors, and organizational factors on employees' level of satisfaction. For this study, data was collected from 300 employees' workings in Malaysian telecommunication companies; and the data was analyzed using PLS-SEM. The findings revealed that technological, organizational, and individual factors are positively and significantly related to satisfaction and perceived usefulness. The results also supported the direct and positive relationship between perceived usefulness between employees' job satisfaction. The study has contributed to the body of literature by exploring the implications of various significant factors in terms of employee satisfaction. Besides, the management of the telecommunication companies may benefit from this study by adopting strategies that not only employee satisfaction but may also enhance the companies' performance. The limitations and the direction for future research are discussed in the end

Specification, Design and Development of a Pyramidal Learning Platform

The aim of this article is to design an online learning platform that allows tutoring between learners from different levels and the possibility of adding content to the fields of knowledge, using measures that assess quality. It is a versatile technological tool appropriate for the collaboration between different agents, both for acquiring new professional skills and for lifelong learning and formal regulated learning of education systems. Learning takes place through a two-way scheme: On the one hand, the learner is assisted through online tutoring by another highly qualified learner (that acts as a teacher). On the other hand, the same learner assists others from lower categories. In that way, their-skills will be consolidated by forcing reflection on the subject in order to explain it. The knowledge base is a wiki platform stratified in the same levels as the professional and training categories. This platform features evaluation and accounting modules for tutorials and contributions to the content of the wiki. The assignment of several disciples of a given level to each tutor of the superior level makes possible an exponential expansion that is of great interest for using the pyramidal school in projects of solidarity cooperation.This research was funded by the Valencian Innovation Agency (AVI) under scientific innovation unit (UCIE Ars Innovatio) of the University of Alicante. https://web.ua.es/es/ars-innovatio/unidad-cientifica-deinnovacion-ars-innovatio.html

A Closer Look into Recent Video-based Learning Research: A Comprehensive Review of Video Characteristics, Tools, Technologies, and Learning Effectiveness

People increasingly use videos on the Web as a source for learning. To support this way of learning, researchers and developers are continuously developing tools, proposing guidelines, analyzing data, and conducting experiments. However, it is still not clear what characteristics a video should have to be an effective learning medium. In this paper, we present a comprehensive review of 257 articles on video-based learning for the period from 2016 to 2021. One of the aims of the review is to identify the video characteristics that have been explored by previous work. Based on our analysis, we suggest a taxonomy which organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners activities, (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative research directions: (1) proposals of tools to support video-based learning, (2) studies with controlled experiments, (3) data analysis studies, and (4) proposals of design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learner activities, and interactive features. Text of transcripts, video frames, and images (figures and illustrations) are most frequently used by tools that support learning through videos. The learner activity is heavily explored through log files in data analysis studies, and interactive features have been frequently scrutinized in controlled experiments. We complement our review by contrasting research findings that investigate the impact of video characteristics on the learning effectiveness, report on tasks and technologies used to develop tools that support learning, and summarize trends of design guidelines to produce learning video

Readiness assessment model in supporting enterprise architecture establishment for Malaysian public sector

Enterprise Architecture (EA) is a strategic approach designed to align business strategy with ICT initiatives which has become part of the digital government transformation programme in most countries. The Malaysian Public Sector (MPS) has embraced EA as one of the pillars in their digital transformation initiative. However, findings from Malaysian Administrative Modernisation and Management Planning Unit (MAMPU) in 2016 revealed that EA establishment in MPS is still at its infancy level due to the lack of EA readiness. Similarly, public sectors in other countries such as Indonesia, Vietnam and Oman are also struggling to resolve this issue. Until June 2020, only six (6) agencies in MPS have established EA compared to 25 agencies targeted by MAMPU. Thus, to address this issue, this research proposes an EA Readiness Assessment Model (EARAM) with the aim to assess readiness of MPS, support decision-making process, and plan strategies for EA establishment. This research has four (4) objectives. The first objective is the identification of EA readiness factors followed by the second objective which is the development of EARAM. The third objective is to validate the developed EARAM, while the fourth objective involved evaluation of EARAM. A sequential exploratory mixed method research design was employed to achieve these four (4) objectives. To achieve the first and second objectives, this research used a systematic review (SR) and interview with five (5) EA experts; while the third objective involved three rounds of modified Delphi technique with 13 EA experts. Finally, for the fourth objective, the researcher adopted a multiple case study method whereby three (3) agencies in MPS that are in the EA establishment stage were selected. The EARAM was formulated based on several inputs from SR, interview findings, as well as Information Technology and Information System (IT/IS) Readiness Maturity model. The overall results of three (3) cycles of Delphi technique yielded the conclusion that 45 statements of elements, factors and items in the questionnaires received high consensus of importance in which their Inter Quartile Range (IQR) is between zero (0), and one (1) and median is more than four (4). Results from the Delphi analysis validated four (4) major elements of EARAM, namely 1) Catalyst Enabler, 2) People, 3) Process and 4) Technology along with 14 factors and 45 items. The EA Readiness Assessment Tool (EARAT) is developed by incorporating EARAM validated elements and factors to provide practitioners with an automated tool to assess the EA readiness level of their organisation. The results of EARAT’s evaluation from three (3) agencies in MPS indicated a high level of agreement (with a median score of more than 4.00) that EARAT provides useful and quality information, supports decision making, as well as provides ease of use and user satisfaction to support EA establishment in MPS. In conclusion, this research contributed to the development of EARAM to assess readiness in MPS, supports decision-making process, and plan strategies for EA establishment. This research is also in line with EA Body of Knowledge (EABOK) related to the areas of Organisational Scope and Structure of EA, specifically focusing on the sub-areas of Organisational Need and Drivers

Mapas de atención para destacar pólipos potenciales durante la colonoscopia

Context: Polyps are protruding masses that grow along the intestinal tract and are considered to be the main precursors of colorectal cancer. In early stages, polyp detection represents a survival probability of up to 93%, whereas, for other stages, this probability can decrease to 8%. Despite the fact that colonoscopy is the most effective method to detect polyps, several studies have shown a loss rate of up to 26% in detecting polyps. Computer tools have emerged as an alternative to support polyp detection and localization, but various problems remain open due to their high variability. Method: This work introduces a computational strategy that produces visual attention maps with the most probable location of polyps to generate alarms and support detection procedures. Each colonoscopy frame is decomposed into a set of deep features extracted from pre-trained architectures. Such features are encoded into a dense Hough representation in order to obtain a polyp template, which is then propagated in each frame to obtain a visual attention map. The maximum regions are back-projected to the colonoscopy in order to draw suspicious polyp regions. Results: The proposed strategy was evaluated in the ASU-Mayo Clinic and CVC-Video Clinic datasets, reporting a detection accuracy of 70% among the four most probable regions, while ten regions yielded 80%. Conclusions: The obtained attention maps highlight the most probable regions with suspicious polyps. The proposed approach may be useful to support colonoscopy analysis.Contexto: Los pólipos son masas protuberantes que crecen a lo largo del tracto intestinal y se consideran los principales precursores del cáncer de colon. En las etapas tempranas, la detección de pólipos representa una probabilidad de supervivencia de hasta el 93%, mientras que, en otras etapas, esta probabilidad disminuye hasta el 8%. A pesar de que la colonoscopia es el método más efectivo para detectar pólipos, varios estudios han demostrado una tasa de pérdida de hasta el 26% en la detección pólipos. Las herramientas computacionales han surgido como una alternativa para soportar la detección y localización de pólipos, pero varios problemas siguen abiertos debido a la alta variabilidad de los mismos. Método: Este trabajo introduce una estrategia computacional que produce mapas de atención visual con la localización más probable de los pólipos para generar alarmas y apoyar la tarea de detección. Cada fotograma de colonoscopia se descompone en un conjunto de características profundas extraídas de arquitecturas preentrenadas. Dichas características se codifican en una representación densa de Hough para obtener una plantilla del pólipo, que posteriormente se propaga en cada fotograma para obtener los mapas de atención visual. Las regiones máximas son proyectadas a la colonoscopia para dibujar las regiones sospechosas de pólipo. Resultados:  La estrategia propuesta fue evaluada en los conjuntos de datos ASU-Mayo Clinic y CVC-Video Clinic, reportando una exactitud de 70% de detección entre las cuatro regiones más probables, mientras que con diez regiones se tiene un 80%. Conclusiones:  Los mapas de atención obtenidos destacan las regiones más probables con pólipos. El enfoque propuesto puede ser útil para apoyar el análisis de la colonoscopia

Job adjustment strategy for predictive maintenance in semi-fully flexible systems based on machine health status

Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies.This work has been funded by the Department of Science and Technology, Science and Engineering Research Board (DST-SERB), a statutory body established through an Act of Parliament: SERB Act 2008, Government of India with sanction order no. ECR/2016/001808, and also by the FCT-Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Predictive maintenance: a novel framework for a data-driven, semi-supervised, and partially online prognostic health management application in industries

Prognostic Health Management (PHM) is a predictive maintenance strategy, which is based on Condition Monitoring (CM) data and aims to predict the future states of machinery. The existing literature reports the PHM at two levels: methodological and applicative. From the methodological point of view, there are many publications and standards of a PHM system design. From the applicative point of view, many papers address the improvement of techniques adopted for realizing PHM tasks without covering the whole process. In these cases, most applications rely on a large amount of historical data to train models for diagnostic and prognostic purposes. Industries, very often, are not able to obtain these data. Thus, the most adopted approaches, based on batch and off-line analysis, cannot be adopted. In this paper, we present a novel framework and architecture that support the initial application of PHM from the machinery producers’ perspective. The proposed framework is based on an edge-cloud infrastructure that allows performing streaming analysis at the edge to reduce the quantity of the data to store in permanent memory, to know the health status of the machinery at any point in time, and to discover novel and anomalous behaviors. The collection of the data from multiple machines into a cloud server allows training more accurate diagnostic and prognostic models using a higher amount of data, whose results will serve to predict the health status in real-time at the edge. The so-built PHM system would allow industries to monitor and supervise a machinery network placed in different locations and can thus bring several benefits to both machinery producers and users. After a brief literature review of signal processing, feature extraction, diagnostics, and prognostics, including incremental and semi-supervised approaches for anomaly and novelty detection applied to data streams, a case study is presented. It was conducted on data collected from a test rig and shows the potential of the proposed framework in terms of the ability to detect changes in the operating conditions and abrupt faults and storage memory saving. The outcomes of our work, as well as its major novel aspect, is the design of a framework for a PHM system based on specific requirements that directly originate from the industrial field, together with indications on which techniques can be adopted to achieve such goals

Koostööäriprotsesside läbiviimine plokiahelal: süsteem

Tänapäeval peavad organisatsioonid tegema omavahel koostööd, et kasutada ära üksteise täiendavaid võimekusi ning seeläbi pakkuda oma klientidele parimaid tooteid ja teenuseid. Selleks peavad organisatsioonid juhtima äriprotsesse, mis ületavad nende organisatsioonilisi piire. Selliseid protsesse nimetatakse koostööäriprotsessideks. Üks peamisi takistusi koostööäriprotsesside elluviimisel on osapooltevahelise usalduse puudumine. Plokiahel loob detsentraliseeritud pearaamatu, mida ei saa võltsida ning mis toetab nutikate lepingute täitmist. Nii on võimalik teha koostööd ebausaldusväärsete osapoolte vahel ilma kesksele asutusele tuginemata. Paraku on aga äriprotsesside läbiviimine selliseid madala taseme plokiahela elemente kasutades tülikas, veaohtlik ja erioskusi nõudev. Seevastu juba väljakujunenud äriprotsesside juhtimissüsteemid (Business Process Management System – BPMS) pakuvad käepäraseid abstraheeringuid protsessidele orienteeritud rakenduste kiireks arendamiseks. Käesolev doktoritöö käsitleb koostööäriprotsesside automatiseeritud läbiviimist plokiahela tehnoloogiat kasutades, kombineerides traditsioonliste BPMS- ide arendusvõimalused plokiahelast tuleneva suurendatud usaldusega. Samuti käsitleb antud doktoritöö küsimust, kuidas pakkuda tuge olukordades, milles uued osapooled võivad jooksvalt protsessiga liituda, mistõttu on vajalik tagada paindlikkus äriprotsessi marsruutimisloogika muutmise osas. Doktoritöö uurib tarkvaraarhitektuurilisi lähenemisviise ja modelleerimise kontseptsioone, pakkudes välja disainipõhimõtteid ja nõudeid, mida rakendatakse uudsel plokiahela baasil loodud äriprotsessi juhtimissüsteemil CATERPILLAR. CATERPILLAR-i süsteem toetab kahte lähenemist plokiahelal põhinevate protsesside rakendamiseks, läbiviimiseks ja seireks: kompileeritud ja tõlgendatatud. Samuti toetab see kahte kontrollitud paindlikkuse mehhanismi, mille abil saavad protsessis osalejad ühiselt otsustada, kuidas protsessi selle täitmise ajal uuendada ning anda ja eemaldada osaliste juurdepääsuõigusi.Nowadays, organizations are pressed to collaborate in order to take advantage of their complementary capabilities and to provide best-of-breed products and services to their customers. To do so, organizations need to manage business processes that span beyond their organizational boundaries. Such processes are called collaborative business processes. One of the main roadblocks to implementing collaborative business processes is the lack of trust between the participants. Blockchain provides a decentralized ledger that cannot be tamper with, that supports the execution of programs called smart contracts. These features allow executing collaborative processes between untrusted parties and without relying on a central authority. However, implementing collaborative business processes in blockchain can be cumbersome, error-prone and requires specialized skills. In contrast, established Business Process Management Systems (BPMSs) provide convenient abstractions for rapid development of process-oriented applications. This thesis addresses the problem of automating the execution of collaborative business processes on top of blockchain technology in a way that takes advantage of the trust-enhancing capabilities of this technology while offering the development convenience of traditional BPMSs. The thesis also addresses the question of how to support scenarios in which new parties may be onboarded at runtime, and in which parties need to have the flexibility to change the default routing logic of the business process. We explore architectural approaches and modelling concepts, formulating design principles and requirements that are implemented in a novel blockchain-based BPMS named CATERPILLAR. The CATERPILLAR system supports two methods to implement, execute and monitor blockchain-based processes: compiled and interpreted. It also supports two mechanisms for controlled flexibility; i.e., participants can collectively decide on updating the process during its execution as well as granting and revoking access to parties.https://www.ester.ee/record=b536494