The monitoring and diagnosis of damage in dynamic machines is an area of growing interest in the cement industry. Indeed, industrial equipment is disturbed throughout its operation by malfunctions, especially in old age, which affect its operating costs and availability. Therefore, the detection and identification of faults in industrial systems - diagnosis - is of paramount importance for their operation and a major challenge for modern industry. Among the most popular techniques used in diagnostics is spectral analysis, a tool for condition monitoring, which is used to study the vibration signals of dynamic machines.\nIn this context, the objective of this work is the early detection of failures by frequency spectral analysis, which is based on an analysis of the vibration signal in order to search for the presence of vibratory images of all the defects likely to affect the installation considered. As a case study, we took the ball mill of the Hamma Bouziane-Constantine cement plant, given its importance in the production process. To do so, a knowledge of the kinematic characteristics of the various constituent parts and their excitation frequencies is required. Our choice is justified by its use in the elaboration of the choice of the conditional maintenance strategy for industrial applications.

Due to the exponential growth in the number of web users, there\'s been a great advancement in the development of fiber-wireless (Fi-Wi) networks during the last few decades. Fi-Wi systems are now proven to be a great component in the sphere of the internet and communication due to their superiority over other technologies. Fi-Wi technology gives a large quantity of bandwidth and consistency to network users in a participatory way which means the network provides \"Anywhere Anytime\" connectivity service to consumers at a great speed. However, the higher energy consumption of Sensor Network causes limited network lifespan and hence affects the transmission. Over the years, a significant number of Media Access Control (MAC) approaches have been proposed by various researchers to effectively handle energy and transmission issues. Nevertheless, these methods faced issues like delays, less throughput caused by collisions, overheating, or some other reasons. In this paper, a hybridized method based on Carrier Sense Multiple Access (CSMA) and Time Division Multiple Access (TDMA) is proposed to mitigate above-mentioned issues. The main objective of the proposed work is to reduce the delays and increase the throughput in Fi-Wi networks. For this, the data is transmitted from the sender’s end, in bit form that is later modulated by the orthogonal frequency-division multiplexing (OFDM) modulator. These modulated signals are then transmitted over the free-space optical communication (FSO) channel, where delay is calculated. At the receiving station, the optical signal is received and detected by the photo detector which demodulates the optical signal through the OFDM demodulation. Finally, the performance of the received signal is analyzed in the Opti-system. The results obtained show the proposed MAC protocol is outperforming the traditional MAC protocols in terms of its throughput, transmission efficiency, and delay.

In the present study, a parallel system is analyzed by using the preventive maintenance with the inspection policy for failed component. A single server investigates the failed component is repairable or replaced by new one. The random variable of each task is statistically independent, and their rates are arbitrary distributed. Semi-Markov epoch and regenerative-point-technique are applied to formulate the expressions of associated reliability measures. For comparing the behavior of MTSF, availability function and profit function for different repair activities, graphs are drawn assuming the exponential distribution for rate of all repair activities.

This article presents experimental and theoretical studies on the response of 6061-T6 aluminum alloy round-hole tubes (Al-RHTs) with five different hole sizes of 2, 4, 6, 8, and 10 mm and with five different hole directions of 0, 45o, 90, 135, and 180 submitted to pure bending creep. Pure bending creep is defined as bending the tube to the required moment and maintaining that moment for a period of time. It can be seen from experimental results that the curvature increases with time. In addition, larger holding moment or hole size results in larger creep curvature. As the curvature continues to increase, the round-hole tube eventually breaks. Finally, the empirical formula proposed by of Pan et al. in 2014 was improved to simulate the creep curvature-time relationship for pure bending creep in the initial and the secondary stages. After comparing with the experimental results, it is found that theoretical analysis can reproduce the experimental results reasonably.

The warehouse is a fundamental element of logistics, which needs efficient ways to classify and assign a storage place. The storage location assignment problem (SLAP) can be treated as a multicriteria problem through decision-making methods that establish the classification of stock-keeping units (SKUs) influenced by the decision maker\'s opinion. This article aims to apply the value-focused thinking (VFT) and ELECTRE-MOr methods to support the strategic decision-making (DM) process in the classification of inventory units through multiple criteria, in a warehouse of a distribution company. The results found showed that, among 100 SKUs, 8% were allocated in the highest priority class A, 19% in the intermediate priority class B, and 73% of the SKUs, the great majority, were assigned to the lesser class.

Processes that establish Compliance at first do not seem to add to the value chain of companies. However, the need to address legislation or issues related to corporate governance, social management, and the environment, lead large corporations to adopt such processes. This article aimed to establish a plan for prioritizing the implementation of compliance processes in a utilities company, through the meth-od of structuring Value-Focused Thinking (VFT) problems, and the application of the new hybrid multicriteria method SAPEVO-WASPAS-2N, derived from the unprecedented junction of SAPEVO-M (Simple Aggregation of Preferences Expressed by Ordinal Vectors – Multi Decision Makers) methods and WASPAS-2N (Weighted Aggregated Sum Product Assessment) with two standardization techniques. The application of the hybrid model SAPEVO-WASPAS-2N proved to be consistent and robust, generating two possibilities of ordering priorities aligned with the strategic situation of the organization based on the criteria established through the opinion of the decision makers.

Background: Hypoxia is harmful to tissues because it predisposes them to anaerobic metabolism and cell death. This lack of oxygen to tissues becomes more significant during anaesthesia. Dexmedetomidine, a novel drug in the anaesthesiology arsenal, has many appealing anaesthetic properties. If this drug also has tissue protective effects after hypoxia, it will increase interest in its use in sick patients. Methodology: As a result, primary cell cultures of chick embryos were used in this study to examine the cytotoxic potential of a standard drug, dexmedetomidine, and its effects on cells induced with hypoxia by a chemical inducer such as Cobalt chloride. Results and Conclusion: With the use of the drug, the effects of hypoxia within the cellular environment were significantly less. This is the first such study on an important anaesthetic drug. The anti-hypoxic quality of this drug may prove that the drug be very useful in conducting major operations.

Various ICT usage has changed our lives in many ways including the work culture of the organization, hence exposes information assets to various threats. This happen when the technology is not handled and managed well. One of the key causes for information security breaches and violations is originated by current and former employees. Employees within organizations have frequently been identified as the weakest link regarding information security. Information security culture has become an important component towards the security exercise in the organization. However, the holistic concept of Information Security Culture has not been extensively testified. The aim of this article is to comprehend common element of ISC used by previous studies on employee’s information security compliance, to explore the different theoretical lenses used in the cultivation of ISC and to investigate the available frameworks that relate to ISC through Systematically Literature Review (SLR). The SLR focuses on the paper published from 2010 to 2020. By adopting Kitchenham and Charters 98 papers were finalized for the critical analysis. In conclusion, the existing research has engaged on a broad set of research topics, but with inadequate deepness. It does not address the effects of different information security cultures influences, elements, application of theories and frameworks in different organization and no focus how the knowledge of ISC and its maturity towards practical implications.

The relevance of ESG measures published from company sustainability reports has experienced significant growth. Over the last years, various methodologies and MCDM techniques to assess the ESG performance of companies have been developed. Our paper develop a novel hybrid methodology that combines AHP and TOPSIS techniques under a neutrosophic environment (N-AHP) to address uncertainty, complexity, and vagueness, i.e., the linguistic variables of expert opinions and decision makers are expressed by triangular neutrosophic number (SVTN). A case study is presented to explain in detail the algorithm of the decision process based on the research of the main companies in the oil and gas industry. A comparative analysis with other similar techniques is carried performed to complete the work where the effectiveness of the new proposed methodology is demonstrated.

The introduction of 4G LTE communication technology was basically designed to meet the increasing demand by users for high quality multimedia services, data communication speed and improved quality of service (QOS). It is pertinent to note that with an ever-increasing subscriber base, it is essential to assess and analyse the network performance. To perform this task, there is need to use the key performance indicators. This research study tends to evaluate KPI’s gathered from field measurements, using statistical approach to establish the performance and determine the present condition of the quality of service offered by a 4G LTE network in Port Harcourt, Nigeria. In this study, drive test approach was adopted to measure the KPI’s and analysis was achieved with the use of TEMs Discovery software adopting statistical approach. The result showed the value range of the measured KPI’s were; RSSI (-90, -49.7dBm), RSRP (-117.7, -68.6 dBm), RSRQ (-14.2, -22.8dB) representing minimum and maximum values. The probability distribution of the various KPI’s indicated that the best signal ranges were distributed as 38.21%, 69.63% and 65.63% for RSSI, RSRP and RSRQ respectively. The KPI parameters were within acceptable range, though require optimization to provide better service for a greater population.

The selection of air freighter type is a strategic decision for air cargo carriers. Aim of this study is to provide a methodology for Turkish air cargo carriers to help them determine the best air freighter type in terms of their business models. The study is applied criteria including qualitative and quantitative drawn from the related literature and experts. AHP technique is used to determine criterion weights. TOPSIS and VIKOR techniques are utilized to select the best alternative freighter type. Findings show that A330-200F and B777F freighter types as the top two freighters for sector-wide results.

The distributed flow shop scheduling (DFSS) problem is an important problem studied in the literature. In flow shop scheduling, the route of each job is the same and the order of the jobs on the machines is determined. In the DFSS problem, on the other hand, the assignment of jobs to factories is carried out in addition to the determination of order of the jobs. In this study, machine-factory dependent setup times, non-identical factories, position-based learning effect on processing times and setup times, and factory eligibility constraints are considered for DFSS problem. A mathematical model is proposed for the solution of the problem. The addressed problem is defined considering the scheduling problem of ERP projects. Since the problem is NP-hard, a multi- start iterative tabu search (ITS) algorithm is proposed for the solution of large scale problems. An encoding scheme, decoding algorithm, local search and multi- start strategy are proposed for the solution of the problem by ITS algorithm. The parameters of the proposed algorithm are determined by the Taguchi experimental design method. The success of the proposed ITS algorithm is demonstrated by comparing it with the state- of- the art heuristic algorithms such as genetic algorithm (GA), simulated annealing (SA) algorithm and tabu search (TS) algorithm. As a result, the proposed heuristic algorithm was found more successful than the algorithms in the literature. The superiority of the ITS algorithm has also been shown statistically.

In today’s world of connectivity there is a huge generation of data than we could imagine. The number of network users are increasing day by day and there are large number of social networks which keeps the users connected all the time. The social networks gives the complete independence to the user to post the data either political, commercial or of entertainment value. Some data among which may be sensitive and will have greater impact on the society. The trustworthiness of each and every data is important when it comes to public social networking sites like face book, twitter etc... Due to large user base and its openness there is huge possibility to spread spam messages in this network. Spam detection is a technique to identify and mark a data as a false data value. There are lot of machine learning approaches proposed to detect spams in social networks. The efficiency of any spam detection algorithm is determined by its cost factor and accuracy. Aiming to improve the detection of spams in the social networks this study proposes using statistical based features that are modelled through the supervised boosting approach called Stochastic Gradient Boosting to evaluate the twitter data sets in English language. The performance of the proposed model is evaluated using simulation results.

The interfacial sliding motion of carbon nanotubes (CNTs) within a polymeric hosting matrix gives rise to energy dissipation. By tuning the interfacial shear strength (ISS) of the CNT-matrix interface, the dissipation can take place within tunable ranges of strain amplitudes. This is the basis for conceiving new multilayered carbon nanotube nanocomposites in which different layers with tunable ISS can lead to a concurrent optimization of strength and dissipation, often seen as two conflicting targets. Such optimization is tackled by a novel meso-mechanical nonlinear inelastic model proven to effectively predict the damping capacity of CNT nanocomposites. The proposed elastoplastic, rate- independent, constitutive theory is based on the mean-field homogenization method which combines the Eshelby equivalent inclusion method, the Mori-Tanaka homogenization, and the concept of inhomogeneous inclusions with inelastic eigenstrains introduced to describe the inelastic stick-slip. Since the ISS parameter plays a key role in the nanocomposite strength and dissipation, the current work seeks to improve the strength and damping properties by suitable interfacial CNT-matrix functionalization. Variations of the ISS parameter can be achieved by a functionalization that affects the chemical bonds between CNTs and hosting matrix. A set of experimental tests - including DMA analysis, calorimetry and spectroscopy — aims to evaluate the influence of the ISS parameter, together with other constitutive parameters, on the nanocomposite strength and damping capacity.

The interfacial sliding motion of carbon nanotubes (CNTs) within a polymeric hosting matrix gives rise to energy dissipation. By tuning the interfacial shear strength (ISS) of the CNT-matrix interface, the dissipation can take place within tunable ranges of strain amplitudes. This is the basis for conceiving new multilayered carbon nanotube nanocomposites in which different layers with tunable ISS can lead to a concurrent optimization of strength and dissipation, often seen as two conflicting targets. Such optimization is tackled by a novel meso-mechanical nonlinear inelastic model proven to effectively predict the damping capacity of CNT nanocomposites. The proposed elastoplastic, rateindependent, constitutive theory is based on the mean-field homogenization method which combines the Eshelby equivalent inclusion method, the Mori-Tanaka homogenization, and the concept of inhomogeneous inclusions with inelastic eigenstrains introduced to describe the inelastic stick-slip. Since the ISS parameter plays a key role in the nanocomposite strength and dissipation, the current work seeks to improve the strength and damping properties by suitable interfacial CNT-matrix functionalization. Variations of the ISS parameter can be achieved by a functionalization that affects the chemical bonds between CNTs and hosting matrix. A set of experimental tests - including DMA analysis, calorimetry and spectroscopy – aims to evaluate the influence of the ISS parameter, together with other constitutive parameters, on the nanocomposite strength and damping capacity