Preparation and characterisation of TIG-alloyed hybrid composite coatings for high-temperature tribological applications

There is an increasing interest in the tribology community for developing high-performance composite coatings to meet severe tribological conditions in advanced mechanical systems which require high operating temperature and long life. In the present work, powder preplacement and tungsten inert gas (TIG) torch melting techniques have been employed to generate titanium carbide (TiC)-based composite coatings containing hexagonal boron nitride (hBN) or Ni–P coated hBN (Ni–P-hBN) lubricant additive. The effects of preplaced powder composition on the cross-sectional microstructures and surface hardnesses of the developed coatings were analysed. Furthermore, the friction and wear behaviours of the composite coatings at 600°C were evaluated using a Ducom ball-on-disc wear test rig. The results indicate that the TIG-melted surface containing TiC and Ni–P-hBN powder mixtures exhibits optimum properties combining good control of microstructures and uniformly distributed hardness as well as excellent tribological properties due to the enhanced wettability action of Ni–P encapsulated hBN particles

Estimation parameters using bisquare weighted robust ridge regression BRLTS estimator in the presence of multicollinearity and outliers

This study presents an improvement to robust ridge regression estimator. We proposed two methods Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) based on ridge least trimmed squares RLTS and ridge least absolute value (RLAV) respectively. We compared these methods with existing estimators, namely ordinary least squares (OLS) and Bisquare ridge regression (BRID) using three criteria: Bias, Root Mean Square Error (RMSE) and Standard Error (SE) to estimate the parameters coe±cients. The results of Bisquare ridge least trimmed squares (BRLTS) and Bisquare ridge least absolute value (BRLAV) are compared with existing methods using real data and simulation study. The empirical evidence shows that the results obtain from the BRLTS are the best among the three estimators followed by BRLAV with the least value of the RMSE for the diÆerent disturbance distributions and degrees of multicollinearity

Comparative study on feature selection techniques in intrusion detection systems using ensemble classifiers

Network usage has become a paramount aspect of life, therefore, securing our networks is crucial. The world is experiencing a rapid breakthrough of internet usage, most especially with the concept of internet of things (IoT), now internet of everything (IoE. ). Real network data is rowdy, noisy and inconsistent. These issues with the data influences the performance of intrusion detection systems (IDS) and develop manifold of false alarms. Feature selection technique is used to remove the inconsistent and rowdy data from a large data set and presents a refined set of data. This research work adopts the use of two distinct feature selection technique in parallel: ReliefF ranking and particle swarm optimization, using linear discriminant analysis (LDA) and logistic regression (LR) as the machine learners, to first clean the data, train the classifiers, and subsequently classify new instances. The results showed that, the combination of the ReliefF with the ensemble machine learning (Linear Discriminant Analysis and Logistic Regression) has a higher classification accuracy of 99.7% compared to the Particle swarm optimization (PSO) which attained an accuracy of 98.6%

Online Formative Assessment Practices Among Academics of Tertiary Education in Sokoto State, Nigeria

Purpose: This study examines the effect of two main factors, that is, lack of knowledge of ICT, and the availability of ICT facilities such as hardware, software, and internet access, which identified to be the common barriers towards practicing online formative assessment.   Theoretical framework:  Many educational institutions have been urged to adopt online learning due to the development of communications and digital device technology as well as the COVID-19 pandemic that ravaged the world in the previous two years. The shift from offline to online mode affects how formative assessment should be conducted during teaching and learning. The lack of knowledge of information and communication technology (ICT) and ICT facilities are prevalent in Nigeria.   Design/methodology/approach: This study employed a survey design to examine online assessment feedback practice as well as factors contributing to the practices among 256 academics in one tertiary education in Sokoto. Descriptive and inferential statistical analyses were used.   Findings: Online formative assessment feedback practice is at low level due to lack of knowledge of software applications and facilities.   Research, Practical & Social implications: Government needs to invest more on educational technology by providing adequate ICT facilities in tertiary institutions in Sokoto, as well as offering suitable trainings on ICT literacy for academics.   Originality/value: Online formative assessment contributes to enhancement in educational attainment and efficiency in learning and teaching

Enhanced Clustering Routing Protocol for Power-Efficient Gathering in Wireless Sensor Network

Wireless sensor network (WSN) is a new and fast advancing technology, which is opening up many opportunities in the field of remote sensing and data monitoring. In spite of the numerous applications of WSN, issues related to determining a suitable and accurate radio model that will foster energy conservation in the network limit the performance of WSN routing protocols. A number of radio models have been proposed to address this issue. However, the underlying assumptions and inaccurate configuration of these radio models make them impractical and often lead to mismanagement of scarce energy and computational resources. This paper addresses this problem by proposing an enhanced radio model that adapts to the frequent changes in the location of the sensor nodes and is robust enough to report reliable data to the base station despite fluctuations due to interference. The impact of incorporating stepwise energy level and specialized data transmission schemes in the proposed radio model is also investigated in this paper. The performance of the proposed radio model is evaluated using OMNET++ and MATLAB and the results obtained is benchmarked against PEGASIS. It is shown by simulation that the novel LEACH-IMP performs better with respect to energy consumption, number of links faults, number of packets received, signal attenuation, and network lifetime

PERSPECTIVES ON CONSUMERS’ RESPONSE TO CORPORATE SOCIAL RESPONSIBILITY

Purpose: This study presents a review of literature on consumers' perception and responses towards the perceived corporate social responsibility (CSR) of companies, with a view to provide additional insight into the phenomenon. Methodology/Approach: The study is essentially a review of existing literature, which entails the identification, review and synthesis of existing studies on the phenomenon. Findings: The review of previous studies on the subject matter reveals that there is no general consensus on the findings regarding consumers' perceptions and response to CSR. The findings from previous studies have been equivocal and largely inconclusive as to whether consumers reward companies CSR efforts with positive responses. Research limitations: The research is basically a review and synthesis of previously conducted studies, and no new data was collected. Practical implications: The findings and conclusions of this study have practical implications for research on the topic of consumers' perceptions and response to perceived social responsible behavior of companies. Essentially, the findings point to the fact that the field of study relating to how the consumers perceive and respond to CSR remains a fertile ground from research to enable management theorists and practitioners get a better understanding of the phenomenon. Originality/Value: The study highlights some important reasons for the mixed findings in previous studies, and further points to the need for researchers to adopt varied methodologies/approaches when conducting researches on how consumers perceive and respond to CSR in contextually different environments

Time division multiple access scheduling strategies for emerging vehicular ad hoc network medium access control protocols: a survey

[EN] Vehicular ad hoc network (VANET) is an emerging and promising technology, which allows vehicles while moving on the road to communicate and share resources. These resources are aimed at improving traffic safety and providing comfort to drivers and passengers. The resources use applications that have to meet high reliability and delay constraints. However, to implement these applications, VANET relies on medium access control (MAC) protocol. Many approaches have been proposed in the literature using time division multiple access (TDMA) scheme to enhance the efficiency of MAC protocol. Nevertheless, this technique has encountered some challenges including access and merging collisions due to inefficient time slot allocation strategy and hidden terminal problem. Despite several attempts to study this class of protocol, issues such as channel access and time slot scheduling strategy have not been given much attention. In this paper, we have relatively examined the most prominent TDMA MAC protocols which were proposed in the literature from 2010 to 2018. These protocols were classified based on scheduling strategy and the technique adopted. Also, we have comparatively analyzed them based on different parameters and performance metrics used. Finally, some open issues are presented for future deployment.Tambawal, AB.; Noor, RM.; Salleh, R.; Chembe, C.; Anisi, MH.; Michael, O.; Lloret, J. (2019). Time division multiple access scheduling strategies for emerging vehicular ad hoc network medium access control protocols: a survey. Telecommunication Systems. 70(4):595-616. https://doi.org/10.1007/s11235-018-00542-8S59561670

CMOS-compatible multi-band plasmonic TE-pass polarizer

A CMOS-compatible plasmonic TE-pass polarizer capable of working in the O, E,S, C, L, and U bands is numerically analyzed. The device is based on an integrated hybrid plasmonic waveguide (HPW) with a segmented metal design. The segmented metal will avoid the propagation of the TM mode, confined in the slot of the HPW, while the TE fundamental mode will pass. The TE mode is not affected by the metal segmentation since it is confined in the core of the HPW. The concept of the segmented metal can be exploited in a plasmonic circuit with HPWs as the connecting waveguides between parts of the circuit and in a silicon photonics circuit with strip or slab waveguides connecting the different parts of the circuit. Using 3D FDTD simulations, it is shown that for a length of 5.5 μm the polarization extinction ratios are better than 20 dB and the insertion losses are less than 1.7dB over all the optical communication bands

Effect of stir casting process parameters on tribological performance of Al6061-SiCp composite

In this study, the tribological performance of Al6061-SiCp composite is investigated considering the influence of stir casting process parameters. The wear and frictional characteristics were studied using the dry reciprocating wear testing machine. Experimentation is generated through the central composite design (CCD) using a four factor five level design plan. The process parameters (reinforcement fraction wt%, stirring speed rpm, processing temperature °C and processing time s) are examined using ANOVA and multiple objective optimization (MOO) analysis. The result shows that stirring speed has the most significant contribution in controlling the wear and friction characteristics. Confirmation test is also conducted to verify and validate the process parameters in order to optimize the tribological output. Moreover, characterization of the composite wear scar mechanism is performed using scanning electron microscope. This study provides an effective method of minimizing the tribological properties of Al6061-SiCp composite by optimizing the stir casting process parameters

Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency

Regression testing performed to provide confidence on the newly or updated software system is a resource consuming process. To ease this process, various techniques are developed. One such technique, test case prioritization, orders test cases with respect to the goals such that the most important test case in achieving those goals is scheduled earlier during the testing session. Among such performance goals, the rate of faults detections, measure how faults are detected quickly throughout the regression testing process. Improved dependency detection among faults provides faster feedback to the developers which gives chance to debug leading faults earlier in time. One other goal, the rate of fault severity detection, measure how fast severe fault can be detected in the testing process. Although, previous works address these issues but assumed that the costs of executing test cases and severities of detected faults are the same. However, costs of test and severities of faults varied. Furthermore, they did not consider incorporating evolution process such as applying genetic algorithms to their technique. In this work, we proposed an evolutionary cost-cognizant regression testing approach that prioritizes test case according to the rate of severity detection of test cases connected with dependent faults using genetic algorithms. The aim is to reveal more severe leading faults earlier using least cost in executing the test suite and to measure the efficacy of the technique using APFDc