Student performance is related to complex and correlated factors. The implementation of a new advancement of technologies in educational displacement has unlimited potentials. One of these advances is the use of analytics and data mining to predict student academic accomplishment and performance. Given the existing literature, machine learning (ML) approaches such as Artificial Neural Networks (ANNs) can continuously be improved. This work examines and surveys the current literature regarding the ANN methods used in predicting students’ academic performance. This study also attempts to capture a pattern of the most used ANN techniques and algorithms. Of note, the articles reviewed mainly focused on higher education. The results indicated that ANN is always used in combination with data analysis and data mining methodologies, allowing studies to assess the effectiveness of their findings in evaluating academic achievement. No pattern was detected regarding selecting the input variables as they are mainly based on the context of the study and the availability of data. Moreover, the very limited tangible findings referred to the use of techniques in the actual context and target objective of improving student outcomes, performance, and achievement. An important recommendation of this work is to overcome the identified gap related to the only theoretical and limited application of the ANN in a real-life situation to help achieve the educational goals.

Software as a Service (SaaS) is widely used and depended on by a wide range of applications. Considering this, the SaaS should capacitate itself to offer service to a large number of customers having their own specific requirements, without encountering software quality problems. Therefore, several researchers delved into the SaaS customization, and many customization solutions have been proposed. However, heretofore, no analysis or study explicitly classifies these proposals using different criteria, e.g., the kind of change required, the component of the software requiring changes, and the quality attributes of the SaaS considered in each proposed solution. This paper adopts the systematic mapping approach to methodically investigate the solutions recommended for the SaaS customization problems. These solutions are classified into various categories to create a classification scheme based on the customization types (personalization, configuration, composition, modification, integration, and extension), customization layer (user interfaces, workflows, services, and data), and quality attributes. Our study identified 81 primary studies reporting SaaS customization solutions. The results show that the configuration, composition, and extension received the highest consideration in the proposed solutions. In addition, the majority of the proposed solutions for the SaaS customization are connected with the workflow and service layers. Furthermore, the attributes, such as multi-tenancy, security, functionality, scalability, availability, and efficiency, are considered much more often than other attributes. The classification of the proposed solutions for the SaaS customization and results of this paper can play an important role in creating a framework for the SaaS customization assessment.

Despite the benefits of standardization, the customization of Software as a Service (SaaS) application is also essential because of the many unique requirements of customers. This study, therefore, focuses on the development of a valid and reliable software customization model for SaaS quality that consists of (1) generic software customization types and a list of common practices for each customization type in the SaaS multi-tenant context, and (2) key quality attributes of SaaS applications associated with customization. The study was divided into three phases: the conceptualization of the model, analysis of its validity using SaaS academic-derived expertise, and evaluation of its reliability by submitting it to an internal consistency reliability test conducted by software-engineer researchers. The model was initially devised based on six customization approaches, 46 customization practices, and 13 quality attributes in the SaaS multi-tenant context. Subsequently, its content was validated over two rounds of testing after which one approach and 14 practices were removed and 20 practices were reformulated. The internal consistency reliability study was thereafter conducted by 34 software engineer researchers. All constructs of the content-validated model were found to be reliable in this study. The final version of the model consists of 6 constructs and 44 items. These six constructs and their associated items are as follows: (1) Configuration (eight items), (2) Composition (four items), (3) Extension (six items), 4) Integration (eight items), (5) Modification (five items), and (6) SaaS quality (13 items). The results of the study may contribute to enhancing the capability of empirically analyzing the impact of software customization on SaaS quality by benefiting from all resultant constructs and items.

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In this manuscript, three new classes of log-type imputation techniques have been proposed to handle missing data when conducting surveys. The corresponding classes of point estimators have been derived for estimating the population mean. Their properties (Mean Square Errors and bias) have been studied. An extensive simulation study using data generated from normal, Poisson, and Gamma distributions, as well as real dataset, has been conducted to evaluate how the proposed estimator performs in comparison to several contemporary estimators. The results have been summarized, and discussion regarding real-life applications of the estimator follows.

Perpendicular rate of recurrence splitting up a group of numeral television or radio channels that are mixed together for broadcast Orthogonal Frequency Division Multiplexing which can be a potential diffusion method for elevating the transmission capacity of the communication systems. In spite of the significance of OFDM, the primary issue of the peak-to-average power ratio (PAPR) which augments communication system complications, reduces the effectiveness of the communication system, resulting in low performance of bit-error-rate (BER), and making OFDM perceptive toward non-linear distortion within a broadcast. Various techniques were projected for treating PAPR issues, inclusive of partial transmit sequence (PTS) which captivated great interest. Thus, this paper proposed a hybrid method inclusive of a boosted PTS scheme with Mu-law compressing and expanding approach. The PTS approach was boosted through boosting its sub-block partitioning scheme, the place where the aggrandized partitioning scheme consolidated a conventional interleaved partitioning into an adjacent partitioning scheme. The present merger concerning Mu-Law characteristic in time domain for PAPR reduction in OFDM fundamentally boosts PAPR diminution performance. Accordingly, though the simulated pseudorandom sub-block partition method improved PAPR diminution supplementary further than other sub-block partition schemes appertaining to conventional PTS, while maintaining low computational complexity. The findings show that the boosted PTS scheme with Mu-law expanding approach, whilst upholding low computational complexity, achieves considerably superior to the pseudorandom partitioning PTS with regard to various type of modulation format and subcarriers.

The synthetic material developed by Dupont in 1963 for solid surfaces has been used since its origin for numerous applications. One of the most popular ones in the last decade is as a finishing layer on façades. The first references that contemplated this use on the outside were the Seeko’o hotel in Bordeaux executed in 2007 and the refurbishment of the 7700 m2 shell of the Hôtel Ivoire congress centre in Abidjan (Ivory Coast) in 2009. In Spain, the first example of the installation of this material is the rehabilitation of the main building of the La Rotonda de la Playa de San Juan urbanisation in Alicante, designed in 1965 by the architect Juan Guardiola Gaya and rehabilitated in 2010 by Miguel Salvador Landmann. Ten years later, our research is focused on the study of the colour ageing of the acrylic resin and natural mineral sheets on each of its façades, with different orientations and exposure to sea and wind. To this end, it has been studied the solar radiation of the surfaces, the wind exposure of their façades and tests with a tele-spectroradiometer has been carried out. The study makes it possible to quantify the differences in colour in all of them and to state that the combination of wind and radiation is the main atmospheric agent causing the degradation.

The key feature of SaaS application is that it addresses the needs of many different customers using only one software, rather than multiple developments and versions, a concept known as multi-tenancy. However, it typically results in a one-size-fits-all approach and the application only fulfills the requirements that are generic to all tenants. Therefore, a multi-tenancy SaaS application is reliant upon an ability to be customized in order to be successful. Responding to distinctive needs of each customer and maintaining the key feature of developing SaaS application creates complexity in SaaS customization. This paper delves into some challenges related to SaaS customization, and then maps among these challenges in order to structure the problem and objective trees of SaaS customization. This paper may serve as a step towards reducing complexity in SaaS customization.