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We compare two approaches of incorporating the long‐range Coulomb electron‐electron interaction into Monte Carlo simulations of bulk, degenerate GaAs, i.e., the semi‐classical approach of solving the Poisson equation self‐consistently, and the first order quantum mechanical treatment in which the electron‐plasmon interaction is included as an additional scattering mechanism. The critical issues involved in the semi‐classical, direct approach are the mesh size, charge assignment to the mesh nodes, and interpolation of the field at the particle location. All of these factors determine the stability of the system, the accuracy and computational time required in the calculation. The steady‐state electron drift velocity in bulk GaAs calculated using the direct, semi‐classical approach for the electron‐plasmon interaction is significantly less than the corresponding bulk drift velocity in the absence of the electron‐plasmon interaction. The alternative approach of treating the electron‐plasmon interaction as a scattering mechanism is attractive since it is computationally easier to include and is, at least to first order, quantum mechanically based. It is found that the calculated steady‐state electron drift velocity in bulk GaAs based on this model is affected in the opposite way, i.e., the velocity is greater than in the absence of the electron‐plasmon interaction. The cause of the discrepancy in the calculated results of the two approaches is not too surprising since they attack the problem from very different directions. Neither model can at present be considered complete. Further detailed investigations are required to achieve a better model for the electron‐plasmon interaction.

The present study is undertaken in the region of Guelma that is located in North-Eastern Algeria. Guelma’s agricultural plain is irrigated from the Seybouse ephemeral river (wadi). The latter collects the entire domestic and industrial wastewaters of the region that are discharged without prior treatment. Hence, the organic and biological or what so ever contributions to the wadi are capable of initiating a significant degradation of its waters’ quality and challenging their use for irrigation. The paper aims to discuss these issues.

The interpretation of the results of three sampling campaigns for chemical and bacteriological analyzes was carried out in terms of the indices’ method (organic pollution index (OPI) and microbiological quality index (MQI)). The results were statistically assessed through the use of the principal component analysis (PCA). The OPI was calculated according to the method of Leclercq and Maquet (1987) whose principle is to classify the contents for the polluting elements into 5 classes each class corresponding to a given range for the considered parameter, and then to calculate the overall average class number for each sample. The MQI depends on the water concentrations in: the total coliforms, the fecal coliforms, and fecal streptococci. One defines five classes of concentrations for each of these parameters. The MQI is again the overall mean of the numbers for the classes for every parameter.

The OPI reflects a moderate pollution for most sampling stations. The PCA indicates that the variables controlling salinity are mainly Cl⁻, Na⁺ and SO₄²⁻. In August 2016, El-Fedjoudj pumping station shows a very strong fecal contamination. According to the recommendations of World Health Organization (1989), waters from wadi Seybouse cannot be used for the irrigation of vegetable crops if they were to be consumed raw.

This study has an environment impact as it reveals the need to protect surface waters used for irrigation and therefore protect consumers of raw vegetables that are to be consumed uncooked.

In visual-based applications, lighting conditions have a considerable impact on quality of the acquired images. Extremely low or high illuminated environments are a real issue for a majority of cameras due to limitations in their dynamic range. Indeed, over or under exposure might result in loss of essential information because of pixel saturation or noise. This can be critical in computer vision applications. High dynamic range (HDR) imaging technology is known to improve image rendering in such conditions. The purpose of this paper is to investigate the level of performance that can be achieved for feature detection and tracking operations in images acquired with a HDR image sensor.

In this study, four different feature detection techniques are selected and tracking algorithm is based on the pyramidal implementation of Kanade-Lucas-Tomasi (KLT) feature tracker. Tracking algorithm is run over image sequences acquired with a HDR image sensor and with a high resolution 5 Megapixel image sensor to comparatively assess them.

The authors demonstrate that tracking performance is greatly improved on image sequences acquired with HDR sensor. Number and percentage of finally tracked features are several times higher than what can be achieved with a 5 Megapixel image sensor.

The specific interest of this work focuses on the evaluation of tracking persistence of a set of initial detected features over image sequences taken in different scenes. This includes extreme illumination indoor and outdoor environments subject to direct sunlight exposure, backlighting, as well as dim light and dark scenarios.

The purpose of this paper is to examine factors that affect Palestinian customers’ use of online banking services.

An empirical study was conducted using a questionnaire in order to test the hypotheses. The questionnaire was distributed to 500 respondents selected by the participating banks. A total of 369 complete questionnaires were returned. The study’s independent variables include technology adoption propensity, customers’ value for online personalization, customers’ privacy concern, e-trust, technological leadership and loyalty. Palestinian customers’ usage of online banking services is the dependent variable.

The results of the model tested clearly suggest that the use of online banking services is influenced, respectively, by the technological leadership, e-trust, e-loyalty, customers’ value for online personalization, customers’ concern for privacy and propensity of technology adoption. Finally, this paper suggests that policy makers should develop a prioritized hierarchy of actions in developing the effective use of bank’s online services, based on the t- and p-values of the latter mentioned factors.

One limitation of the study is relying on self-reported cross-sectional data collection, rather than longitudinal surveying. Despite such limitation, the study provides the Palestinian banking sector with recommendations to promote online banking services based on the empirically identified factors affecting such service adoption.

Palestinian banks should promote the adoption of online banking services by supporting personalization of services, privacy and trust. Customers should always be informed that their bank is among the first banks to introduce the latest state-of-the-art online services. Technology innovative and diverse online services should be offered by banks to attract customers.

Although numerous research studies have studied the factors affecting customers in using electronic and online banking services, few studies have considered such usage in the developing countries, such as Arab countries in general and Palestine in particular. This is the first study to examine the factors affecting the adoption of online banking services in Palestine. This study provides empirical evidence to fill in the gap by providing a deeper understanding of the factors affecting the usage of online banking services in the country. The findings of this study can help decision makers in the Palestinian banks to develop practical plans that might accelerate and expand the adoption of online banking emphasizing personalized and trusted services offered with high level of security and privacy.

This paper aims to propose an approach to automatically annotate a large corpus in Arabic dialect. This corpus is used in order to analyse sentiments of Arabic users on social medias. It focuses on the Algerian dialect, which is a sub-dialect of Maghrebi Arabic. Although Algerian is spoken by roughly 40 million speakers, few studies address the automated processing in general and the sentiment analysis in specific for Algerian.

The approach is based on the construction and use of a sentiment lexicon to automatically annotate a large corpus of Algerian text that is extracted from Facebook. Using this approach allow to significantly increase the size of the training corpus without calling the manual annotation. The annotated corpus is then vectorized using document embedding (doc2vec), which is an extension of word embeddings (word2vec). For sentiments classification, the authors used different classifiers such as support vector machines (SVM), Naive Bayes (NB) and logistic regression (LR).

The results suggest that NB and SVM classifiers generally led to the best results and MLP generally had the worst results. Further, the threshold that the authors use in selecting messages for the training set had a noticeable impact on recall and precision, with a threshold of 0.6 producing the best results. Using PV-DBOW led to slightly higher results than using PV-DM. Combining PV-DBOW and PV-DM representations led to slightly lower results than using PV-DBOW alone. The best results were obtained by the NB classifier with F1 up to 86.9 per cent.

The principal originality of this paper is to determine the right parameters for automatically annotating an Algerian dialect corpus. This annotation is based on a sentiment lexicon that was also constructed automatically.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.