Many cloud providers offer very high precision services to exploit Optical Character Recognition (OCR). However, there is no provider offers Tifinagh Optical Character Recognition (OCR) as Web Services. Several works have been proposed to build powerful Tifinagh OCR. Unfortunately, there is no one developed as a Web Service. In this paper, we present a new architecture of Tifinagh Handwriting Recognition as a web service based on a deep learning model via Google Colab. For the implementation of our proposal, we used the new version of the TensorFlow library and a very large database of Tifinagh characters composed of 60,000 images from the Mohammed Vth University in Rabat. Experimental results show that the TensorFlow library based on a Tensor processing unit constitutes a very promising framework for developing fast and very precise Tifinagh OCR web services. The results show that our method based on convolutional neural network outperforms existing methods based on support vector machines and extreme learning machine.
Many cloud providers offer very high precision services to exploit optical character recognition (OCR). However, there is no provider that offers Tifinagh optical character recognition (OCR) as web services. Several works have been proposed to build powerful Tifinagh OCR. Unfortunately, there is no one developed as a web service. In this paper, the authors present a new architecture of Tifinagh handwriting recognition as a web service based on a deep learning model via Google Colab. For the implementation of the proposal, they used the new version of the TensorFlow library and a very large database of Tifinagh characters composed of 60,000 images from the Mohammed Vth University in Rabat. Experimental results show that the TensorFlow library based on a tensor processing unit constitutes a very promising framework for developing fast and very precise Tifinagh OCR web services. The resultsshow that the method based on convolutional neural network outperforms existing methods based on support vector machines and extreme learning machines.
Purpose The purpose of this paper is to highlight the interest of focusing public policies for wildfire management on behavioral changes supported by sustainable development projects dedicated to the Algerian forest heritage. Thus, the Aurès region in the eastern part of Algeria will be used as an example to illustrate the proposed new strategy. Design/methodology/approach The proposed method, guided by projects’ management in sustainable development, consists of developing a responsible citizenship strategy focused on behavioral changes of citizens. Therefore, the title of the proposed method: The Construct of Responsible Citizenship. Findings In order to cope with forest fires, the proposed approach highlights the interest of promoting responsible citizenship. Likewise, it outlines a tool for sustaining behavioral changes based on the principle of continuous improvement and field follow-up using a multicriteria approach known as “goal programming.” Practical implications The proposed new forest fire protection plan addresses the shortcomings in Algeria’s current forest fire management policy, which appears unable to deal with the increasing severity of forests’ fire risk that the country has been experiencing in recent decades. Originality/value The aim is to highlight the interest of investment in forest fires prevention within the framework of the sustainable development of Algerian forest heritage, specifically, to work toward citizen subcontracting of the Algerian forest heritage.
This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.
This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.
Automated plant classification using tree trunk has attracted increasing interest in the computer vision community as a contributed solution for the management of biodiversity. It is based on the description of the texture information of the bark surface. The multi-scale variants of the local binary patterns have achieved prominent performance in bark texture description. However, these approaches encode the scale levels of the macrostructure separately from each other. In this paper, a novel handcrafted texture descriptor termed multi-scale Statistical Macro Binary Patterns (ms-SMBP) is proposed to encode the characterizing macro pattern of different bark species. The proposed approach consists of defining a sampling scheme at high scale levels and summarizing the intensity distribution using statistical measures. The characterizing macro pattern is encoded by an in-depth gradient that describes the relationship between the scale levels and their adaptive statistical prototype. Besides this handcrafted feature descriptor, a learning-based description is performed with the ResNet34 model for bark classification. Extensive and comprehensive experiments on challenging and large-scale bark datasets demonstrate the effectiveness of ms-SMBP to identify bark species and outperforming different multi-scale LBP approaches. The tree trunk classification with ResNet34 shows interesting results on a very large-scale dataset.
According to a United Nations report, the proportion of the urban population living in informal houses worldwide had reached 23.5% in 2018, which means over 1 billion people have been living in slums, and an estimated 3 billion people will be requiring affordable housing by 2030. Slums are often linked to developing countries, where weak governance and misled socio-economic choices aggravate the situation and lead to continual conflict with the authorities. This research aims to model this conflict through Game Theory and shed the light on the different parameters that influence the decision-making process and finally propose a management model to limit the spread of this phenomenon as much as possible. This model will be applied in the city of Hassi Bahbah using ABM, the results of the game modeling allowed us to extract the delta threshold which will allow decision-makers to know when they have to make decisions. Our study aims to offer decision-makers a tool based on our model, allowing them to better manage and thus monitor the evolution of informal houses. The authors hope that the findings could provide means and insights for policies and strategic directions in land uses and planning systems.
Solanum pseudocapsicum L. (Solanaceae) et Calicotome villosa (Poir.) Link (Fabaceae) sont des plantes très utilisées dans la médecine traditionnelle en Algérie. Notre étude vise à démontrer des bases scientifiques de l’activité antibactérienne des feuilles de S.pseudocapsicum et des fleurs de C.villosa, plantes médicinales qui semblent êtres efficaces contre les infections bactériennes. Nous avons préparés différents extraits par l’utilisation de solvants à polarité croissante. Nos dosages ont montré que l’extrait aqueux est le plus riche en polyphénols pour S.pseudocapsicum alors que l’extrait d’acétate d'éthyle est le plus riche en flavonoïdes cas de l’extrait chloroformique de C.villosa. Les extraits issus de ces plantes ont été testés sur la croissance bactérienne, in vitro de dix souches ATCC par la technique de diffusion sur l’agar. Les résultats ont révélé que l’extrait d’acétate d’éthyle de S.pseudocapsicum et l’extrait chloroformique de C.villosa ont une activité antibactérienne dose-dépendante sur les souches bactériennes étudiées. Notons, l’action des extraits aqueux des deux plantes citées qui ont donné les meilleures valeurs antibactériennes sur les souches bactériennes utilisées. Ainsi, ces extraits peuvent être une ressource indéniable pour la mise au point de phyto-médicaments contre les infections bactériennes.
Sedimentation of dam reservoirs is a complex problem with several dimensions, including filling rates and characteristics of accumulated sediments. Sediment supply from river basins is particularly high in this region because of its semi-arid climate and especially because of poor vegetation protection. The amount of silt accumulated annually since the construction of this dam is estimated at 330000 m3. This silt accumulation strongly limits its storage capacity and consequently its operating duration. The consequences of this serious problem have been catastrophic, including a considerable reduction of 43–84% of the storage capacity of the dams and a clear degradation of water quality that can cause the degradation of the ecosystem functioning and can lead to irreversible changes. The silt present in abundance in the Algerian dams can, thus, constitute a potential resource to be judiciously exploited towards the increase of the performances of the construction materials. The extraction of sediments accumulated in the dam reservoir is, therefore, imperative. These sediments have a great geotechnical value. The objective of this study is to assess the feasibility of the recovery of mud by studying the knowledge of the sediments of the dam of Koudiat Medouar. The results of the tests carried out in laboratory allowed us to identify the various sediments from a physical and geotechnical point of view. These materials must of course meet certain rigorous criteria in terms of mechanical strength and durability and environmental impact. The experimental approach that we adopted allowed us to determine the characteristics of the materials necessary for the realization of compressed earth bricks (BTC) in conformity with the recommendations of the technical guides of construction.
Sedimentation of dam reservoirs is a complex problem with several dimensions, including filling rates and characteristics of accumulated sediments. Sediment supply from river basins is particularly high in this region because of its semi-arid climate and especially because of poor vegetation protection. The amount of silt accumulated annually since the construction of this dam is estimated at 330000 m3. This silt accumulation strongly limits its storage capacity and consequently its operating duration. The consequences of this serious problem have been catastrophic, including a considerable reduction of 43–84% of the storage capacity of the dams and a clear degradation of water quality that can cause the degradation of the ecosystem functioning and can lead to irreversible changes. The silt present in abundance in the Algerian dams can, thus, constitute a potential resource to be judiciously exploited towards the increase of the performances of the construction materials. The extraction of sediments accumulated in the dam reservoir is, therefore, imperative. These sediments have a great geotechnical value. The objective of this study is to assess the feasibility of the recovery of mud by studying the knowledge of the sediments of the dam of Koudiat Medouar. The results of the tests carried out in laboratory allowed us to identify the various sediments from a physical and geotechnical point of view. These materials must of course meet certain rigorous criteria in terms of mechanical strength and durability and environmental impact. The experimental approach that we adopted allowed us to determine the characteristics of the materials necessary for the realization of compressed earth bricks (BTC) in conformity with the recommendations of the technical guides of construction.
This paper is about the study of the well-posedness of a stochastic Cahn-Hilliard equation driven by white noise induced by a Q-Brownian motion. The proof of the existence of a unique global solution relies on the Galerkin method together with a monotonicity method.
This paper is about the study of the well-posedness of a stochastic Cahn-Hilliard equation driven by white noise induced by a Q-Brownian motion. The proof of the existence of a unique global solution relies on the Galerkin method together with a monotonicity method.
الهدف من هذه الدراسة هو معرفة أثر الوحدات التدريبية المقترحة بطريقة التدريب التكراري في التحسين من السرعة الانتقالية والقوة الانفجارية للأطراف السفلية للاعبي فريق كرة اليد للرياضة المدرسية(16-18 سنة)، حيث اعتمد الباحثان المنهج التجريبي، وكانت عينة الدراسة متكونة من 22 لاعبا لكرة اليد، 12 لاعبا مثلوا المجموعة التي أجريت عليهم التجربة الاستطلاعية واستبعدوا بعدها من التجربة الأساسية، و10 لاعبين مثلوا المجموعة التجريبية للدراسة، ودامت هذه التجربة مدة 09 أسابيع بتطبيق وحدات تدريبية بطريقة التدريب التكراري، وقد توصلنا إلى أهم النتائج التي بينت أن الوحدات التدريبية المقترحة بطريقة التدريب التكراري أثرت بصورة إيجابية في تحسين صفتي السرعة الانتقالية والقوة الانفجارية للأطراف السفلية للاعبي فريق كرة اليد للرياضة المدرسية، وأن طريقة التدريب التكراري التي أثبتت فعاليتها في التحسين من صفتي السرعة الانتقالية والقوة الانفجارية للأطراف السفلية.
