For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

The  lossy-FDNR  based  aclive  fil ter has an  important   property among  many  design  realizations. 'This includes  a significant reduction in component count particularly in the number  of OP-AMP which consumes   power.  However  the·  problem  of  this   type  is the  large component spreads  which affect the fdter performance.

In  this  paper   Genetic   Algorithm   is  applied   to  minimize   the component  spread   (capacitance  and  resistance  p,read). The minimization of these spreads allow the fil

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

The study aimed to recommend a new spectrophotometric-kinetic method for determination of carbamazepine (CABZ) in its pure form and pharmaceutical forms. The proposed procedure based on the coupling of CABZ with diazotized sulfanilic acid in basic medium to yield a colored azo dye. Factors affecting the reaction yield were studied and the conditions were optimized. The colored product was followed spectrophotometrically via monitoring its absorbance at 396 nm. Under the optimized conditions, two method (the initial rate and fixed time (10 minute)) were applied for constructing the calibration graphs. The graphs were linear in concentration ranges 2.0 to 18.0 µg.mL^-1 for both methods. The proposed was applied successfully in

The cathodic deposition of zinc from simulated chloride wastewater was used to characterize the mass transport properties of a flow-by fixed bed electrochemical reactor composed of vertical stack  of stainless steel nets, operated in batch-recycle mode. The electrochemical reactor employed potential value in such a way that the zinc reduction occurred under mass transport control. This potential was determined by hydrodynamic voltammetry using a borate/chloride solution as supporting electrolyte on stainless steel rotating disc electrode. The results indicate that mass transfer coefficient (K_m) increases with increasing of flow rate (Q) where .The electrochemical reactor proved to be efficient in removing zinc and was abl

Background: Cystinosis is a rare autosomal recessive lysosomal storage disease with high morbidity and mortality. It is caused by mutations in the CTNS gene that encodes the cystine transporter, cystinosin, which leads to lysosomal cystine accumulation. It is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. Elevated white blood cell cystine content is the cornerstone of the diagnosis. Since chitotriosidase (CHIT1 or chitinase-1) is mainly produced by activated macrophages both in normal and inflammator

The United States government allowed Native Americans to abandon their reservations in the 1950s and 1960s. The historical, social, and cultural backgrounds shaped the forms and themes of works by American Indian writers who urged people to refuse their culture's sense of shame. Moreover, their behavior corresponded with the restoration of individuals to their rituals after disappointment, loss of sense of life, and mental illness performed from the influence of mainstream American society. Among these writers, N. Scott Momaday and Leslie Marmon Silko participate in similar interest in portraying characters caught between indigenous beliefs and white mainstream standards.  

      The construction of