Metal complexes chrome(III), manganese(II), iron(III), cobalt(II), nickel(II), cupper(II) and zinc(II) with diazonium of 3-amino-2-chloropyridine of general formula [2-Cl-C₅H₃N≡N]_n[MX_m], where n=2 or 3 for divalent and trivalent metal, m= 4 or 6  were synthesized. The complexes have been characterized by flame atomic absorption, (C.H.N), molar conductance, magnetic susceptibility UV-vis spectra, infrared spectra,¹H-NMR spectroscopy and thermo gravimetric analysis (TGA and DTA). The measurements showed that the divalent metal ion complexes (M²⁺) have (1:2) M:L ratio with tetrahedral geometry around metal ions while the trivalent metal ions (M³⁺) formed (1:3) m

A new method based on the Touchard polynomials (TPs) was presented for the numerical solution of the linear Fredholm integro-differential equation (FIDE) of the first order and second kind with condition. The derivative and integration of the (TPs) were simply obtained. The convergence analysis of the presented method was given and the applicability was proved by some numerical examples. The results obtained in this method are compared with other known results.

In this paper, Touchard polynomials (TPs) are presented for solving Linear Volterra integral equations of the second kind (LVIEs-2k) and the first kind (LVIEs-1k) besides, the singular kernel type of this equation. Illustrative examples show the efficiency of the presented method, and the approximate numerical (AN) solutions are compared with one another method in some examples. All calculations and graphs are performed by program MATLAB2018b.

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Nitrogen-comprising heterocyclic compounds and their derivatives have empirically been invaluable as therapeutic agents. Fundamentally, 4-chloro-6-nitro-2-amino-1,3-benzothiazole 1 was synthesized via bromination of 2-chloro-4-nitro aniline with ammonium thiocyanate. This new heterocyclic haloorganoamino-1,3-benzothiazole derivative, was a starting material, which condensed and tethered with three different aromatic aldehyde pendant arm in presence of ethanol and glacial acetic acid isolating an interesting sequence of tridentate Schiff bases 2-4. These compounds were used for complexation reactions in 1:1 (metal: ligand) stoichiometry to obtain heteroleptic Al(III), Ni (II) and K(I) benzothiazole chelat

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

The present study aimed to identify teaching problems which facing the teachers for first three grades classes, and if these problems different according to some variables teacher qualification, experience period, class grade). The study sample consist of (137 )

 female teachers who teach the first three grades in Braimy city in Oman, teachers spread in five government schools. Both researchers developed questionnaire to measure problems faced by the mentioned teachers, consist of 50 questions distributed into 4 dimensions (teacher, students, the curriculum, the evaluations), Also researchers checked questionnaire validity and stability. The results indicate to: The most common probl

For many problems in Physics and Computational Fluid Dynamics (CFD), providing an accurate approximation of derivatives is a challenging task. This paper presents a class of high order numerical schemes for approximating the first derivative. These approximations are derived based on solving a special system of equations with some unknown coefficients. The construction method provides numerous types of schemes with different orders of accuracy. The accuracy of each scheme is analyzed by using Fourier analysis, which illustrates the dispersion and dissipation of the scheme. The polynomial technique is used to verify the order of accuracy of the proposed schemes by obtaining the error terms. Dispersion and dissipation errors are calculated

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie