Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Receive money laundering phenomenon of interest to researchers and scholars on different intellectual orientation of economic or political or other, as this process is gaining paramount importance in light of business and increase the number of banks in the province of Kurdistan of Iraq and Erbil in particular and in the presence of openness developments chaotic economic and there are no factors encourage money laundering operation because of the presence of the hidden economy and the weakness of the banking and legal measures to combat them, and on this basis there is a need to examine money laundering operation in the province of Arbil, to indicate the presence or absence of a money laundering operation in working in the provin

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The current study deals with the performance of constructed wetland (CW) incorporating a microbial fuel cell (MFC) for wastewater treatment and electricity generation. The whole unit is referred to as CW-MFC. This technique involves two treatments; the first is an aerobic treatment which occurs in the upper layer of the system (cathode section) and the second is anaerobic biological treatment in the lower layer of the system (anode section). Two types of electrode material were tested; stainless steel and graphite. Three configurations for electrodes arrangement CW-MFC were used. In the first unit of CW-MFC, the anode was graphite plate (GPa) and cathode was also graphite plate (GPc), in the second CW-MFC unit, the anode was stainless st