The continuous phase modulation (CPM) is a adaptive phase modulation technique which performs a vital role in OFDM system than constant envelope based on OFDM. The system combines the frequency diversity and low complexity type of equalizer. The attractive digital modulation adopted two types of equalizers; zero forcing and MMSE equalizer. The constant envelope modulation also used to attract the OFDM in future communications. The digital modulations QPSK, DPSK, 4-FSK and 4-PAM are analyzed to achieve good error rate and QPSK/QAM outperforms the PAM and FSK. The constant envelope OFDM (CE-OFDM) propagates the signal with near ideal PAPR than conventional systems and gives good performance with suitable FDE. In this paper, we proposed CE- CPM based FDE which is feasible than CE –CPM based OFDM and non OFDM systems. The error rate can minimize via selected equalizer which will results in good performance under channel conditions.

Cobalt chloride solutions exhibit different colours in different solvents thus displaying solvatochromic behaviour. This study reports spectrophotometric investigation of solvatochromic behavior of cobalt chloride solutions in different polar protic and aprotic solvents. The results are discussed in correlation with solvent properties such as dielectric constant, hydrogen bonding ability of solvent, ratio between hydrocarbon chain length and number of polar groups. Spectrophotometric analysis of solutions was carried out to understand interaction between solvent and cobalt salt as well as probable molecular structure of salt-solvent complex. The results showed that most of the polar protic solvents displayed pink color and polar aprotic ones showed blue colour. When the results with a series of alcoholic solvents were compared it was found that colour is not only a function of hydrogen bonding ability of solvent but also depends on hydrocarbon chain length.

A lesion is an area of tissue that has been damaged through injury or disease. So a brain lesion is an area of injury or disease within the brain. While the definition sounds simple, understanding brain lesions can be complicated. That's because there are many types of brain lesions. They can range from small to large, from few to many, from relatively harmless to life-threatening. magnetic resonance imaging (MRI) is increasingly used nowadays. Manual delineation of Multiple Sclerosis (MS) lesions in MR images by human experts is time-consuming, subjective and prone to inter-expert variability. Therefore, automatic segmentation is needed as an alternative to manual segmentation. In this paper, the 2D discrete wavelet transform (DWT) is used to extract local information from analyzing MR images. Ensemble decision trees (EDT) and Ensemble support vector machines (ESVM) are used to segment MS lesions and automatically differentiate between blocks in regions of MS lesions and the blocks in non-MS. lesions. We evaluate our approach on real MRI data sets. We can detect MS lesions with accuracy more than 98 %. Technique evaluated using real MRI datasets. The results compared with ground truth. The main contribution of the proposed techniques described in this paper is the use of DWT with Ensemble Machine Learning and solving the problem of imbalanced classification data without changing or losing trained data.

Agriculture is the backbone of the economic system declining its production due to overpopulation and urbanization, so there is a need of precision agriculture. Precision agriculture requires sensor integration, automatic control, and networking and data processing capabilities. With the implementation of rapidly growing IoT, challenges of based site-specific farming practice with the aim of maximizing the crop production along with the efficient usage of resources involved in farming process. It provides real time assessment of various crop and environment parameters by précising the observed farming land as well as the amount of required water, fertilizer and other input needs. This method enables our farmers to achieve efficiency with proper amount in the required time and therefore ensures growth of non-toxic safe and healthy crop. LPWAN is a wireless network technology, which can be inculcated in the agriculture farms for precision purpose. In this study Lora based technology is used to monitor the agriculture parameters i.e; temperature, humidity and soil moisture to realize timely monitoring of the crop growth parameters, which solves the problem of manually collecting the data and overcomes the problem of long distance communication and anti-interference of the intelligent systems. The hardware installation of reducing the sensor implementation is also represented in the study.

The PREN value of the alloy may lead to a misleading prediction of pitting corrosion resistance because in the event of an imbalance of  ferrite and austenite volume fraction, the chemical composition of the phases may be very different from that of the alloy. In this case, the PREN of one of the phases may be below the PREN of the alloy. Three laminated duplex stainless steels with different PRENs were characterized: UNS S32304 (Lean Duplex), UNS S31803 (Duplex) and UNS S32750 (Super Duplex). Several complementary techniques of microstructural analysis were used, such as optical emission spectrometry, optical microscopy and scanning electron microscopy with coupled EDS. Quantitative metallographic analyzes were carried out to determine the volume fraction of  ferrite and austenite, and semi-quantitative chemical analyzes of the present phases, using a coupled EDS-SEM. For all the alloys studied, it was observed that the  ferrite presents higher Cr and Mo contents than the austenite phase, which had N contents higher than the  ferrite. The PREN of  ferrite is higher than that observed for austenite for both UNS S32304 (Lean Duplex) and UNS S31803 (Duplex). In UNS S32750 (Super Duplex), the PREN of the austenite is higher than that observed for  ferrite due to the higher content of N of this alloy.

Clay is an earth resource which is taken as a raw material for a vast range of industrial applications because of peerless properties of such clay. Analysis of the particle size distributions of anthill clay, brick clay and roof tile clay with the important parameters were the aims and objectives of the existing research. In the dry sieve analysis, ASTM D422 standard methodology was followed while performing a microscopic analysis of each type of clay using an optical microscope. Based on the requirements of the testing of water absorption and splitting tensile loads, bricks were manufactured from each clay type. As the major outcomes of the existing investigation, there were obtained well graded particle arrangement from roof tile clay, gap graded arrangement from anthill clay and uniformly graded arrangement from anthill clay, lowest PH value from anthill clay, maximum splitting tensile load from roof tile clay brick, maximum water absorption from anthill clay brick, maximum natural moisture content from roof tile clay and relatively higher finer weight percentage of particles from roof tile clay under both microscopic analysis and sieve analysis.

Cognitive radio network is a key to effectively utilize the underutilized radio spectrum. It works on the basis of Software Defined Radio. Spectrum sensing is the most important part of the cognitive radio system and it is used to detect the presence of signal in the air. There are many techniques to sense spectrum like Matched filter based detection, Energy detection, Cyclostationary detection and Wavelet based detection. In the proposed work, Energy detection is chosen in which spectrum sensing is done by considering static and dynamic threshold level. To evaluate the performance of the detection techniques, MATLAB software has been used for simulation. Simulations were carried out and graphs of probability of detection vs. the probability of false alarm were observed and analysed. The detection probability increases with respect to the increase in false alarm. Also significant reductions in probability of missed detection have been achieved with this sensing technique. The detection probability also varies with the SNR value. SNR has a great influence on the probability of detection. With an increase in SNR value, the probability of detection increases.

The procurement process is an important process in supply chain management as it is the spearhead of the entire process. In carrying out the procurement process, there are often problems with the supplier selection activities. This is because the supplier selection process spends a lot of time and resources collecting data and conducting careful analysis that will affect the entire decision alternative. In making decisions relating to the many criteria and the number of alternative suppliers, it requires an effective and uncomplex assessment technique, but it provides accurate results. A mapping and determination of supplier selection criteria is required as a basis for valuation to obtain a qualified supplier. This study focused on PT. XYZ is a construction company in South Tangerang. Analytical Hierarchy Process (AHP) is used to determine the best supplier; there are 4 variables that are reference in conducting the selection of suppliers, such as: cost, quality, delivery, and service. The result in the selection of the supplier company is cost with a weight of 0.268, quality with a weight of 0.290, delivery with a weighting of 0.248, and the service with a weight of 0.194 where conclusions obtained from the analysis of the selection of the best suppliers and in accordance with the criteria, namely PT. CBL for iron suppliers, PT.SAS for cement suppliers, and PT. Citra BSD for suppliers of natural materials.