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Current paper reports the findings of a content analysis of Open Educational Resources. Twenty three studies were collected for the analysis. The studies were collected from different journals depending on open access policy. Every study was categorised by author, year of publication, title of the study, author characteristics and analysis. The analysis refers to the information about Open Educational Resources variables. Therefore the investigators categorize the research papers based on OER. An analysis of research papers was formed in conclusion and finalizing the common dimensions of content analysis of OER studies.

An ancient B.T.M. with P.C.M. was controlled through the issues of high inflexibility of phase change material, leakage problems and very low conductivity in thermal energy. This research paper reports a facile batter thermal management and creativity along with induced non-rigid phase change material composites. This battery model can be determined by the flexible phase change material composites along with an intervention due to the recovery in shape and non-rigidity of flexible phase change components. This assemble was modelled to be efficient and compact without any requirement for grease. A constant state reveals various stages of phase change material which has various properties in thermal efficiency. A unified state was linked with the recovery shape of flexible phase change components, which can cause a low resistance in FCPCM and battery. Battery thermal management demonstrates the perfect process of thermal control power. If the battery was discharged from 90 to 10% of charge, then the temperature of flexible phase change components depends upon battery thermal management. It was 44.5 °C during the 3.5 °C rate, which was 29.8 °C lower than no phase change material. It also reveals low-temperature oscillation inside the long-time process and range of heat of recovered phase change material. The performance of battery thermal management and its flexibility will give perceptions of passive battery thermal management systems.

The recent trends in material science are focused toward composite materials. It has been used in a lot of real-life applications. In composite material, recently researchers concentrated on the na...

An ancient BTM with PCM was controlled through the issues of high inflexibility of phase change material, leakage problems and very low conductivity in thermal energy. This research paper reports a facile batter thermal management and creativity along with induced non-rigid phase change material composites. This battery model can be determined by the flexible phase change material composites along with an intervention due to the recovery in shape and non-rigidity of flexible phase change components. This assemble was modeled to be efficient and compact without any requirement for grease. A constant state reveals various stages of phase change material which has various properties in thermal efficiency. A unified state was linked with the recovery shape of flexible phase change components which can cause a low resistance in FCPCM and battery. Battery thermal management demonstrates the perfect process of thermal control power. If the battery was discharged from 90 to 10% of charge, then the temperature of flexible phase change components depends upon battery thermal management. It was 44.5°C during the 3.5°C rate which was 29.8°C lower than no phase change material. It also reveals low-temperature oscillation inside the long-time process and range of heat of recovered phase change material. The performance of battery thermal management and its flexibility will give perceptions of passive battery thermal management systems.

A Meta analytical review investigated the study habits and academic achievement of school and college students. In this study the sample consists of twenty seven reviews based on study habits and academic achievement/ performance. The sample of the review based on inclusion criteria such as study habits and academic achievement. The review was collected by following details such as title of the study, Name of the author, Sample of the study, correlation Value and findings of the study. The Meta analysis is on the relationship between study habits and academic achievement. The main aim of the study is to find the fixed effects, random effects model values, Heterogeneity and forest plots. A Meta analysis of research paper was formed the conclusion.

Chemical precipitated and followed by calcinations is a versatile process for synthesising undoped ZnO and Mn (5, 10 and 15 wt%) doped ZnO nanoparticles at pH-10 and calcinations temperature of 450...

The rapid development of various services that are provided by information technology has been widely accepted by the users who are making use of such services in their day-to-day life activities. Securing such a system application from various intrusions still remains to be a one of the major issues in the current era. Detecting such anomalies from the regular events involves various steps such as data pre-processing, feature selection, and classification. Many of the computational models intend to accurately discriminate the samples of each group for better classification by identifying candidate features prior to the learning phase. This research studies the implementation of a combined feature selection technique such as the GRRF-FWSVM method which is applied to the benchmarked anomaly detection dataset KDD CUP 99. The results prove the novel proposed hybrid model is an effective method in identifying anomalies and it increases the detection rate of about 98.55% of the intrusion detection system with the two most common benchmark models.

Magnetic Resonance Imaging (MRI) is an emerging research area, employed extensively in radiology for the diagnosis of various neurological diseases. Here, as the classification of MRI gains significant importance for the tumor diagnosis, various techniques are developed in the literature for the automatic classification of MRI images. In this paper, a clustering scheme, namely gaussian hybrid fuzzy clustering (GHFC) is developed by hybridizing the fuzzy c-means (FCM) clustering and sparse FCM along with the Gaussian function for the segmentation purpose. After segmenting the image, the suitable features are extracted from the image and given to the Exponential cuckoo based Radial Basis Neural Network (Exponential cuckoo based RBNN) classifier. The features serve as the training information for the Exponential cuckoo based RBNN classifier, and it finally detects the training class. Simulation of the proposed work is done using BRATS and SIMBRATS databases, and the results are compared with several state-of-art techniques. Simulation results depict that the proposed GHFC along with the RBNN classifier achieved improved accuracy and mean squared error results with the values of 0.8952, and 0.0074, respectively, for the BRATS dataset and 0.8719 and 0.0036, for the SIMBRATS dataset.

The objective of this work is to investigate the effect of graphite addition to Al/SiC composites manufactured by stir casting process. The reinforcement content of graphite was varied from 2.5 wt....

Silver doped cerium oxide nanocomposites were prepared at nitrogen atmosphere using polyindole as reducing agent (Polyindole/Ag-CeO2). The samples were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction study (XRD), scanning electron microscopy coupled with energy dispersive X-ray diffraction (SEM-EDAX), transmission electron microscopy (TEM). The FTIR study revealed the formation of polyindole/Ag-CeO2 nanocomposites. The XRD analysis confirmed the amorphous nature of nanocomposites. The porous structure of the polyindole and spherical shape of the Ag and CeO2 present in the nanocomposites were confirmed by SEM and TEM images. The prepared nanocomposites showed moderate antibacterial and antifungal activities.

A computational analysis has been performed to study the effect of magnetic parameter on magneto-natural convection and entropy generation inside a wavy cabinet filled by Al2O3-H2O nanosuspension. The vertical boundaries of the cavity are designed as wavy and kept at cooled temperature (Tc), while the horizontal borders are modeled as flat and supposed to be thermally insulated except the centrally heated portion on the bottom wall. The higher constant temperature (Th) of the isothermal line source can supply thermal energy in uniform manner. The transformed dimensionless governing equations were solved using finite volume technique along with power-law scheme. The system was optimized for significant variety of controlling parameters namely, number of undulations (N = 0 – 3), volume fraction of nanosuspension ( ϕ = 0.0 – 0.04), magnetic parameter (Ha = 0 and 50), magnetic tilted angle ( ζ = 0 ◦ – 90 ◦ ) and dimensionless heat difference ( Ω = 0.001 – 0.1). The numerical results are analyzed for streamlines, isotherms, entropy isolines, overall Nusselt number and average entropy production strength. From this study, it is noticeable that growth of undulation number causes the reduction of convective heat transfer rate as well as average entropy production intensity. Further, the findings elucidate that the average entropy production intensity and overall heat transfer rate are decreased upon growing magnetic parameter.

This study focused catalytic transesterification process for the production of biodiesel from restaurant based waste cooking oil. Fifteen pre-designed experiments are used to explore the significance of three reaction parameters with three different levels such as methanol to oil ratio, catalyst concentration and agitation speed as well as their combined effect on biodiesel production. Box-Behnken experimental design based on Response Surface methodology (RSM) is utilized for optimizing the process parameters A quadratic model was developed to estimate biodiesel yield, and the R2 value was determined to be 0.99, indicating that the model is accurate. The result showed optimized process parameters for maximum biodiesel yield as methanol:oil molar ratio of 12.97:1, NaOH concentration of 0.1834 wt% and at the agitation speed of 1088 rpm. The obtained results reveal that the yield of 98.45% and the experimental yield of 97.80% respectively which shows the deviation of 0.7%.

The evolution of computing is increasing in a vast manner that will integrate many physical objects and the internet to generate a new interconnection, such as the Internet of Things (IoT). It is estimated that the number of devices that will be interconnected to the internet will be more than trillions until 2025. Due to the lack of interoperability when these devices are interconnected in a vast heterogeneous network, it is tough to define and apply security mechanisms. The IoT networks have been exposed to many vulnerable attacks that disturb the network. Therefore, designing an intrusion detection system that provides additional security tools specific to IoT is needed to apply security mechanisms to detect the attacks in the network. In this paper, we propose a novel hybrid GA-CMIM machine learning algorithm that improves the efficiency in detecting the botnet intrusions with the set of optimal features that are selected from the dataset using a feature selection method.

The role of piperine, a water insoluble alkaloid compound on the nucleation, crystallinity, size, shape and dispersion of hydroxyapatite (HAp) nanoparticles was investigated. Two different concentrations of piperine were used as an organic modifier. FTIR spectra support the transformation of functional groups. The XRD pattern reveals the crystalline nature of the materials. The TEM images disclose the mechanism of nucleation, formation, shape, size and morphology of HAp nanorods. The addition of the piperine during the synthesis altered the morphology of HAp nanorods. Piperine, as water insoluble alkaloid could affect the morphology of the HAp nanoparticles with agglomeration. These types of well defined and shaped HAp nanorods can be used as a delivery service for drug release and in the field of biomaterial research.

The present study investigates the in vitro cytotoxic efficacy of polymer encapsulated bare and Mn-doped ZnO nanoparticles against human liver carcinoma Huh7 cell lines. PEG capped bare and Mn (2.0...

The objective of this endeavor is to investigate the influence of graphite particles addition to the Al/SiC composites manufactured by stir casting method. Al/SiC/Gr hybrid metal matrix composites are preferred replacement for single reinforced composites by virtue of strengthened mechanical and tribological properties. A layered SiC/Gr composite material is required in gas turbine combustor can. Al/SiC/Gr composites are required in bearings, and pistons due to selflubrication, low wear rate and less friction. The inclusion of both strong reinforcement like SiC and smooth reinforcement like graphite enhances hardness and wear resistance of aluminium composites. The reinforcement content of graphite was varied from 2.5 to 7.5 wt % in a step of 2.5 wt. The SiC was fixed at 5 wt. % for all the three specimens, and Al6061 was used as matrix base material. The microstructure and EDAX analyses were required for three samples of hybrid metal matrix composites. Vickers hardness and porosity decreases for Al/SiC/Gr hybrid composites when percentage of graphite content increases. A review of surface modification of Al/SiC/Gr was done to find the different materials used for coating hybrid composites.

From ancient times, the economic growth of India is mainly based on agricultural output. Agriculture is demographically the broadest economical sector and acts as an important part in the entire socio-economic fabric of India. Nearly half of the population of our country are connected to agriculture as their industry and make a livelihood out of it. At the same time, the crop productivity depends upon based on several climatic and economical factors namely soil type, weather, irrigation, fertilizer, rainfall, and so on. The present advancements in Information Technology for agriculture field become a hot research topic for predicting the crop yield, which can be resolved by the use of data mining techniques. This paper focuses to design a new predictive approach which offers a high yield of paddy crops by the use of data mining models and Hungarian model in Kuruvai season which generally starts from June to July. The data set used in this research for mining process is real data of Kuruvai season are collected from Tamil Nadu Agricultural University (TNAU) AgriTech Portal, Aduthurai, Thanjavur district and a set of three data mining approaches namely Apriori method, Naive Bayes (NB) and J48 classifier are employed to predict the paddy yield. The outcome of various models has been analyzed, and it is shown that the NB model has offered superior outcome over the compared classifier models.

Diabetes is one of the most feared diseases currently faced by humanity. The disease is due to a poor reaction of the body to insulin: it is an important hormone in our body that converts sugar into energy that is necessary for the proper functioning of a normal life. Diabetic disease has serious complications on our body because it increases the risk of developing kidney disease, heart disease, retinal disease, nerve damage, and blood vessels. In this article, we have proposed a decision tree model: SLDPS (Diabetes Prediction System with Supervised Learning). The data set is collected via IoT sensors. The classification accuracy obtained with this model was improved to 94.63% after the rebalancing of the data set and shows a potential relative to other classification models in the literature.

Logistics industry has been the second largest industry to emit the greenhouse gas. Carbon emission can be reduced by analyzing and controlling those influencing factors that affect the implementation of low carbon measures in the logistics industry. In India, Small and Medium level Enterprises (SMEs) account for 60% of all private sector jobs and about 40% of low carbon business. This paper reveals the findings and result of a qualitative statistical study conducted on the SMEs located in the southern parts of India. Based on the existing literature, research hypotheses were formed on the aspects of environmental, economic, and social factors that affect the implementation of low-carbon logistics. To test these hypotheses, a questionnaire was developed and pre-tested by pilot study. Then pre-tested questionnaire was circulated to the various levels of people involved in the logistics activities of SMEs, and responses were obtained. After data collection, a statistical analysis was conducted using SPSS software to prove the research hypotheses.

In the 21st century, people are connecting with technology, and most of the people are spending time in social networks for sharing information. For the most part, spending time on social media is linked with an increased risk of loneliness and depression. Negative effects of social media and social network are affecting the person's mental, emotional, and physical health. The World Health Organization (WHO) reported that 8,000,000 people are dying due to suicide every year, and especially, every 40 seconds teenagers are dying. Generally, most of the teenagers are emotionally imbalanced; most of the suicide is committed on high depression. Depression is the foremost cause of emotional and mental illness. Emotional health is a state of emotional wellbeing, and it's a hidden and invisible factor as well as a factor for good mental health; mental health is a deep-seated problem for most humans. With this background, this chapter discusses the emotional and mental health with respect to technological issues.

Polyindole stabilized silver‒cobalt oxide (Pind/Ag‒Co3O4) nanocomposites were synthesized, characterized and evaluated for their antibacterial and antifungal activities. Polyindole, cobalt oxide and Pind/Ag‒Co3O4 were prepared by chemical oxidative polymerization, co-precipitation and reflux condensation method, respectively. Colloidal nanoparticles of polyindole, cobalt oxide and nanocomposite were characterized by Fourier transform infrared spectrophotometer (FT-IR), X-ray diffraction pattern (XRD), scanning electron microscope with energy dispersive X-ray diffraction study (SEM-EDAX) and high resolution transmission electron microscope with selected area diffraction (HRTEM-SAED). FTIR spectra revealed the functional group’s transformation of cobalt oxide nanoparticles. The crystalline nature of the samples was confirmed by XRD study. The SEM images revealed the various shapes and surface morphology of the nanocomposites. Further, the elemental composition was confirmed by EDAX. The HRTEM images showed shapes such as spherical, cylindrical, rectangular, rods, oval and square. The average particle size of the nanocomposites found to be ∼20 nm which is in good agreement with XRD analysis in terms of the size of the crystalline. The Pind/Ag‒Co3O4 nanocomposites exhibited improved antibacterial and antifungal activities against pathogenic bacteria and fungi. Hence, these nanocomposites could be used as a potential candidate for the biomedical applications.

Nano crystalline pure and Mg doped ceriaparticles were synthesized by simple chemical co-precipitation method using cerium nitrate hexahydrate as a source material and magnesium nitrate as doping precursor at room temperature. The effect of doping were investigated by X-ray diffraction pattern(XRD), FT-Raman,fourier transform infrared spectroscopy(FTIR), Ultraviolet spectroscopy(UV), photoluminescence spectroscopy(PL), field emission scanning electron microscope(FESEM) and high resolution transmission electron microscopy with energy dispersive spectroscopy (HRTEM &EDS). The X-ray diffraction pattern and FT-Raman studies showed that the prepared samples were nano particulates with cubic fluorite structure. The XRD pattern analysis showed that the size of the particles ranged from 13 to 20 nm, however 4 wt% Mg doping results in reduction of particle size compared with other doping concentrations. The effects of Mg concentration on various structural parameters of the prepared samples were also determined. The slight blue shift observed upon doping in UV–Vis absorption region around 330–360nmrecorded for reduction in particle size. The FTIR unveils the presence of Metal oxygen bonds below 700 cm−1in the prepared samples. All samples showed a broad emission band at 430 nm with linearly increasing intensity with respect to dopant concentrations. The Spherical morphology with weak agglomeration was identified through FESEM and HRTEM analysis. The elemental analysis of Ce, O and Mg were confirmed through EDS analysis.

Cloud computing is one of the new age technologies which has great prominent factor in the development of the enterprises and markets. The major exertion in the cloud computing is related to the resource being allocated. The optimal resource allocation is one which allocates the best suitable cluster resources for the task to execute with consideration of the different parameters, such as time, cost, and scalability, makespan, reliability, availability, throughput, resource utilization and so on. In this paper, a resource allocation optimization method in the cloud computing based on the exponential lion algorithm is proposed. The exponential lion based resource allocation for cloud computing taken into account saves the execution time, run time, and improves the revenue for the cloud provider. The proposed E-Lion based resource allocation approaches are compared with the PSO, SL-PSO, and Lion using the performance measures profit, CPU utilization rate, and memory utilization rate. The simulations of the experiments show that the algorithm in this paper has improved the algorithm performance efficiently with profit maximal profit of 38.74 and minimal CPU and memory utilization rate of 0.00031, and 0.00036 respectively.

Novel nanostructure formations like core-shell influence the sensing nature of the optoelectronic devices. In this report, transition metal oxides (TMOs) and transition metal dichalcogens (TMDCs) based sensing layer fabrication and their influence in photo sensing performances were analysed. The metastable h-MoO3, thermally stable α-MoO3, as synthesized MoS2 and combinational MoO3@MoS2 core@shell nanocomposites are synthesized by co-precipitation method. Phase purity of synthesized particles was analysed with XRD. Vibration modes of the samples were confirmed with Raman spectroscopy. The morphology behaviours of MoO3 in different polymorphs due to annealing temperature namely prismatic like h-MoO3, layered rod like α-MoO3 and sphere like MoS2 decorated core@shell MoO3@MoS2 were observed in the FE-SEM micrographs. The core@shell rod like structured was recorded with HRTEM. Further construction of photodiodes such as n-(h-MoO3)/p-Si, n-(α-MoO3)/p-Si, n-MoS2/p-Si and n-MoO3@MoS2/p-Si by employing solution processed method with pre-synthesized particles were discussed in detail. The current-voltage (I–V) characteristics and photo sensing parameters of detector are compared. From the experimental result, n-MoO3@MoS2/p-Si has better photosensitivity (PS) of 21678.6 (%) and the specific detectivity (D*) of 5.813 × 1010 Jones.

Radiographic examination performed based on the increase in flow through one of the steam generators (SG) indicated the physical separation of orifice assembly from the orifice holder. Subsequently, this failed orifice assembly was cut from the feed water inlet header of the SG Module and subjected to further investigation. Both metallurgical and mechanics based post-failure investigations were performed. The failure of orifice assembly is attributed to stress corrosion cracking (SCC). Scanning electron microscopic (SEM) observation of the fractured surface showed an inter-granular mode of SCC failure. SCC occurred due to the residual tensile stresses developed due to the geometrical constraint against the thermal shrinkage during welding. A minimum gap of 160 µm at the top mating portion of the orifice assembly before the welding could have absorbed the thermal shrinkage to prevent the existence of sustained residual stresses and thereby SCC failure. Austenitic stainless steels are highly susceptible to SCC under the combined action of tensile stress and favourable environmental conditions. Under the favourable situation to SCC, cracks propagate slowly without any noticeable deformation until the stresses in the remaining ligament of metal exceed the fracture strength. Based on the insights gained from the root cause analysis, the design of the orifice assembly has been revised to mitigate a similar kind of failure in future.

Polyindole-based silver and copper oxide (polyindole/Ag–CuO) nanocomposites were synthesized using reflux condensation method by varying the concentrations of polyindole and silver nitrate ...

Objectives: This work contributes for an understanding of cyber crime investigation methodology and its prosecution in India.Alsoit covers investigation mechanism and various methodologies carried out by police department and Indian judicial system. Methods/Statistical Analysis: By the method of questioning and gathering of information, cyber crime investigation begins; after that computer forensic tool is used to find the criminal and also the amount of damage caused to data. Once the evidences are collected it has to be protected without any loss to the originality. The evidences which are collected by the investigating officer should organise it and finally submit the report for prosecution. Findings: According to cyber crime cases in India,it lacks technical experts in handling the cases. Technically trained police officers are very less. There is a lacuna in judicial department also. The second major issue is Judicial Jurisdiction in handling cyber crime cases. Judicial and police officers are to be trained regularly. Information Technology Act to be modified and severe punishment to be given to the criminals. Most of the sections in IT Act having minimum punishment only which has to be changed. Application/Improvements: Establishment of cyber crime police stations and cyber forensic labs throughout the country is the need of the hour. By realising the seriousness of this emerging crime government should take steps in improving the technology in handling the Hi-tech crimes. Keywords: Cyber Crime, Computer Forensic, Investigation, Jurisdiction, IT Act

Generally, Magnetic Resonance Imaging (MRI) is utilised in radiology for diagnose the anatomy and the physiological processes of the body. Nowadays, the classification of tumour region play...

Enterprise modernization refers to enhancing the capability of the existing application to meet the business demands. This modernization can lead to vast quantities of data generated from infrastructure, channels, database and other roots of computing involved which leads to the quantity of information generated. The data getting generated impact the resources called for these sorts of computing as it is directly proportional to recurring computing cost model and incurs a huge cost for enterprise opting for enterprise modernization. In this paper, we suggest a method to place the relevant transaction filtering of information in the context of enterprise modernization. This is answered by presenting the non-intrusive transaction aware filtering framework to get just the relevant information needed to further optimize the computing resources. Simulation and experimental results show an improvement in network, memory, throughput, CPU utilization compared against the non-transaction aware filtering during various load conditions.

Cd-doped ZnO thin films were deposited on a glass substrate via spin coating techniques. The structural properties of the thin film were studied by X-ray diffractometry. X-ray diffraction data show...

In this article, the self-assembly of cyanuric acid (CA) molecules into nano-structures is examined. Equilibrium geometry of CA is planar and it belongs to the D 3h point group. It is shown that CA clusters form three dimensional bowls and balls. Cyclic pentamer (5-bowl) is the basic motif responsible for these non-planar geometries. It is also shown that the cyclic hexamer based clusters can be non-planar if they contain a 5-bowl. A unified criterion for the formation of bowls and balls from basic molecular building blocks emerges from this study. The role of symmetry in supramolecular self-assembly is also clearly evident from the present study.

Polyindole/Silver Zinc Oxide (PIND/Ag ZnO) nanocomposites were synthesized by loading ZnO and Ag nanoparticles on the surface of polyindole. Polyindole and PIND/Ag ZnO were prepared using chemical oxidative polymerization and co-precipitation method in nitrogen (N2) atmosphere. The functional groups, crystalline structure, morphology, elemental composition and shapes of the nanocomposites were characterized by Fourier transform spectrophotometer (FT-IR), X-ray diffraction study (XRD), scanning electron microscope with energy dispersive X-ray diffraction studies (SEM-EDAX) and transmission electron microscope with selected area diffraction (TEM-SEAD). The results were obtained from the characterization techniques reveals the formation of nanocomposites consist of polyindole, Ag and ZnO nanoparticles. Prepared nanocomposites were evaluated for the antibacterial activity against selected gram negative and gram positive bacteria. PIND/Ag ZnO nanocomposites with different shapes such as spherical, cylindrical and hexagonal were reported. This is the first report on the simple chemical synthesis of polyindole based Ag ZnO nanocomposites, which exhibits good antibacterial activity.

In the present work, solution based simple chemical precipitation method has been used to prepare undoped and Gd doped ZnS nanoparticles. The prepared nanoparticles were characterized by standard analytical methods the X-ray diffraction results revealed that the undoped and Gd doped ZnS nanoparticles corresponds to hexagonal wurtizite structure. The FESEM images shows that the formation of agglomerated nanoparticles. The compositional analysis confirmed the presence of Gd in ZnS matrix with reasonable dissolution range. HRTEM results show that undoped and Gd doped ZnS nanoparticles exhibit a uniform size distribution with average grain size lying in the range of 2.4–3.9 nm. The magnetic studies of Gd doped ZnS nanoparticles carried out at room temperature by vibrating sample magnetometer shows that the materials exhibit magnetic hysteresis. The prepared samples shows paramagnetic behavior at room temperature. The degradation of methylene blue dye (MB), methyl orange dye (MO) and effluent collected from industry by the undoped and Gd doped ZnS nanoparticles was studied using 8 W, UV visible lamp light irradiation. The color degradation efficiency for MB is found to be 95%, whereas the color degradation efficiency for MO is 97% and for the effluent collected from a dye industry it was nearly 90%.

This research aims in studying the pre-buckling and post-buckling behaviour of composite panels stiffened by hat stiffeners under compressive loading. Stiffened panels are used in aerospace, marine and also in bridge structures. They are used to make the plate girders stiff. By using composite materials, the strength can be increased, and the weight can be reduced. In Composite panels which are stiffened, local buckling and failure of panel happens because of the applied compressive loads and due to combination of compressive and shear loads. The Collapse of the stiffened composite structure starts from the intersection between the plate and the stiffeners due to stress effect caused by deformation of lamina skin and stiffeners then leads to the structural buckling of skin of the panel. This research uses nonlinear Finite element approach to investigate the collapsing behavior using ABAQUS software.

Background: The process of hepatocytes cryopreservation is standardised by most of the laboratories. However there is a variation with respect to the Protocols, media and equipments used amongst the laboratories. Similarly, the tests available to evaluate the efficacy also varies. They are expensive and sometimes might not measure the parameter required for a particular research study. Hence we propose a methodology to study the few basic parameters like cell viability, synthetic function of the cell and cell stability. We have also used a simple percentile calculation to know the efficacy of cryopreservation. This shall help in functional validation of the cell after cryopreservation. The same can also be used to compare the quality of hepatocytes between different batches. The objective of the study was to characterisation of the cells to determine the efficacy of cryopreservation.Methods: Two step collagen isolation method was used to isolate the hepatocytes. Initial cell viability was calculated. A sample of cells were taken for characterisation and the remaining cells cryopreserved. The sample cells were divided into two batches one for pre cryopreservation culture and the other for post cryopreservation. The pre cryopreservation culture was done on monolayer using collagen coated 6 well plate. The other sample was placed in the cryovials for cryopreservation for 1week. After 1 week the cryopreserved cells were thawed and the post cryopreservation viability calculated, followed by post cryopreservation culture. During the process of culture (both pre cryopreservation and post cryopreservation) for 5days Albumin was measured daily and average calculated, peak Aspartate (AST) at 24 hours was recorded. The percentile difference of the obtained values between the pre cryopreservation and post cryopreservation culture was calculated.Results: A total of 12 specimen were enrolled for the study. The mean pre cryopreservation viability of the cells was 66.58%. The post cryopreservation, viability of the cells was 36.43%. The mean difference was -30.170%. The pre cryopreservation albumin values had a mean of 150ng/ml. The post cryopreservation albumin values had a mean of 135.83ng/ml. The mean difference was -14.170ng/ml. The pre cryopreservation peak Aspartate values had a mean of 234.17 IU/ml. The post cryopreservation peak aspartate values had a mean of 230 IU/ml. The mean difference was -4.176 IU/ml.Conclusions: This simple method can validate the cells after cryopreservation by measurement of cell viability, synthetic function of the cell and cell stability.

The cutting parameters like cutting speed, feed, and depth of cut can affect the tool life. Also, the vibration of the tool can affect the tool life. The aim of this study is to predict the cutting tool vibration to enhance the tool life. In this paper, vibration of tool is studied with HSS tool (high speed steel) while turning mild steel. The tool vibration is measured using X Viber vibration meter. The experimental data are tabulated and imported to artificial neural network (ANN). A multilayer perceptron model is trained with back-propagation algorithm using the experimental data. The rake angle, cutting speed, and feed are considered as input parameters for training the ANN. The trained ANN is used to predict tool vibration for different conditions. The predicted values are compared for the specific range to justify the tool change.

Graphical abstract, Highlights • Novel high-performance p-CuO@CuS/n-Si photodetectors have been facilely fabricated for the first time. • Structural and vibrational studied confirm the synthesis of fabrication of CuO@CuS nanocomposite system. • Core-shell structure like morphology was approved by FESEM & HRTEM analyses. • The high photosensitivity (Ps) of ∼ 7.76 × 104 % and photoresponsivity (R) ∼ 798.61 mA/W was observed for the fabricated photodetector. • The high specific detectivity (D*) of 8.19 × 1011 Jones and external quantum efficiency (QE) of ∼ 309.66 %, was observed for the fabricated photodetector., Development of photo detectors based on different semiconducting materials with high performance has been in progress in recent past, however, there is a lot of difficulties in developing the more effective photo detectors-based devices with high responsivity, detectivity and quantum efficiency. Hence, we have synthesized pure CuS and CuO@CuS core-shell heterostructure based photo detectors with high performance by simple and cost-effective two-step chemical co-precipitation method. The phase purity of CuS and CuO@CuS composite was observed by XRD analysis and the result were verified with Raman spectroscopy studies. Sphere like morphology of pure CuS and core-shell structure formation of CuO@CuS are observed with scanning and transmission electron microscopes. The presence of expected elements has been confirmed with EDX elemental mapping. Light harvesting photodiodes were fabricated by using n-type silicon substrate through drop cost method. Photo sensitive parameters of fabricated diodes were analyzed by I–V characteristics. The p-CuO@CuS (1:1)/n-Si diode owned a maximum photosensitivity (Ps) ∼ 7.76 × 104 %, photoresponsivity (R) ∼ 798.61 mA/W, external quantum efficiency (EQE)∼309.66 % and specific detectivity (D*) ∼ 8.19 × 1011 Jones when compared to p-CuS/n-Si diode. The obtained results revealed that the core/shell heterostructure of CuO@CuS is the most appropriate for photo detection.

A greenhouse system (GHS) is a closed structure that facilitates modified growth conditions to crops and provides protection from pests, diseases and adverse weather. However, a GHS exhibits non-linearity due to the interaction between the biological subsystem and the physical subsystem. Non-linear systems are difficult to control, particularly when their characteristics change with time. These systems are best handled with methods of computation intelligence, such as artificial neural networks (ANNs) and fuzzy systems. In the present work, the approximation capability of a neural network is used to model and control sufficient growth conditions of a GHS. An optimal neural network-based non-linear auto regressive with exogenous input (NARX) time series model is developed for a GHS. Based on the NARX model, two intelligent control schemes, namely a neural predictive controller (NPC) and non-linear auto regressive moving average (NARMA-L2) controller are proposed to achieve the desired growth conditions such as humidity and temperature for a better yield. Finally, closed-loop performances of the above two control schemes for servo and regulatory operations are analysed for various operating conditions using performance indices.

Ni doped ZnSe precipitated particles were prepared using three different pH precursor solutions (8, 9 and 10) and two different solution temperatures (303 K and 363 K) by wet chemical precipitation technique. The SEM analysis reveals that the size of the particles is in the order of 5 nm at 303 K and it becomes 20 nm at 363 K. The XRD studies show that the prepared nanoparticles of Ni:ZnSe switch from cubic zinc blende to hexagonal wuzurite structure as the temperature increase from 303 K to 363 K. The UV–vis spectra of Ni:ZnSe nanoparticles show that there is no change in optical band gap with increase in pH value at 303 K but the gap increases slightly at 363 K. Linear incremental and non linear decremental natured band edge absorptions were identified for the nanoparticles prepared at different conditions of pH and temperature. The weak interaction between Se 2- and Zn 2+ /Ni 2+ and the property of superficially adhered functional groups were confirmed from the analysis of FT-IR absorption spectra. The conductivity and dielectric studies confirm that the material can be used in high frequency applications.

In the present work, we propose a cost effective, less complicated and an effective way of synthesizing Zn1−xNixS nanoparticle using wet chemical precipitation method. And the material is used for removal of dye decolorization process, which overcomes the constraints caused in the conventional techniques namely chlorination, adsorption, ozonization. The structural analysis shows primary phase cubic zinc blende Zn1−xNixS and rhombohedral α-NiS secondary phase with the average grain size of 20 nm. The electron microscopic analysis clearly depicts the nanophase formation. The strong blue shift in the UV–visible absorption region (410 nm) confirms the nano dimensional state of Zn1−xNixS nano particles. FT-IR analysis shows the presence of functional groups adsorbed on the surface of the nanoparticles. Magnetic measurement by VSM shows that the prepared nanoparticles possess super paramagnetic and room temperature weak ferromagnetic properties. Visible light driven photocatalytic decolorization of methylene blue is observed for Zn0.90Ni0.10S nanoparticles with a degradation of 94% during 150 min of irradiation at 150 ppm of dye concentration.

There is an increasing demand for primary human hepatocytes for toxico-pharmacological studies and for exploring their role in liver cell transplantation. During the whole process of isolation, culture and cryopreservation hepatocytes are subjected to various stress. All these factors will lead to the impairment in the metabolic capability of the hepatocytes post isolation. Hepatocyte isolation is an expensive and resource driven procedure. Thus, it is important to consider all the factors before we subject the specimen for isolation of cells. By considering the factors that influence hepatocyte isolation, hepatocytes of good quality can be obtained. With recommendations on the ideal parameters for isolation being made the researcher shall have a knowledge on what critical factors need to be taken care of during hepatocyte isolation. There will be an opportunity to modify critical factors if possible, during the procurement of specimen by working in tandem with the clinicians. The specimen which shall be deemed un fit when two or more factors have exceeded the critical limits can be rejected.

Internet of Things (IoT) is the connection with the network and physical devices, objects, vehicles, electronics, software, sensors, which are connected to the internet for collect and exchange data and connected to actuators, drones, and robots etc. The main objective of the research should be able to develop the framework for the unique format to communicate multiple devices for any format of the file and address the Security challenges of the fifth-generation mobile networks. Healthcare is an essential part of everyone's life. Modern healthcare applications require a huge demand for IoT Devices from hospital beds to doctors and this will be more advantages for the nurses and patients at the same time data from these devices need to be more secure. This solution was mainly used to decrease pressure on health applications to use this framework solution by providing the continue to quality to decrease the risk in patients. Internet of Things(IoT) used to identify a more important solution to mitigate pressure on healthcare applications. The main objective of the research should be able to develop the framework for the unique format to communicate the multiple devices for any format of the file and address the Security challenges of fifth generation mobile networks in Healthcare applications. In the Next Generation of Fifth Generation Mobile Network Communications in this communication is very different in that which we are used currently. Demand for mobile broadband and wireless communication will continue to increase, largely driven by ultrahigh definition videos with better screens, due to the tech-savvy mobile community and to propose the security algorithms.