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Stock market is very uncertain and highly volatile as the prices of stocks keep fluctuating due to several factors that make prediction of stocks a very difficult and complicated task. In the finance and trading world stock analysis and trading is a method for investors and traders to make buying and selling decisions. Investors and traders try to gain an edge in the markets by taking informed decisions by studying and evaluating past and current data. Stock market prediction has always been an important research topic in the financial and trading field [2]. Prediction of stock market is the act of trying to determine the future value of a company stock (nifty & sensex) or other financial instrument traded on an exchange. Our project explains the prediction of a stock using Machine Learning, which itself employs different models to make prediction easier and authentic. The paper focuses on the use of Recurrent Neural Networks (RNN) called Long Short Term Memory (LSTM) to predict stock values. This will help us provide more accurate results when compared to existing stock price prediction algorithms. The eminent analysis of the stock will be an asset for the stock market investors and will provide real-life solutions to the problems and also yield significant profit. Keywords: Stock Price Prediction, Machine Learning, Long Short-Term Memory, Recurrent Neural Networks

The study identified the expectations of employees working in NEW SPP, ERODE. Employees are the assets of the organization. Fulfilments of employees’ requirements contributes to the organization’s growth. The impact of employee expectations on employee satisfaction has been examined to enhance their satisfaction level which paves way for productivity. The study identified several factors and the most important factor is employee participation. The most influencing and least influencing factors of employee expectations were found for the betterment of employees and the organization. This study was conducted from February to April. The researcher administrated a questionnaire method to collect data and stratified random sampling has been used. The findings of the study would help the policymaker in general of the textile industry to frame suitable policy regarding retention of employees. REFERENCES C.Swarnalatha, T.S. Prasanna(2012), “Employee Engagement”, Indian Journal of Research- Paripex,Volume: 1, Issue: 11, November 2012,ISSN - 2250-1991 DaivaBudriene, DanutaDiskiene (June 2020), “Employee Engagement: Types, Levels And Relationship With Practice Of HRM”, Malaysian E Commerce Journal 4(2):42-47 Anitha J.(2014), “Determinants of employee engagement and their impact on employee performance”, International Journal of Productivity and Performance Management, ISSN: 1741-0401 Alan M. Saks (2006), “Antecedents and consequences of employee engagement”, Journal of Managerial Psychology, ISSN: 0268-3946

Speech emotion detection has been extremely relevant in today’s digital culture in recent years. RAVDESS, TESS, and SAVEE Datasets were used to train the model in our project. To determine the precision of each algorithm with each dataset, we looked at ten separate Machine Learning Algorithms. Following that, we cleaned the datasets by using the mask feature to eliminate unnecessary background noise, and then we applied all 10 algorithms to this clean speech dataset to improve accuracy. Then we look at the accuracies of all ten algorithms and see which one is the greatest. Finally, by using the algorithm, we could calculate the number of sound files correlated with each of the emotions described in those datasets.

Fahr's syndrome is a rare, genetically dominant, inherited, neurological disorder characterised by abnormal depositsof calcium in areas of the brain that control movement, including the basal ganglia and the cerebral cortex.Symptoms of the disorder may include deterioration of motor functions, dementia, seizures, headache, blurring ofvision, spasticity (stiffness of limbs) and athetosis (involuntary, writhing movements). The most common site ofcalcification is the globus pallidus. However additional areas of calcification are putamen, caudate nucleus, internalcapsule, dentate nucleus, thalamus, cerebellum and cerebral white matter. We are presenting a case of a 30 year oldmale, who complained of stiffening of upper limbs and blurring of vision followed by giddiness which wasassociated with slowness of movements. His CT scan revealed a symmetrical large area of calcification over thebasal ganglia. Secondary causes of this disease were ruled out to make the clinical diagnosis of BilateralStriopallidodentate Calcinosis, [BSPDC] which is otherwise called as the Fahr's syndrome.

Costunolide (CE) is a sesquiterpene lactone well-known for its antihepatotoxic, antiulcer, and anticancer activities. The present study focused on the evaluation of the cytogenetic toxicity and cellular death-inducing potential of CE in CHO cells, an epithelial cell line derived from normal ovary cells of Chinese hamster. The cytotoxic effect denoting MTT assay has shown an IC50 value of 7.56 μM CE, where 50% proliferation inhibition occurs. The oxidative stress caused by CE was confirmed based on GSH depletion induced cell death, conspicuously absent in N-acetylcysteine (GSH precursor) pretreated cells. The evaluation of genotoxic effects of CE using cytokinesis block micronucleus assay and chromosomal aberration test has shown prominent induction of binucleated micronucleated cells and aberrant metaphases bearing chromatid and chromosomal breaks, indicating CE’s clastogenic and aneugenic potential. The apoptotic death in CE treated cells was confirmed by an increase in the number of cells in subG1 phase, exhibiting chromatin condensation and membranous phosphatidylserine translocation. The apoptosis induction follows mitochondrial mediation, evident from an increase in the BAX/Bcl-2 ratio, caspase-3/7 activity, and mitochondrial membrane permeability. CE also induces cytostasis in addition to apoptosis, substantiated by the reduced cytokinetic (replicative indices) and mitotic (mitotic indices and histone H3 Ser-10 phosphorylation) activities. Overall, the cellular GSH depletion and potential genotoxic effects by CE led the CHO cells to commit apoptosis and lowered cell division. The observed sensitivity of CHO cells doubts unintended adverse effects of CE on normal healthy cells, suggesting higher essentiality of further studies in order to establish its safety efficacy in therapeutic explorations.

Phytochemical screening of Caralluma lasiantha was carried out and one C21 pregnane steroid was isolated from chloroform extract. Based on spectroscopic studies (IR, 1H NMR, 13C NMR and ESI-MS) the isolated compound is 3b,14b-dihydroxy-14b-pregn-5-en-20-one which was earlier isolated from other species.

BACKGROUND : Carcinoma of the breast has clinical heterogeneity with high morbidity and mortality. Determination of prognostic factors is important in improving the overall survival breast cancer patients. Her2/neu is one of the powerful predictors of poor prognosis. Thus a study of Her2/neu expression estimated by immunohistochemistry in breast cancer is the need of the hour. This study investigates correlations between the presence of Her2/neu and various clinicopathological prognostic parameters in primary breast carcinomas. OBJECTIVES : 1. Study of the HER2/neu status in breast carcinomas in the study sample. 2. To find the association of HER2/neu status with clinicopathological prognostic parameters in breast carcinomas in the study sample. 3. To find the association of HER2/neu status with lymph node status. METHODOLOGY : Patients diagnosed as carcinoma breast, admitted in Department of General surgery, Govt. Royapettah Hospital and post operative modified radical mastectomy specimens were examined for gross and microscopic features. Immunohistochemistry was used to study the Her2/ neu expression. Her2/neu status was correlated with various clinicopathological prognostic parameters. RESULTS : There was a significant statistical association between Her2/neu expression with lymph node status(p=0.012) and presenting symptoms such as pain and nipple discharge. Expression of Her2/ neu expression was increased in tumour size of more than 2 cms (64%) and higher tumour grade (90%). The major histological subtype was Infiltrating duct carcinoma, NOS type. Meanwhile there was no significant association of Her2/neu expression with menopausal status, NPI groups and other histological parameters. CONCLUSION : Our study data indicates that Her2/neu may be a more powerful predictor for poor prognosis as its expression is associated with important prognostic parameters like increased tumour size, high tumour grade, high NPI score and lymph node involvement.

Human recognition through faces has elusive challenges over a period of time. In this paper, an efficient method using three matrix decompositions for face recognition is proposed. The proposed model uses Discrete Wavelet Transform (DWT) with Extended Directional Binary codes (EDBC) in one branch. Three matrix decompositions combination with Singular Value Decomposition (SVD) is used in the other branch. Preprocessing uses Single Scale Retinex (SSR), Multi Scale Retinex (MSR) and Single scale Self Quotient (SSQ) methods. The Approximate (LL) band of DWT is used to extract one hundred EDBC features. In addition, Schur, Hessenberg and QR matrix decompositions are applied individually on pre-processed images and added. Singular Value Decomposition (SVD) is applied on the decomposition sum to yield another one hundred features. The combination EDBC and SVD features are final features. City-block or Euclidean Distance (ED) measures are used to generate the results. Performance on YALE, GTAV and ORL face datasets is better compared to other existing methods.

Iris is a physiological biometric trait, which is unique among all biometric traits to recognize person effectively. In this paper we propose Multi-scale Independent Component Analysis (ICA) based Iris Recognition using Binarized Statistical Image Features (BSIF) and Histogram of Gradient orientation (HOG). The Left and Right portion is extracted from eye images of CASIA V 1.0 database leaving top and bottom portion of iris. The multi-scale ICA filter sizes of 5X5, 7X7 and 17X17 are used to correlate with iris template to obtain BSIF. The HOGs are applied on BSIFs to extract initial features. The final feature is obtained by fusing three HOGs. The Euclidian Distance is used to compare the final feature of database image with test image final features to compute performance parameters. It is observed that the performance of the proposed method is better compared to existing methods.&nbsp

The present work evaluates the occupant safety and the mechanical behavior of the Jute-Epoxy-Glass hybrid composite materials and to carry out dynamic analysis of an automobile car frontal components like Bumper beam by using Jute-Epoxy-Glass Hybrid composite material by FE approach. In the present study, HYPERMESH and LS-DYNA software is employed to obtain a better composite material. Durability, NVH, Crash safety and Aesthetics are some of the important vehicle attributes that need to be meet the vehicle manufacturer. While the crash safety for NHTSA requires the G level should be less then 40G'S at the occupant seat. Initially manufacturing of 4 ply, 6 ply (Jute-Epoxy) and 5 ply (Jute-Glass-Epoxy) laminates is done and there characterization is done under Quasi static (1mm/min) and Impact High strain rate loading (100mm/min and 200mm/min) for tensile tests. The mechanical properties obtained are set for the existing bumper beam of a meshed model. For bumper beam of a car with a given velocity of 56 km/h according to the NHTSA high speed crash test. For a high speed crash speed test of bumper beam the G levels is taken into consideration so that the G levels acting upon the occupant doesn't cross 40 G'S as safer. The results obtained from high strain rate of 200mm/min tensile tests explore to bumper beam for which G level acting on the occupant is 35 G's for hybrid jute glass epoxy with 6mm thickness which is found to be best suited composite material which is safer for the occupant and also the weight reduction is also considered where conventionally used steel is 6.6 kgs and the hybrid material of Jute-Glass-Epoxy is 2.9 kgs these weight savings leads to fuel efficiency of the car.

Dehydrocostus lactone (DHCL), a sesquiterpene lactone is well-known for its antiulcer, anti-hepatotoxic and anticancer activity. However, the studies concerning the safety/toxicity potential of DHCL toward the cells of normal origin remain unclear. The present study is aimed at investigating the toxicity potential of DHCL in renal distal tubular and interstitial fibroblast cell lines (MDCK and NRK-49F cells, respectively), and also in ovarian epithelial cell line (CHO cells). The MTT assay has predicted potential cytotoxic activity of DHCL against the cell line types with IC50 values of 0.99, 2.1 and 5.15??M, respectively. The prominent dose-dependent (IC30,50 & 70) increase in the percentage of cells at subG1 phase in all the cell lines revealed apoptosis induction, further establishing the cytotoxic effect of DHCL. The DHCL exposure (4?h) revealed the induction of ROS in both renal cell lines, which is responsible for apoptosis induction. The NRK-49F cells displayed dose-wise (IC30-70) increase in chromatin condensation and membranous phosphatidylserine translocation further confirming apoptotic cell death. Also, their increase in BAX/Bcl-2 ratio, mitochondrial membrane permeability and caspase-3/7 activity establishes mitochondrial mediated apoptosis. In case of CHO cells, the higher percentage of cells at G2/M phase and expression of Cyclin B1 at lower concentration of DHCL (?IC30), indicate mitotic arrest. The incidence of chromatid gaps and negligible micronuclei formation in treated cells (IC10-30) suggest that sub-lethal concentrations of DHCL exposure causes mitotic arrest in response to the damages by steady expression of Cyclin B1. Under in vitro condition, the study of DHCL's potential cytotoxic effect on both kidney cells and ovarian epithelial cells indicated the possibility of adverse effects on normal healthy cells as well. Hence, the study recommends in-depth investigations on DHCL usage concerning its safety in therapeutic applications.

Air-dried, milled leaves of Knoxia corymbosa (220 gm) were extracted repeatedly with dichloromethane. After removal of solvent in vacuo, the CH2Cl2-solvent residue was fractionated by using hexane and ethyl acetate solvents. After fractionation, all fractions are submitted for NMR spectroscopy. Out of all fractions interesting fractions are subjected to column chromatography, so that we isolated one pure compound as Ursolic acid which is a known compound as it is characterized by using reference data. This is the first time to be isolated the above compound from this species. Ursolic acid is a five-membered cyclic triterpenoid compound. A structure of the isolated compound has been assigned on the basis of their analytical data. By surveying the literature, we came to understand that the compound ursolic acid is a cyclic five-member triterpenoid first to be isolated from Knoxia corymbosa. And also, it is first time to isolate the above compound from this species Knoxia corymbosa.

The biometric is used to identify a person effectively and employ in almost all applications of day to day activities. In this paper, we propose compression based face recognition using Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM). The novel concept of converting many images of single person into one image using averaging technique is introduced to reduce execution time and memory. The DWT is applied on averaged face image to obtain approximation (LL) and detailed bands. The LL band coefficients are given as input to SVM to obtain Support vectors (SV’s). The LL coefficients of DWT and SV’s are fused based on arithmetic addition to extract final features. The Euclidean Distance (ED) is used to compare test image features with database image features to compute performance parameters. It is observed that, the proposed algorithm is better in terms of performance compared to existing algorithms.&nbsp

In today’s world as the internet users become more mobile, hence the need for location determination is a key need to provide services based on location, but many devices do not have GPS receivers or transmitters, hence the location determination of these devices is important to provide the location based services, like Advertisements, security, so forth. Location determination of mobile devices has been there for some time but most approaches are based on client intervention, so they are not suitable for integrating in security related components like intrusion detection systems or access control systems. In this paper we propose an approach based on that works on concept of trilateration to determine client location without his/her intervention.

Applications using face biometric are ubiquitous in various domains. We propose an efficient method using Discrete Wavelet Transform (DWT), Extended Directional Binary codes (EDBC), three matrix decompositions and Singular Value Decomposition (SVD) for face recognition. The combined effect of Schur, Hessenberg and QR matrix decompositions are utilized with existing algorithm. The discrimination power between two different persons is justified using Average Overall Deviation (AOD) parameter. Fused EDBC and SVD features are considered for performance calculation. City-block and Euclidean Distance (ED) measure is used for matching. Performance is improved on YALE, GTAV and ORL face databases compared with existing methods.

There is increased incidence of Metabolic Syndrome across the globe. Metabolic Syndrome a strong predictor of coronary vascular disorder and Diabetes Mellitus is not highlighted enough especially in women. This study was undertaken to learn the prevalence of Metabolic Syndrome among urban and rural women.A detailed history, clinical examination along with mini glucose tolerance test, FBS and PPBS in a known diabetic and fasting lipid profile were done in 590 urban and 433 rural women. Metabolic Syndrome was defined using Modified NCEP ATP III Criteria.Metabolic Syndrome was detected in 342 (57.96%) urban and 239 (55.19%) rural women. Individual components of Metabolic Syndrome like Waist circumference of80 cm was found in 283 (82.74%) urban and 171 (71.54 %) rural women, Systolic blood pressure130 mm Hg was found in 261 (76.31%) urban and 187 (78.24 %) rural women, Diastolic blood pressure of85 mm Hg was found in 201 (58.77%) urban and 143 (59.83 %) rural women, Triglycerides of150 mg/dl was found in 187 (43.85%) urban and 159 (66.52 %) rural women, High density lipoprotein of50 mg/dl was found in 309 (90.35%) urban and 224 (93.72 %) rural women and Fasting blood sugars of110 mg/dl was found in 93 (27.19%) urban and 44 (18.41 %) rural women.Our study showed increased prevalence of Metabolic Syndrome in urban women however there is also increasing prevalence in rural women due to changing life style pattern.

Deposition of composite materials as thin film by electron beam physical vapor deposition technique (EB-PVD) still remains as a challenge. Here, the authors report the deposition of NiO-CeO2 (30/70 wt. %) composites on quartz substrate by EB-PVD. Two NiO-CeO2 nanocomposite targets—one as green compact and the other after sintering at 1250 °C—were used for the deposition. Though the targets varied with respect to physical properties such as crystallite size (11–45 nm) and relative density (44% and 96%), the resultant thin films exhibited a mean crystallite size in the range of 20–25 nm underlining the role of physical nature of deposition. In spite of the crystalline nature of the targets and similar elemental concentration, a transformation from amorphous to crystalline structure was observed in thin films on using sintered target. Postannealing of the as deposited film at 800 °C resulted in a polycrystalline structure consisting of CeO2 and NiO. Deposition using pure CeO2 or NiO as target resulted in the...