This paper deals with the implementation of Simple Algorithm for detection of range and shape of tumor in brain MR images. Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different Characteristics and different treatment. As it is known, brain tumor is inherently serious and life-threatening because of its character in the limited space of the intracranial cavity (space formed inside the skull). Most Research in developed countries show that the number of people who have brain tumors were died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intracranial cavity produces a complete image of brain. This image is visually examined by the physician for detection & diagnosis of brain tumor. However this method of detection resists the accurate determination of stage & size of tumor. To avoid that, this work uses computer aided method for segmentation (detection) of brain tumor based on the k.means and fuzzy c-means algorithms. This method allows the segmentation of tumor tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it also reduces the time for analysis.

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ABSTRACT:Circadian and other biological rhythms affect diseases, there symptoms and severity of symptoms and drug therapy can be modified keeping these variations under consideration. Chronopharmacology refers to the manner & extent to which the kinetics and dynamics of medication is directly affected by endogenous biological rhythm and also how the dosing time of medications affects biological timekeeping & features. It has a number of advantages as it reduces drug dosage, increases therapeutic efficacy of drug, limits the time of therapy, reduces side effects, slows down speed of progression of disease and especially helpful in preventing drug toxicity in case of compromised body systems. There is a great deal of interest in how chronotherapy can particularly benefit patients suffering from allergic rhinitis, rheumatoid arthritis and related disorders, asthma, cancer, cardiovascular diseases, ankylosing Spondylitis, renal disorders, antimicrobial therapy, diabetes mellitus, ant-inflammatory therapy, peptic ulcer disease etc. Various drug delivery systems have been developed like pulsatile drug delivery systems, Enteric-coated systems, Layered systems, time-controlled explosion systems (TES), sigmoidal release systems (SRS), electric based drug delivery systems system, controlled-release microchip, etc for effective chronotherapy. There is great deal of hope for effective drug therapy using chronopharmacology in near future.

Psoriasis is inflammatory skin disorder, which is chronic and an autoimmune disease and affect the life of approximately 2% of the world population. There are various topical treatments which has been used such as topical steroids, dithranoletc andall shows very low efficacy, poor solubility andhas low aesthetic and cosmetic appeal, ultimately results in low patient compliance on the other hand systemic therapiesproduces significant side effects. Successive progress in the development of new drug delivery system such as colloidal drug delivery systems has led to effective and safe treatment of psoriasis. Colloidal carriers such as vesicular and particulate carriers includes liposome, emulsome, transferosomes, ethosomes, SLNs, microspheres, micelles, dendrimers etc. have gained unique and impotant position in drug delivery system. Several approaches are done for treatment of psoriasis but, rate of success is always a questionwhen conventional system is concerned for the treatment of psoriasis. Present article is an attempt to improve the therapy of psoriasis related to its pathogenesis and offers disease management of this, treatment of psoriasis and the pharmaceutical approach was done for effective and safe drug delivery for the treatment and management of this disease. It will also discuss details about topical drug delivery in general and its challenges in designing effective drug delivery against psoriasis.

Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. This paper implemented a method to detect moving object based on background subtraction. First of all, we establish a reliable background updating model based on statistical and use a dynamic optimization threshold method to obtain a more complete moving object. The moving human bodies are accurately and reliably detected. The experiment results show that the proposed method runs quickly, accurately and fits for the real-time detection.