Design of Double Loop CDM Controllers for Proton Exchange Membrane Fuel Cell Fed DC-DC Boost Converter Under Wide Source and Load Variations

Heena Mishra,Shashwati Ray,Tata Venkat Dixit 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.5

Proton Exchange Membrane Fuel Cell (PEMFC) are emerging as the new renewable energy source. The output voltage of PEMFC is not sufficient to fulfill the load demands which varies with variations in temperature and load. So, it is integrated with a properly designed power conditioning unit to enhance and stabilize the voltage. In this paper Nexa 1.2 KW PEMFC is initially modeled using successive trust region. Next, a DC-DC boost converter connected to the fuel cell is designed using interval analysis to boost and regulate the output voltage adhering to the changes in the temperature and loading conditions. To stabilize the output of PEMFC fed boost converter, double loop robust controllers are implemented which are designed by Coefficient Diagram Method (CDM). All the responses of the CDM controlled boost converter settle down smoothly at the desired settling time with zero overshoot. The proposed controller fair quite well as compared to other similar controllers in the existing literatures.

Enhancement of Anxiety and Modulation of TH and pERK Expressions in Amygdala by Repeated Injections of Corticosterone

( Heena Lim ),( Soyong Jang ),( Yeonju Lee ),( Sohyeon Moon ),( Jieun Kim ),( Seikwan Oh ) 한국응용약물학회 2012 Biomolecules & Therapeutics(구 응용약물학회지) Vol.20 No.4

Repeated stress induces corticosterone release. However, it is not clear that stress results in further elevation of corticosterone levels, and the roles of released corticosterone to aggravate stress-related symptoms are also not clear. This study investigated whether neuronal modulation was induced in the amygdala after two kinds of stress, that is, such as electric shock and corticosterone injection. It was found that stress by electric shock decreased the expression of tyrosine hydoroxylase (TH) in the amygdala while the expression of pERK was increased. However, there is no difference in the expressions of TH and pERK in the frontal cortex compared with those of the control group. The level of corticosterone was signifi cantly increased in the serum after stress. To determine the effect of corticosterone on the induction of anxiety and the expression of TH, the rats received corticosterone (20 mg or 40 mg/kg i.p.) for 1 day, 1 week, 2 weeks and 3 weeks, respectively. The spent time in open arms of the EPM (elevated plus maze) test was signifi cantly decreased after 1 week, 2 weeks and 3 weeks. The time spent in open arms of the EPM test after repeated injections of corticosterone was signifi cantly decreased in a dose-dependent manner. The expression of TH in the amygdala was reduced after following repeated corticosterone treatment for 2 weeks and 3 weeks. Collectively, this study suggests that corticosterone has a major role in the induction of anxiety and the modulation of TH expression, at least, in the amygdala.

Earthworms diversity of Koppal district with the updated information on genus Thatonia of Hyderabad–Karnataka region, Karnataka, India

Heena Mubeen,Shankerappa S. Hatti 국립중앙과학관 2018 Journal of Asia-Pacific Biodiversity Vol.11 No.4

Earthworm survey was conducted in the selected habitats of Koppal district (15°09′00″ to 16°03′30″) of Hyderabad- Karnataka region. Earthworms were collected from Holemudalapura, Matti Mudalapura, Shivapur, Nelogal, Taralkatti, Putakmari, Kurubanhal, Budakunti, Anegundi and Rampur. 8 genera and 14 species of earthworms were identified viz., Dichogaster bolaui, Dichogaster modigliani, Octochaetona albida, Octochaetona paliensis, Octochaetona parva and Octochaetona prashadi belonging to family OCTOCHAETIDAE; Lampito mauritii, Perionyx fulvus, Perionyx koboensis, Perionyx millardi, Polypheretima elongata thecomorph and Polypheretima elongata athecomorph belonging to family MEGASCOLICIDAE; Thatonia gracilis and Thatonia parva belonging to family OCNERODRILIDAE and Eudrilus eugeniae belonging to family EUDRILIDAE. The smallest being Thatonia gracilis having a length of 2–2.5 cm and diameter of 1–1.5 mm and largest being Eudrilus euginiae having length 26–27 cm and diameter 5–5.6 mm. Dichogaster bolaui, Lampito mauritii, Perionyx koboensis Perionyx millardi, Thatonia gracilis & Thatonia parva were found in the garbage. Dichogaster modigliani, Lampito mauritii, Octochaetona albida, Octochaetona paliensis, Octochaetona parva, Polypheretima elongata thecomorph were found near the bore-well sewage water. Eudrilus eugeniae, Perionyx millardi, Polyperetima elongata athecomorph, Thatonia parva and Octochaetona prashadi in the gutter. Perionyx koboensis was found in the irrigated land. Parameters like temperature, humidity were recorded and physicochemical analysis of the soil was carried out.

Covalent Organic Framework (COF-10)를 이용한 암모니아 흡착 및 탈착에 관한 연구

양희나 ( Heena Yang ),김익태 ( Iktae Kim ),고영돈 ( Youngdon Ko ),김신동 ( Shindong Kim ),김화중 ( Whajung Kim ) 한국공업화학회 2016 공업화학 Vol.27 No.3

수소가 청정 에너지 원으로서의 중요성이 증가하면서 수소의 생산원인 암모니아 기체가 큰 주목을 받고 있다. 그러나 암모니아가 금속을 잘 부식시키고 유독성을 가지고 있기 때문에 암모니아의 저장과 운반을 가능하게 하는 흡착제의 연구가 다각도로 진행되고 있다. 이 중 공유결합 유기구조 물질(covalent organic framework)의 하나인 COF-10은 붕소를 포함한 큰 기공을 가진 물질이다. 암모니아 흡착과정에서 COF-10의 구조 안에 있는 붕소는 루이스 산으로 작용하여 암모니아와 강한 결합을 한다. 본 논문에서는 이러한 COF-10을 합성하여 BET, XRD, FT-IR을 통해 구조를 확인한다. 또한 TPD와 등온 흡착 실험을 통해 실제 암모니아의 흡착능력에 대한 분석을 진행하였다. COF-10는 9.79 mmol/g 으로 우수한 암모니아 흡착 능력을 보였으며 암모니아 흡착제로서 활용 가능할 것으로 사료된다. Ammonia gas as a hydrogen source has received great attention since the importance of hydrogen gas as a clean energy source increased. However, ammonia is toxic and corrosive to metal such that the absorbent that can store and transport ammonia became an important issue. As an effort to solve this, a large pored covalent organic framework, COF-10 was proposed as an adsorbent for storage and safe transportation of ammonia. During the ammonia adsorption process, boron in COF-10 structure can act as a Lewis acid site and bind with ammonia. In this study, COF was synthesized and its structure was identified by BET, XRD and FT-IR. The adsorption characteristics of COF were investigated by TPD and adsorption isotherm. The COF-10 showed an excellent adsorption capacity for ammonia (9.79 mmol/g) which could be utilized as an ammonia adsorbent.

Efficacy of Flaxseed Flour as Bind Enhancing Agent on the Quality of Extended Restructured Mutton Chops

Sharma, Heena,Sharma, Brahma Deo,Mendiratta, S.K.,Talukder, Suman,Ramasamy, Giriprasad Asian Australasian Association of Animal Productio 2014 Animal Bioscience Vol.27 No.2

Consumers have become very conscious about their nutrition and well being due to changes in their socio-economic lifestyle and rapid urbanization. Therefore, development of technology for production of low cost and functional meat products is urgently required. One such approach is innovative restructuring technology in which binding of meat pieces still remains the main challenge and extension of product is generally associated with poor binding and texture. Thus, the present study was envisaged as an attempt to solve this problem by the incorporation of flaxseed flour (FF) as bind enhancing agent. The FF was used at three different levels viz., 0.5%, 1%, and 1.5% to replace lean meat in pre-standardized restructured mutton chops formulation. The products were subjected to analysis for physico-chemical, sensory and textural properties. Cooking yield, moisture percentage and fat percentage increased with increase in the level of incorporation of FF, however, protein percent and pH decreased with increase in the level of incorporation. Shear force value of product incorporated with 1.5% FF was significantly higher (p<0.01) than control and product containing 0.5% FF level. Among the sensory attributes, product with 1% flaxseed flour showed significantly higher values (p<0.05) for general appearance, binding, texture and overall acceptability. Hardness showed significant increasing (p<0.01) values with increasing levels of incorporation of flaxseed flour, however all other parameters of texture profile analysis showed a decreasing trend. On the basis of sensory scores and physico-chemical properties, the optimum incorporation level of FF was adjudged as 1%. Products incorporated with optimum level of flaxseed flour (1%) were also assessed for water activity and microbiological quality during the storage period of 15 days. It was found that the extended restructured product could be safely stored under refrigeration ($4^{\circ}C{\pm}1^{\circ}C$) in low density polyethylene (LDPE) pouches for 15 days without marked deterioration in sensory and microbiological quality. Thus, it was concluded that flaxseed flour can be used as a good bind enhancing agent in extended restructured meat products at an economic cost.

표면 사이징 된 종이의 가속 열화 특성 구명

신희내(Heenae Shin),윤혜정(Hye Jung Youn),이학래(Hak Lae Lee) 한국펄프·종이공학회 2010 한국펄프·종이공학회 학술발표논문집 Vol.2010 No.10

서구의 신안선 연구 현황과 전망

윤희나(Heena Youn) 국립광주박물관 2020 아시아 도자문화 연구 Vol.- No.3

A Hybrid Model for Android Malware Detection using Decision Tree and KNN

Sk Heena Kauser,V.Maria Anu International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.7

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.

Android Malware Detection using Machine Learning Techniques KNN-SVM, DBN and GRU

Sk Heena Kauser,V.Maria Anu International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.7

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

셀룰로오스 나노섬유 시트의 습윤강도 향상을 위한 가교화제 적용

신희내(Heenae Shin),오유진(Yujin Oh),박신영(Shin Young Park),윤혜정(Hye Jung Youn) 한국펄프·종이공학회 2022 한국펄프·종이공학회 학술발표논문집 Vol.2022 No.4