Special Issue No. – 9, May, 2020

Conference on “Emerging Trends in Applied Science, Engineering and Technology”

Organized by MDSG Research Group, Malaysia

EVALUATION OF CATHODE ELECTRODE PERFORMANCE IN MICROBIAL FUEL CELL BY CYCLIC VOLTAMMETRY

Authors:

Ryuhei Kishida,Dang Trang Nguyen,Kozo Taguchi,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00021

Abstract:

Recently, the Microbial Fuel Cell (MFC) technology has captured the researcher’s attention for potentially solving the energy and environmental problems. In this work, we used cyclic voltammetry (CV) technique to evaluate carbon-based cathode electrode performance in MFC. Although activated carbon sheet (AC) has larger surface area than carbon sheet, experimental results showed that the MFC using carbon sheet for the cathode electrode generated higher power density than the case using AC. Based on the result of CV experiments, we formulate a hypothesis that the above result could be attributed to AC had absorbed more ferrocyanide in the cathodic chamber (ferricyanide turned into ferrocyanide by the oxidation reaction during MFC operation). This led to that the surface area of AC became smaller than that of carbon sheet, as a result, carbon sheet had outperformed AC in the role of the cathode in our MFC experiments.

Keywords:

Microbial fuel cell,Carbon sheet,Activated carbon sheet,Cyclic voltammetry,

Refference:

I. Bard, A. J., Faulkner, L. R., Swain, E., & Robey, C. (n.d.). (2001). Fundamentals and Application

II. Chandrasekhar, K., Kadier, A., Kumar, G., Nastro, R. A., &Jeevitha, V. (2018). Challenges in Microbial Fuel Cell and Future Scope, 483–499.

III. Deng, Q., Li, X., Zuo, J., Ling, A., & Logan, B. E. (2010). Power generation using an activated carbon fiber felt cathode in an upflow microbial fuel cell. Journal of Power Sources, 195(4), 1130–1135.

IV. Franks, A. E., & Nevin, K. P. (2010). Microbial fuel cells, a current review. Energies, 3(5), 899–919.

V. Kumar, R., Singh, L., Zularisam, A. W., & Hai, F. I. (2018). Microbial fuel cell is emerging as a versatile technology: a review on its possible applications, challenges and strategies to improve the performances. International Journal of Energy Research, 42(2), 369–394.

VI. Li, S., Cheng, C., & Thomas, A. (2017). Carbon-Based Microbial-Fuel-Cell Electrodes: From Conductive Supports to Active Catalysts. Advanced Materials, 29(8).

VII. Liang, P., Huang, X., Fan, M. Z., Cao, X. X., & Wang, C. (2007). Composition and distribution of internal resistance in three types of microbial fuel cells. Applied Microbiology and Biotechnology, 77(3), 551–558.

VIII. Logan, B. E., Hamelers, B., Rozendal, R., Schröder, U., Keller, J., Freguia, S., …Rabaey, K. (2006). Microbial fuel cells: Methodology and technology. Environmental Science and Technology, 40(17), 5181–5192.

IX. Nicholson, R. S. (1965). Theory and Application of Cyclic Voltammetry f m Measurement of Electrode Reaction Kinetics. Analytical Chemistry, 37(11), 1351–1355.

X. Ortiz, M. E., & Nu, L. J. (2003). Voltammetric determination of the heterogeneous charge transfer rate constant for superoxide formation at a glassy carbon electrode in aprotic medium, 549, 1–4.

XI. Ozaki, J., Mitsui, M., Nishiyama, Y., Cashion, J. D., & Brown, L. J. (1998). Effects of Ferrocene on Production of High Performance Carbon Electrodes from Poly ( furfuryl alcohol ), (17), 3386–3392.

XII. Santoro, C., Arbizzani, C., Erable, B., &Ieropoulos, I. (2017). Microbial fuel cells: From fundamentals to applications. A review. Journal of Power Sources, 356, 225–244.

XIII. Schröder, U. (2007). Anodic electron transfer mechanisms in microbial fuel cells and their energy efficiency. Phys. Chem. Chem. Phys., 9(21), 2619–2629.

XIV. Taherian, R. (2014). A review of composite and metallic bipolar plates in proton exchange membrane fuel cell: Materials, fabrication, and material selection. Journal of Power Sources, 265, 370–390.

XV. Tursun, H., Liu, R., Li, J., Abro, R., Wang, X., Gao, Y., & Li, Y. (2016). Carbon material optimized biocathode for improving microbial fuel cell performance. Frontiers in Microbiology, 7(JAN), 1–9.

XVI. Zhao, F., Rahunen, N., Varcoe, J. R., Chandra, A., Avignone-Rossa, C., Thumser, A. E., & Slade, R. C. T. (2008). Activated carbon cloth as anode for sulfate removal in a microbial fuel cell. Environmental Science and Technology, 42(13), 4971–4976.

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EARLY FAULT DETECTION IN BEARING USING TIME DOMAIN TECHNIQUE: FAULTY BEARING SEEDED ON INNER RACEWAY AND BALL

Authors:

Abdoulhdi A. Borhana,Uma Shankar,R. Kalaivani,M.A. Khattak,Yasir Hassan Ali,Omar Suliman Zaroog,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00022

Abstract:

One of the most important assets in an industry would be rotating machines. The reliability and availability are very crucial in order to support the accomplishment of an industry field. Major and even minor faults in rotating machines cause a decrease in both productivity and cost efficiency. Various methods have been studied by researcher and introduced in the industry for the detection of an early fault in rotating machines. Vibration signal analysis is one of a standout amongst other methods. This research paper focused on early fault detection in the bearing component at two different positions; inner raceway and ball. The faults were established at three different diameters of 0.007 inches, 0.021 inches, and 0.028 inches. By utilizing time domain technique, parameters such as mean, median, standard deviation, RMS, skewness, impulse factor and shape factor were determined. The vibration signal for both healthy and faulty bearing was deliberated by using the MATLAB software. All the data obtained were represented in graphs where the healthy and faulty bearing values were compared and analyzed.

Keywords:

Ball bearing,early fault detection,time domain technique,inner raceways,

Refference:

I. Csegroups.case.edu. (2017). Download a Data File | Bearing Data Center. [online] Available at: http://csegroups.case.edu/bearingdatacenter/pages/download-data-file [Accessed 31 Aug. 2017].

II. Igba, J., Alemzadeh, K., Durugbo, C. and Eiriksson, E. (2016). Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes. Renewable Energy, 91, 90-106. doi: 10.1016/j.renene.2016.01.006

III. Jiang, Q., Shen, Y., Li, H. and Xu, F. (2018). New Fault Recognition Method for Rotary Machinery Based on Information Entropy and a Probabilistic Neural Network. Sensors, 18(2), 337. doi: 10.3390/s18020337

IV. Liu, W.Y., Tang, B.P., Han, J.G., Lu, X.N., Hu, N.N. and He, Z.Z. (2015). The structure healthy condition monitoring and fault diagnosis methods in wind turbines: A review. Renew. Sustain. Energy Rev. 44, 466–472.

V. Muszynska, A. (1995). Vibrational Diagnostics of Rotating Machinery Malfunctions. International Journal Of Rotating Machinery, 1(3-4), 237-266. doi: 10.1155/s1023621x95000108

VI. Shukla, S. and Karma, V. (2014). Fault Detection of Two Stage Spur Gearbox using Time Domain Technique: Effect of Tooth Breakage and Improper Chamfering. International Journal of Innovative Science, Engineering & Technology, Vol. 1(Issue 4). ISSN 2348 – 7968

VII. Soleimani, A. and Khadem, S. (2015). Early fault detection of rotating machinery through chaotic vibration feature extraction of experimental data sets. Chaos, Solitons& Fractals, 78, 61-75. doi: 10.1016/j.chaos.2015.06.018

VIII. TabriziZarringhabaei, A.A. (2015). Development of new fault detection methods for rotating machines (roller bearings) (PhD Thesis). Mechanical and Aerospace Engineering Department, Porto Institutional Repository, Politenico di Torino.

IX. Tatis De leon, R. (2012). Vibration Measurement for Rotatory Machines (Degree Programme in Automation Engineering). HAMK University of Applied Science.

X. Zayeri, R., Attaran, B., Ghanbarzadeh, A. and Moradi, S. (2011). Artificial Neural Network Based Fault Diagnostics of Rolling Element bearings using Continuous Wavelet Transform. The 2Nd International Conference on Control, Instrumentation, and Automation (IEEE), At Shiraz University, Iran. doi: 10.1109/ICCIAutom.2011.6356754

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PREDICTION OF CARBON DIOXIDE SOLUBILITY IN BLENDS OF AQUEOUS POTASSIUM LYSINATE AND PIPERAZINE USING THERMODYNAMIC MODELING

Authors:

Afaf Syalsabila,Abdulhalim Shah Maulud,Humbul Suleman,Nik Abdul HadiMd Nordin,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00023

Abstract:

In the present study, a thermodynamic modeling using explicit model is performed for the determination of carbon dioxide solubility in blends of aqueous potassium lysinate with piperazine at a wide range of pressure from 500 to 4100 kPa, temperature within 303.15-343.15 K, and solvent concentrations of 1, 2 and 3 M. The model has suitably predicted the carbon dioxide thermodynamics of the solutions. The average absolute deviation from the correlation of the explicit model is found to be 8.5%.

Keywords:

vapor-liquid equilibrium,carbon dioxide,thermodynamic modeling,amino acid,alkanolamine,

Refference:

I. Aronu UE, Hessen ET, Haug-Warberg T, Hoff KA, Svendsen HF. Equilibrium absorption of carbon dioxide by amino acid salt and amine amino acid salt solutions. Energy procedia. 2011;4:109-16.
II. Bougie F, Iliuta MC. Sterically hindered amine-based absorbents for the removal of CO2 from gas streams. J ChemEng Data. 2012;57(3):635-69.
III. Chung P-Y, Soriano AN, Leron RB, Li M-H. Equilibrium solubility of carbon dioxide in the amine solvent system of (triethanolamine+ piperazine+ water). J ChemThermodyn. 2010;42(6):802-7.
IV. Donaldson TL, Nguyen YN. Carbon dioxide reaction kinetics and transport in aqueous amine membranes. IndEngChemFundam. 1980;19(3):260-6.
V. Edwards T, Maurer G, Newman J, Prausnitz J. Vapor‐liquid equilibria in multicomponentaqueous solutions of volatile weak electrolytes. AIChE J. 1978;24(6):966-76.
VI. Gabrielsen J. CO2 capture from coal fired power plants. Graduate Schools Yearbook 2005.2005:61.
VII. Hamzehie ME, Najibi H. Carbon dioxide absorption in aqueous solution of potassium glycinate+ 2-amino-2-methyl-1-propanol as new absorbents. RSC Advances. 2016;6(67):62612-23.
VIII. Kang D, Park S, Jo H, Min J, Park J. Solubility of CO2 in amino-acid-based solutions of (potassium sarcosinate),(potassium alaninate+ piperazine), and (potassium serinate+ piperazine). J ChemEng Data. 2013;58(6):1787-91.
IX. Kumar P, Hogendoorn J, Feron P, Versteeg G. Equilibrium solubility of CO2 in aqueous potassium taurate solutions: Part 1. Crystallization in carbon dioxide loaded aqueous salt solutions of amino acids. IndEngChem Res. 2003;42(12):2832-40.
X. Lerche BM, Stenby EH, Thomsen K. CO 2 capture from flue gas using amino acid salt solutions: Technical University of DenmarkDanmarksTekniskeUniversitet, Department of ChemistryInstitut for Kemi; 2012.
XI. Mondal MK, Balsora HK, Varshney P. Progress and trends in CO2 capture/separation technologies: a review. Energy. 2012;46(1):431-41.
XII. Muñoz DM, Portugal AF, Lozano AE, José G, de Abajo J. New liquid absorbents for the removal of CO 2 from gas mixtures. Energy & Environmental Science. 2009;2(8):883-91.
XIII. Nainar M, Veawab A. Corrosion in CO2 capture process using blended monoethanolamine and piperazine. IndEngChem Res. 2009;48(20):9299-306.
XIV. Portugal A, Sousa J, Magalhães F, Mendes A. Solubility of carbon dioxide in aqueous solutions of amino acid salts. ChemEng Sci. 2009;64(9):1993-2002.
XV. Sakwattanapong R, Aroonwilas A, Veawab A. Behavior of reboiler heat duty for CO2 capture plants using regenerable single and blended alkanolamines. IndEngChem Res. 2005;44(12):4465-73.
XVI. Song H-J, Lee S, Maken S, Park J-J, Park J-W. Solubilities of carbon dioxide in aqueous solutions of sodium glycinate. Fluid Phase Equilib. 2006;246(1):1-5.
XVII. Suleman H, Maulud AS, Man Z. Carbon Dioxide Solubility in Aqueous Potassium Lysinate Solutions: High Pressure Data and Thermodynamic Modeling. Procedia Engineering. 2016;148:1303-11.
XVIII. Suleman H, Maulud AS, Syalsabila A. Thermodynamic modelling of carbon dioxide solubility in aqueous amino acid salt solutions and their blends with alkanolamines. Journal of CO2 Utilization. 2018;26:336-49.
XIX. Syalsabila A, Maulud AS, Nordin NAHM, Suleman H, editors. VLE of carbon dioxide loaded aqueous potassium lysinate with separate blends of piperazine and 2-amino-2-methyl-1-propanol. AIP Conference Proceedings; 2018: AIP Publishing.
XX. Van Holst J, Politiek PP, Niederer JP, Versteeg GF, editors. CO2 capture from flue gas using amino acid salt solutions. Proceedings of 8th International Conference on Greenhouse Gas Control Technologies; 2006.

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THE ARCHITECTURE OF THE SOVIET MAUSOLEUM IN THE CONTEXT OF TIME

Authors:

Dmitry A. Chistyakov,Galina I. Bykova,Natalya N. Korshunova,Alexander N. Kalugin,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00024

Abstract:

The Soviet Mausoleum in Red Square is an object of historical, political, architectural and town-planning significance. Lenin's mausoleum is a construction of absolutely exceptional importance, not limited to the red square, Moscow or even the entire Soviet Union. This building is unique both for its purpose and architectural forms and artistic qualities. The creation of the Mausoleum is an integrated approach of the architect, according to the time period in which the design was carried out. The identification of its viability, nowadays, is an actual task for representatives of various professions: sociologists, psychologists, political scientists, city planners and architects. The analysis of the history of the mausoleum creation, the establishment of time parallel and also an assessment of the importance of town planning and space planning solutions let us suggest possible prospects for the existence of this object

Keywords:

Red Square,mausoleum,ziggurat,radiation,

Refference:

I. Abramov A. Truth and fiction about the Kremlin necropolis and the Mausoleum. Moscow: Eksmo, 2005.
II. Afanasyev K. N. From the history of Soviet architecture 1917-1925.
III. Brian Curran. The Egyptian Renaissance. The after life of Ancient Egypt in early Modern Italy. Chicago: University of Chicago Press. 2007.
IV. Brodsky B.. The heart of the Kremlin. Moscow: Fine arts, 1996.
V. Curl J.S. Egyptian Revival. London. 2005.
VI. Demkina, S. M., Davydova, I. I., Novikova E. B. Architect
VII. F. O. Shekhtel. Moscow, 2009.
VIII. Jean-Marcel Humbert, Michael Pantazzi, Christiane Ziegler. Egyptomania; Egypt in Western art. 1994.
IX. Khan-Magomedov S. O. Hundred masterpieces of Soviet architectural avant-garde. Moscow: Bilingua, editorial URSS. 2005.
X. Khan-Magomedov S. O., Lenin’s Mausoleum. Moscow: S. E. Gordeev, 2012.
XI. Moscow: Documents and materials. 1963.
XII. Nashchokina M. V. Architects of Moscow art Nouveau. Moscow. 1998.
XIII. Riabchikov, E. I., Abramov A. S., Romanovsky.PP. Red square Moscow: Moscow worker Press. 1980.
XIV. Strada Vittorio. About the mausoleum of Lenin. Kontinent No. 77. Moscow: Continent, 1993.
XV. Vaskin. A. Shchusev: the Architect of all the Russias. Moscow: Young guard, 2015.
XVI. Yaralov U.S. Architects of Moscow. Book 2. Of the twentieth century. Moscow: Moscow worker, 1988.

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CHARACTERIZING PROTECTION ABILITY OF BLUE BLOCKING LENSES USING K-MEANS CLUSTERING

Authors:

Mohd Zulfaezal Che Azemin,Norsham Ahmad,Mohd Hafidz Ithnin,Mohd Hazimin Mohd Salleh,Mohd Izzuddin Mohd Tamrin,Saiful Azlan Rosli,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00025

Abstract:

Blue light protection ophthalmic lenses have been regularly marketed as the ultimate protection against short-wavelength visible radiation mainly in the range of 400 nm and 450 nm. However, the actual protective effects of such lenses are currently unknown; most claims are provided by the manufacturers with limited scientific validation. This will not only make selling such lenses challenging but may provide the lens wearers little or no protection against the blue light hazard. It is recently discovered that the protection needs to take into accounts the light source that the wearers wish to protect from – heavy electronic gadget users for instance, are exposed to different spectrum of radiation compared to non-users. This problem is aggravated when the hazard needs to further be classified into the visual and non-visual effects. Non-visual impact includes the disruption in the circadian cycle which is governed by the physiological cycles of our body within 24 hours such as the melatonin hormone secretion. Such knowledge will help to educate optometrist to explain to their prospective customers and will also assist the spectacle wearers to make an informed decision based on validated scientific data.

Keywords:

Blue-blocking lens,retinal index,circadian index,k-means clustering,,

Refference:

I. Ámundadóttir, M. L., Lockley, S. W., & Andersen, M. (2017). Unified framework to evaluate non-visual spectral effectiveness of light for human health. Lighting Research & Technology, 49(6), 673-696.
II. Ashar, A. M., Lam, M. C., Zainudin, S., & Ismail, A. K. (2018, September). A preliminary study on the decision support mobile application for remote snakebite management consultation in Malaysia. In AIP Conference Proceedings (Vol. 2016, No. 1, p. 020086). AIP Publishing.
III. Atkinson, K. M., El-Khatib, Z., Barnum, G., Bell, C., Turcotte, M. C., Murphy, M. S. Q., & Wilson, K. (2017). Using Mobile Apps to Communicate Vaccination Records: A City-wide Evaluation with a National Immunization App, Maternal Child Registry and Public Health Authorities. Healthcare quarterly (Toronto, Ont.), 20(3), 41-46.
IV. Beaudoin, D. L., Kupershtok, M., & Demb, J. B. (2017). Selective synaptic connections in the retinal pathway for night vision. Journal of Comparative Neurology.
V. BlueControl. (2018). Retrieved from https://www.hoyavision.com/my/discover-products/for-eye-care-professionals/coatings-and-treatments/bluecontrol/
VI. Che Azemin, M. Z., & Khalilah, A. (2018). Textural analysis in meibomian gland image. International Journal of Allied Health Sciences, 2(1), 215-225.
VII. Che Azemin, M. Z., Ashimi, T. A., & Syah, M. M. (2018). Machine learning cases in clinical and biomedical domains. International Medical Journal Malaysia, 17, 135-140.
VIII. Colombo, L., Melardi, E., Ferri, P., Montesano, G., Attaalla, S. S., Patelli, F., & Rossetti, L. (2017). Visual function improvement using photocromic and selective blue-violet light filtering spectacle lenses in patients affected by retinal diseases. BMC ophthalmology, 17(1), 149.
IX. Comparetto, R., & Farini, A. (2018). Blue-blocking spectacles lenses for retinal damage protection and circadian rhythm: evaluation parameters. arXiv preprint arXiv:1806.04751.
X. Hatori, M., Gronfier, C., Van Gelder, R. N., Bernstein, P. S., Carreras, J., Panda, S., & Furukawa, T. (2017). Global rise of potential health hazards caused by blue light-induced circadian disruption in modern aging societies. NPJ aging and mechanisms of disease, 3(1), 9.
XI. Hilmi, M. R., Che Azemin, M. Z., Mohd Kamal, K., Mohd Tamrin, M. I., Abdul Gaffur, N., & Tengku Sembok, T. M. (2017). Prediction of changes in visual acuity and contrast sensitivity function by tissue redness after pterygium surgery. Current eye research, 42(6), 852-856.
XII. Jamaludin, I., Che Azemin, M. Z., Sapuan, A. H., Zainuddin, A. A., & Hassan, R. (2018). 2D and 3D Complexity Analysis on MRI Images using Fractal Dimension. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-8), 161-164.
XIII. Lau, C., & Kolli, V. (2017). App use in psychiatric education: a medical student survey. Academic Psychiatry, 41(1), 68-70.
XIV. Leung, T. W., Li, R. W. H., & Kee, C. S. (2017). Blue-light filtering spectacle lenses: optical and clinical performances. PloS one, 12(1), e0169114.
XV. Malik, S., Bibi, N., Khan, S., Sultana, R., & Rauf, S. A. (2017). Mr. Doc: A Doctor Appointment Application System. arXiv preprint arXiv:1701.08786.
XVI. Ng, Andrew. “CS229 Lecture notes.”CS229 Lecture notes 1.1 (2000): 1-3.
XVII. Park, S. I., & Jang, Y. P. (2017). The protective effect of brown-, gray-, and blue-tinted lenses against blue led light-induced cell death in A2E-laden human retinal pigment epithelial cells. Ophthalmic research, 57(2), 118-124.
XVIII. Tamrin, M. I. M., Turaev, S., Che Azemin, M. Z., Razi, M. J. M., & Maifiah, M. H. M. (2019). Benchmarking of halal food products using similarity measures–a conceptual model. Journal of Information Systems and Digital Technologies, 1(1), 17-24.
XIX. Wei, M., & Chen, S. (2018). Impact of spectral power distribution of daylight simulators on whiteness specification for surface colors. Color Research & Application, 43(1), 27-33.
XX. Westland, S., Pan, Q., & Lee, S. (2017). A review of the effects of colour and light on non‐image function in humans. Coloration Technology, 133(5), 349-361.

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PRINCIPLES IN DESIGNING THE HOSPITAL BUILDING

Authors:

Yahaya Hassan,Azli Yahya,Jasmy Yunus,Sarajul Fikri,Norhalimah Idris,Husna Hamzah,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00026

Abstract:

Special attention and provisions must be done when designing and building a hospital. Designing a hospital that satisfies those criteria are difficult, but not entirely impossible. Extra effort in adhering to specific rules and regulations of Ministry of Health, especially when integrating latest technology in the hospital design are challenging. Therefore, based on the above dilemma, this paper discusses the principles in designing an optimum hospital, which able to accommodate the present and future needs of hospital capacity

Keywords:

Design,elements,hospital building,hospital planning,principles,

Refference:

I. Asian Development Bank, “Key Indicators for Asia and The Pacific 2016” (47th Edition), 2016, pp 119.
II. Cahnman, S.F., “Design Guidelines for Short-Stay Patient Units: Outpatient Observation Prompts New Thinking in Health Care Space Configuration”, Health Facilities Management Magazine (online), 3 May 2017.
III. Department of Statistics Singapore, “Singapore in Figure 2017”, (2017), pp 4, 27.
IV. McDermott, C and Stock G.N., “Hospital Operations and Length of Stay Performance”, International Journal of Operations & Production Management, Vol. 27 (9) (2007), pp 1020-1042.
V. Ministry of Health Malaysia, “Health Facts 2016”, 2016.
VI. Ministry of Health Malaysia, Private Healthcare Facilities and Services Act 1998 and 2006.
VII. Nwagbara, V.C., Rasiah, R, Aslam, M.M, “An Approach toward Public Hospital Performance Assessment”, Medicine, Vol. 95 (36) (2016), pp 1-6.
VIII. Personal observations on planning and design of the hospital development.
IX. Yamaguchi, Y, “Better Healing from Better Hospital Design”, Harvard Business Review (online), 5 October 2015.

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THE RELATIONSHIP BETWEEN FIVE ELEMENTS AND NINE VARIABLES IN HOSPITAL PLANNING

Authors:

Yahaya Hassan,Azli Yahya,Jasmy Yunus,Sarajul Fikri,Norhalimah Idris,Husna Hamzah,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00027

Abstract:

Hospital is a place where the sick comes to seek for treatment from doctor. Hence, special attention and provisions must be given when designing and building the hospital which include assurance in terms of safety requirements, convenience, accessibility and functional for all stakeholders (patients, visitors and staffs). Designing an ideal hospital, which satisfies the above criteria, is challenging, but not entirely impossible. Extra efforts are required in ensuring a design not only functional but adheres to specific rules and regulations, especially incorporating latest technology. This paper discusses the initial stage of hospital planning and design, which incorporates all the necessary parameters (elements and variables) in hospital planning such as bed sizing, service area and locations, which are crucial for the mass users of population. Some analysis based on researcher’s professional judgement is applied in making projection of the present and future hospital capacity.

Keywords:

Design,elements,hospital building,hospital planning,principles,variables,

Refference:

I. Asian Development Bank, “Key Indicators for Asia and The Pacific 2016” (47th Edition), 2016, pp 119.
II. Cahnman, S.F., “Design Guidelines for Short-Stay Patient Units: Outpatient Observation Prompts New Thinking in Health Care Space Configuration”, Health Facilities Management Magazine (online), 3 May 2017.
III. Department of Statistics Singapore, “Singapore in Figure 2017”,(2017, pp 4, 27.
IV. McDermott, C and Stock G.N., “Hospital Operations and Length of Stay Performance”, International Journal of Operations & Production Management, Vol. 27 (9) (2007), pp 1020-1042.
V. Ministry of Health Malaysia, “Health Facts 2016”, 2016.
VI. Nwagbara, V.C., Rasiah, R, Aslam, M.M, “An Approach toward Public Hospital Performance Assessment”, Medicine, Vol. 95 (36) (2016), pp 1-6.
VII. Yamaguchi, Y, “Better Healing from Better Hospital Design”, Harvard Business Review (online), 5 October 2015.

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ENERGY MANAGEMENT SYSTEM WITH DEMAND RESPONSE FOR SOLAR HOME

Authors:

Ghania Mohand Kaci,Achour Mahrane,Madjid Chikh,Smain Berkane,

DOI:

https://doi.org/10.26782/jmcms.spl.9/2020.05.00028

Abstract:

In order to reduce the energy consumption and the environmental footprint of the residential sector, the use of renewable energy sources seems to be an interesting option. However, the intermittent nature of these sources necessitates the installation of a Solar Home Energy Management System (SHEMS) that would ensure both the management of the energy flows and the optimization of the energy demand satisfaction through on-site photovoltaic production of electricity. Regarding the relative incompatibility of photovoltaic production and residential energy consumption profiles, it has been practically demonstrated that the integration of a demand response strategy in the SHEMS system made it possible to adapt the consumption profile to the photovoltaic production profile by shifting the running of the controllable loads to periods of high energy production. This demand management (DR) increases the direct consumption of the PV production by 22%, reduces the energy exchanges with the network and improves, at the same time, the satisfaction rate of the demand by 14%.

Keywords:

Home Energy Management System,Renewable Energy,Solar home,Demand Response,Appliance scheduling,

Refference:

I. A. Anis, M. Mohibullah, and V. K. Sharma, “Optimal Hybrid Renewable Energy Systems for Energy Security: A Comparative Study”, International Journal of Sustainable Energy, vol. 29 (1), pp. 48-58, July 2010
II. A. Chiu. “Framework for integrated demand response (DR) and distributed energy resources (DER) models”, NAESB &UCAIug, North America, Tech. Rep. 1.3, September 2009
III. A. Mohsenian-Rad, V. W. S. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “Autonomous demand-side management based on game theoretic energy consumption scheduling for the future smart grid” IEEE Trans. Smart Grid, vol. 1, no 3, pp. 320-331, 2010
IV. A. Sathisshkumar, S. Jayamani, “Renewable energy management system in home appliance”, Presented at the International Conference on Circuit, Power and Computing Technologies (ICCPCT), Nagercoil, India. March 19-20, 2015
V. C. Davide, C. Vittorio, C. Lorenzo, C. Federica, D. Idiano, and F. Federico, “Evaluating solar energy profitability: A focus on the role of self-consumption”, Energy Conversion and Management, Vol. 88, pp.317-331, 2014
VI. C.H. Lien, H.C. Chen, Y. W. Bai, and M.B. Lin, “Power monitoring and control for electric home appliances based on power line communication”, In Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, British Columbia, Canada, pp. 2179-2184, May 2008
VII. H. Jinsoo, C. Chang-Sic, P. Wan-Ki, L. Ilwoo, and K. Sang-Ha, “Smart home energy management system including renewable energy based on zigbee and PLC”, In Proceedings of the IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, Nevada, USA, January 10-13, 2014
VIII. H. Yamauchi, K. Uchida, and T. Senjyu, “Advanced Smart Home” In Proceedings of the IEEE International Conference on Harmonics and Quality of Power, Hong Kong, China, pp.130-135, Jun 2012
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