American Journal of Scientific Research and Essays


Influence of Elements of Work Realities on HRD Mandate Capability in Banking Organisations in Nairobi County, Kenya

Research article of American Journal of Scientific Research and Essays Influence of Elements of Work Realities on HRD Mandate Capability in Banking Organisations in Nairobi County, Kenya Angeline Oyomo1, Leonard Mulongo2, Pacifica C. Mining3 1Moi University, School of Business and Economics, Department of Human Resource Development, P. O. Box 3900-30100, Eldoret, Kenya.2Moi University, School of Arts and Social Sciences, Department of Development Studies, P. O. Box 3900-30100, Eldoret, Kenya. 3Moi University, School of Business and Economics, Department of Human Resource Development, P. O. Box 3900-301, Eldoret, Kenya. Globally, business organizations recognize that engaging human resource management practices on an international standard is imperative. But realizing target performance from just scarce resources is a challenge to most organisations. Many organisations are continuously spending time trying to control and master change making them losers. With the current practice, HR has not been able to deliver on training line management in methods of achieving high employee production. This paper investigated the Influence of Elements of Work Realities on HRD Mandate Capability in Banking Organisations in Nairobi County, Kenya. The main objectives pursued included to establish the relationship between employer-employee champion and HRD mandate capability in Banking Organisations in Nairobi County, Kenya; to determine the association between continuous transformation agent and HRD mandate capability in Banking Organisations in Nairobi County, Kenya. A survey of banking institutions was used while a questionnaire and interview schedule and content analysis were used to gather primary data. The target population was 850 and a sample size of 272 was used. Statistical analysis was done using Statistical Package of Social Sciences (SPSS) current version. The findings confirmed that there are problems facing human resource mandate delivery capability. It was concluded that all the two elements of work realities have significant influence on HR mandate delivery capability. It was therefore ...

DIGITAL LEARNING of MACHINES AND ITS INTERFACING TECHNIQUES

Research article of American Journal of Scientific Research and Essays DIGITAL LEARNING of MACHINES AND ITS INTERFACING TECHNIQUES Prashant Unnikrishnan Nair University of North Carolina, Kenan-Flagler Business School The paper discusses a unique technique developed initially at Nation Institute of Technology, Surat that is remodeled in real world applications. The concept consists primarily of a user-friendly software facilitating direct communication with any intelligent or learning system/robot operating under known parameters of motor specifications. Any software base permitting high level PC interface without ASCII interrupt can be used and here Visual Basic is represented for easy programing. This allow for a learning operation mode where a prevention of time lag implementation stores machine data based on movements by the machine stored or actions taught. Such learning aspects make the machine more efficient where the robot can either perform individual actions as needed or learn new methods for the same results and can perform a series of actions continuously. Using the stored data, the machine is also capable of autonomous movements based on the path of least resistance as calculated by the time it takes to perform an act. Unlike the ALPHA model, new and improved model is tested on a CNC 6 axis manufacturing machine This paper focuses on methodology of interface through VB programing and does not contain associated files to retain any possible patent applications. Keywords: AI- Artificial intelligence Interface- Firmware device that interacts with the machine and the user. RPM- rotation per minute Hexadecimal – a 16 digits format in sequence of 4 that is used instead of traditional ASCII codes ...

Ca-Markov Model for Simulating Land Use Land Cover Dynamics in Rufiji Delta of Tanzania

Research article of American Journal of Scientific Research and Essays Ca-Markov Model for Simulating Land Use Land Cover Dynamics in Rufiji Delta of Tanzania Job Asheri Chaula School of Earth Science, Real Estate, Business and Informatics, Department of Computer Systems and Mathematics, Ardhi University-Tanzania Sustainable management and resilience of ecosystems and their different services from land, water, biodiversity and forests has been highlighted as a means to address environmental degradation in Tanzania. On contrary, there is in adequate information to aid sustainable management of fragile natural resources such as Rufiji Delta. To address the limitation this research was carried out using Landsat data for appraising and simulating the future situation of Rufiji Delta using CA-Markov model. Maximum Likelihood Classification algorithm in ERDAS Imagine software was used for Landsat image classification and accuracy assessment for year 1998, 2008 and 2018 while Ca-Markov model of IDRIS Selva software was used for quantification of LULC change and simulation, correspondingly. The classification results of four different study periods have depicted the quantity land use land cover status in year 1998, 2008 and 2018. In year 1998 the impervious land cover was the largest class with 53413.40 ha (35.74% composition), followed by water bodies with 42506.10 ha (28.44% composition) while mangrove forest and non-mangrove vegetation consisted of 38060.40 ha (25.47 % composition) and 15468.50 ha (10.35% composition), correspondingly. In year 2018 the impervious land cover increased to 60759.70 ha (40.66% composition) while mangrove forest and non-mangrove vegetation consisted of 35062.2 ha (23.46% composition) and 23019.2 ha (15.40% composition), correspondingly. Water bodies declined to 30607.10 ha (20.48% composition) following the consumption of water in hydro-electrical and agricultural expansion proximal to the Rufiji Delta. In year 2048 a notable decline to about 29757.07 ha, (18.91%), 34891.44 ha (21.35were recorded for mangrove forest and water bodies, correspondingly. The ...

Modeling Cure Rate of Infectious Disease with or Without Co-Infection: An Application to Tuberculosis / Human Immuno Virus

Research article of American Journal of Scientific Research and Essays Modeling Cure Rate of Infectious Disease with or Without Co-Infection: An Application to Tuberculosis / Human Immuno Virus Olaosebikan, A.1; Aderoju, S.A.2* and Balogun, O.S.3 1, 2*Department of Statistics and Mathematical Sciences, Kwara State University, Malete, P.M.B. 1530, Ilorin, Kwara State, Nigeria. 3Department of Statistics and Operations Research, Modibbo Adamawa University of Technology, Yola, Adamawa State, Nigeria. In this study, we examined the challenges of modeling infectious diseases using tuberculosis (TB) as a case study. The tuberculosis and tuberculosis co-infected with Human Immuno Virus (HIV) is one of the common health problems in the world. Time-to-event outcomes are common data type in medical research. The data examined time until a patient is cured of the disease having some patients right censored. With the nature of the data, the appropriate analysis is survival analysis method. The study aims at fitting appropriate models to the TB and TB/HIV co-infection data examining age and gender as factors influencing the cure rate of the disease. Hence, Kaplan-Meier estimation, Cox PH and some parametric models were adopted in the study. The result shows that among the parametric models, generalized gamma fit TB data best and there is no significant difference in the survival rate of male and female while gamma fit TB co-infected with HIV best and there is a significant difference in the male and female patient. However, Cox PH model (having smaller AIC) performs better than all the parametric models considered (for both data) in this study though with the same conclusion. Keywords: Survival analysis, TB, HIV co-infection, parametric, Kaplan_Meier, Cox PH ...

Prof. Dr. Mohammad Mehdi Rashidi
Shanghai Key Lab of Vehicle Aerodynamics and Vehicle Thermal Management, Systems, Tongji Clean Energy Institute of advanced studies- Tongji University.

Dr. Milena Palczewska
Vice Dean for student affairs, Military Faculty, War Studies University, al. gen. Antoniego Chruściela “Montera” 10300-910 Warszawa

Dr. Piyush Chaudhary
Assistant Professor, Deptt of Ras Shastra (Ayurvedic Pharmaceutics), Incharge, Gurukul Pharmacy, MSM Institute of Ayurveda, BPS Women University, Khanpur Kalan, Sonepat, Haryana

Dr. M. M. Awad
Mechanical Power Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt

Dr.Eng. Ahmed Kadhim Hussein
College of Engineering, Department of Mechanical Engineering, Babylon University, Babylon City, HIILA , IRAQ

Dr. KATSURA Hidemitsu 
Guest Lecturer for ICEEE-2016, Coimbatore Institute of Technology (CIT) in COIMBATORE, TAMIL NADU 641014, INDIA

Dr. Sang-Bing Tsai
Prof., School of Business, Dalian University of Technology, Panjin, 124221, China; Prof., Zhongshan Institute, University of Electronic Science and Technology of China; Prof., TEDA College, Nankai University, China

Dr. Deepmala 
Visiting Scientist, SQC & OR Unit, Indian Statistical Institute

Dr. Begum Sertyesilisik
Assoc. Prof. at the Istanbul Technical University

Dr. Palani Elumalai
National Research Foundation Fellow of Korea, Department of Chemistry & Biology, University of Ulsan

Dr. Shittu Lukeman Adelaja Joseph
HOUSTON, TX. 77099, USA

Prof. Dr. Naqib Ullah Khan
Department of Plant Breeding and Genetics, The University of Agriculture, Peshawar 25130, Khyber Pakhtunkhwa, PAKISTAN.

Dr. V. Ananthaswamy
Assistant Professor, The Madura College (Autonomous), Madurai – 625 011, Tamil Nadu, India.

Prof. Dr. M.Nageeb Rashed
Professor of Analytical and Environmental Chemistry, Faculty of Science, Aswan University, Egypt

Dr. Hossein Kazemian
Faculty& Director; Northern Analytical Lab Services (NALS), University of Northern British Columbia (UNBC), 3333 University Way, Prince George, BC, Canada, V2N 4Z9

Dr. Vishnu Narayan Mishra
Applied Mathematics and Humanities Department, Sardar Vallabhbhai National Institute of Technology.

Dr. Balaram Kundu
Associate Professor, Department of Mechanical Engineering, Jadavpur University, Kolkata – 700 032, INDIA

Dr. Sergio Nardini
Associate Professor, Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università degli Studi di Napoli, via Roma 29, 81031 Aversa (CE)

Dr. Sanjay Mishra
Professor, Department of Biotechnology, School of Engineering & Technology, IFTM University

Dr. Lakshmi Narayan Mishra
Professor, Department of Mathematics, National Institute of Technology

Dr. DHANANJAYA REDDY
Dept.of Mathematics, Assistant Professor In Mathematics, Govt. Degree & PG College

Dr. S. Krishna Murthy
Associate Professor, Department of Applied Mathematics,Defence Institute of Advanced Technology, Deemed University(DU), Girinagar, Pune

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1. Shuo Zhang. Experimental study on scouring of coarse sand and fine sand seabed caused by propeller washing in front of solid wharf.American Journal of Scientific Research and Essays, 2018 3:14. DOI:10.28933/ajsre-2018-12-1805 
2.Zhang Bo and Xie Xionggang. Numerical simulation and analysis of coupled Thermal-Hydrological-Mechanical in coalbed methane heating mining. American Journal of Scientific Research and Essays, 2018 3:13. DOI:10.28933/ajsre-2018-12-0808 

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