Heap Leach Pad Surface Moisture Monitoring Using Drone-Based Aerial Images and Convolutional Neural Networks: A Case Study at the El Gallo Mine, Mexico

An efficient metal recovery in heap leach operations relies on uniform distribution of leaching reagent solution over the heap leach pad surface. However, the current practices for heap leach pad (HLP) surface moisture monitoring often rely on manual inspection, which is labor-intensive, time-consuming, discontinuous, and intermittent. In order to complement the manual monitoring process and reduce the frequency of exposing technical manpower to the hazardous leaching reagent (e.g., dilute cyanide solution in gold leaching), this manuscript describes a case study of implementing an HLP surface moisture monitoring method based on drone-based aerial images and convolutional neural networks (CNNs). Field data collection was conducted on a gold HLP at the El Gallo mine, Mexico. A commercially available hexa-copter drone was equipped with one visible-light (RGB) camera and one thermal infrared sensor to acquire RGB and thermal images from the HLP surface. The collected data had high spatial and temporal resolutions. The high-quality aerial images were used to generate surface moisture maps of the HLP based on two CNN approaches. The generated maps provide direct visualization of the different moisture zones across the HLP surface, and such information can be used to detect potential operational issues related to distribution of reagent solution and to facilitate timely decision making in heap leach operations.

Constraints in Production, Marketing and Processing of Onion (Allium Cepa L.) in Nuh District of Haryana

Onion (Allium cepa L.) is one of the important commercial vegetable crops grown in India. The present study was conducted in Nuh district of Haryana on the basis of highest production of onion among other districts of the state. The block named Tauru was selected for sampling and a total of thirty onion farmers from various villages in this block were selected randomly. The primary data for the agriculture year 2017-18 were collected by personal interviews of the selected farmers with the help of specially designed schedule. The results of the study revealed that the major problems faced by the onion farmers in production were observed high cost of pesticide (93.33%), lack of knowledge about recommended fertilizer doses (86.67%), high cost of fertilizer (83.33%), lack of knowledge about the control measures for various pests and diseases (83.33%), difficulty in identifying the pests and diseases (80.00%) and lack of knowledge about seed/seedling treatment (76.67%). As for as marketing of onion is concerned, 83.33 per cent of respondents opined that high cost of transportation, absence of minimum support prices (83.33%), existence of large number of intermediaries in marketing process (83.33%) and too much fluctuation in prices (80.00%). The problems related to processing expressed by onion growers 80.00 per cent of the respondents reported the problem of technical manpower, higher charges of power and fuels (73.33%), fluctuation in raw material and procurement (73.33%) and lack of good quality packaging material (66.67%).

Challenges of Tax Auditors and Investigators in Abia State, Nigeria

The objective of this study is to examine the challenges of tax auditors and investigators in Abia State, Nigeria. The population of the study consisted of 400 people and a sample size of forty respondents based on a judgmental sampling technique comprising of chartered accountants, tax consultants, and tax officials in public and private sectors in Umuahia, Abia State with the aid of a scaled questionnaire. The data obtained were qualitatively analyzed. The study concludes that the following were challenges facing tax auditors and investigators: poor record-keeping by taxpayers, lack of cooperation by taxpayers and agents, lack of technical manpower, bribery and corruption, obsolete tax laws, low funding of the tax authority, lack of database, etc. The study recommends modernization and automation of tax system, recruitment of qualified professionals well versed in tax and accounting among others. JEL Classification: H20, H26, H29

Continuous Monitoring and Improvement of the Blasting Process in Open Pit Mines Using Unmanned Aerial Vehicle Techniques

The current techniques used for monitoring the blasting process in open pit mines are manual, intermittent and inefficient and can expose technical manpower to hazardous conditions. This study presents the application of unmanned aerial vehicle (UAV) systems for monitoring and improving the blasting process in open pit mines. Field experiments were conducted in different open pit mines to assess rock fragmentation, blast-induced damage on final pit walls, blast dynamics and the accuracy of blastholes including production and pre-split holes. The UAV-based monitoring was done in three different stages, including pre-blasting, blasting and post-blasting. In the pre-blasting stage, pit walls were mapped to collect structural data to predict in situ block size distribution and to develop as-built pit wall digital elevation models (DEM) to assess blast-induced damage. This was followed by mapping the production blasthole patterns implemented in the mine to investigate drillhole alignment. To monitor the blasting process, a high-speed camera was mounted on the UAV to investigate blast initiation, sequencing, misfired holes and stemming ejection. In the post-blast stage, the blasted rock pile (muck pile) was monitored to estimate fragmentation and assess muck pile configuration, heave and throw. The collected aerial data provide detailed information and high spatial and temporal resolution on the quality of the blasting process and significant opportunities for process improvement. The current challenges with regards to the application of UAVs for blasting process monitoring are discussed, and recommendations for obtaining the most value out of an UAV application are provided.

Bio-Floc Technology: Prospects & Challenges in Fish Farming of Nepal

Bio-floc technology is the blue revolution in aquaculture & new technique of enhancing water quality & utilizing feed wastes in the aquaculture system. It follows the concept of conversion of ammonium in addition to organic nitrogenous wastes into bacterial biomass in where heterotrophic bacterial growth is stimulated & nitrogen uptake through the production of microbial proteins is promoted by the addition of carbohydrates to the pond. Nitrogen generated by uneaten feed and excreta of cultured organisms is converted into proteinaceous feed available for those same organisms. This technique recycles nutrients & nitrogenous wastes by maintaining a high carbon: nitrogen ratio and provides essential & higher quality nutrition to the shrimps & fishes in achieving fast growth, lesser FCR & possibility to prevent diseases. Water requirement in BFT is extremely less & it is advantageous than the conventional system where there is continuous water & nutrient recycling, lower FCR. On the other hand, many challenges are existing in practicing bio-floc in Nepal as it requires frequent pond monitoring by the technical manpower. The choice of carbon source should be made wisely and correctly as the performance of fish and water quality in the bio-floc ponds depend highly upon carbon source. Further, vitamins required for fish may not be produced by microbes thus needed to identify them and supply through the feed. However, the practice of bio-floc technology will be proven worth for farmers in Nepal. Int. J. Appl. Sci. Biotechnol. Vol 8(2): 140-145

TO COMPARE GAVAGE, CUP AND PALADY FEEDING METHODS IN TERMS OF ECONOMY IN PRETERM NEWBORN

Background: UNICEF and WHO recommended that children be exclusively breastfed during the first six months of life. Breast milk is uncontaminated and contains all nutrients necessary for children in the first few months of life. Methods: This randomized control trial conducted at Umaid hospital, attached to Dr. S.N Medical College, Jodhpur. All preterm neonates with a gestational age between 30 to 34 weeks as defined below were included in the study after a written informed consent. A total of 100 neonates, those meeting the inclusion criteria were taken in the study. These neonates were randomized into four groups – NG group, OG group, Palady group, and Cup group by block randomization comprising of 25 neonates each. Results- The mean expenditure in NG, OG, PALADY and CUP groups were 15427±10317 Rs., 17065±6807 Rs., 9231±1790 Rs. and 7319±1657 Rs. respectively. The difference was statistically significant for NG vs PALADY, NG vs CUP, OG vs PALADY, OG vs CUP and PALADY vs CUP. Conclusion: we conclude that feeding in preterm low birth weight neonates who cannot breast feed is best achieved by cup which was found to be the most economical method. Neonates on cup feeding required less expertise. Once mastered under supervision, cup feeding can be used independently in-home setting and in remote areas with less technical manpower at hand. Keywords: Feeding, Cup, Palady, OG.

Construct the Educational Training Model of the Taiwanese Bakery Industry by using Consistent Fuzzy Preference Relation Analytic Hierarchy Process

Whereas Taiwan baking industry is actively participating in large baking competitions, therefore, the more baking talents are in need. However, the good education and training have become urgent issues on the baking industry because of the shortage of qualified technical manpower. The research aim is to build an educational training model for the Taiwan baking industry. We use the research method which is called Consistent Fuzzy Preference Relationship Hierarchy Analysis (CFPR-AHP). CFPR-AHP is a better method than traditional AHP because it could solve the inconsistency of AHP and reduce the questionnaire burden of the respondents. The results are from seven practical experts with an average of 35.2 years of working experiences who have verified the simulation cases and have evaluated the applicability of the model. Also, five levels and 20 evaluation items have been established. The results show that the baking industry training model is composed of creativity, cultural awareness and teaching staff, as well as originality, ethics of mentorship and multiple experiences. The research uses CFPR-AHP such an innovative method to construct the educational training model for Taiwan Baking Industry. It will be helpful for launching the educational training model and also to provide the new training model for the government.

Performance Assessment of Engineering Educational Institutes in Madhya Pradesh using Topsis and GRA

This paper uses multi criteria decision making methods to measure the performance assessment in engineering educational institutions in the state of Madhya Pradesh, India. To cater the need of technical manpower, a very large number of private engineering colleges have been established in the state of Madhya Pradesh of central India within a short span. The diminishing quality made so many engineering colleges forced towards closure is a concern in the state today. Therefore, the need for performance assessment and ranking of these engineering institutions is predominant. For the proposed framework, Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Grey Relational Analysis methods are applied for performance assessment of 28 engineering educational institutions taking into account some selected criteria.