EVALUATION OF NUTRIENT SOLUTIONS PRODUCED FROM AQUEOUS EXTRACTS AND DECOMPOSITION PRODUCTS OF ORGANIC WASTE MATERIALS ON THE PLANT GROWTH PERFORMANCE IN HYDROPONICS

Hydroponic plant production involves the cultivation of plants in absence of soil. In this system, the supply of the plant root with water and nutritional elements occurs via a nutrient solution made of inorganic salts. Hydroponic plant cultivation often achieves higher yields, water use efficiencies and quality of crops compared with soil production. In addition, it renders the farming system independent from soil properties. However, the currently available systems rely on the steady input of non-renewable inorganic salts. Unlike soil-based systems, hydroponics, so far, do not offer feasible opportunities for recycling nutritional elements from within crop residues or organic waste materials. The main aim of this thesis was thus to elucidate the potential of producing nutrient solutions suitable for hydroponic plant cultivation from locally produced vegetable crop residues, commercial compost, and biosolids. In a first experiment, the release of soluble nutritional elements from the organic test materials was investigated over time and for different substrate/water ratios. Dried and ground organic substrate samples were placed into nylon mesh bags and allowed to extract and mineralize in aerated water for up to 23 days. The release of nutritional elements was monitored at intervals of three days and revealed that the highest amounts of soluble nutrients were present in the extraction solution between 3 and 6 days after the set-up of the trial. The use of one L of water for the extraction of six g of dry organic substrate resulted in the highest nutrient release. In a second experiment, the ability of two different nutrient solutions produced from organic waste materials to support the growth and element uptake of corn and cucumber seedlings was investigated. Either dry and ground biosolids or cucumber crop residues were extracted and mineralized for five days in aerated water before the extraction solution was used as a growth medium for hydroponic plant seedlings. A control treatment was supplied with a standard nutrient solution prepared from mineral fertilizer salts. The results revealed that all tested solutions well supported the growth of the seedlings. The solution prepared from biosolids was superior to the one deriving from cucumber leaves. Cucumber plants growing on the biosolid solution grew even better than those on the standard mineral nutrient solution. Corn plants performed best on the standard nutrient solution and the least on the one prepared from cucumber leaves. The results of this study suggest that recycling nutritional elements from organic waste materials into vii hydroponic plant production systems is well possible, using a relatively simple and cheap extraction procedure that could easily be upscaled. Biosolids might be particularly suitable in this respect, and hydroponic plant production might be a feasible way of valorizing this material, which is currently largely dumped into landfills

Effect of Firm Size on Risk and Return: Evidences from Sultanate of Oman

The size of the firms is one of the important factors that determine the firm performance. This study covers the listed firms in MSM. These firms were classified into finance sector, industrial sector and services sectors. The information of the study was collected for a period of 10 years starting from 2008. MSM 30 Index is considered as the benchmark index in Sultanate of Oman. Out of 30 components firms in MSM 30 Index, the required data was available for 24 firms only. Therefore, the study was undertaken with the sample size of 24 firms. The descriptive statistics show that the larger firms risk and return is less while the smaller firms risk and return is high. The result of analysis shows that there is enough evidence to conclude that the firm size has no significant effect on return during the study period. However, the firm size has significant effect with market risk of firms. Keywords: Firm Size, Risk, Return, MSM, Effect of Firm Size, MSM-30 Index DOI: 10.7176/EJBM/12-9-08 Publication date:March 31st 202

Efficient Design of Triplet Based Spike-Timing Dependent Plasticity

Spike-Timing Dependent Plasticity (STDP) is believed to play an important role in learning and the formation of computational function in the brain. The classical model of STDP which considers the timing between pairs of pre-synaptic and post-synaptic spikes (p-STDP) is incapable of reproducing synaptic weight changes similar to those seen in biological experiments which investigate the effect of either higher order spike trains (e.g. triplet and quadruplet of spikes), or, simultaneous effect of the rate and timing of spike pairs on synaptic plasticity. In this paper, we firstly investigate synaptic weight changes using a p-STDP circuit and show how it fails to reproduce the mentioned complex biological experiments. We then present a new STDP VLSI circuit which acts based on the timing among triplets of spikes (t-STDP) that is able to reproduce all the mentioned experimental results. We believe that our new STDP VLSI circuit improves upon previous circuits, whose learning capacity exceeds current designs due to its capability of mimicking the outcomes of biological experiments more closely; thus plays a significant role in future VLSI implementation of neuromorphic systems

Confident-DEA: A Unified Approach For Efficiency Analysis With Cardinal, Bounded And Ordinal Data

This paper proposes an extension to the existing literature in DEA, the authors call Confident-DEA approach. The proposed new approach involves a bi-level convex optimization model, and hence NP-hard, to which a solution method is suggested. Confident-DEA constitutes a generalization of DEA for dealing with imprecise data and hence a potential method for forecasting efficiency. Imprecision in data is defined as two forms, one is bounded data and the second is cardinal data. Complementing the methodology proposed by Cooper et al (1999) which provides single valued efficiency measures, Confident-DEA provides a range of values for the efficiency measures, e.g. an efficiency confidence interval, reflecting the imprecision in data. For the case of bounded data, a theorem defining the bounds of the efficiency confidence interval is provided. For the general case of imprecise data, that is a mixture of ordinal and cardinal data, a Genetic-Algorithm-based meta-heuristic is used to determine the upper and lower bounds defining the efficiency confidence interval. To the best knowledge of the authors, this is the first work combining Genetic algorithms with DEA. In both cases of imprecision, a Monte-Carlo type simulation is used to determine the distribution of the efficiency measures, taking into account the distribution of the bounded imprecise data over their corresponding intervals. Most of previous DEA works dealing with imprecise data implicitly assumed a uniform distribution. Confident-DEA, on the other hand, allows for any type of distribution and hence expands the scope of the analysis. The bounded data used in the illustrative examples are assumed to have truncated normal distributions. However, the methodology suggested here allows for any other distribution for the data

Modelling of fines migration mechanisms in high permeability sands: impact on reservoir performance.

Today the oil and gas industry suffers significant production losses due to fines migrations in high permeability sandstone formations or sand packs. During drilling, production or injection, fines migration continues to cause formation impairment resulting in oil and gas inflow reductions or injectivity resistance. The problem is further enhanced in mature reservoirs where increased water ingress and multiphase production aggravate the fines mobilisation. Proper fines management can optimise productivity, injectivity, safeguard facilities and reduce well maintenance cost. Todays core flood tests as part of risk assessment limit tests to single phase or at best two-phase oil/water flow. Meanwhile existing reservoir simulators have no facilities to analyse solid particles impact on productivity and injectivity. This research work presents the unique technique adopted to analyse fines migration mechanisms in a true multiphase environment. The methodologies adopted include studies of fines particle impacts on pressure drawdowns in several sensitivities of rock permeability, water cut, multiphase flow, liquid flow, porosity, fines grain size, and the rest of relevant rock and fluid properties performed using an appropriate Computational Fluid Dynamics (CFD) simulator. The resultant drawdown pressures were then used to back-calculate corresponding particle-damaged permeabilities using a conventional field approach. From the results obtained, detailed mapping of prevailing pore blocking mechanisms and corresponding permeability impairment profiles are presented as functions of operating conditions. The technique integrates the CFD and 3-D reservoir simulation concepts to define and quantify the effects of different operating conditions on discretised reservoir blocks. Among the major research outcomes are two developed particle-damaged absolute permeability models for multiphase and liquid flow conditions involving fines migration in porous media. The models were tested and validated using ten examples of field data with acceptable error margins in the majority of the cases. Contributions to knowledge include: i) new analysis of particle impact in multiphase and liquid flows, ii) integration of CFD with 3-dimensional reservoir simulator and iii) the developed particle-damaged models. Areas where more study is required include: a) dry gas CFD simulation, b) use of real rock (thin-section) pore structure scans as the computational mesh and c) adapting the application to EOR (enhanced oil recovery) operations such as steam injection, miscible fluid injection and others. These are highlighted as suggestions for further work to improve effectiveness of the developed advances towards better fines migration management. The research work is concluded with recommendations (supported by flow efficiency case studies) on contemporary innovations in fines management

Design and Implementation of BCM Rule Based on Spike-Timing Dependent Plasticity

The Bienenstock-Cooper-Munro (BCM) and Spike Timing-Dependent Plasticity (STDP) rules are two experimentally verified form of synaptic plasticity where the alteration of synaptic weight depends upon the rate and the timing of pre- and post-synaptic firing of action potentials, respectively. Previous studies have reported that under specific conditions, i.e. when a random train of Poissonian distributed spikes are used as inputs, and weight changes occur according to STDP, it has been shown that the BCM rule is an emergent property. Here, the applied STDP rule can be either classical pair-based STDP rule, or the more powerful triplet-based STDP rule. In this paper, we demonstrate the use of two distinct VLSI circuit implementations of STDP to examine whether BCM learning is an emergent property of STDP. These circuits are stimulated with random Poissonian spike trains. The first circuit implements the classical pair-based STDP, while the second circuit realizes a previously described triplet-based STDP rule. These two circuits are simulated using 0.35 um CMOS standard model in HSpice simulator. Simulation results demonstrate that the proposed triplet-based STDP circuit significantly produces the threshold-based behaviour of the BCM. Also, the results testify to similar behaviour for the VLSI circuit for pair-based STDP in generating the BCM

ANALISIS DAN IMPLEMENTASI ACTIVE LEARNING PADA SUPPORT VECTOR MACHINE

ABSTRAKSI: Pada supervised machine learning, data latih yang telah diberi label yang benar merupakan suatu hal yang menjadi prasyarat. Namun, dalam banyak pengaplikasiannya, tugas memberi label tidak bisa dilakukan secara otomatis, tapi melibatkan keputusan manusia dan oleh karena itu membutuhkan waktu yang banyak dan mahal.Pada tugas akhir ini, active learning diimplementasikan pada support vector machine dan diteliti apa faktor yang mempengaruhi jumlah data latih yang diberi label dan tingkat akurasi sistem, dan bagaimana pengaruhnya. Selain itu juga dibandingkan metode pemilihan inisial data dan next data, yaitu metode random dan metode dissimilarity. Data yang digunakan dalam tugas akhir ini adalah Winsconsin Breast Cancer Diagnosis dan Hill-Valley dari UCI Repository. Tujuan utama dari active learning adalah memilih data yang penting atau berpengaruh pada sistem, sehingga bisa mengurangi jumlah data yang perlu diberi label.Hasil penelitian adalah active learning mampu mengurangi jumlah data yang harus diberi label sampai 82.5% tanpa terjadi penurunan akurasi sistem yang significant.Kata Kunci : Active Learning, Support Vector Machine, klasifikasi, label data, pengurangan.ABSTRACT: In supervised machine learning, a training set of examples which are assigned to the correct target labels is a necessary prerequisite. However, in many applications, the task of assigning target labels cannot be conducted in an automatic manner, but involves human decisions and is therefore time-consuming and expensive.In this final task, active learning is implemented in a support vector machine and examined what factors affect the amount of labeled training data and the accuracy of the system, and how they affect. It also compared the selection method of initial data and next data, the random method and the dissimilarity method. Data used in this final task is the Wisconsin Breast Cancer Diagnosis and Hill-Valley from the UCI Repository. The main goal of active learning is to select the data that is important or have influence in the system, so that it can reduce the amount of data that need to be labeled.The results showed that active learning can reduce the amount of data need tobe labeled up to 82.5% without any significant decrease in the system accuracy.Keyword: Active Learning, Support Vector Machine, classification, data label, reduction

Manajemen pembelajaran tahfizh al-Qur’an di SMP Islam Terpadu Al Binaa Bekasi

This study aims to examine the management of tahfizh al-Qur'an learning at Al Binaa Integrated Islamic Junior High School Bekasi. The research method used is qualitative. Data were obtained from interviews, observations, documentation, and a literature review. The main subjects of information in writing this research are the general chairman of the tahfizh al-Qur'an program, the administrative staff of the tahfizh al-Qur'an program, the halaqah (group) supervisor, and the student. The results of this study can be said that the management of tahfizh al-Qur'an learning at Al Binaa Integrated Islamic Junior High School Bekasi starts from the basic stage, students are to learn to read the al-Qur'an well. Furthermore, the memorization stage is a continuation of the basic stage after students have mastered the reading of al-Qur'an well and tested. In addition to regular halaqah, there is also a special accelerated halaqah, namely halaqah which is prepared to provide facilities for students who have above-average memorization abilities and strong will. Evaluation of learning with the Juz Ascension Exam (UKJ) system which starts from ziyadah (new memorization) and tasmi 'kamil (perfect deposit) deposits to their respective halaqah supervisors. AbstrakPenelitian ini bertujuan untuk mengkaji manajemen pembelajaran tahfizh al-Qur’an di SMP Islam Terpadu Al Binaa Bekasi. Metode penelitian yang digunakan adalah kualitatif. Data diperoleh dari hasil wawancara, observasi, dokumentasi, dan kajian pustaka. Subyek utama informasi dalam penulisan penelitian ini ialah ketua umum program tahfizh al-Qur’an, staf administrasi program tahfizh al-Qur’an, pembimbing halaqah (kelompok), dan peserta didik. Hasil dari penelitian ini dapat disimpulkan bahwa manajemen pembelajaran tahfizh al-Qur’an di SMP Islam Terpadu Al Binaa Bekasi dimulai dari tahap dasar, peserta didik difokuskan agar menguasai bacaan al-Qur’an dengan baik. Selanjutnya tahap menghafal yaitu lanjutan dari tahap dasar setelah peserta didik benar-benar sudah menguasai bacaan al-Qur’an dengan baik dan teruji. Selain halaqah reguler, ada juga halaqah khusus percepatan yaitu halaqah yang dipersiapkan untuk memberikan fasilitas kepada para peserta didik yang mempunyai kemampuan menghafal di atas rata-rata dan kemauan kuat. Evaluasi pembelajaran dengan sistem Ujian Kenaikan Juz (UKJ) yang dimulai dari setoran ziyadah (hafalan baru) dan tasmi’ kamil (setoran sempurna) kepada pembimbing halaqah masing-masing