Green coffee beans feature extractor using image processing

This study offers a novel solution to deal with the low signal-to-noise ratio and slow execution rate of the first derivative edge detection algorithms namely, Roberts, Prewitt and Sobel algorithms. Since the two problems are brought about by the complex mathematical operations being used by the algorithms, these were replaced by a discriminant. The developed discriminant, equivalent to the product of total difference and intensity divided by the normalization values, is based on the “pixel pair formation” that produces optimal peak signal to noise ratio. Results of the study applying the discriminant for the edge detection of green coffee beans shows improvement in terms of peak signal to noise ratio (PSNR), mean square error (MSE), and execution time. It was determined that accuracy level varied according to the total difference of pixel values, intensity, and normalization values. Using the developed edge detection technique led to improvements in the PSNR of 2.091%, 1.16 %, and 2.47% over Sobel, Prewitt, and Roberts respectively. Meanwhile, improvement in the MSE was measured to be 13.06%, 7.48 %, and 15.31% over the three algorithms. Likewise, improvement in execution time was also achieved at values of 69.02%, 67.40 %, and 65.46% over Sobel, Prewitt, and Roberts respectively

Chaotic Rivest-Shamir-Adlerman Algorithm with Data Encryption Standard Scheduling

Cryptography, which involves the use of a cipher, describes a process of encrypting information so that its meaning is hidden and thus, secured from those who do not know how to decrypt the information. Cryptography algorithms come with the various types including the symmetric key algorithms and asymmetric key algorithms. In this paper, the authors applied the most commonly used algorithm, which is the RSA algorithm together with the Chaos system and the basic security device employed in the worldwide organizations which is the Data Encryption Standard (DES) with the objective to make a hybrid data encryption. The advantage of a chaos system which is its unpredictability through the use of multiple keys and the secrecy of the RSA which is based on integer factorization’s difficulty is combined for a more secure and reliable cryptography. The key generation was made more secure by applying the DES schedule to change the keys for encryption. The main strength of the proposed system is the chaotic variable key generator that chages the value of encrypted message whenever a different number of key is used. Using the provided examples the strength of security of the proposed system was tested and demonstrated

Smart Wheelchair with Dual Control using Touchpad and Android Mobile Device

The general objective of the design was to develop a touchpad controlled Android-based electronic wheelchair. It aimed to construct the Android-based circuitry and program for the path finding mechanism of the drive system and interface the Arduino-based circuit to the electronic wheelchair setup. It was designed to evaluate the system in terms of the speed of the electronic wheelchair, reliability of the sensors to avoid obstacle, and ease of use of the wheelchair. C Programming Language was used by the system to control and manipulate the microcontroller, Gizduino AtMega644. The Android application was programmed using the Java Language and Eclipse as the IDE. Its ports were used to interface input and output devices such as the ultrasonic sensors, infrared proximity sensor, touchpad, Bluetooth module, motor and motor driver. There was a satisfactory rating for the evaluation of the system while the Android software was rated excellent as a navigational controller

Chaotic Rivest-Shamir-Adlerman Algorithm with Data Encryption Standard Scheduling

Cryptography, which involves the use of a cipher, describes a process of encrypting information so that its meaning is hidden and thus, secured from those who do not know how to decrypt the information. Cryptography algorithms come with the various types including the symmetric key algorithms and asymmetric key algorithms. In this paper, the authors applied the most commonly used algorithm, which is the RSA algorithm together with the Chaos system and the basic security device employed in the worldwide organizations which is the Data Encryption Standard (DES) with the objective to make a hybrid data encryption. The advantage of a chaos system which is its unpredictability through the use of multiple keys and the secrecy of the RSA which is based on integer factorization's difficulty is combined for a more secure and reliable cryptography. The key generation was made more secure by applying the DES schedule to change the keys for encryption. The main strength of the proposed system is the chaotic variable key generator that chages the value of encrypted message whenever a different number of key is used. Using the provided examples the strength of security of the proposed system was tested and demonstrated

Intelligent Temperature-Controlled Poultry Feed Dispensing System with Fuzzy Logic Algorithm

This study introduces a novel fuzzy logic algorithm tailored to the thermoneutral zone of poultry, offering a precise and adaptive approach to feed dispensation. This involved the utilization of an LCD module to present essential information such as the selected age, real-time ambient temperature, current time, and the dispensed feed quantity. Data gathered during the process were stored in a memory device. The design of the fuzzy logic algorithm centered on the thermoneutral zone of the chicken serves as the determinant for feed dispensed by the system. It's crucial to note that while the system lacked artificial intelligence (AI), its logical analysis operated based on the fuzzy logic algorithm. Rigorous testing ensued, encompassing the comparison of feed dispensation between automated and manual systems and the assessment of feed waste and broiler weight.  Significant feed waste reduction in the first week demonstrated the efficacy of the fuzzy-based method, with consistently low p-values of 0.00069, 0.015195, and 0.034 across subsequent weeks confirming the consistent outperformance in broiler weight compared to the traditional feeding technique. The findings contribute to the advancement of temperature-based poultry feed systems, addressing key challenges in optimizing feed quantity. The study successfully met its objectives, demonstrating the system's capability to dispense feeds effectively across varying ambient temperatures.  Notably, the study revealed a consistent alignment of system outputs with those obtained from a digital thermometer and digital weighing scale, confirming the accuracy and reliability of the temperature-based feed dispensing system

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution