Identifikasi Jenis dan Mutu Teh Menggunakan Pengolahan Citra Digital dengan Metode Jaringan Syaraf Tiruan

Teh merupakan hasil pucuk daun muda tanaman Camelia sinensis dan menjadi salah satu produk ekspor terbesar. Salah satu kendala yang dihadapi konsumen dalam memilih teh berkualitas baik adalah minimnya pengetahuan konsumen terhadap jenis dan mutu teh, sehingga menyebabkan perbedaan penentuan jenis dan mutu teh. Penelitian untuk mengidentifikasi jenis dan mutu teh dari 3 jenis teh yaitu teh hitam, teh hijau, dan teh putih perlu dilakukan. Tujuan penelitian ini adalah merancang aplikasi sistem pengolahan citra digital untuk mengidentifikasi jenis dan mutu teh serta menentukan hasil pengenalan terbaik berdasarkan akurasi yang diperoleh. Penelitian ini menerapkan metode pengolahan citra digital dengan teknik Learning Vector Quantization yang menggunakan 6 parameter warna yaitu R, G, B, H, S, dan I sebagai neuron input dan 13 mutu dari 3 jenis teh sebagai neuron output. Penelitian menggunakan 403 citra dengan perbandingan training dan testing sebesar 80:20. Akurasi training diperoleh sebesar 62,7%. Prediksi menggunakan 26 sampel citra teh berbeda menunjukkan tingkat akurasi sebesar 42,31%. Kata Kunci: jaringan syaraf tiruan, learning vector quantization (LVQ), te

Securing Cognitive Radio Networks using blockchains

Due to the increase in industrial applications of Internet of Things (IoT), number of internet connected devices have been increased accordingly. This has resulted in big challenges in terms of accessibility, scalability, connectivity and adaptability. IoT is capable of creating connections between devices on wireless medium but the utilization of scarce spectrum in efficient manner for the establishment of these connections is the biggest concern. To accommodate spectrum allocation problem different radio technologies are being utilized. One of the most efficient technique being used is cognitive radio, which dynamically allocate the unlicensed spectrum for IoT applications. Spectrum sensing being the fundamental component of Cognitive Radio Network (CRN) is threatened by security attacks. Process of spectrum sensing is disturbed by the malicious user (MU) which attacks the primary signal detection and affects the accuracy of sensing outcome. The presence of such MU in system, sending false sensing data can degrade the performance of cognitive radios. Therefore, in this article a blockchain based method is proposed for the MU detection in network. By using this method an MU can easily be discriminated from a reliable user through cryptographic keys. The efficiency of the proposed mechanism is analyzed through proper simulations using MATLAB. Consequently, this mechanism can be deployed for the validation of participating users in the process of spectrum sensing in CRN for IoTs.publishe

Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models

Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m. Future smart homes demand low-cost, high-accuracy and low-power indoor positioning systems that can provide accuracy of less than 5 m and enable battery operation for mobility and long-term use. We propose and implement an intelligent, highly accurate and low-power indoor positioning system for smart homes leveraging Gaussian Process Regression (GPR) model using information-theoretic gain based on reduction in differential entropy. The system is based on Time Difference of Arrival (TDOA) and uses ultra-low-power radio transceivers working at 434 MHz. The system has been deployed and tested using indoor measurements for two-dimensional (2D) positioning. In addition, the proposed system provides dual functionality with the same wireless links used for receiving telemetry data, with configurable data rates of up to 600 Kbauds. The implemented system integrates the time difference pulses obtained from the differential circuitry to determine the radio frequency (RF) transmitter node positions. The implemented system provides a high positioning accuracy of 0.68 m and 1.08 m for outdoor and indoor localization, respectively, when using GPR machine learning models, and provides telemetry data reception of 250 Kbauds. The system enables low-power battery operation with consumption of <200 mW power with ultra-low-power CC1101 radio transceivers and additional circuits with a differential amplifier. The proposed system provides low-cost, low-power and high-accuracy indoor localization and is an essential element of public well-being in future smart homes

Prevalence of suicidal ideation and suicide attempts in individuals with psychosis and bipolar disorder in South Asia: systematic review and meta-analysis.

BackgroundSuicidal ideation and attempts are growing public health concerns globally. Evidence from high-income countries suggests that individuals with psychosis and bipolar disorder are at increased risk of suicidal ideation and attempts, but there is a scarcity of evidence from South Asia.AimsTo estimate the prevalence of suicidal ideation and attempts in individuals with psychosis and bipolar disorder in South Asia.MethodIn this systematic review and meta-analysis, four databases (PsycINFO, Web of Science, EMBASE and Medline) were searched until December 2022. Pooled prevalence was estimated with random-effects models. Heterogeneity was quantified with the I2-statistic.ResultsThe pooled sample size across the 21 studies was 3745 participants, 1941 (51.8%) of which were male. The pooled prevalence of suicide attempts in South Asian people with either psychosis or bipolar disorder was 22% (95% CI 17-27; n = 15). The pooled prevalence of suicidal ideation with psychosis or bipolar disorder combined was 38% (95% CI 27-51; n = 10). Meta-regression, subgroup and sensitivity analysis showed that the pooled prevalence estimates for both suicide attempt and ideation remained unaffected by variations in critical appraisal ratings and study designs. Only one study reported data on suicide-related deaths.ConclusionsOne in four individuals diagnosed with psychosis or bipolar disorder have reported suicide attempts, whereas up to one in three have experienced suicidal ideation. These findings underscore the urgent need for clinicians to regularly assess and monitor suicidal ideation and attempts among individuals with these disorders in South Asia

Influence of rotating magnetic field on Maxwell saturated ferrofluid flow over a heated stretching sheet with heat generation/absorption

This article is focused on Maxwell ferromagnetic fluid and heat transport characteristics under the impact of magnetic field generated due to dipole field. The viscous dissipation and heat generation/absorption are also taken into account. Flow here is instigated by linearly stretchable surface, which is assumed to be permeable. Also description of magneto-thermo-mechanical (ferrohydrodynamic) interaction elaborates the fluid motion as compared to hydrodynamic case. Problem is modeled using continuity, momentum and heat transport equation. To implement the numerical procedure, firstly we transform the partial differential equations (PDEs) into ordinary differential equations (ODEs) by applying similarity approach, secondly resulting boundary value problem (BVP) is transformed into an initial value problem (IVP). Then resulting set of non-linear differentials equations is solved computationally with the aid of Runge–Kutta scheme with shooting algorithm using MATLAB. The flow situation is carried out by considering the influence of pertinent parameters namely ferro-hydrodynamic interaction parameter, Maxwell parameter, suction/injection and viscous dissipation on flow velocity field, temperature field, friction factor and heat transfer rate are deliberated via graphs. The present numerical values are associated with those available previously in the open literature for Newtonian fluid case (γ 1 = 0) to check the validity of the solution. It is inferred that interaction of magneto-thermo-mechanical is to slow down the fluid motion. We also witnessed that by considering the Maxwell and ferrohydrodynamic parameter there is decrement in velocity field whereas opposite behavior is noted for temperature field

A Symbols Based BCI Paradigm for Intelligent Home Control Using P300 Event-Related Potentials

Brain-Computer Interface (BCI) is a technique that allows the disabled to interact with a computer directly from their brain. P300 Event-Related Potentials (ERP) of the brain have widely been used in several applications of the BCIs such as character spelling, word typing, wheelchair control for the disabled, neurorehabilitation, and smart home control. Most of the work done for smart home control relies on an image flashing paradigm where six images are flashed randomly, and the users can select one of the images to control an object of interest. The shortcoming of such a scheme is that the users have only six commands available in a smart home to control. This article presents a symbol-based P300-BCI paradigm for controlling home appliances. The proposed paradigm comprises of a 12-symbols, from which users can choose one to represent their desired command in a smart home. The proposed paradigm allows users to control multiple home appliances from signals generated by the brain. The proposed paradigm also allows the users to make phone calls in a smart home environment. We put our smart home control system to the test with ten healthy volunteers, and the findings show that the proposed system can effectively operate home appliances through BCI. Using the random forest classifier, our participants had an average accuracy of 92.25 percent in controlling the home devices. As compared to the previous studies on the smart home control BCIs, the proposed paradigm gives the users more degree of freedom, and the users are not only able to control several home appliances but also have an option to dial a phone number and make a call inside the smart home. The proposed symbols-based smart home paradigm, along with the option of making a phone call, can effectively be used for controlling home through signals of the brain, as demonstrated by the results

Unmanned Aerial Vehicle for Laser Based Biomedical Sensor Development and Examination of Device Trajectory

Controller design and signal processing for the control of air-vehicles have gained extreme importance while interacting with humans to form a brain–computer interface. This is because fewer commands need to be mapped into multiple controls. For our anticipated biomedical sensor for breath analysis, it is mandatory to provide medication to the patients on an urgent basis. To address this increasingly tense situation in terms of emergencies, we plan to design an unmanned vehicle that can aid spontaneously to monitor the person’s health, and help the physician spontaneously during the rescue mission. Simultaneously, that must be done in such a computationally efficient algorithm that the minimum amount of energy resources are consumed. For this purpose, we resort to an unmanned logistic air-vehicle which flies from the medical centre to the affected person. After obtaining restricted permission from the regional administration, numerous challenges are identified for this design. The device is able to lift a weight of 2 kg successfully which is required for most emergency medications, while choosing the smallest distance to the destination with the GPS. By recording the movement of the vehicle in numerous directions, the results deviate to a maximum of 2% from theoretical investigations. In this way, our biomedical sensor provides critical information to the physician, who is able to provide medication to the patient urgently. On account of reasonable supply of medicines to the destination in terms of weight and time, this experimentation has been rendered satisfactory by the relevant physicians in the vicinity

The development of accounting practices and the adoption of IFRS in selected MENA countries

Purpose: The purpose of this paper is to examine the level of accounting development and the adoption of IFRS in the four foremost economies in the Middle East and North Africa (MENA)—Egypt, Jordan, Libya and UAE. Through the lens of institutional theory, the study investigates the impact of economic, political, legal and cultural institutions on the development of these countries’ accounting practices and their readiness to use IFRS. Design/methodology/approach: This research uses accounting development indices obtained from current literature as well as recent World Economic Forum and UNCTAD reports to examine the development of accounting in these MENA countries and their inclination to adopt IFRS. Findings: The study identifies a number of impediments to the development of accounting practices and adoption of IFRS in these countries. It also reveals that three of the four MENA countries (Egypt, Jordan and UAE) could be placed on a level playing field with their principal trading partners (the US, the UK, Germany and Italy) given the formers’ business environments, methods of raising finance and levels of professional accounting practices. Research Implications/limitations: Although limited to only four jurisdictions, findings from the study have important implications for investors and parties that are interested in improving the value relevance of the information presented by firms especially in a globalised economy with increasing cross-listing. Originality/value: This study extends the frontier of knowledge on the development of accounting and IFRS adoption by focusing on the MENA region. It is the first effort that the authors are aware of to adopt such a multifarious approach