Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach

Numerous approaches exist for disaggregating power consumption data, referred to as non-intrusive load monitoring (NILM). Whereas NILM is primarily used for energy monitoring, we intend to disaggregate a household’s power consumption to detect human activity in the residence. Therefore, this paper presents a novel approach for NILM, which uses pattern recognition on the raw power waveform of the smart meter measurements to recognize individual household appliance actions. The presented NILM approach is capable of (near) real-time appliance action detection in a streaming setting, using edge computing. It is unique in our approach that we quantify the disaggregating uncertainty using continuous pattern correlation instead of binary device activity states. Further, we outline using the disaggregated appliance activity data for human activity recognition (HAR). To evaluate our approach, we use a dataset collected from actual households. We show that the developed NILM approach works, and the disaggregation quality depends on the pattern selection and the appliance type. In summary, we demonstrate that it is possible to detect human activity within the residence using a motif-detection-based NILM approach applied to smart meter measurements.

Identification of aquaporin markers in Solanum melongena for water stress response

Aim: The study focused on identifying markers linked to aquaporin genes from the expressed regions of S. melongena using bioinformatics applications. Methodology: The EST collections were explored for identification of aquaporin markers for water stress response using comparative analysis and in-house developed repeat motif detection program. An algorithm was developed to generate repeat motifs which can be effectively used for collecting EST of S. melongena to filter the sequences having repeat motifs for further analysis. Results: From the results generated, the 22 potential sequences with the markers were found to be associated with aquaporin proteins. The detected repeat motifs are inherent part of markers and these markers are found to be evolutionarily conserved and associated with aquaporin proteins. Hence, identifying markers for the presence of aquaporin proteins play an important role in water diffusion across cell membranes in plants. Interpretation: Identifying aquaporin markers are useful for plant breeders for developing water stress tolerant crops during elevated temperatures. These markers are linked to water channel proteins that belong to superfamily Major Intrinsic Protein, that primarily plays an important role in conduction of water in plants.

Batik Motifs Detection Using Pattern Recognition Method

Batik motif is one of the factors that makes batik unique and attractive. There are various kinds of batik motif designs in various areas. Each of these design motifs implies symbols/illustrations that contain certain meanings.The design of the batik motif is used in different events according to the occasions. But unfortunately, not many people understand this, even though local wisdom on the design of batik motifs is one form of cultural heritage of the archipelago that must be preserved. Related to this, development of information technology and multimedia should be used as a solution. However, until now, there is no accurate and fast information system in detecting batik motifs. This study applies pattern recognition methods to find the most appropriate and accurate method for detecting and interpreting batik motifs. The method will be used to build a batik motif detection information system to help users get information quick and accurately.Keywords: pattern recognition, batik motifs, analysis and design of information systems.Abstrak. Motif batik merupakan salah satu faktor yang menjadikan batik unik dan menarik. Terdapat berbagai macam desain motif batik di berbagai area. Setiap desain motif tersebut mengisyaratkan simbol-simbol/ilustrasi yang mengandung makna tertentu. Tentu saja desain motif batik tersebut digunakan dalam acara yang berbeda-beda sesuai dengan keperluanya. Namun sayang, tidak banyak orang yang mengerti hal ini, padahal kearifan lokal pada desain motif batik tersebut merupakan salah satu bentuk warisan budaya nusantara yang wajib dilestarikan. Terkait hal tersebut, seharusnya perkembangan teknologi informatika dan multimedia dapat digunakan sebagai solusi. Namun demikian, sampai saat ini, belum ada system informasi yang akurat dan cepat dalam mendeteksi dan menginterpretasi motif batik. Penelitian ini menerapkan metode-metode pengenalan pola guna menemukan metode yang paling tepat dan akurat untuk mendeteksi dan menginterpretasi motif batik. Metode tersebut akan digunakan untuk membangun system informasi deteksi motif batik untuk membantu pengguna yang tidak mengenal motif batik mendapatkan informasi secara lebih cepat dan akurat.Kata Kunci: pattern recognition, batik motifs, analysis and design of information systems.