The gathering and use of play data in professional sports, such as baseball and soccer, has recently gained pace. In handball, the European Federation has started collecting play data during a game using wearable terminals, such as KINEXON. However, these gadgets are highly costly, and it is difficult to introduce them to Japan’s amateur handball sector. Additionally, there is an increasing need to use IT tools to enhance player evaluation and training with the goal of everyone improving regardless of the setting or the coach’s skill. Therefore, the purpose of this study is to categorize shooting by gathering joint coordinates and categorizing them using publicly available footage of shooting scenes in handball games.We specifically used the open-source program CenterNet to extract joint coordinates from the video. We categorized the shooters and discussed their traits based on these values.
This work is related to a method and technology that can produce human speech signal from 3-dimensional glottal vibration signals. Due to vibration of vocal folds during phonation there is acceleration of the intrinsic laryngeal muscles in the 3-dimesional space. These accelerometric signals are non-invasively acquired by placing a sensor on human larynx. The acceleration in three orthogonal axes is captured using tri-axial MEMS (Micro-Electro-Mechanical-Systems) based accelerometer and signals are electronically pre-amplified and filtered. Using these signals required speech harmonics are generated to produce speech signal. The signal is further amplified to play in a standard speaker system.This kind of device may be helpful for people whose vocal folds vibrate but cannot produce speech due to various reasons such as inability of articulation or loss of articulator organ. It may also be useful for some pathological cases in clinical application.
In the Covid-19 epidemic, the automated guided vehicles (AGVs) could be use in material handling which prevent interpersonal contact and be a factor in reducing the epidemic. As the consequence of the labor shortage, the recruitment of labor on material handling tends to be scarce and the labor cost is also higher. Therefore, the solution is to use AGVs in the material handling in the production line. The benefit of reducing the human labor is the ability to reduce the cycle time and human error in the operation. However, at present, the cost of the AGVs from the manufacturer or the dealer is high. This paper introduces the development process of an automatic transport vehicle by using Mecanum wheels which can carry payload up to 20 kg. The hardware and software of material handling vehicle was designed such as the material of the structure, sensors, electrical circuit, controller, and computer algorithm. The autonomous material handling vehicle was tested in the transportation of small parts in factories within limited workspaces where conventional wheeled vehicles cannot operate. The RP-LiDAR S1 was used to acquire main sensing signal to find the appropriate escape route. The experimental results showed that the intelligent nagavative system enhance the ability of obstacle avoidance to the material handling vehicles in the real situation in the transportation of small parts in a factory.
Lightning events are consequential in investigating meteorological phenomena. These prompted various scientific investigations and research efforts conducted across the globe along with the development of physical devices to locate, detect, track, and gather information about lightning. The need to analyze, visualize and share this information is easily attainable with the rise in technological platforms and the availability of open-source software. In the Philippines, since it is among the most disaster-prone countries in the world because of its geographical location, the government has taken steps to address the problem using the data collected from the sensors deployed throughout the country. These sensors record weather and lightning data every minute, and a daylong generated dataset can quickly become overwhelming when analyzed and interpreted. To better view and comprehend the weather and lightning data, we propose an interactive web application designed and constructed utilizing free and open-source software (FOSS) tools and frameworks such as Python, Django, ReactJS, and Leaflet.
Having reliable information is very important while using a process mining technique as data mining is all about finding out how processes are actually performed to discover problems and areas for improvement. In this paper, we analyzed the real-life event log from a financial institution using the data mining tool called Fluxicon disco. The dataset is related to the application process for a personal loan or overdraft. The event log has a total of 262200 events and 13087 cases. The data was collected from October 1, 2011, to March 14, 2012. The whole loan procedure started with the customer submitting an application and the successful endpoint is the application being activated. For this study, we collected the data in CSV format and imported it into the Fluxicon Disco software. The Disco makes it easier to deal with large event logs and complex models. After importing the data, we defined the column as Case ID, Activity, Resource, Timestamp, and Attributes. We do not have any large specific problem; the dataset simply shows the loan process activities and path. But we assume that there might be some departments and activities which might be taking longer than necessary, and it might be increasing the entire loan selection process. We assume that some work is not being done in an efficient way, resources of the organization are not optimized, and as a result, clients have to wait for more for the loan process. So based on these problems, our objective is to find those activities and paths where duration is comparatively very high, and cases are being piled up there. But the data analytics tool does not exactly state what the real problem is, it just gives us direction and we have to find it out on our own. In this data analyzing process, we came up with two major areas which we think need to be taken care of. The first one is the activity which is modifying approved contracts where the frequency is very low, but the mean duration is very high. And it is placed in a bit of a weird place which is after application and offer events are completed. So, we assume that it is the result of faults in the above process and things can be improved in the application and offer selection process either. Another finding is the path from W_Nabellenoffertes-COMPLETE to W_Nabellenoffertes-START (which basically means following up with client start and complete) is taking a very high total duration and a lot of cases are being piled up here. So, we assume that this particular path and activity needs to be looked up to find if the work is being done in an efficient way.
