Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.

Is intuition allied with jumping to conclusions in decision-making? An intensive longitudinal study in patients with delusions and in non-clinical individuals

Research suggests that a jumping-to-conclusions (JTC) bias, excessive intuition, and reduced analysis in information processing may favor suboptimal decision-making, both in non-clinical and mentally disordered individuals. The temporal relationship between processing modes and JTC bias, however, remains unexplored. Therefore, using an experience sampling methodology (ESM) approach, this study examines the temporal associations between intuitive/analytical information processing, JTC bias, and delusions in non-clinical individuals and patients with schizophrenia. Specifically, we examine whether a high use of intuitive and/or a low use of analytical processing predicts subsequent JTC bias and paranoid conviction. In a smartphone-based ESM study, participants will be prompted four times per day over three consecutive days to answer questionnaires designed to measure JTC bias, paranoid conviction, and preceding everyday-life intuition/analysis. Our hierarchical data will be analyzed using multilevel modelling for hypothesis testing. Results will further elucidate the role of aberrant human reasoning, particularly intuition, in (non-)clinical delusions and delusion-like experiences, and also inform general information processing models.

Implementasi OLAP pada Data Kerja Praktik dan Tugas Akhir Menggunakan Framework Modular Cube JS

The government's role in the implementation of higher education in Indonesia is to provide a university database. It is hoped that the government and the public can participate in assessing and conducting surveillance with the database. Every tertiary institution must report everything related to the implementation of education, starting from lecturer data, student data, and lecture data. In its performance, a Dikti Feeder application has been prepared that can transmit data. Each university will adjust the data entry following the Dikti standards. As one of the higher education providers, STMIK STIKOM Indonesia has been able to report data well, but specifically for final assignments and work practices, it has not been maximized due to the development of a separate system from the academic system. For this reason, a suitable system will be developed to accommodate Thesis and Internship data related to reporting on the Dikti Feeder by applying the Online Analytical Processing (OLAP) method using the Cube JS modular framework. Some of the tests carried out are schema file testing, frontend and backend testing, cube client testing, querying testing and load request testing showing the data can be displayed correctly and the process is successful.

High Throughput pre-analytical processing of wastewater settled solids for SARS-CoV-2 RNA analyses v2

This process instruction describes the steps for pre-analytical processing of primary settled solids from wastewater treatment plants for downstream nucleic acid purification and quantification. Previous research has demonstrated that enveloped viral particles, such as SARS-CoV-2, associate with the solids in wastewater. Therefore, concentrating the solids in the sample and removing the water concentrates the viral particles as well and increases the sensitivity of the assay. Bovine coronavirus vaccine (BCoV) is spiked into samples before nucleic acid extraction and serves as a process control as well as an indicator of PCR inhibition. The dry weight of the sample is determined to account for sample variability between different treatment plants and between samples collected on different days and allows for the final quantification to be normalized to the precise quantity of solids in the sample. A dry weight conversion factor to adjust for the final amount of solids in the quantified sample is determined by measuring the difference in mass between the “wet” dewatered solid and after the sample is dried at 110°C overnight. For long term storage, up to 50mL of the original primary settled solid sample is stored at 4°C and small aliquot of the dewatered solids is stored at -80°C. This process instruction applies to sample dewatering, BCoV control spike in, homogenization, dry weight measurement, aliquoting and storage.

Classifying the Unknown: Identification of Insects by Deep Zero-shot Bayesian Learning

Insects represent a large majority of biodiversity on Earth, yet so few species are described. Describing new species typicallyrequires specific taxonomic expertise to identify morphological characters that distinguish it from other known species andDNA-based methods have aided in providing additional evidence of separate species. Machine learning (ML) provides apowerful method in identifying new species given its analytical processing is more sensitive to subtle physical differencesin images humans may not process. Existing ML algorithms are limited by image repositories that only contain describedspecies, leaving out the possibility of identifying new species. We develop a Bayesian deep learning method for zero-shotclassification of species. The proposed approach forms a Bayesian hierarchy of species around corresponding genera anduses deep embeddings of images and DNA barcodes to identify insects to the lowest taxonomic level possible. To demonstratethis proof of concept, we use a database of 32,848 insect images from 1,040 described species split into training and test datawherein the test data includes 243 species not present in the training data. Our results demonstrate that using DNA sequencesand images together, known insects can be classified with 96.66% accuracy while unknown (to the database) insects have anaccuracy of 81.39% in identifying the correct genus. The proposed deep zero-shot Bayesian model demonstrates a powerfulnew approach that can be used for the gargantuan task of identifying new insect species.

Pengembangan Business Intelligence Dashboard untuk Monitoring Aktivitas Pariwisata (Studi Kasus: Dinas Pariwisata Provinsi Bali)

<p class="Judul2">Bali merupakan satu dari beberapa destinasi wisata yang mendatangkan wisatawan nusantara dan mancanegara di Indonesia. Pada tahun 2017, wisatawan mancanegara yang berkunjung ke Bali adalah sebesar 5,6 juta orang dan didominasi oleh wisatawan dari negara Cina. Jumlah kunjungan pada seluruh objek wisata yang ada di Bali tahun 2017 mencapai 17,8 juta kunjungan. Berdasarkan hal tersebut, pemerintah daerah membutuhkan strategi dan keputusan dalam pembangunan sarana dan prasarana yang dapat mendukung pengembangan dan kemajuan pariwisata di Bali. Pemanfaatan teknologi <em>business intelligence</em> dalam menganalisa data dalam jumlah yang besar akan membantu. Penelitian ini mengembangkan sistem informasi memakai pendekatan BI dalam menganalisis data pariwisata Bali dan manajemen data dengan menggantikan pemakaian kertas menjadi media komputer sehingga data tidak hilang begitu saja, namun digunakan sebagai acuan saat menentukan keputusan. Dalam pengembangan sistem digunakan beberapa metode diantaranya <em>framework </em>Codeigniter dengan arsitektur <em>web</em> MVC (<em>Model, View, </em>Controller), OLAP (<em>On-line Analytical Processing</em>) untuk menampilkan visualisasi data, dan <em>double exponential smoothing</em> menampilkan hasil peramalan data pada periode berikutnya. Nilai <em>error </em>dari metode peramalan tersebut dapat dihitung menggunakan algoritma <em>Mean Absolute Percentage Error</em>. Agar dapat mengetahui tingkat pemanfaatan terhadap pengembangan sistem ini, maka digunakan metode <em>black box testing</em>, <em>usability testing</em>, dan <em>user acceptance test</em> untuk mengetahui kualitas dan fungsionalitas sistem dari segi input, output, dan penilaian oleh pengguna sistem. Penelitian ini memperlihatkan bahwa pemakaian teknologi BI tidak hanya mendukung pada perusahaan namun juga mendukung pada bidang pariwisata, pemerintahan dan layanan. Sistem yang dikembangkan dapat membantu proses pemantauan pariwisata dan pendukung dalam pengambilan keputusan.</p><p class="Judul2"> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Judul2"><em><em>Bali is one of several tourist destinations that bring domestic and foreign tourists to Indonesia. In 2017, there were 5.6 million foreign tourists visiting Bali and dominated by tourists from China. The number of visits to all tourist objects in Bali in 2017 reached 17.8 million visits. Based on this, local governments need strategies and decisions in the development of facilities and infrastructure that can support the development and progress of tourism in Bali. The use of business intelligence technology in analyzing large amounts of data will help. This study develops an information system using the BI approach in analyzing Bali tourism data and data management by replacing paper use as computer media so that data does not just disappear, but is used as a reference when making decisions. In system development, several methods are used including the Codeigniter framework with the MVC web architecture (Model, View, Controller), OLAP (On-line Analytical Processing) to display data visualization, and double exponential smoothing to display the results of forecasting data in the next period. The error value of this forecasting method can be calculated using the Mean Absolute Percentage Error algorithm. In order to determine the level of utilization of this system development, black box testing, usability testing and user acceptance tests are used to determine the quality and functionality of the system in terms of input, output, and assessment by system users. This study shows that the use of BI technology is not only supportive of companies but also supports tourism, government and services. The system developed can assist the tourism monitoring process and support decision making.</em></em></p>

Do You Have a "Strict Purse"? The Routes to Meaning in Metaphor

<p>Theoretically there are two processing systems through which meaning can be found for a given statement: an effortless, associative processing system (meaning retrieval), or an effortful, analytical processing system (meaning construction). The current study investigated whether or not the context in which target (loosely figurative) word-pairs are presented can influence whether a person relies on associative or analytical processing to find their meaning. Participants were presented with target (loosely figurative) novel word-pairs and asked to judge them for meaningfulness. These target novel word-pairs were presented in different contexts: either mixed with clearly meaningful word-pairs or with additional novel word-pairs. By nature, meaning cannot be retrieved for novel word-pairs, so if a novel word-pair is to be found "meaningful," then its meaning must usually be constructed online (via the analytical processing system). Consistent with increased reliance on analytical processing, participants who saw target novel word-pairs mixed with additional novel word-pairs judged them meaningful more often than did participants who saw them mixed with clearly meaningful word-pairs. Participants who saw target novel word-pairs mixed with additional novel word-pairs also had more negative N400s to target novel word-pairs, indicating that they committed more semantic effort to the processing of these (again consistent with analytical processing). Associative processing does not involve attempts to construct new meaning for given word-pairs. Consistent with increased reliance on associative processing, participants who saw target novel word-pairs mixed with clearly meaningful word-pairs judged them meaningful less often than did participants who saw them mixed with additional novel word-pairs. These participants also had less negative N400s to target novel word-pairs, indicating that they committed less semantic effort to the processing of these (again fitting with associative processing). Further evidence for different contexts leading to differential processing of the same target novel word-pairs was provided by examination of wave morphology. Two distinctive patterns of neural activation were found in response to the same target novel word-pairs, differing depending on the context in which these appeared. Overall, the results of the current study were consistent with the hypothesis that context can influence which processing system is relied upon to find meaning for a given statement. This finding challenges contemporary models of meaning construction and metaphor comprehension by showing that context is essential to these processes and needs to be taken into consideration.</p>