This study will identify the superior model by grade recognition of building images of office buildings and residential buildings by two image recognition models that are known to be highly accurate. With respect to expert grade evaluation in facade images of buildings, for practical use in the real estate business, focus on the layer depth of convolutional neural networks (CNN), an AI image recognition technology, and build two models using VGG-16 and ResNet-50, which are different layer depths. Modify the network so that it can be applied to the model, perform transfer learning, and obtain a transition graph of classification accuracy. The results of this accuracy comparison considered showed that VGG-16 outputs higher accuracy than ResNet-50 for both applications, indicating that VGG-16 has the advantage. This also suggests that the performance required of the model (architecture) is not only based on layer thickness, but also includes the need to avoid overlearning due to layer depth.

The organization rate of labor unions, which have supported the development of Japanese industry, has been declining year by year, and this trend continues. In addition, Japanese labor unions are organized by company, and employees are required to serve as union officers, making it difficult to appoint officers. This time, with the cooperation of some labor union organizations, we would like to use network analysis techniques to consider measures to revitalize labor union activities from the perspective of executive relationships.

国内医薬品市場において、処方量は高齢化による医療ニーズの拡大や画期的な新薬 の発売等で増加している一方、薬剤費は政府による医療費増加抑制策(薬価引下げや GE 使用推 進)の結果、市場規模は頭打ちとなってきている。そのような中、国内製薬企業は自社が強みを 持つ疾患或いは技術領域に経営資源を集中的に投資している動きが見られている。しかし、製薬 企業の経営資源の集中度合は、IR 情報等の定性的な情報では測ることが困難である。そこで、 本研究では技術領域に焦点を当て、製薬企業の技術領域を特許文書にベクトル表現を持たせる ことで定量化し、2000 年以降の技術領域の推移を可視化することを試みた。

The demand for energy conservation in large-scale facilities is increasing year by year, and there is a growing momentum for air-conditioning equipment operation managers to respond to this demand. Due to the fear of complaints and the resulting busyness of dealing with them, it becomes difficult for operation managers to make drastic operational changes, to try and implement measures such as relaxing temperature settings or stopping AHU fans. In this study, the purpose of this study is to use the physical quantities related to AHU in central air conditioning equipment to clarify the physical quantities when complaints about the thermal environment arise, and to determine whether the operation manager should relax the set temperature or stop the operation of the AHU fan. Consider the ''discomfort index'' that can be used as a guideline.

顧客中心のサービス設計のため，マーケティング領域では，ペルソナ手法が広く用い られている.デザイナーのインタビューによる定性的な作成手法に加え，昨今では，多量のデー タと様々な分析手法を組み合わせた定量的ペルソナデザイン手法が多用されている.本稿では，著者らが提案しているシミュレーションベースの定量的手法について，ペルソナの企画者やデザイナーなどの実務有識者にヒアリングを行う.当該手法の有用性や限界を議論するとともに，今後の改善に向けた方向性を議論する.

Currently, the emergence of technologies such as generative AI, Web3, and other technologies that are significantly changing the existing framework of work requires the need for reskilling in the entire country. However, in many companies and employees, productivity remains low due to the inability to adapt to changes in technology and society. In this study, we will simulate how companies can catch up in a situation where completely new skills are required by society as a whole. We will then conduct a qualitative comparative analysis of the changes in the process caused by differences in the organizational structure of companies and the attributes of their employees, in order to obtain suggestions on how to realize reskilling in organization.

Global warming has caused a number of serious disasters in Japan and abroad. Meanwhile, disaster forecast information is becoming more sophisticated every year, and the means of communication is evolving with the spread of smartphones. Despite the fact that disaster information is readily available, the spread of damage has not been contained. Minimization of damage could be achieved through evacuation actions by those who do not evacuate. The purpose of this study is to derive the best information transmission method for guiding evacuation in river floods. What information communication methods can be considered to achieve effective evacuation? With the goal of changing the behavior of residents, including those who cannot obtain disaster information, those who obtain disaster information but do not take evacuation action, and those who do take evacuation action, we will conduct research on disincentive to evacuation action and intervention methods.

We conducted text mining on data from review sites where information and reputations about companies can be shared, and evaluated the labor environment score from that data through sentiment analysis. As a result of investigating the impact of the labor environment score on corporate performance, a positive correlation was shown between the labor environment score and the operating profit margin. Furthermore, by conducting morphological analysis of the review data and analyzing co-occurring keywords, we were able to identify common words between companies and visually confirm them.

Recently, the importance of ethical, legal, and social issues (ELSI) brought about by science and technology has been intensively discussed, and the social inclusion of handicapped people is the one important issue of the ELSI. Responding to the global environment and aging society, which previously required a cost burden, is now becoming an industry that drives innovation. Similarly, it is foreseeable that the social inclusion of handicapped people, which is recognized as a issue necessary of cost-burden, will drive innovation. In this study, we will use special subsidiaries of social welfare corporations as case studies to investigate and analyze the relationship between the social inclusion of people with disabilities and innovation, and to design social systems that will make social inclusion of people with disabilities sustainable.

Financial news is undeniably crucial for investment decisions, it is considered an effective way to predict stock movement in the natural language processing (NLP) field as well. Since financial news corpus always comes with very few features and lots of noise, the models must be capable of handling ultra-long texts and being strong in feature extraction. The mainstream NLP patterns are generally based on pre-trained language models (PLMs), but PLMs are not good at processing ultra-long texts, so will the PLMs outperform the traditional statistical models in this task? We built several typical NLP patterns for experimental comparison and proposed a text extraction algorithm to improve the ultra-long text handling problem. According to the results, the PLMs have no significant advantage in analyzing ultra-long news corpus, and the algorithm we proposed can improve the accuracy of the PLMs by about 3%.

This study examines the involvement of local communities in addressing traffic accident issues, based on the traffic accident statistics provided by the National Police Agency. Both the frequency of traffic accidents and the resulting injuries have shown a declining trend. Nevertheless, a challenge persists in reducing accidents influenced by contemporary factors, including those involving elderly individuals, young people, and bicycle-related incidents. Given the significant influence and role that local communities are believed to play in resolving this issue, we explore the relationship between them.

電気自動車(以下、EV)など次世代自動車普及の方策を立案する目的としてエージェ ントベースモデル(以下、ABM)を用いた研究は多数なされているが、一般消費者への普及予測を 対象としたものが多く、企業への普及予測を行なったものは限定的である。本研究では、消費者 モデルに加え、企業モデルの構築も行なった。企業への普及予測も行なうことで、今後のガソリ ン・軽油の需要に与える影響をより正確に把握することが期待される。EV などの次世代自動車の普及予測を行ない、ガソリン・軽油の配送モデル構築を行なうことを本研究の最終目的とする。

The economic impact of mega sporting events including both tangible and intangible legacy is a complex issue and challenging to predict due to the difficulty of accurately estimating. However, traditional methods often encounter problems handling large and complex datasets, noisy input sequences, and missing values. Consequently, this study introduces a novel approach using machine learning to optimize the selection of key indicators, thereby enhancing the predictive accuracy for the multifaceted impacts associated with hosting sporting events, such as the FIFA World Cup. Specifically, we utilize the Boosting Algorithms to analyze the most predictive economic and sportive indicators. As a result, we have developed an economic model for estimating the event's impact, offering a robust analytical tool for policymakers and financial analysts.

EC の取り扱い量の増加に伴い、商品の保管や出荷を担う物流センターの生産性向上が 求められており、ピッキング業務の効率化のため、棚搬送型倉庫ロボットが導入されている。棚 搬送型倉庫ロボットは作業員との協調システムであり、作業員には梯子の昇降、身体の屈伸、段 取り替えといった作業が発生している。人手不足の物流業界において、持続可能な物流センター を運営していくためには、作業員の負担も考慮に入れた生産性向上が必須となる。本研究では、 棚搬送型倉庫ロボットによる移動棚の移動時間の最小化と、作業員による作業時間の最小化で 構成される多目的非線形最適化問題をイジング模型によって求解し、最適な商品配置方法の存 在を明らかにすることを目的とする。

社会技術システムの設計・実装のため，構成的な接近法として，エージェントシミュ レーションが用いられている.しかし，多様な背景を持つステークホルダーに対し，モデルの構造やシミュレーションの全体的な結果を理解・共有させることが課題となっている.先行研究ではシミュレーション結果を自然言語により記述しビジネスケースと接地させる方法論が存在するが，本稿では当該手法の改善提案を行う.具体的には，1)シミュレーション結果を大域的に分析し系統的に分類する，2) 分類結果につき大規模言語モデルを用いて自然言語により書き下す. このことにより，シミュレーション全体の構造を俯瞰し「あり得る結果」を同定した上で，それに基づき半自動的に仮想的なビジネスケースを作成しうることを確認した.

The purpose of this study is to investigate the importance of location information and patient volume estimation as strategic factors for clinic management in Japan's increasingly competitive medical institution environment. Official patient surveys are typically used to estimate the number of patients, but this provides only limited information. In this study, we will use urology-related diseases in the elderly as an example, estimate the number of patients based on out-of-hospital prescription dispensing data for each city, ward, town and village, and use synthetic population data to explore the relationship between family structure and diseases. In addition, to evaluate the attractiveness of clinics, we will use GIS to visualize location information and analyze it in combination with location information of competing clinics. Furthermore, we will use the Huff model to search for attractive locations for opening clinics, and for this purpose, we will conduct a questionnaire survey among urological disease patients living in the target area and set numerical values for attractiveness. This is expected to provide strategic geographic information for clinic management.